PrimeFish Wiki - User contributions [en]

PrimeFish Wiki

2019-02-06T11:50:32Z

Jacandrade:

= Welcome to the PrimeFish Decision Support Framework. =

==== The [http://www.primefish.eu/ PrimeFish] wiki. ====

== PrimeFish ==

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PrimeFish project is developing an innovative market orientated prediction toolbox. It allows to strengthen the economic sustainability and competitiveness of European Seafood on Local and Global markets.

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=== The Wiki ===

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The PrimeFish project aims to transfer the developed science and technology to Seafood agents, decision-makers and general audience, whilst enhancing the seafood consumption. In particular, the Learning Resources Centre is a multi-platform designed for learning on the PrimeFish outcomes.

As the PrimeFish evolved, different tools will be developed for improving the awareness of the project and to further use among researchers, fishing associations, producers, managers and interested public, including peer-educators.

The Learning Resources Centre includes all training material in this accessible platform. A series of webinars and quick-start tutorial videos (friendly and short video tutorials) will be available. Additionally, scheduled events will be recorded and stored in this section.

The overarching goal is to identify shortcomings of the Seafood market, discuss ideas on how to improve the competitiveness and the economic performance, exploring how the stakeholders can participate and learn of PrimeFish. If you want to contribute with any material, please contact us at learning@primefish.eu

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=== Getting Started ===

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The PrimeFish wiki uses MediaWiki (the same as Wikipedia) for it's main engine. For help on usage, how to create articles, add links and more, visit the help page by clicking the Navigation Menu -> Help in any page or clicking [https://www.mediawiki.org/wiki/Help:Contents Here].

To upload files, click the cog menu on the right -> Upload file or click [http://dsf.primefish.eu/wiki/Special:Upload Here]. You can also click the Special Pages sub-menu for more tools.

If you just want to create a page, create a link with the name wanted for the page, click the link and then click edit on the side menu. You can also change "PrimeFish_Wiki" in your browser URL to the name desired for the page and hit enter. E.g.: [http://dsf.primefish.eu/w/Your_Page_Name [1]].

If you need any support or want to report a bug, please feel free to contact the administrators.

|}

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=== FAQ ===

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Here you can find answers to the most common questions about the PrimeFish Framework.

*[[How_do_I_determine_my_competitive_position?|How do I determine my competitive position?]]
*[[How_do_I_know_where_my_new_product_will_succeed?|How do I know where my new product will succeed?]]
*[[How_much_would_a_customer_be_willing_to_pay_for_my_product?|How much would a customer be willing to pay for my product?]]
*[[How_can_I_find_what_the_pricing_trend_for_my_product_will_be_over_the_next_12_months?|How can I find what the pricing trend for my product will be over the next 12 months?]]
*[[How_do_I_find_information_on_how_to_survive_in_a_consolidating_market_place?|How do I find information on how to survive in a consolidating market place?]]
*[[Where_can_I_find_more_information_on_innovative_product_approaches_in_the_fisheries_market_place?|Where can I find more information on innovative product approaches in the fisheries market place?]]

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=== Quick Reference ===

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Useful links to project resources.

*[[The_Project|The Project]]
*[[Research_papers|Research papers]]
*[[WP1|Collected data]]

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=== Tools ===

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*[[CPA|CPA - Competitive Position Analyser]]

*[[GRA|GRA - Growth Risk Analyser]]

*[[PSC|PSC - Product Success Check]]

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*[[SFS|SFS - Success & Fails Stories]]

*[[VCA|VCA - Value Chain Analyser]]

*[[WTP|WTP - Willingness to Pay]]

|}

MediaWiki:Tweeki-navbar-left

2018-11-05T11:18:02Z

Jacandrade:

MediaWiki:Tweeki-navbar-left

2018-11-05T11:16:17Z

Jacandrade:

MediaWiki:Tweeki-navbar-left

2018-11-05T11:15:56Z

Jacandrade:

WP2

2018-10-25T01:27:49Z

Jacandrade:

= Work Package 2: Economic performance and prices =

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== General information ==

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WP2 analyses economic performance of the European fisheries and aquaculture sectors using aggregate data obtained from available public sources as well as detailed data from individual companies. This will allow for comparison of the performance of these sectors within Europe, as well as between European countries and other relevant international players. In particular, detailed analysis of growth, productivity and forefront efficiency, using parametric and non-parametric methods, will be conducted on individual European case studies of the chosen species and compared with the performance of Canadian cod and Vietnamese pangasius producers. Additionally, WP2 analyses historically the behaviour of seafood prices in general, as well as the development of market prices of the chosen species, focusing especially on the “boom and bust” cycles characteristics. The outcome of the WP will be critical factors and bottlenecks in the economic performance of the salmon, freshwater trout, cod, sea-bass and bream and herring sectors (SO2).

=== Economic performance and prices ===

== Deliverables ==

=== [[Media:D2 4.pdf|D2.4 - Report on “boom and bust” cycles for selected European fisheries and farmed species]] ===

The seafood production and trade system is exposed to a variety of disruptions including fishery collapses, natural disasters, policy changes and price spikes. Especially the shocks caused by the latter are particularly negative for fisheries and aquaculture operations because they limit the ability to generalise or predict and, consequently, to adequately response to the market‘s shocks. The overall objective of PrimeFish is to enhance the economic sustainability of European fisheries and aquaculture sectors to inform operators and help them to identify potential risks and opportunities to build resilience in the global food system. As part of WP2 “Economic performance and prices” in PrimeFish, this deliverable is devoted to provide a detection of the component of time series of prices and an analysis of the occurrence for “boom and bust” cycles for the selected species studied in PrimeFish. (click title to download deliverable)

== Links & Resources ==

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*[http://www.primefish.eu/work-package-2-economic-performance-and-prices More]information on Work Package 2.
*Main project [http://www.primefish.eu website]
*[http://primefish.eu/project#WP2 WP2 Consortium]

File:D2 4.pdf

2018-10-25T01:25:31Z

Jacandrade:

WP2

2018-10-25T01:13:37Z

Jacandrade: Created page with " = Work Package 2: Economic performance and prices = ---- ---- == General information == ---- WP2 analyses economic performance of the European fisheries and aquaculture..."

= Work Package 2: Economic performance and prices =

----

----

== General information ==

----

WP2 analyses economic performance of the European fisheries and aquaculture sectors using aggregate data obtained from available public sources as well as detailed data from individual companies. This will allow for comparison of the performance of these sectors within Europe, as well as between European countries and other relevant international players. In particular, detailed analysis of growth, productivity and forefront efficiency, using parametric and non-parametric methods, will be conducted on individual European case studies of the chosen species and compared with the performance of Canadian cod and Vietnamese pangasius producers. Additionally, WP2 analyses historically the behaviour of seafood prices in general, as well as the development of market prices of the chosen species, focusing especially on the “boom and bust” cycles characteristics. The outcome of the WP will be critical factors and bottlenecks in the economic performance of the salmon, freshwater trout, cod, sea-bass and bream and herring sectors (SO2).

=== Economic performance and prices ===

== Deliverables ==

=== [[File:d2_4.pdf|D2.4 - Report on “boom and bust” cycles for selected
European fisheries and farmed species]] ===

The seafood production and trade system is exposed to a variety of disruptions including fishery
collapses, natural disasters, policy changes and price spikes. Especially the shocks caused by the latter
are particularly negative for fisheries and aquaculture operations because they limit the ability to
generalise or predict and, consequently, to adequately response to the market‘s shocks. The overall
objective of PrimeFish is to enhance the economic sustainability of European fisheries and aquaculture
sectors to inform operators and help them to identify potential risks and opportunities to build
resilience in the global food system. As part of WP2 “Economic performance and prices” in PrimeFish,
this deliverable is devoted to provide a detection of the component of time series of prices and an
analysis of the occurrence for “boom and bust” cycles for the selected species studied in PrimeFish. (click title to download deliverable)

== Links & Resources ==

----

*[http://www.primefish.eu/work-package-2-economic-performance-and-prices More]information on Work Package 2.
*Main project [http://www.primefish.eu website]
*[http://primefish.eu/project#WP2 WP2 Consortium]

MediaWiki:Tweeki-navbar-left

2018-10-24T13:19:26Z

Jacandrade:

File:Wtp figure i.png

2018-10-24T13:16:09Z

Jacandrade:

Deliverable 4.7

2018-10-24T13:15:53Z

Jacandrade:

= Willingness to Pay =

----

----

== Executive Summary ==

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The objective of this study was to investigate consumer demand and choice behaviour for fresh fish at the retail market. In particular, we examined consumer preferences for different fish alternative species, as well as different attributes, using a labelled choice experiment (LCE). The outcomes allow to elicit consumers’ preferences and willingness to pay (WTP) for the salient attributes of a variety of fresh fish species in the retail market. Data for this study were collected in June 2017 through a nationwide online survey administered in the five countries (Italy, France, Spain, UK and Germany) by a third-party contractor using its consumer panel database. The sample in each country consisted of approximately 500 fish consumers (2,509 in total), representative of the national populations. The final experimental design consisted in five attributes, defined for the seven fish alternatives (trout, herring, salmon, sea bass, sea bream, cod and pangasius): price (average market price +/-30%), production method (wild-caught, farm-raised), format (whole/round cut, fillet, ready-to-cook), sustainability certification, nutrition and health claim. The questionnaire included questions regarding socio-demographics, fish frequency of consumption, past consumption, level of responsibility in fish purchasing and cooking, fish choice motives, attitude towards environmental concerns, attitude towards health concerns, self-efficacy, trust, and attitude towards ready-to-cook fish.

The part-worth, i.e. the marginal utility associated with the single attribute/level, and the price premium (WTP) have been estimated applying two different logit models:

*the first one with fish species-specific effects (FSSE); this is needed for obtaining WTP

specific for the seven species;

*the second one with random price effect (RPE) models; this is needed for

segmentation.

Based on the questions of the survey about the fish choice motives, value for money, price and general appearance are the most important aspects considered by consumers in their fish selection. However, in Italy wild-caught and days since catch/harvest are relevant aspects, in France, Germany and in the UK the easy-to-cook products are more important, and the sustainability certification is relatively more quoted in Germany. Regarding attitudinal beliefs, consumers are more worried about the negative consequences of fishing on marine resources, than those of fish farming on the environment, and believe that fish consumption has more benefits than risks. Consumers’ trust in information provided about the sustainable fish production is higher for independent organisations and public authorities, than for industries and retailers. Trust for farmers and fishermen is higher than trust for industry and retailers in every country. In general, consumers show a rather negative perception about ready-to-cook products, in terms of risk of losing the original fish characteristics. The choice experiment has shown that, in general, the fish species with the highest choice probability is salmon in France, Germany, Spain and in the UK, and seabream in Italy. As Figure 1 shows, the choice probability varies across countries, therefore justifying the application of a model where the attribute part-worth are estimated separately for every species.

[[File:Wtp figure i.png|center|Figure i]] ''Figure i: Choice probability for fish species (mean value) estimated with FSSE model.''

The results show that, in general, wild-caught fish is more appreciated than farm-raised. However, the WTP estimates varies between countries and species, with highest premiums found in France for salmon (+58%), and for seabass in Germany (+51%); Spanish consumers exhibited the lowest premiums for wild-caught fishes. Ready-to-cook products are generally preferred to whole (or round cut) fish in all countries, except with round-cut salmon, with higher premiums found in Germany, UK and France, in particular for pangasius, herring and cod. Fish fillets preference is more species-specific: salmon, cod and seabream fillet are generally preferred to ready-to-cook alternatives, while ready-to-cook trout and pangasius are more appreciated than fillets. The results show positive premiums for a sustainability label, with high heterogeneity across species and countries. The highest premiums have been found in the UK for herring (above 60%), in Germany for seabream, seabass and pangasius (above 40%), in Spain for trout and pangasius (above 30%), in Italy for cod, herring and pangasius (above 20%), and in France for salmon (above 20%).

The WTP for nutritional and health claims varied among countries too, with higher premium found for pangasius and salmon. Price premiums above 20% were found in Spain for pangasius (68%), trout (37%) and salmon (20%), in Germany for pangasius (44%), seabream (30%) and salmon (24%), in Italy for seabream (27%) and salmon (21%), in the UK for pangasius (26%). The relatively low willingness to pay of French consumers for both sustainability label and nutritional and health claim can be partially explained by their weak belief strength in the benefits of sustainability certification to the environment and society, and in the nutrition and health claim. The clusters resulting from the segmentation, based on the choice probabilities, exhibited a higher willingness to pay for fish species and attributes as follows:

*In Italy, the first cluster is the largest (36% of the sample), and exhibits a higher WTP

in general for all fish species and attributes. It is indeed one of the least sensitive to price changes. Mostly composed of females, middle aged, highly educated and with high income level, living in a medium-large family.

*In France, the first two segments (overall 45%) have the largest WTP scores for all fish

species and attributes, including a higher WTP for ready-to-cook products. Consumers in these two segments are less sensitive to price changes. The first one is mostly made up of younger males, highly educated and with high income level, living in two-three people families. The second segment is mostly composed of older females, highly educated and with high income level, living in larger-sized families (four members).

*In Germany, the segment one (28% of the sample), is the one with the highest

estimated WTP for all species and attributes. It is almost equally composed of young males and females, with medium-to-high educational level, and high incomes, mostly living with small family units (one or two members).

*In the UK, segment four (19%) is the one with the highest estimated WTP; middle-aged

and older females are more represented, as well as middle educated and income levels, and mostly living in families with two members.

*In Spain, segment two (18% of the sample), showing the highest WTPs, is composed

of young males, with high income, living in large family units (four people or more). Segment three (19%), showing medium-high WTP estimates, is relatively more represented by older females, with low income level, living in small family units.

 

== Introduction ==

----

The average apparent fish consumption per capita in the EU is the second highest in the world (at around 22 kg/capita/year), and some individual EU Member States are among the highest fish consuming countries in the world (EEA, 2016). The EU is the largest market in the world for fish; with a value of €55 billion and a volume of 12 million tons (FAO, 2016). While EU fish and seafood consumption has risen over the past 10 years with stable or declining supply from the fisheries sector, most of this increase has come from imports rather than from EU aquaculture. In 2014, around 75% of fisheries and aquaculture products consumed in the EU came from marine capture fisheries, which remains consistent with trends over the last decade (EUMOFA, 2015). Today 25% of all EU seafood consumption comes from EU fisheries, 10% from EU aquaculture and 65% from imports from third countries, both fisheries and aquaculture products. European aquaculture growth has stagnated since the turn of the century partly because its products have not been competitive compared with imports. In a market driven by the demand a better understanding of consumer purchasing behaviour towards fish products is paramount to developing more effective marketing and policy strategies (Carlucci et al., 2015). Therefore, understanding the consumers’ preferences across the EU countries for fish species and fish product attributes is crucial to sustain the fisheries and aquaculture sectors. The objective of this study was to investigate consumer demand and choice behaviour for fresh fish at the retail market. In particular, we examined consumer preferences for different fish alternative species, as well as different attributes. The outcomes allowed us to elicit consumers’ preferences and willingness to pay (WTP) for the salient attributes of a variety of fresh fish species in the retail market. We applied a discrete choice experiment (DCE) to accomplish this objective; this method is strongly consistent with the economic demand theory and in particular with the multi-attribute demand studies based on the Lancastrian consumer theory (Lancaster, 1966), This theory assumes that consumer’s utility stems from product properties rather than the products themselves. Thus, multi-attribute demand models can elicit the intrinsic value of the product attributes and have been applied widely in marketing research. Moreover, this method is highly flexible with respect to data collection and model specifications. DCE is based on random utility theory about individual decision making, and seems realistic in imitating real shopping behaviour (Louviere et al., 2000). Choice modelling techniques are multi-attribute valuation techniques that elicit values for multiple attributes by asking respondents to rate, rank or choose a set of attributes (levels). In particular, choice experiments are valuation techniques where respondents have to make trade-offs and indicate their preferred option out of a set of alternatives. We developed a choice-based on-line experiment, on a number of 500 respondents per country (Italy, France, Spain, UK and Germany). The profile attributes and levels analysed are derived from previous qualitative tasks (i.e., qualitative analysis by in-person interviews), and include product innovation features such as health claims, sustainability certification, etc. To accommodate the evaluation of choice alternatives through both attribute judgment and alternative comparison, we applied a labelled choice experiment (LCE), where choice alternatives were labelled by the respective names of the seafood (e.g., salmon, cod, herring, etc.) (Nguyen et al., 2015). We set our model specification in such a way that the constant terms, which represent intrinsic value of the alternatives, and attribute parameters were varied both over fish alternatives and across countries. The WTP associated with each attribute, by species and country, was also estimated.

 

== Methods ==

----

We applied a labelled choice experiment (LCE) to investigate consumer demand and choice behaviour for fresh fish in a retail market hypothetical situation in five European countries: Italy, France, Spain, UK and Germany. The LCE was conducted for seven fish alternatives (i.e., cod, herring, seabass, seabream, salmon, trout and pangasius) labelled by the respective fish names. Consumer heterogeneity in preference was expressed by estimating a labelled latent class model with alternative-specific effects, which varies choice probability and model parameters over seafood alternatives and across classes. The WTP for extrinsic attributes (i.e., product format, production method, health claim, and sustainability certification), and the rank orderedintrinsic value are estimated for each seafood alternative within classes and the entire market. The WTP estimate in our study is expected to be more accurate than those derived from studies based on single product alternatives because the LCE allows respondents to evaluate choice alternatives through both attribute judgment and alternative comparison. Exploring a variety of product alternatives is also meaningful to firms with multiple products (e.g., fresh fish retailers) or firms with many direct competitors.

=== 2.1 The choice experiment ===

The choice experiment was preceded by a cheap talk aiming at explaining the rationale behind the experiment and the need to respond carefully to the questions: “In this part of the questionnaire you will be asked to choose your preferred product from a set of 7 alternative products. Options A to G represent 7 different descriptions of a fish product. Please mark the displayed. Experience from previous similar surveys suggests that people often respond in one way but act in another. For instance, people sometimes state they would pay a higher price for a product than they actually would in reality. Therefore, please do consider thoroughly how the price would affect your budget, so that you are able to give as accurate an answer as possible. Similarly to the price, pay attentions to all fish alternatives and attributes“. At the end of the choice experiment, each consumer had to respond to the following questions in order to quantify the potential purchase: “What quantity would you purchase of the above product?“ Then, we have also asked consumers about their beliefs of health benefit claims and of the benefits of the sustainable certification to the environment and society, by answering the following questions: “In the marketplace, some producers provide health benefit information from consuming their products. On a scale of 0-100, to what extent do you believe such health benefit claims? (e.g., 0 = completely unbelievable; 50 = neutral; 100 = completely believable).“ “We assume you have read the definition of sustainability certification above. On a scale of 0-100, to what extent do you believe in the benefits of such certification to the environment and society? (e.g., 0 = completely unbelievable; 50 = neutral; 100 = completely believable).“

=== 2.2 Attributes and levels ===

A previous qualitative study was performed with 30 individual in-depth interviews conducted in five countries identifying the positive or negative motives, perceptions, associations, attitudes towards fish/seafood consumption, with a focus on the chosen species: salmon, trout, seabass/seabream, herring and cod (Task 4.2). The findings of this qualitative work were collected considering the main attributes, barriers and format used by consumers for fish in general and for the selected fish species. These findings were summarized in Table A1 (see Appendix). This table 1 has been used to identify the main attributes that were mentioned quite uniformly across all fish species. Therefore, the following attributes were evaluated for all the different fish species:

*production method (farmed / wild caught)
*origin (specific countries to be agreed specie by specie)
*nutritional and health claims (high in omega-3, source of omega-3, etc.)
*date of catch / harvest (as a proxy of freshness)

Other attributes were instead relevant for specific fish species:

*format (fillet, whole, frozen, etc.)
*preparation (processed, “ovenable tray”, etc.)
*sustainability (MSC, organic, etc.)
*traceability

This preliminary set of attributes was represented in Table A22 (see Appendix), including: price, origin, production method, format, preparation, sustainability, health / nutrition claim and freshness. This list was discussed in the WP4 meeting in Paris (January 2017). From the discussion, we agreed to simplify the design, suggesting to concentrate the experiment on a more limited, and manageable, set of attributes and levels. Therefore, the final experimental design consisted in five attributes, defined for the seven fish alternatives: price, production method, format, sustainability certification, nutrition and health claim (Table 1). Table 2 provides the complete list specific for each fish species.

''Table 1. Attributes and levels for the choice experiment in the five countries and for the seven'' fish species (trout, herring, salmon, sea bass, sea bream, cod and pangasius).

{| class="wikitable" style="width: 100%;"
|-
! Attributes
! Levels
|-
! scope="row" | Price
|
*Average market price
*-30%
*+30%

|-
! scope="row" | Production method
|
*Wild-caught fish
*Farm-raised fish

|-
! scope="row" | Format (picture)
|
*Whole fish/round cut*
*Fillet
*Easy to cook

|-
! scope="row" | Sustainability certification
|
*No
*Yes

|-
! scope="row" | Nutrition and Health claim
|
*No
*Yes

|}

*Round cut for salmon and pangasius

''Table 2: Final list of attributes and levels by fish species, common in the five countries.''

{| class="wikitable"
|-
! scope="col" | Attributes
! scope="col" | Trout
! scope="col" | Herring
! scope="col" | Salmon
! scope="col" | Sea bass
! scope="col" | Sea bream
! scope="col" | Cod
! scope="col" | Pangasius
|-
! scope="row" | Price
|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|-
! scope="row" | Production method
|
Farm-raised fish

|
Wild-caught fish

|
*Wild-caught fish
*Farm-raised fish

|
*Wild-caught fish
*Farm-raised fish

|
*Wild-caught fish
*Farm-raised fish

|
*Wild-caught fish
*Farm-raised fish

|
Farm-raised fish

|-
! scope="row" | Format (picture)
|
*Whole fish
*Fillet
*Ready to cook

|
*Whole fish
*Fillet
*Ready to cook

|
*Round cut
*Fillet
*Ready to cook

|
*Whole fish
*Fillet
*Ready to cook

|
*Whole fish
*Fillet
*Ready to cook

|
*Whole fish
*Fillet
*Ready to cook

|
*Round cut
*Fillet
*Ready to cook

|-
! scope="row" | Sustainability certification
|
*No
*Yes

|
*No
*Yes

|
*No
*Yes

|
*No
*Yes

|
*No
*Yes

|
*No
*Yes

|
*No
*Yes

|-
! scope="row" | Nutritional and Health claim
|
*No
*Yes*

|
*No
*Yes*

|
*No
*Yes*

|
*No
*Yes*

|
*No
*Yes*

|
*No
*Yes*

|
*No
*Yes*

|}

'''* Product high of omega 3 fatty acids which contributes to maintenance of normal function of the heart and normal blood pressure''' (the beneficial effect is obtained with a daily intake of 250 mg of omega 3 fatty acids. Such amount can be consumed as part of a balanced diet).

For the definition of the attribute price, we have provided some indication by email3 to the reference project partners for each country, suggesting to have, as much as possible, an yearly average market price level (at the retail stage) from an official data source (e.g., governmental/Ministry agencies, like ISMEA in Italy, etc.), possibly for year 2016. The price was indicated in €/kg potentially paid by consumers (£/kg in the UK), more detailed as possible (also with decimals), and considered for the average product/format (fresh product). If the data was not retrieved data from official source, we suggested to search it from other renowned sources (e.g., producers associations or syndicates, or the industry reference group), or from other sources (e.g., grey literature). The last possibility suggested was to perform a shop check to get the missing price(s); in this case, we have suggested to visit multiple shops of different format (large retailers, fishmongers, etc.), and calculate an average price. We have also suggested, if possible, to get the data also different geographical locations. For practical purposes, we have provided a table with some price levels downloaded by [http://www.eumofa.eu/ http://www.eumofa.eu/]. The average prices, with corresponding levels +/- 30%, are reported in Table 3.

The production method attribute (wild / farmed) is usually considered relevant in purchasing decision, where wild fish is generally perceived as being superior to farmed fish by the majority of consumers in terms of taste, safety, healthiness and nutritional value (Carlucci et al., 2015). However, consumers’ perception of farmed fish is also positive for popular cultivated species, such as seabass, seabream, trout and salmon. Considering these patterns, we have decided to include the production method in the experimental design. The format attribute was presented as a picture to consumers. The pictures has been done by a professional agency based on our suggestions. The first shots have been commented by the partners, and several modifications have been suggested, in particular for the ready-tocook level. The final set of pictures, specific by fish species and country, is reported in Table A3 (see Appendix).

The sustainability certification attribute was based on the following definition, provided to respondents before the choice experiment, mostly derived from the Marine Stewardship Council (MSC) and Aquaculture Stewardship Council (ASC) standards:''When certified'' according to a sustainability scheme, any fish can be traced back to a fishery or to a fish farm that meets principles reflecting the maintenance and re-establishment of healthy populations of targeted species, the maintenance of the integrity of ecosystems, the use of feed and other inputs that are sourced responsibly, and the social responsibility for workers and communities impacted by fishing and fish farming. This standard is intended to be used on a global basis by accredited third party certifiers to undertake the certification of fisheries and fish farmers to the above mentioned principles and criteria

The nutrition and health claim used in the experiment is “Product high of omega 3 fatty acids which contributes to maintenance of normal function of the heart and normal blood pressure”, with the following condition of use: “the beneficial effect is obtained with a daily intake of 250 mg of omega 3 fatty acids. Such amount can be consumed as part of a balanced diet”. This claim has already been approved by the EFSA (2009; 2010).

''Table 3: Price levels (€/kg, and £/kg for the UK) by fish species for each country''

{| class="wikitable" style="width: 100%;"
|-
!  
! scope="col" | Trout
! scope="col" | Herring
! scope="col" | Salmon
! scope="col" | Seabream
! scope="col" | Seabass
! scope="col" | Cod
! scope="col" | Pangasius
|-
! colspan="8" scope="row" | France
|-
| Price + 30%
| 16.64
| 12.87
| 19.37
| 14.95
| 18.59
| 19.37
| 11.05
|-
| Avg. price
| 12.80
| 9.90
| 14.90
| 11.50
| 14.30
| 14.90
| 8.50
|-
| Price -30%
| 8.96
| 6.93
| 10.43
| 8.05
| 10.01
| 10.43
| 5.95
|-
! colspan="8" scope="row" | Spain
|-
| Price + 30%
| 7.76
| 15.47
| 16.73
| 12.83
| 14.35
| 15.60
| 6.80
|-
| Avg. price
| 5.97
| 11.90
| 12.87
| 9.87
| 11.04
| 12.00
| 5.23
|-
| Price -30%
| 4.18
| 8.33
| 9.01
| 6.91
| 7.73
| 8.40
| 3.66
|-
! colspan="8" scope="row" | Italy
|-
| Price + 30%
| 13.66
| 12.87
| 19.63
| 14.07
| 15.37
| 15.87
| 7.28
|-
| Avg. price
| 10.51
| 9.90
| 15.10
| 10.82
| 11.82
| 12.21
| 5.60
|-
| Price -30%
| 7.36
| 6.93
| 10.57
| 7.57
| 8.27
| 8.55
| 3.92
|-
! colspan="8" scope="row" | Germany
|-
| Price + 30%
| 15.05
| 14.12
| 21.89
| 21.71
| 21.84
| 21.78
| 6.83
|-
| Avg. price
| 11.58
| 10.86
| 16.84
| 16.70
| 16.80
| 16.75
| 5.25
|-
| Price -30%
| 8.11
| 7.60
| 11.79
| 11.69
| 11.76
| 11.73
| 3.68
|-
! colspan="8" scope="row" | UK (€/kg)
|-
| Price + 30%
| 21.83
| 6.81
| 20.97
| 28.09
| 30.73
| 20.68
| 13.48
|-
| Avg. price
| 16.79
| 5.24
| 16.13
| 21.61
| 23.64
| 15.91
| 10.37
|-
| Price -30%
| 11.75
| 3.67
| 11.29
| 15.13
| 16.55
| 11.14
| 7.26
|-
! colspan="8" scope="row" | UK (£/kg)
|-
| Price + 30%
| 19.32
| 6.03
| 18.56
| 24.86
| 27.20
| 18.30
| 11.93
|-
| Avg. price
| 14.86
| 4.64
| 14.27
| 19.12
| 20.92
| 14.08
| 9.18
|-
| Price -30%
| 10.40
| 3.25
| 9.99
| 13.39
| 14.64
| 9.86
| 6.42
|}

We have decided to exclude the attribute origin; indeed, this attribute has already been deeply studied in the literature (Carlucci et al., 2015). Moreover, a huge effect of the domestic origin has been documented: 145% WTP by Stefani et al. (2012), 108% by Mauracher et al. (2013), 100% by McClenachan et al. (2016). We have evaluated that this effect might overwhelm the impact of other attributes on the consumers’ choices. Therefore, since other attributes have been studied much less, we have preferred to exclude the origin from the experiment.

=== 2.3 Measures ===

Apart the choice experiment, the questionnaire included the following items: sociodemographics, frequency of consumption of fish, past consumption, level of responsibility in fish purchasing and cooking, fish choice motives, attitude towards environmental concerns, attitude towards health concerns, self-efficacy, trust, and attitude towards ready-to-cook fish. The survey questionnaire was developed and revised based on input from qualitative analysis and pre-tests. The questionnaire has been submitted online and was approx. 15 minutes long. The items with the asterisk (*) are common “bridge questions” with the survey performed in Task 5.4. The English version of the questionnaire is reported in the Appendix (see Appendix A4); the partners have translated the English version of the questionnaire in their national language (i.e. Italian, French, German and Spanish). Their versions were checked using a back-translation method to avoid semantic variance between countries.

The frequency of consumption of fish was measured by the following item: “Please indicate how often you consume fish (fresh, frozen, canned, smoked, ready to eat, etc.) at home, at restaurants and other food outlets (canteens, bars, etc.): Almost every day; 3-4 times a week; 1 or 2 times a week; 2-3 times a month; Once a month or less; Few times a year; Never” (*). This question has been replicated for every species considered in the experiment (salmon, trout, seabass, seabream, herring, cod, and pangasius). Past consumption was assessed by the following 7-point scaled item: “In the past 3 years has your fish consumption: strongly decreased – strongly increased” (*).

We have assessed the level of responsibility in fish purchasing and cooking by asking respondents to indicate the level of involvement in their household in fish purchasing, and in preparing and cooking fish (Not at all involved/Somewhat involved/Fairly involved/Completely involved).

Then we asked respondents to indicate the importance of each of the following attributes when purchasing fish: general appearance (*), free of smell (*), value for money (*), sustainability certification (*), easy to cook (*), low in calories (*), not previously frozen, wild caught, domestic origin, days since catch/harvest, organic certification, price (fish choice motives).

Attitude towards environmental concerns was assessed with two items (7-point scale, from ‘‘strongly disagree” to ‘‘strongly agree”): “I believe that fishing has negative consequences on marine resources” (*), “I believe that fish farming has negative consequences on the environment” (*).

We have measured attitude towards health concerns with two items (7-point scale, from ‘‘strongly disagree” to ‘‘strongly agree”): “I believe that eating fish containing omega-3 fatty acids benefits my health” (*), “I believe that eating fish would expose myself to substances (e.g. mercury, antibiotics, etc.) risking negative consequences on my health” (*).

We assessed self-efficacy with two items, using a 7-point scale (from ‘‘strongly disagree” to ‘‘strongly agree”): “I feel confident in evaluating the quality of the fish before buying it” (*), “I feel confident in cooking fish” (*).

Trust was defined by asking respondents the level of agreement (using a 7-point scale, from ‘‘strongly disagree” to ‘‘strongly agree”) with the following five statements: “I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by a: Public authority (e.g., the national Government or the EU) / Fish farmer or fisherman / Fish processing industry / Retailer / Independent organization (e.g., an NGO)”.

Attitude towards ready-to-cook fish was measured with four items using a 7-point scale (from ‘‘strongly disagree” to ‘‘strongly agree”): “I believe that ready-to-cook products would alter the original fish characteristics” (*), “I prefer to eat ready-to-cook fish because it allows me to save time” (*), “Preferably, I spend as little time as possible on meal preparation” (*), and “I prefer to eat ready-to-cook fish because it does not smell”.

 

=== 2.4 Data collection and sample ===

Data for this study were collected in June 2017 through a nationwide online survey administered in the five countries (Italy, France, Spain, UK and Germany) by a third-party contractor using its consumer panel database. The sample in each country consisted of approximately 500 fish consumers (2,509 in total), representative of the national populations in at least three of the following criteria: age, gender, educational level and geographical macro-areas (e.g. in Italy: North, Centre, South). The main sample characteristics are reported in Table 4.

''Table 4: Sample characteristics.''

{| class="wikitable"
|-
|  
! colspan="2" scope="col" | France
! colspan="2" scope="col" | Germany
! colspan="2" scope="col" | Italy
! colspan="2" scope="col" | Spain
! colspan="2" scope="col" | UK
! colspan="2" scope="col" | Total
|-
! scope="row" | Gender
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
|-
| Males
| 256
| 51.1%
| 262
| 52.2%
| 250
| 49.6%
| 260
| 51.9%
| 254
| 50.7%
| 1282
| 51.1%
|-
| Females
| 245
| 48.9%
| 240
| 47.8%
| 254
| 50.4%
| 241
| 48.1%
| 247
| 49.3%
| 1227
| 48.9%
|-
! scope="row" | Age
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
|-
| 18-24
| 61
| 12.2%
| 56
| 11.2%
| 51
| 10.1%
| 56
| 11.2%
| 49
| 9.8%
| 273
| 10.9%
|-
| 25-34
| 91
| 18.2%
| 101
| 20.1%
| 98
| 19.4%
| 97
| 19.4%
| 121
| 24.2%
| 508
| 20.2%
|-
| 35-44
| 113
| 22.6%
| 99
| 19.7%
| 117
| 23.2%
| 132
| 26.3%
| 105
| 21.0%
| 566
| 22.6%
|-
| 45-54
| 117
| 23.4%
| 130
| 25.9%
| 127
| 25.2%
| 114
| 22.8%
| 118
| 23.6%
| 606
| 24.2%
|-
| 55+
| 119
| 23.8%
| 116
| 23.1%
| 111
| 22.0%
| 102
| 20.4%
| 108
| 21.6%
| 556
| 22.2%
|-
! scope="row" | Education
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
|-
| Lower secondary education or below
| 92
| 18.4%
| 86
| 17.1%
| 197
| 39.1%
| 181
| 36.1%
| 79
| 15.8%
| 635
| 25.3%
|-
| Upper secondary education
| 140
| 27.9%
| 97
| 19.3%
| 156
| 31.0%
| 65
| 13.0%
| 149
| 29.7%
| 607
| 24.2%
|-
| University or college below a degree
| 97
| 19.4%
| 191
| 38.0%
| 68
| 13.5%
| 75
| 15.0%
| 71
| 14.2%
| 502
| 20.0%
|-
| Bachelor's or equivalent level
| 88
| 17.6%
| 58
| 11.6%
| 41
| 8.1%
| 116
| 23.2%
| 133
| 26.5%
| 436
| 17.4%
|-
| Postgraduate MSc or PhD
| 84
| 16.8%
| 70
| 13.9%
| 42
| 8.3%
| 64
| 12.8%
| 69
| 13.8%
| 329
| 13.1%
|-
! scope="row" | Geographical area
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
|-
| Rural area
| 164
| 32.7%
| 100
| 19.9%
| 93
| 18.5%
| 52
| 10.4%
| 113
| 22.6%
| 522
| 20.8%
|-
| Small sized urban area
| 170
| 33.9%
| 187
| 37.3%
| 208
| 41.3%
| 144
| 28.7%
| 180
| 35.9%
| 889
| 35.4%
|-
| Large urban area
| 167
| 33.3%
| 215
| 42.8%
| 203
| 40.3%
| 305
| 60.9%
| 208
| 41.5%
| 1098
| 43.8%
|-
! scope="row" | Coastline
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
|-
| Yes
| 160
| 31.9%
| 91
| 18.1%
| 215
| 42.7%
| 294
| 58.7%
| 184
| 36.7%
| 944
| 37.6%
|-
!  
! scope="col" | mean
! scope="col" | sd
! scope="col" | mean
! scope="col" | sd
! scope="col" | mean
! scope="col" | sd
! scope="col" | mean
! scope="col" | sd
! scope="col" | mean
! scope="col" | sd
! scope="col" | mean
! scope="col" | sd
|-
! scope="row" | BMI
! 25.2
! 5.6
! 26.8
! 6.9
! 25.2
! 5.2
! 25.5
! 4.8
! 31.2
! 15.5
! 26.8
! 8.9
|-
| Persons in household (n)
| 2.6
| 1.3
| 2.4
| 1.2
| 3.0
| 1.2
| 3.2
| 1.2
| 2.8
| 1.6
| 2.8
| 1.3
|-
| < 18 years (n)
| 0.7
| 1.0
| 0.4
| 0.7
| 0.6
| 0.8
| 0.8
| 0.9
| 0.7
| 1.2
| 0.6
| 1.0
|-
| > 60 years (n)
| 0.4
| 0.7
| 0.4
| 0.7
| 0.5
| 0.8
| 0.4
| 0.7
| 0.3
| 0.7
| 0.4
| 0.7
|- style="text-align: center;"
! scope="row" | Total (n)
| colspan="2" | 501
| colspan="2" | 502
| colspan="2" | 504
| colspan="2" | 501
| colspan="2" | 501
| colspan="2" | 2509
|}

=== 2.5 The experimental design ===

The experimental design resulted in 9 blocks of 8 choice sets with 7 product profiles plus the “no choice” option. Figure 1 shows an example of the layout of the choice set.

[[File:Wtp figure 1.jpg|Figure 1: Example of choice set.]] ''Figure 1: Example of choice set.''

 

== Models ==

=== 3.1 Descriptive analysis ===

The median values of fish consumption is reported in Table 5. In our samples, fish is more frequently consumed in Italy, France and Spain: ‘‘3-4 times a week” as a median value. As a median value, pangasius, herring and trout are the fish species less consumed in every country, whilst cod and salmon are those more consumed. Seabass and seabream are frequently consumed in the Mediterranean countries (Italy and Spain, in particular).

''Table 5: Frequency of fish consumption (median values).''

{| class="wikitable"
|-
!  
! Italy
! France
! Germany
! Spain
! UK
|-
! scope="2" | Trout
| Few times a year
| Few times a year
| Few times a year
| Few times a year
| Few times a year
|-
! scope="row" | Herring
| Few times a year
| Few times a year
| Few times a year
| Few times a year
| Never
|-
! scope="row" | Salmon
| Once a month
| Once a month
| Once a month
| Once a month
| Once a month
|-
! scope="row" | Seabass
| Once a month
| Few times a year
| Never
| Once a month
| Few times a year
|-
! scope="row" | Seabream
| Once a month
| Few times a year
| Never
| Once a month
| Never
|-
! scope="row" | Cod
| 2-3 times a month
| Once a month
| 2-3 times a month
| 2-3 times a month
| 2-3 times a month
|-
! scope="row" | Pangasius
| Few times a year
| Never
| Few times a year
| Few times a year
| Never
|-
! scope="row" | Fish
| 3-4 times a week
| 3-4 times a week
| 2-3 times a week
| 3-4 times a week
| 2-3 times a week
|}

Overall, 40% of the respondents increased fish consumption in the past 3 years, 16% decreased fish consumption in the same period, and 44% maintained the same level. The share of those who increased fish consumption is higher in the UK (45%) and Italy (43%), whilst the quota of those who decreased fish consumption is higher in France (20%), Germany (17%) and Spain (17%) (Figure 2).

[[File:Wtp figure 2.jpg|Figure 2: Evolution of fish consumption in the past 3 years.]] ''Figure 2: Evolution of fish consumption in the past 3 years.''

The level of involvement is high in all countries both for fish purchasing (83% are completely or fairly involved) and for fish preparing and cooking (79%). The level of involvement is higher in the UK, respectively, 86% and 84% (Figure 3).

[[File:Wtp figure 3.jpg|Figure 3: Level of involvement in fish purchasing in your household.]] ''Figure 3: Level of involvement in fish purchasing in your household.''

[[File:Wtp figure 4.jpg|Figure 4: Level of involvement in your household when preparing and cooking fish.]] ''Figure 4: Level of involvement in your household when preparing and cooking fish.''

Table 6 shows the fish choice motives expressed by the participants. Value for money, price and general appearance are the most important attributes in every country. However, in Italy wild caught and days since catch/harvest (likely as a proxi of freshness) are more important than price. Easy to cook is ranked as another important attribute in fish selection, in particular in France, UK and Germany. Sustainability certification is ranked as 5th and 6th aspect in fish selection, respectively, in Germany and Spain. Table 7 shows the level of agreement on the attitudinal beliefs attitude towards environmental concerns (AE), attitude towards health concerns (AH), self-efficacy (SE), trust in information about sustainable production (TI), attitude towards ready-to-cook fish (AR). The results about the attitudinal beliefs are also displayed in Figures 5-9.

''Table 6: Relative importance of different aspects in fish selection (1 = Not at all important; 7 = Extremely important).''

{| class="wikitable"
|-
|  
! colspan="2" scope="col" | France
! colspan="2" scope="col" | Germany
! colspan="2" scope="col" | Italy
! colspan="2" scope="col" | Spain
! colspan="2" scope="col" | UK
! colspan="2" scope="col" | Total
|-
! scope="row" | Fish choice motives
! scope="col" | Mean
! scope="col" | sd
! scope="col" | Mean
! scope="col" | sd
! scope="col" | Mean
! scope="col" | sd
! scope="col" | Mean
! scope="col" | sd
! scope="col" | Mean
! scope="col" | sd
! scope="col" | Mean
! scope="col" | sd
|-
| Value for money
| 5.63
| 1.24
| 5.15
| 1.39
| 5.61
| 1.17
| 5.62
| 1.27
| 5.33
| 1.42
| 5.47
| 1.31
|-
| Price
| 5.57
| 1.24
| 5.10
| 1.34
| 5.31
| 1.25
| 5.44
| 1.29
| 5.29
| 1.42
| 5.34
| 1.32
|-
| General appearance
| 5.43
| 1.49
| 5.19
| 1.48
| 5.66
| 1.38
| 5.38
| 1.47
| 5.01
| 1.65
| 5.33
| 1.51
|-
| Free of smell
| 4.81
| 1.64
| 4.77
| 1.64
| 5.17
| 1.48
| 5.34
| 1.49
| 4.90
| 1.76
| 5.00
| 1.62
|-
| Easy to cook
| 5.09
| 1.44
| 4.87
| 1.49
| 4.99
| 1.35
| 4.97
| 1.44
| 5.00
| 1.49
| 4.98
| 1.44
|-
| Days since catch/harvest
| 5.01
| 1.51
| 4.39
| 1.63
| 5.36
| 1.43
| 5.25
| 1.46
| 4.70
| 1.67
| 4.94
| 1.58
|-
| Sustainability certification
| 4.80
| 1.48
| 4.81
| 1.59
| 5.14
| 1.36
| 5.09
| 1.45
| 4.65
| 1.72
| 4.90
| 1.54
|-
| Domestic origin
| 5.01
| 1.47
| 4.13
| 1.57
| 5.26
| 1.42
| 4.97
| 1.49
| 4.35
| 1.68
| 4.74
| 1.59
|-
| Wild caught
| 4.77
| 1.44
| 4.01
| 1.47
| 5.39
| 1.34
| 4.74
| 1.49
| 4.33
| 1.64
| 4.65
| 1.55
|-
| Organic certification
| 4.60
| 1.45
| 4.04
| 1.69
| 4.94
| 1.45
| 5.00
| 1.47
| 3.92
| 1.77
| 4.50
| 1.64
|-
| Not previously frozen
| 4.54
| 1.61
| 3.88
| 1.55
| 5.11
| 1.54
| 4.81
| 1.58
| 4.16
| 1.70
| 4.50
| 1.66
|-
| Low in calories
| 4.28
| 1.61
| 3.89
| 1.65
| 4.45
| 1.61
| 4.62
| 1.50
| 4.16
| 1.77
| 4.28
| 1.65
|}

''Table 7: Level of agreement on the following attitudinal beliefs: attitude towards environmental concerns (AE), attitude towards health'' concerns (AH), self-efficacy (SE), trust in information about sustainable production (TI), attitude towards ready-to-cook fish (AR).

{| class="wikitable" style="width: 98%"
|-
! colspan="2" scope="col" |  
! colspan="2" scope="col" | France
! colspan="2" scope="col" | Germany
! colspan="2" scope="col" | Italy
! colspan="2" scope="col" | Spain
! colspan="2" scope="col" | UK
! colspan="2" scope="col" | Total
|-
! scope="row" style="width: 50%;" | Fish choice motives
! scope="row" | Att
! scope="row" | Mean
! scope="row" | sd
! scope="row" | Mean
! scope="row" | sd
! scope="row" | Mean
! scope="row" | sd
! scope="row" | Mean
! scope="row" | sd
! scope="row" | Mean
! scope="row" | sd
! scope="row" | Mean
! scope="row" | sd
|-
| I believe that fishing has negative consequences on marine resources.
| AE
| 4.73
| 1.43
| 4.39
| 1.41
| 4.02
| 1.53
| 4.39
| 1.52
| 4.27
| 1.41
| 4.36
| 1.48
|-
| I believe that fish farming has negative consequences on the environment.
| AE
| 4.38
| 1.47
| 3.79
| 1.44
| 3.74
| 1.51
| 3.88
| 1.66
| 4.14
| 1.44
| 3.98
| 1.52
|-
| I believe that eating fish containing omega-3 fatty acids benefits my health.
| AH
| 5.40
| 1.34
| 5.41
| 1.22
| 5.57
| 1.27
| 5.69
| 1.35
| 5.42
| 1.30
| 5.50
| 1.30
|-
| I believe that eating fish would expose myself to substances (e.g. mercury, antibiotics, etc.) risking negative consequences on my health.
| AH
| 3.99
| 1.53
| 3.79
| 1.42
| 3.95
| 1.50
| 4.19
| 1.61
| 3.64
| 1.56
| 3.91
| 1.54
|-
| I feel confident in evaluating the quality of the fish before buying it.
| SE
| 4.85
| 1.25
| 4.47
| 1.25
| 4.85
| 1.23
| 5.06
| 1.38
| 4.76
| 1.39
| 4.80
| 1.32
|-
| I feel confident in cooking fish.
| SE
| 4.97
| 1.28
| 4.88
| 1.33
| 5.11
| 1.29
| 5.38
| 1.32
| 5.14
| 1.48
| 5.09
| 1.35
|-
| I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by a public authority (e.g., the Government or the EU)
| TI
| 4.49
| 1.43
| 4.68
| 1.39
| 4.79
| 1.47
| 5.00
| 1.54
| 4.88
| 1.46
| 4.77
| 1.47
|-
| I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by a fish farmer or fisherman
| TI
| 4.71
| 1.38
| 4.53
| 1.35
| 4.65
| 1.37
| 4.85
| 1.36
| 4.69
| 1.39
| 4.68
| 1.37
|-
| I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by a fish processing industry
| TI
| 3.97
| 1.51
| 3.91
| 1.44
| 4.43
| 1.41
| 4.65
| 1.47
| 4.47
| 1.45
| 4.29
| 1.49
|-
| I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by a retailer
| TI
| 4.19
| 1.39
| 4.16
| 1.36
| 4.30
| 1.42
| 4.47
| 1.47
| 4.48
| 1.33
| 4.32
| 1.40
|-
| I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by an independent organization (e.g., an NGO)
| TI
| 4.89
| 1.34
| 4.81
| 1.34
| 4.91
| 1.41
| 4.96
| 1.52
| 4.93
| 1.38
| 4.90
| 1.40
|-
| I believe that ready-to-cook products would alter the original fish characteristics
| AR
| 4.91
| 1.32
| 4.45
| 1.15
| 4.47
| 1.25
| 4.95
| 1.39
| 4.52
| 1.21
| 4.66
| 1.28
|-
| I prefer to eat ready-to-cook fish because it allows me to save time
| AR
| 3.89
| 1.66
| 4.49
| 1.34
| 4.03
| 1.46
| 4.03
| 1.65
| 4.34
| 1.58
| 4.15
| 1.56
|-
| Preferably, I spend as little time as possible on meal preparation
| AR
| 3.74
| 1.64
| 4.35
| 1.45
| 3.92
| 1.53
| 3.82
| 1.71
| 4.14
| 1.56
| 3.99
| 1.60
|-
| I prefer to eat ready-to-cook fish because it does not smell
| AR
| 3.39
| 1.60
| 4.19
| 1.36
| 3.62
| 1.60
| 3.59
| 1.68
| 3.98
| 1.56
| 3.75
| 1.59
|}

''Note: all items are scored on the scale: 1 = Strongly disagree; 7 = Strongly agree.''

In general consumers are more warried about the negative consequences of fishing on marine resources, than those of fish farming on the environment (Figure 5). The concern is higher in France and lower in Italy.

[[File:Wtp figure 5.jpg|Figure 5: Attitude towards environmental concerns.]] ''Figure 5: Attitude towards environmental concerns.''

In general, respondents believe that fish consumption has more benefits than risks (Figure 6). The benefits are more appreciated in Spain, as well as the risks of negative consequences.

[[File:Wtp figure 6.jpg|Figure 6: Attitude towards health concerns.]] ''Figure 6: Attitude towards health concerns.''

In general consumers are more confident in cooking fish than in evaluating the quality of the fish before buying it (Figure 7).

[[File:Wtp figure 7.jpg|Figure 7: Self-efficacy.]] ''Figure 7: Self-efficacy.''

Consumers’ trust in information provided about the sustainable fish production is higher for independent organizations and public authorities, than for industries and retailers. Trust for farmers and fishermen is higher than trust for industry and retailers in every country. In France, the trust for fish farmers or fishermen is higher than for the public authority (Figure 8).

[[File:Wtp figure 8.jpg|Figure 8: Trust for information about sustainable fish production]] ''Figure 8: Trust for information about sustainable fish production.''

In general, consumers show a rather negative perception about ready-to-cook products, in terms of loss of original characteristics. The preference for ready-to-cook fish products because of saving time is lower than the risk of alter the original fish characteristics (Figure 9). This difference is much larger in France and Spain, while is lower in the UK. Only in Germany consumers’ preference for ready-to-cook fish products is higher than the risk of alter the original fish characteristics.

[[File:Wtp figure 9.jpg|Figure 9: Attitude towards ready-to-cook fish.]] ''Figure 9: Attitude towards ready-to-cook fish.''

Once having performed the choice experiment, the respondents had to state how they believed in the benefits of sustainability certification to the environment and society, and how they believed in the nutrition and health claim. The results are reported in Figure 10 and 11. The belief strength is generally higher for the sustainability certification scheme, while, for both labels, is lower in France compared to Spain, Italy and UK.

[[File:Wtp figure 10.jpg|Figure 10: Belief strength about the sustainability label.]] ''Figure 10: Belief strength about the sustainability label.''

Note: “We assume you have read the definition of sustainability certification above. On a scale of 0-100, to what extent do you believe in the benefits of such certification to the environment and society? (e.g., 0 = completely unbelievable; 50 = neutral; 100 = completely believable)

[[File:Wtp figure 11.jpg|Figure 11: Belief strength about the nutritional and health claim.]] ''Figure 11: Belief strength about the nutritional and health claim.''

Note: “In the marketplace, some producers provide health benefit information from consuming their products. On a scale of 0-100, to what extent do you believe such health benefit claims? (e.g., 0 = completely unbelievable; 50 = neutral; 100 = completely believable).

 

=== 3.2 The choice experiment results ===

Two different models were estimated:

*the first one with fish species-specific effects (FSSE); this is needed for obtaining WTP

specific for the 7 species;

*the second one with random price effect (RPE) models; this is needed for

segmentation.

 

=== 3.2.1 Model specification and estimation ===

According to Lancaster’s consumer theory (1966), consumer utility stems from product attributes, not the products themselves. In other words, consumer utility can be separated into part-worth utilities. The part-worth utilities equal consumers’ preference for corresponding attributes. In marketing research, the product attributes are classified into extrinsic and intrinsic attributes (Zeithaml, 1988; Olsen et al., 2008). Regardless of whether consumers are exposed to these attributes, they may be important signals of product quality and determinants of consumer preference.

The overall utility that a consumer obtains from consuming a seafood species j (Uj) can be expressed as:

[[File:Wtp eq 1.JPG|center|Equation 1.]]

It is generally assumed that an individual would choose a product alternative if the utility derived from this alternative is maximized compared to the other alternatives:

[[File:Wtp eq 2.JPG|center|Equation 2.]]

When facing a “basket” of seafood products, consumers assign a random utility to each product alternatives and select the one with the highest derived utility. Assuming that the stochastic components εj have independent and identical distributed (iid) forms, the probability of a consumer i choosing a fish product j(P( yij = 1 ) given by the multinomial logit (MNL) model (McFadden, 1974), is expressed in the following equation:

[[File:Wtp eq 3.JPG|center|Equation 3.]]

The MNL model presented in equation (3) is the basic choice model and has been approved to have several disadvantages such as assuming iid of the error and assuming the homogeneity of consumers’ preference. To overcome the limitations of MNL, there many advanced discrete choice models suggested such as the mixed logit models (random coefficient, scaled-multinomial logit, and generalized-multinomial logit) and the latent class model (LCM) (see Fiebig et al., 2010; Greene & Hensher, 2003). We estimated two types of models in this report to elicit the consumers’ WTP for fish attributes that are specific to particular fish species and for individual consumers, named as fish speciesspecific effect model (FSSE) and random (i.e price) parameter effect model. The fish species-specific effect (FSSE) model (fish j), is expressed as:

[[File:Wtp eq 4.JPG|center|Equation 4.]]

where β parameters are estimated for the j-th fish species and for the attributes production method (i.e. Method, as wild caught vs. farmed fish), product format (i.e. Format, as whole fish/round cut, fillet or ready-to-cook), nutritional and health claim (i.e. Health, as with/without nutritional and health claim), and sustainability label (i.e. Sustain, as with/without sustainability certification). The Random price effect (RPE) model is specified so that the price coefficients includes two components, such as the average effect of price and the individual variance of price effects, expressed as:

[[File:Wtp eq 5.JPG|center|Equation 5.]]

where αj, βk are fixed-effect coefficients, γ3 is random coefficient of price estimated for individual i. The specification of FSSE allows us to calculate the willingness to pay (WTP) for each of seven fish species in the choice experiment, while random price effect model allows us to elicit the WTP of each fish attributes at individual consumers’ level. The WTP for a non-monetary attribute is the price premium that consumers are willing to pay for obtaining a desired attribute level. The WTP for an attribute level A (e.g. health) from FSSE model in equation (4) is calculated as:

[[File:Wtp eq 6.JPG|center|Equation 6.]]

where 𝑊𝑇𝑃Aj is the price premium paid for obtaining a desired level of attribute A (i.e., product with health claim) of the fish j, and β𝐴𝑗 and β5𝑗 are the estimated coefficients of attribute A and price attributes of fish j. Similarly, the WTP for attribute A (not specific to fish species) at consumers' individual level (𝑊𝑇𝑃𝐴i) is calculated from model in equation (5) is:

[[File:Wtp eq 7.JPG|center|Equation 7.]]

We estimate the WTP specific to fish species with expectation that consumers‘ preference for fish quality attributes depends in specific species (Thong et al., 2015). For instance, consumers may prefer filleted cod to the whole fish cod, but they may prefer whole fish herring to the filleted herring. The WTP for fish quality attributes are calculated at individual consumers because the nature of heterogeneity of preference. The random price effect model also allows us to obtain choice probability for fish species at the individual consumer‘s level. The individual consumers‘ choice probability thus will be used for segmentations that are actionable for marketing strategy and developing the decision support system (DSS). The segments are derived in every country using SAS macros, and three parameter criterion: cubic clustering criterion (Sarle, 1983), Pseudo-F statistics (Calinski and Harabasz, 1974), and Pseudo-t squared statistics (Duda and Hart, 1973).

 

== Reports & Data ==

----

=== Data ===

==== '''Italy''' ====

Table 8 reports the coefficients estimates for models with fish species-specific effect (FSSE) in the Italian sample. The higher coefficient reported for seabass indicate that this species is the most preferred by the Italian consumers, followed by cod and seabream, while the least preferred is herring. Wild caught alternative is the most preferred comparted to the farm-raised fish for all species, with higher incidence for cod and seabass. Ready-to-cook products are preferred compared to whole or round cut in the case of cod, herring and pangasius, while is less preferred for salmon and seabream. Fish fillet is preferred than ready-to-cook products for salmon, seabream and cod, while is less preferred for trout and seabass. The sustainability label is generally appreciated for all species, where the effect is higher for cod, seabream, pangasius and trout. The nutritional and health claim is also generally appreciated, where higher scores are found for seabream, pangasius and cod. The willingness to pay is directly derived from these results, applying the formula (6). The results are shown in Table 9, where the price premium (in €/kg) and the marginal WTP (in % above or below the average price in Table 3) are reported. Considering the production method, the higher relative WTP has been found in the case of wild salmon, compared to the farmraised alternative (+48%). Again the higher marginal WTP for format attribute is found for salmon fillet and round cut compared to the ready-to-cook alternative (respectively, +70% and +38%). The higher WTP for the sustainability scheme was found for cod (+27%), while the WTP for nutritional and health claim is higher for seabream (+27%).

''Table 8: Fish Species-Specific Effect (FSSE) Model, β (mean and standard deviation) - Italy. '' [[File:Wtp table 8.JPG|center|WTP Table 8.]]

''Table 9: Italian consumers' WTP a price premium (in €/kg and % above or below the average'' market price) for specific fish attributes, based on the estimates of the FSSE model.'' [[File:Wtp table 9.JPG|center|WTP Table 9.]]

The random price effect (RPE) model, able to estimate the price coefficient for every single consumer, resulted in the mean effects (and standard deviation) reported in Table 10. The attribute effects, in this case, are computed without the interaction with the species (i.e. on average for all species). The higher utility score was found for wild caught fishes compared to the farm-raised ones, and for the sustainability label and nutritional and health claims. The WTP estimates, based on these effects, are reported in Table 11. These estimates are the mean values estimated for each consumer in the sample.

''Table 10: Random Price Effect (RPE) model, β (mean and standard deviation) - Italy. '' [[File:Wtp table 10.JPG|center|WTP Table 10.]]

Table 11: Italian consumers' WTP (in €/kg) for fish species and attributes, based on the estimates of the RPE model. [[File:Wtp table 11.JPG|center|WTP Table 11.]]

The choice probability for fish species is reported in Table 12. This probability is very similar using both models, indicating the robustness of the effects across the models. Seabream, seabass and salmon exhibit the higher choice probability, while herring and pangasius and trout the lowest.

Table 12: Choice probability for fish species (mean value, standard deviation, minimum and maximum) with Fish Species-Specific Effect (FSSE) and Random Price Effect (RPE) models - Italy. [[File:Wtp table 12.JPG|center|WTP Table 12.]]

We have derived five different segments, based on choice probabilities, shown in Table 13. The first cluster is the largest (36% of the sample), and exhibits a higher WTP in general for all fish species and attributes. It is indeed one of the least sensitive to price changes. Mostly composed by females, middle aged, high educated and with high income level, living in a medium-large family. The second segment (12% of the sample) exhibits a low WTP, compared to the other segments, and a high sensitivity to price changes. It is made of females (61%), with lower education level, mostly living in two people families. The third segment is the second large one (30%), and expressed a medium WTP for all species, and a medium-high WTP for sustainability label and wild-caught fishes. It shows a low sensitivity with price changes. It is mostly composed by men (53%), middle-high aged, both low and high educated, with medium income and large family units (> three people). The fourth segment, representing 20% of the sample, shows slightly higher WTP values compared to the third one, only with a higher sensitivity with price changes. It is mostly composed by men (58%), younger, with lower educational level, and lower income (even if the higher income level is well represented), and living in larger family units. The fifth sample is the smallest (3%), and exhibits a low WTP for all species and attributes, and high price sensitivity.

Table 13: Segmentation of the Italian market, based on individuals’ choice probabilities. [[File:Wtp table 13.JPG|center|WTP Table 13.]]

 

==== '''France''' ====

Table 14 reports the coefficients estimates in the French sample for models with fish speciesspecific effect (FSSE). The higher β coefficient reported for seabream, cod and seabass indicate that these species are the most preferred by the French consumers, while the least preferred are herring and pangasius. Wild caught alternative is preferred comparted to the farm-raised fish for all species, with higher incidence for seabream. Ready-to-cook products are preferred compared to whole or round cut for all species, except with salmon. Fish fillet is preferred than ready-tocook products for salmon and cod, while is less preferred for pangasius. The sustainability label is generally appreciated by consumers, with higher effects for seabass and pangasius. The nutritional and health claim is appreciated for seabass, whilst the other effects are less significant. The willingness to pay results, applying the formula (8), are shown in Table 15 where the price premium (in €/kg) and the marginal WTP (in % above or below the average price in Table 3) are reported. Considering the production method, the higher relative WTP has been found in the case of wild salmon, compared to the farm-raised alternative (+58% compared to average market price); high premiums have been also estimated for wild seabream (+34%) and wild cod (+33%). The higher marginal WTP for format attribute is found for salmon fillet and round cut compared to the ready-to-cook alternative (respectively, +58% and +48%). Round cut pangasius is the least accepted, with a WTP for ready-to-cook alternative of 72%. Significant price premiums are also estimated for ready-to-cook cod (35%) and herring (33%), compared to, respectively, round cut and whole alternatives. The higher price premium for the sustainability scheme was found for salmon (+23%), seabass (+20%) and pangasius (+17%); the WTP for nutritional and health claim is higher for seabass (+13%).

Table 14: Fish Species-Specific Effect (FSSE) Model, β (mean and std. deviation) - France. [[File:Wtp table 14.JPG|center|WTP Table 14.]]

Table 15: French consumers' WTP a price premium (in €/kg and % above or below the average market price) for specific fish attributes, based on the estimates of the FSSE model. [[File:Wtp table 15.JPG|center|WTP Table 15.]]

The random price effects (RPE) model results (mean and standard deviation) are reported in Table 16 where the β coefficients are shown. The higher utility score was found for salmon and cod, and for wild caught fishes compared to the farm-raised ones. To a lesser extent the β coefficients are also positive for the fillets compared to the ready-to-cook alternatives, and for the sustainability label. The WTP estimates, based on these effects, are reported in Table 17; the higher premiums are associated with salmon and cod (respectively, 24.6 and 20.6 €/kg), and with wild-caught fishes (3.2 €/kg). The relatively low willingness to pay of French consumers for both sustainability label and nutritional and health claim can be partially explained by their weak belief strength in the benefits of sustainability certification to the environment and society, and in the nutrition and health claim.

Table 16: Random Price Effect (RPE) model, β (mean and standard deviation) - France. [[File:Wtp table 16.JPG|center|WTP Table 16.]]

Table 17: French consumers' WTP (in €/kg) for fish species and attributes, based on the estimates of the RPE model. [[File:Wtp table 17.JPG|center|WTP Table 17.]]

The choice probability for fish species is reported in Table 18. This probability is very similar using both models, indicating the robustness of the effects across the models. Salmon, cod and seabream exhibit the higher choice probability, while pangasius and herring the lowest.

Table 18: Choice probability for fish species (mean value, standard deviation, minimum and maximum) with Fish Species-Specific Effect (FSSE) and Random Price Effect (RPE) models - France. [[File:Wtp table 18.JPG|center|WTP Table 18.]]

Finally, we have derived six different segments, based on choice probabilities, shown in Table 19. The first two segments (CL1 and CL2), representing overall 45% of the sample, have the largest WTP scores for all fish species and attributes, including a higher WTP for ready-tocook fishes compared to whole alternatives. These two clusters are less sensitive to price changes. The first segment is mostly composed by younger males, highly educated and with higher income level, living in two-three people families. The second segment is mostly composed by older females, highly educated and with higher income level, living in largersized families (four people). The third segment (29% of the sample) exhibits an average WTP, compared to the other segments. It is mostly made of males (53%), middle-high aged, less educated and with lower income, mostly living alone. The fourth and the fifth segments, representing 9% and 5% of the sample, show low price premiums compared to the other ones, exhibiting a higher sensitivity with price changes. Segment four is mostly composed by young females (64%), with lower education and income, living either alone or in larger families (four people or more). Segment six, representing 13% of the sample, exhibits a medium-low willingness to pay premium for all species, but with low sensitivity with price change. It is mostly composed by young males with medium educational level, and high income, living in larger family units (three and more components).

Table 19: Segmentation of the French market, based on individuals’ choice probabilities. [[File:Wtp table 19.JPG|center|WTP Table 19.]]

 

==== '''Germany''' ====

Table 20 reports the coefficients estimates in the German sample for models with fish speciesspecific effect (FSSE), with and without beliefs. Cod, salmon, trout and seabass reported the higher β coefficients, indicating that these species are the most preferred by German consumers. Wild caught alternative is the most preferred comparted to the farm-raised fish for all species, with higher β coefficient for seabass. Readyto-cook products are generally preferred compared to whole (or round cut) fishes and fillets, except for salmon, where fillet is preferred than ready-to-cook product. The sustainability label is generally appreciated for all species, with more significant effects where found for seabass and seabream. The nutritional and health claim reported higher coefficients for seabream and herring. The willingness to pay results, applying the formula (8), are shown in Table 21. Wild-caught seabass exhibits the highest premium compared to the farm-raised alternative (+51% above the average market price), followed by wild-caught salmon (+35%) and seabream (+32%). As said before, the ready-to-cook products are generally preferred, with highest premiums found for pangasius, cod and seabass, compared to the whole or round cut fish. Consumers are willing to pay 38% price premium for salmon fillets compared to ready-to-cook products. The higher marginal WTP for the sustainability label was found for seabream (+53%), pangasius (49%) and seabass (42%). The WTP for nutritional and health claim is higher for pangasius (+44%) and seabream (+30%).

Table 20: Fish Species-Specific Effect (FSSE) Model, β (mean and std. deviation) - Germany. [[File:Wtp table 20.JPG|center|WTP Table 20.]]

Table 21: German consumers' WTP a price premium (in €/kg and % above or below the average market price) for specific fish attributes, based on the estimates of the FSSE model. [[File:Wtp table 21.JPG|center|WTP Table 21.]]

The RPE model effects (β coefficients mean and standard deviation) are reported in Table 22. The higher utility score was found for salmon, trout and cod, and for wild-caught fishes compared to the farm-raised ones and for ready-to-cook products compared to whole or round cut fishes. The β coefficients are also significant for the sustainability label and nutritional and health claim. The WTP estimates, based on these effects, are reported in Table 23; the higher premiums are associated with salmon and trout (respectively, 28.5 and 22.6 €/kg), and with ready-to-cook (2.7 €/kg compared to the whole alternative) and wild-caught fishes (2.4 €/kg).

Table 22: Random Price Effect (RPE) model, β (mean and standard deviation) - Germany. [[File:Wtp table 22.JPG|center|WTP Table 22.]]

Table 23: German consumers' WTP (in €/kg) for fish species and attributes, based on the estimates of the RPE model. [[File:Wtp table 23.JPG|center|WTP Table 23.]]

Table 24 shows the choice probability for fish species. This probability is higher for salmon, trout and pangasius, while is lower for seabream and seabass.

Table 24: Choice probability for fish species (mean value, standard deviation, minimum and maximum) with Fish Species-Specific Effect (FSSE) and Random Price Effect (RPE) models - Germany. [[File:Wtp table 24.JPG|center|WTP Table 24.]]

We have derived four different segments, based on choice probabilities, shown in Table 25. The first cluster, representing 28% of the sample, is the one with the highest willingness to pay for all species and attributes, including the ready-to-cook alternatives. It is almost equally composed by young males and females, with medium-to-high educational level, and high incomes, mostly living with small family units (one or two members). Segment two is the smallest one (13.5%). It reports a low willingness to pay for all species and attributes, compared to the other segments. This segment is made by young and old people (middle aged less represented), with medium educational level, and high income, living in large family units (three people or more). The third segment is the largest (32%); it exhibits a medium willingness to pay for species and attributes. It is mostly composed by males, middle-old aged, average education, high income, and living in families with two people. Finally, the fourth segment (26%), reports a low willingness to pay for all species and attributes. It is made by middle-age females (59%), with low educational level, middle income and living in small family units.

Table 25: Segmentation of the German market, based on individuals’ choice probabilities. [[File:Wtp table 25.JPG|center|WTP Table 25.]]

 

==== '''UK''' ====

Table 26 reports the coefficients estimates in the UK sample for models with fish speciesspecific effect (FSSE). The high coefficients reported for salmon and cod indicate that these species are the most preferred by the UK consumers, while the least preferred are pangasius and seabass, exhibiting a negative β coefficient which denotes that these species decrease the consumers’ utility. Wild caught alternative are generally preferred, in particular seabass and salmon. Ready-to-cook products are preferred compared to while or round cut for all fish species, except for salmon. Fish fillet is preferred than ready-to-cook products for salmon and seabream, while it is less preferred for trout and pangasius. The sustainability label is mostly appreciated for herring and seabream, whilst it is detrimental for consumers’ utility in the case of pangasius. The nutritional and health claim is mostly appreciated for pangasius, salmon and trout. Table 10 shows the WTP estimates, in £/kg and as a % of the average price, applying the formula (8). The results show a +48% price premium consumers are willing to pay for wildcaught seabass compared to farmed alternative. The higher marginal WTP for format attribute have been found for ready-to-cook products, compared to whole/round cut fish, in the case of herring (81%), seabass (49%), cod (37%), trout (33%) and seabream (30%). Salmon fillet is preferred compared to the ready-to-cook alternative (+44%). The higher WTP for the sustainability scheme was found for herring (+62%), while the WTP for nutritional and health claim is higher for pangasius (+26%).

Table 26: Fish Species-Specific Effect (FSSE) Model, β (mean and standard deviation) – UK. [[File:Wtp table 26.JPG|center|WTP Table 26.]]

Table 27: UK consumers' WTP a price premium (in £/kg, €/kg (5) and % of the average market price) for specific fish attributes, based on the estimates of the FSSE model. [[File:Wtp table 27.JPG|center|WTP Table 27.]] ''(5) The exchange rate used is 1 GB £ = 1.16 €.''

The RPE model results are reported in Table 28, where the β coefficients (mean and standard deviation) are shown.

Table 28: Random Price Effect (RPE) model, β (mean and standard deviation) - UK. [[File:Wtp table 28.JPG|center|WTP Table 28.]]

Table 29: UK consumers' WTP (in £/kg and €/kg (6) ) for fish species and attributes, based on the estimates of the RPE model. [[File:Wtp table 29.JPG|center|WTP Table 29.]] ''6 The exchange rate used is 1 GB £ = 1.16 €.''

The higher utility score was found for salmon and cod, and for wild caught fishes compared to the farm-raised ones. Ready-to-cook products are generally preferred compared to the whole/round cut alternatives. To a lesser extent the β coefficients are also positive for the fillets compared to the ready-to-cook alternatives, and for the sustainability label. The WTP estimates, based on these effects, are reported in Table 29; the higher premiums for fish species are associated with salmon and cod (respectively, 23.4 and 21.8 €/kg). For the attributes, wild-caught fishes carry the higher premiums (1.8 €/kg), followed by ready-to-cook products compared to whole alternative (1.4 €/kg), and by fish fillets compared to ready-tocook ones (1.1 €/kg). The choice probability, reported in Table 30, indicate that salmon and cod are the most chosen alternatives, while pangasius, seabream and trout are the least preferred ones.

Table 30: Choice probability for fish species (mean value, standard deviation, minimum and maximum) with Fish Species-Specific Effect (FSSE) and Random Price Effect (RPE) models - UK. [[File:Wtp table 30.JPG|center|WTP Table 30.]]

We have derived four different segments for the UK market, based on choice probabilities (Table 31). The first segment (13%) is the one with the lowest WTP for all species and attributes, and the one more sensitive with price changes. It shows, compared to the other segments, a higher incidence of middle-aged females, with low education and low income, living in larger family units. Segment 2 is the largest one (41% of the sample), showing, compared to the other segment a medium-high WTP. Younger males are more represented, with higher educational level and income, and living in families with three or four members. The third segment (27%) shows low estimates of premium prices; it is mostly composed by females, with medium income level and education, living in small family units. Segment 4 (19%) is the one with the highest estimated WTP; middle-aged and older females are more represented, as well as middle educated and income levels, and mostly living in families with two members.

Table 31: Segmentation of the UK market, based on individuals’ choice probabilities. [[File:Wtp table 31.JPG|center|WTP Table 31.]]

 

==== '''Spain''' ====

Table 32 reports the coefficients estimates in the Spanish sample for models with fish speciesspecific effect (FSSE), with and without beliefs. Seabass, seabream and cod are the species with the highest β coefficients in the FSSE model, indicating a stronger preference of Spanish consumers for these products, while pangasius is the least preferred one. Wild-caught alternative are generally appreciated, while wild-caught seabass carrying the highest utility. Ready-to-cook products are preferred compared to while or round cut in the case of cod, pangasius and herring, while it is less preferred for salmon and seabream. This result is very similar to the Italian case. Fish fillets are generally preferred than ready-to-cook products apart from trout and pangasius. The sustainability label coefficient carrying the higher utility for consumers was found for trout, herring and seabream. The nutritional and health claim is generally appreciated, where higher scores are found for pangasius. The price premiums (in €/kg and % of the average price) that Spanish consumers are willing to pay for species and attributes, estimated with formula (8), are shown in Table 33. The higher relative WTP has been found in the case of wild-caught seabass, compared to the farm-raised alternative (+19%). Salmon fillet carries the higher premium compared to ready-to-cook alternative (+53%), whilst ready-to-cook trout is preferred than the fillet alternative, showing a 47% WTP. Consumers are willing to pay a premium for ready-to-cook pangasius compared to round cut and fillets, respectively, +36% and 32% premium. The higher WTP for the sustainability label and nutritional and health claim was found for trout (respectively, +33% and +37%) and pangasius (respectively, +30% and +68%).

Table 32: Fish Species-Specific Effect (FSSE) Model, β (mean and standard deviation) - Spain. [[File:Wtp table 32.JPG|center|WTP Table 32.]]

Table 33: Spanish consumers' WTP a price premium (in €/kg and % above or below the average market price) for specific fish attributes, based on the estimates of the FSSE model. [[File:Wtp table 33.JPG|center|WTP Table 33.]]

The RPE model effects (β coefficients mean and standard deviation) are reported in Table 34. The higher utility score was found for salmon, seabream, seabass and cod, and for wild-caught fishes compared to the farm-raised ones. The β coefficients are also significant for the sustainability label and nutritional and health claim. The WTP estimates, based on these effects, are reported in Table 35; the higher premiums for species are associated with salmon (mean premium 20.7 €/kg), seabream (18.4 €/kg) and cod (18.1 €/kg). The nutritional and health claim carries the highest premium among the attributes, with 1.1 €/kg.

Table 34: Random Price Effect (RPE) model, β (mean and standard deviation) - Spain. [[File:Wtp table 34.JPG|center|WTP Table 34.]]

Table 35: Spanish consumers' WTP (in €/kg) for fish species and attributes, based on the estimates of the RPE model. [[File:Wtp table 35.JPG|center|WTP Table 35.]]

Table 36 shows the choice probability for fish species. This probability is higher for salmon, seabream and trout, while is lower for herring and pangasius.

Table 36: Choice probability for fish species (mean value, standard deviation, minimum and maximum) with Fish Species-Specific Effect (FSSE) and Random Price Effect (RPE) models - Spain. [[File:Wtp table 36.JPG|center|WTP Table 36.]]

We have derived seven different segments, based on choice probabilities, shown in Table 37. The first cluster, which is the larger one (21%), shows medium price premiums, compared to the other clusters, for species and attributes. It is mostly made by young females, highly educated, with high income and relatively medium-large family units (four people). Segment 2 (18% of the sample), showing the highest WTPs, is composed by young males, with high income, living in large family units (four people or more). Segment 3 shows medium-high WTP estimates too (19% of the sample), is relatively more representative of older females, with lower income level, living in smaller family units. The fourth segment (19% of the sample) shows an average WTP for species and attributes. It is mostly composed by middle-aged males, less educated and with lower income. Segments 5, 6 and 7 are all exhibiting lower premiums estimates for species and attributes.

Table 37: Segmentation of the Spanish market, based on individuals’ choice probabilities. [[File:Wtp table 37.JPG|center|WTP Table 37.]]

 

=== Appendix ===

==== Synthesis of the qualitative phase ====

''Table A1: Familiarity, attributes, barriers, and format for fish species and countries, as retrieved from the qualitative phase (Task 4.1)''

[[File:Wtp table a1.JPG|center|WTP Table A1.]]

==== Preliminary list of attributes ====

''Table A2: Preliminary list of attributes and levels by species.''

[[File:Wtp table a2.JPG|center|WTP Table A2.]]

==== Pictures of the format attribute ====

''Table A3: Set of pictures of the format attribute, by species in each country.''

===== France =====

[[File:Wtp table a3 france.png|center|WTP Table A3 - France.]]

===== Germany =====

[[File:Wtp table a3 germany.png|center|WTP Table A3 - Germany.]]

===== Italy =====

[[File:Wtp table a3 italy.png|center|WTP Table A3 - Italy.]]

===== Spain =====

[[File:Wtp table a3 spain.png|center|WTP Table A3 - Spain.]]

===== UK =====

[[File:Wtp table a3 uk.png|center|WTP Table A3 - UK.]]

 

=== The questionnaire ===

'''Appendix A4: The questionnaire in the English version. (5 pages)''' [[File:Wtp question 1.JPG|center|WTP questionnaire page 1.]] [[File:Wtp question 2.JPG|center|WTP questionnaire page 2.]] [[File:Wtp question 3.JPG|center|WTP questionnaire page 3.]] [[File:Wtp question 4.JPG|center|WTP questionnaire page 4.]] [[File:Wtp question 5.JPG|center|WTP questionnaire page 5.]]

 

== References & Readings ==

----

=== Conclusions ===

The activity performed in Task 4.4, resulting in this Deliverable (D4.7), investigated consumer demand and choice behaviour for fresh fish using an online choice experiment. In particular, we examined consumer preferences in five countries for different fish alternative species and attributes, using a labelled choice experiment (LCE). The results in terms of part-worth associated with the single attributes allowed to estimate consumers’ willingness to pay (WTP) for the salient product characteristics. The heterogeneous choices and preferences across countries and species suggested the application of a model where the attribute part-worth were estimated separately for every species in every country (fish species-specific effects model – FSSE). Using a random price effect (RPE) model we estimated the effects and WTP for attributes at consumers’ individual level; the individual consumers‘ choice probability so estimated thus was used for segmentations in every country. These results are actionable for marketing strategy and useful input in the developing of the decision support system (PrimeDSS). In particular, using the WTP results of the FSSE model it will be possible to estimate, in the five countries, the consumers’ willingness to pay a premium for specific species-related attributes cumulated in a product profile with certain characteristics. In other words, the DSS user, by selecting the preferred characteristics of the given species in a specific country, will retrieve the estimated consumers’ willingness to pay for that product, based on the estimated model on the data collected. Given the representativeness of the sample in every country, this result will provide stakeholder with a clear guidance about the (hypothetical) consumers’ preferences for each product profile. Similarly, the segmentation performed using the RPE model will provide DSS users with more details about the characteristics of the market segment more attracted by the given product profile. In addition, RPE model effects will enable us to estimate price elasticities, in which cross price elasticities among fish species are not constant. With these outcome it will be possible to develop competitiveness clouds and vulnerability index. Finally, the present activity have been implemented in parallel with the survey in Task 5.4, with a number of common questions (the “bridge questions”) leaving the possibly to combine the results of both surveys in a more powerful tool to be implemented in the PrimeDSS. The results of WTP and price elasticity for markets and segments across the five surveyed countries, as well as the possibility to combine the survey in Tasks 4.4 and 5.4, will be further investigated in Tasks 5.4 and 5.5, and eventually used as an input for the PrimeDSS development in WP6 of the project.'

 

=== Acknowledgement ===

We gratefully acknowledge the Primefish project partners for having provided feedback and helpful input to the present research. In particular, we thank Birgit Hagen, Emilia Cubero Dudinskaya and Antonella Carcagnì (University of Pavia, Italy), José Luis Santiago CastroRial, (Centro Tecnológico del Mar - Fundación CETMAR, Spain), Dimitar Taskov (University of Stirling, United Kingdom), Sterenn Lucas (Institut National de la Recherche Agronomique – INRA, France), Bjorn Suckow (TTZ, Germany), and Olga Untilov (Universite de Savoie, France).

=== References ===

Calinski, T. & Harabasz, J. (1974). A Dendrite Method for Cluster Analysis. Communications in Statistics, 3, 1–27.

Carlucci D., Nocella G., De Devitiis B., Viscecchia R., Bimbo F., Nardone G. (2015). Consumer purchasing behaviour towards fish and seafood products. Patterns and insights from a sample of international studies. Appetite 84, 212–227.

Duda, R.O. & Hart, P.E. (1973). Pattern Classification and Scene Analysis, New York: John Wiley & Sons, Inc.

EEA (2016). Seafood in Europe: A food system approach for sustainability. European Environmental Agency Report No 25/2016.

EFSA (2009). Scientific Opinion on the substantiation of health claims related to EPA, DHA, DPA and maintenance of normal blood pressure (ID 502), maintenance of normal HDLcholesterol concentrations (ID 515), maintenance of normal (fasting) blood concentrations of triglycerides (ID 517), maintenance of normal LDL-cholesterol concentrations (ID 528, 698) and maintenance of joints (ID 503, 505, 507, 511, 518, 524, 526, 535, 537) pursuant to Article 13(1) of Regulation (EC) No 1924/2006. EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA), Parma (Italy).

EFSA (2010). Scientific Opinion on the substantiation of health claims related to eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), docosapentaenoic acid (DPA) and maintenance of normal cardiac function (ID 504, 506, 516, 527, 538, 703, 1128, 1317, 1324, 1325), maintenance of normal blood glucose concentrations (ID 566), maintenance of normal blood pressure (ID 506, 516, 703, 1317, 1324), maintenance of normal blood HDL-cholesterol concentrations (ID 506), maintenance of normal (fasting) blood concentrations of triglycerides (ID 506, 527, 538, 1317, 1324, 1325), maintenance of normal blood LDL-cholesterol concentrations (ID 527, 538, 1317, 1325, 4689), protection of the skin from photo-oxidative (UV-induced) damage (ID 530), improved absorption of EPA and DHA (ID 522, 523), contribution to the normal function of the immune system by decreasing the levels of eicosanoids, arachidonic acid-derived mediators and pro-inflammatory cytokines (ID 520, 2914), and “immunomodulating agent” (4690) pursuant to Article 13(1) of Regulation (EC) No 1924/2006. EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA), Parma (Italy).

EUMOFA (2015). The EU fish market — 2015 edition, European Market Observatory for Fisheries and Aquaculture Products. FAO (2016). The state of world fisheries and aquaculture. Contributing to food security and nutrition for all, Food and Agriculture Organization of the United Nations, Rome. Fiebig, D.G., Keane, M.P., Louviere, J.J, & Wasi, N. (2010). The generalized multinomial logit model: accounting for scale and coefficient heterogeneity. Marketing Science, 29(3), 393-421.

Greene, W.H., & Hensher, D.A. (2003). A latent class model for discrete choice analysis: contrasts with mixed logit. Transportation Research B, 37(8), 681-698.

Lancaster, K. J. (1966). A new approach to consumer theory. The Journal of Political Economy, 132–157.

Lancaster, K.J. (1966). A New Approach to Consumer Theory. Journal of Political Economics 74(2):132-57.

Louviere, J. J., Hensher, D. A., & Swait, J. D. (2000). Stated choice methods: Analysis and application. Cambridge UK: Cambridge University Press.

Mauracher C., Tempesta T., Vecchiato D. (2013). Consumer preferences regarding the introduction of new organic products. The case of the Mediterranean sea bass (Dicentrarchus labrax) in Italy. Appetite 63, 84–91.

McClenachan L., Dissanayake S.T.M., Chen X. (2016). Fair trade fish: consumer support for broader seafood sustainability. Fish and Fisheries 17, 825–838.

McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P.

Zarembka (ed.), Frontiers in Economics. New York: Academic Press.

Nguyen T.T., Haider W., Stubbe Solgaard H., Ravn-Jonsen L., Roth E. (2015). Consumer willingness to pay for quality attributes of fresh seafood: A labeled latent class model. Food Quality and Preference 41, 225–236.

Olsen, S.O., K. Toften, D.C. Dopico, A. Tudoran, & A. Kole. (2008). Consumer Evaluation of Tailor-Made Seafood Products. Improving seafood products for the consumer. Børresen, T. Eds, CRC Press.

Sarle, W.S. (1983). Cubic Clustering Criterion, SAS Technical Report A-108, Cary, NC: SAS Institute Inc.

Stefani G., Scarpa R., Cavicchi A. (2012). Exploring consumer’s preferences for farmed sea bream. Aquaculture International 20(4), 673–691.

Zeithaml, V.A. (1988). Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing 52(3): 2-22.

[[Category:Pages with broken file links]]

Deliverable 4.7

2018-10-24T13:14:03Z

Jacandrade: Created page with " = Willingness to Pay = ---- ---- == Executive Summary == ---- The objective of this study was to investigate consumer demand and choice behaviour for fresh fish at the r..."

= Willingness to Pay =

----

----

== Executive Summary ==

----
The objective of this study was to investigate consumer demand and choice behaviour for
fresh fish at the retail market. In particular, we examined consumer preferences for different
fish alternative species, as well as different attributes, using a labelled choice experiment
(LCE). The outcomes allow to elicit consumers’ preferences and willingness to pay (WTP)
for the salient attributes of a variety of fresh fish species in the retail market.
Data for this study were collected in June 2017 through a nationwide online survey
administered in the five countries (Italy, France, Spain, UK and Germany) by a third-party
contractor using its consumer panel database. The sample in each country consisted of
approximately 500 fish consumers (2,509 in total), representative of the national populations.
The final experimental design consisted in five attributes, defined for the seven fish
alternatives (trout, herring, salmon, sea bass, sea bream, cod and pangasius): price (average
market price +/-30%), production method (wild-caught, farm-raised), format (whole/round cut,
fillet, ready-to-cook), sustainability certification, nutrition and health claim. The questionnaire
included questions regarding socio-demographics, fish frequency of consumption, past
consumption, level of responsibility in fish purchasing and cooking, fish choice motives, attitude
towards environmental concerns, attitude towards health concerns, self-efficacy, trust, and
attitude towards ready-to-cook fish.

The part-worth, i.e. the marginal utility associated with the single attribute/level, and the price
premium (WTP) have been estimated applying two different logit models:

* the first one with fish species-specific effects (FSSE); this is needed for obtaining WTP
specific for the seven species;
* the second one with random price effect (RPE) models; this is needed for
segmentation.

Based on the questions of the survey about the fish choice motives, value for money, price
and general appearance are the most important aspects considered by consumers in their fish
selection. However, in Italy wild-caught and days since catch/harvest are relevant aspects, in
France, Germany and in the UK the easy-to-cook products are more important, and the
sustainability certification is relatively more quoted in Germany.
Regarding attitudinal beliefs, consumers are more worried about the negative consequences
of fishing on marine resources, than those of fish farming on the environment, and believe that
fish consumption has more benefits than risks. Consumers’ trust in information provided about
the sustainable fish production is higher for independent organisations and public authorities,
than for industries and retailers. Trust for farmers and fishermen is higher than trust for industry
and retailers in every country. In general, consumers show a rather negative perception about
ready-to-cook products, in terms of risk of losing the original fish characteristics.
The choice experiment has shown that, in general, the fish species with the highest choice
probability is salmon in France, Germany, Spain and in the UK, and seabream in Italy. As
Figure 1 shows, the choice probability varies across countries, therefore justifying the
application of a model where the attribute part-worth are estimated separately for every
species.

[[File:Wtp_figure_i.jpg|Figure i]]
''Figure i: Choice probability for fish species (mean value) estimated with FSSE model. ''

The results show that, in general, wild-caught fish is more appreciated than farm-raised.
However, the WTP estimates varies between countries and species, with highest premiums
found in France for salmon (+58%), and for seabass in Germany (+51%); Spanish consumers
exhibited the lowest premiums for wild-caught fishes.
Ready-to-cook products are generally preferred to whole (or round cut) fish in all countries,
except with round-cut salmon, with higher premiums found in Germany, UK and France, in
particular for pangasius, herring and cod. Fish fillets preference is more species-specific:
salmon, cod and seabream fillet are generally preferred to ready-to-cook alternatives, while
ready-to-cook trout and pangasius are more appreciated than fillets.
The results show positive premiums for a sustainability label, with high heterogeneity across
species and countries. The highest premiums have been found in the UK for herring (above
60%), in Germany for seabream, seabass and pangasius (above 40%), in Spain for trout and
pangasius (above 30%), in Italy for cod, herring and pangasius (above 20%), and in France
for salmon (above 20%).

The WTP for nutritional and health claims varied among countries too, with higher premium
found for pangasius and salmon. Price premiums above 20% were found in Spain for
pangasius (68%), trout (37%) and salmon (20%), in Germany for pangasius (44%), seabream
(30%) and salmon (24%), in Italy for seabream (27%) and salmon (21%), in the UK for
pangasius (26%). The relatively low willingness to pay of French consumers for both
sustainability label and nutritional and health claim can be partially explained by their weak
belief strength in the benefits of sustainability certification to the environment and society, and
in the nutrition and health claim.
The clusters resulting from the segmentation, based on the choice probabilities, exhibited a
higher willingness to pay for fish species and attributes as follows:

* In Italy, the first cluster is the largest (36% of the sample), and exhibits a higher WTP
in general for all fish species and attributes. It is indeed one of the least sensitive to
price changes. Mostly composed of females, middle aged, highly educated and with
high income level, living in a medium-large family.

* In France, the first two segments (overall 45%) have the largest WTP scores for all fish
species and attributes, including a higher WTP for ready-to-cook products. Consumers
in these two segments are less sensitive to price changes. The first one is mostly made
up of younger males, highly educated and with high income level, living in two-three
people families. The second segment is mostly composed of older females, highly
educated and with high income level, living in larger-sized families (four members).

*In Germany, the segment one (28% of the sample), is the one with the highest
estimated WTP for all species and attributes. It is almost equally composed of young
males and females, with medium-to-high educational level, and high incomes, mostly
living with small family units (one or two members).

*In the UK, segment four (19%) is the one with the highest estimated WTP; middle-aged
and older females are more represented, as well as middle educated and income
levels, and mostly living in families with two members.

*In Spain, segment two (18% of the sample), showing the highest WTPs, is composed
of young males, with high income, living in large family units (four people or more).
Segment three (19%), showing medium-high WTP estimates, is relatively more
represented by older females, with low income level, living in small family units.

== Introduction ==

----

The average apparent fish consumption per capita in the EU is the second highest in the world (at around 22 kg/capita/year), and some individual EU Member States are among the highest fish consuming countries in the world (EEA, 2016). The EU is the largest market in the world for fish; with a value of €55 billion and a volume of 12 million tons (FAO, 2016). While EU fish and seafood consumption has risen over the past 10 years with stable or declining supply from the fisheries sector, most of this increase has come from imports rather than from EU aquaculture. In 2014, around 75% of fisheries and aquaculture products consumed in the EU came from marine capture fisheries, which remains consistent with trends over the last decade (EUMOFA, 2015). Today 25% of all EU seafood consumption comes from EU fisheries, 10% from EU aquaculture and 65% from imports from third countries, both fisheries and aquaculture products. European aquaculture growth has stagnated since the turn of the century partly because its products have not been competitive compared with imports. In a market driven by the demand a better understanding of consumer purchasing behaviour towards fish products is paramount to developing more effective marketing and policy strategies (Carlucci et al., 2015). Therefore, understanding the consumers’ preferences across the EU countries for fish species and fish product attributes is crucial to sustain the fisheries and aquaculture sectors. The objective of this study was to investigate consumer demand and choice behaviour for fresh fish at the retail market. In particular, we examined consumer preferences for different fish alternative species, as well as different attributes. The outcomes allowed us to elicit consumers’ preferences and willingness to pay (WTP) for the salient attributes of a variety of fresh fish species in the retail market. We applied a discrete choice experiment (DCE) to accomplish this objective; this method is strongly consistent with the economic demand theory and in particular with the multi-attribute demand studies based on the Lancastrian consumer theory (Lancaster, 1966), This theory assumes that consumer’s utility stems from product properties rather than the products themselves. Thus, multi-attribute demand models can elicit the intrinsic value of the product attributes and have been applied widely in marketing research. Moreover, this method is highly flexible with respect to data collection and model specifications. DCE is based on random utility theory about individual decision making, and seems realistic in imitating real shopping behaviour (Louviere et al., 2000). Choice modelling techniques are multi-attribute valuation techniques that elicit values for multiple attributes by asking respondents to rate, rank or choose a set of attributes (levels). In particular, choice experiments are valuation techniques where respondents have to make trade-offs and indicate their preferred option out of a set of alternatives. We developed a choice-based on-line experiment, on a number of 500 respondents per country (Italy, France, Spain, UK and Germany). The profile attributes and levels analysed are derived from previous qualitative tasks (i.e., qualitative analysis by in-person interviews), and include product innovation features such as health claims, sustainability certification, etc. To accommodate the evaluation of choice alternatives through both attribute judgment and alternative comparison, we applied a labelled choice experiment (LCE), where choice alternatives were labelled by the respective names of the seafood (e.g., salmon, cod, herring, etc.) (Nguyen et al., 2015). We set our model specification in such a way that the constant terms, which represent intrinsic value of the alternatives, and attribute parameters were varied both over fish alternatives and across countries. The WTP associated with each attribute, by species and country, was also estimated.

 

== Methods ==

----

We applied a labelled choice experiment (LCE) to investigate consumer demand and choice behaviour for fresh fish in a retail market hypothetical situation in five European countries: Italy, France, Spain, UK and Germany. The LCE was conducted for seven fish alternatives (i.e., cod, herring, seabass, seabream, salmon, trout and pangasius) labelled by the respective fish names. Consumer heterogeneity in preference was expressed by estimating a labelled latent class model with alternative-specific effects, which varies choice probability and model parameters over seafood alternatives and across classes. The WTP for extrinsic attributes (i.e., product format, production method, health claim, and sustainability certification), and the rank orderedintrinsic value are estimated for each seafood alternative within classes and the entire market. The WTP estimate in our study is expected to be more accurate than those derived from studies based on single product alternatives because the LCE allows respondents to evaluate choice alternatives through both attribute judgment and alternative comparison. Exploring a variety of product alternatives is also meaningful to firms with multiple products (e.g., fresh fish retailers) or firms with many direct competitors.

=== 2.1 The choice experiment ===

The choice experiment was preceded by a cheap talk aiming at explaining the rationale behind the experiment and the need to respond carefully to the questions: “In this part of the questionnaire you will be asked to choose your preferred product from a set of 7 alternative products. Options A to G represent 7 different descriptions of a fish product. Please mark the displayed. Experience from previous similar surveys suggests that people often respond in one way but act in another. For instance, people sometimes state they would pay a higher price for a product than they actually would in reality. Therefore, please do consider thoroughly how the price would affect your budget, so that you are able to give as accurate an answer as possible. Similarly to the price, pay attentions to all fish alternatives and attributes“. At the end of the choice experiment, each consumer had to respond to the following questions in order to quantify the potential purchase: “What quantity would you purchase of the above product?“ Then, we have also asked consumers about their beliefs of health benefit claims and of the benefits of the sustainable certification to the environment and society, by answering the following questions: “In the marketplace, some producers provide health benefit information from consuming their products. On a scale of 0-100, to what extent do you believe such health benefit claims? (e.g., 0 = completely unbelievable; 50 = neutral; 100 = completely believable).“ “We assume you have read the definition of sustainability certification above. On a scale of 0-100, to what extent do you believe in the benefits of such certification to the environment and society? (e.g., 0 = completely unbelievable; 50 = neutral; 100 = completely believable).“

=== 2.2 Attributes and levels ===

A previous qualitative study was performed with 30 individual in-depth interviews conducted in five countries identifying the positive or negative motives, perceptions, associations, attitudes towards fish/seafood consumption, with a focus on the chosen species: salmon, trout, seabass/seabream, herring and cod (Task 4.2). The findings of this qualitative work were collected considering the main attributes, barriers and format used by consumers for fish in general and for the selected fish species. These findings were summarized in Table A1 (see Appendix). This table 1 has been used to identify the main attributes that were mentioned quite uniformly across all fish species. Therefore, the following attributes were evaluated for all the different fish species:

*production method (farmed / wild caught)
*origin (specific countries to be agreed specie by specie)
*nutritional and health claims (high in omega-3, source of omega-3, etc.)
*date of catch / harvest (as a proxy of freshness)

Other attributes were instead relevant for specific fish species:

*format (fillet, whole, frozen, etc.)
*preparation (processed, “ovenable tray”, etc.)
*sustainability (MSC, organic, etc.)
*traceability

This preliminary set of attributes was represented in Table A22 (see Appendix), including: price, origin, production method, format, preparation, sustainability, health / nutrition claim and freshness. This list was discussed in the WP4 meeting in Paris (January 2017). From the discussion, we agreed to simplify the design, suggesting to concentrate the experiment on a more limited, and manageable, set of attributes and levels. Therefore, the final experimental design consisted in five attributes, defined for the seven fish alternatives: price, production method, format, sustainability certification, nutrition and health claim (Table 1). Table 2 provides the complete list specific for each fish species.

''Table 1. Attributes and levels for the choice experiment in the five countries and for the seven'' fish species (trout, herring, salmon, sea bass, sea bream, cod and pangasius).

{| class="wikitable" style="width: 100%;"
|-
! Attributes
! Levels
|-
! scope="row" | Price
|
*Average market price
*-30%
*+30%

|-
! scope="row" | Production method
|
*Wild-caught fish
*Farm-raised fish

|-
! scope="row" | Format (picture)
|
*Whole fish/round cut*
*Fillet
*Easy to cook

|-
! scope="row" | Sustainability certification
|
*No
*Yes

|-
! scope="row" | Nutrition and Health claim
|
*No
*Yes

|}

*Round cut for salmon and pangasius

''Table 2: Final list of attributes and levels by fish species, common in the five countries.''

{| class="wikitable"
|-
! scope="col" | Attributes
! scope="col" | Trout
! scope="col" | Herring
! scope="col" | Salmon
! scope="col" | Sea bass
! scope="col" | Sea bream
! scope="col" | Cod
! scope="col" | Pangasius
|-
! scope="row" | Price
|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|
*Average market price
*-30%
*+30%

|-
! scope="row" | Production method
|
Farm-raised fish

|
Wild-caught fish

|
*Wild-caught fish
*Farm-raised fish

|
*Wild-caught fish
*Farm-raised fish

|
*Wild-caught fish
*Farm-raised fish

|
*Wild-caught fish
*Farm-raised fish

|
Farm-raised fish

|-
! scope="row" | Format (picture)
|
*Whole fish
*Fillet
*Ready to cook

|
*Whole fish
*Fillet
*Ready to cook

|
*Round cut
*Fillet
*Ready to cook

|
*Whole fish
*Fillet
*Ready to cook

|
*Whole fish
*Fillet
*Ready to cook

|
*Whole fish
*Fillet
*Ready to cook

|
*Round cut
*Fillet
*Ready to cook

|-
! scope="row" | Sustainability certification
|
*No
*Yes

|
*No
*Yes

|
*No
*Yes

|
*No
*Yes

|
*No
*Yes

|
*No
*Yes

|
*No
*Yes

|-
! scope="row" | Nutritional and Health claim
|
*No
*Yes*

|
*No
*Yes*

|
*No
*Yes*

|
*No
*Yes*

|
*No
*Yes*

|
*No
*Yes*

|
*No
*Yes*

|}

'''* Product high of omega 3 fatty acids which contributes to maintenance of normal function of the heart and normal blood pressure''' (the beneficial effect is obtained with a daily intake of 250 mg of omega 3 fatty acids. Such amount can be consumed as part of a balanced diet).

For the definition of the attribute price, we have provided some indication by email3 to the reference project partners for each country, suggesting to have, as much as possible, an yearly average market price level (at the retail stage) from an official data source (e.g., governmental/Ministry agencies, like ISMEA in Italy, etc.), possibly for year 2016. The price was indicated in €/kg potentially paid by consumers (£/kg in the UK), more detailed as possible (also with decimals), and considered for the average product/format (fresh product). If the data was not retrieved data from official source, we suggested to search it from other renowned sources (e.g., producers associations or syndicates, or the industry reference group), or from other sources (e.g., grey literature). The last possibility suggested was to perform a shop check to get the missing price(s); in this case, we have suggested to visit multiple shops of different format (large retailers, fishmongers, etc.), and calculate an average price. We have also suggested, if possible, to get the data also different geographical locations. For practical purposes, we have provided a table with some price levels downloaded by [http://www.eumofa.eu/ http://www.eumofa.eu/]. The average prices, with corresponding levels +/- 30%, are reported in Table 3.

The production method attribute (wild / farmed) is usually considered relevant in purchasing decision, where wild fish is generally perceived as being superior to farmed fish by the majority of consumers in terms of taste, safety, healthiness and nutritional value (Carlucci et al., 2015). However, consumers’ perception of farmed fish is also positive for popular cultivated species, such as seabass, seabream, trout and salmon. Considering these patterns, we have decided to include the production method in the experimental design. The format attribute was presented as a picture to consumers. The pictures has been done by a professional agency based on our suggestions. The first shots have been commented by the partners, and several modifications have been suggested, in particular for the ready-tocook level. The final set of pictures, specific by fish species and country, is reported in Table A3 (see Appendix).

The sustainability certification attribute was based on the following definition, provided to respondents before the choice experiment, mostly derived from the Marine Stewardship Council (MSC) and Aquaculture Stewardship Council (ASC) standards:''When certified'' according to a sustainability scheme, any fish can be traced back to a fishery or to a fish farm that meets principles reflecting the maintenance and re-establishment of healthy populations of targeted species, the maintenance of the integrity of ecosystems, the use of feed and other inputs that are sourced responsibly, and the social responsibility for workers and communities impacted by fishing and fish farming. This standard is intended to be used on a global basis by accredited third party certifiers to undertake the certification of fisheries and fish farmers to the above mentioned principles and criteria

The nutrition and health claim used in the experiment is “Product high of omega 3 fatty acids which contributes to maintenance of normal function of the heart and normal blood pressure”, with the following condition of use: “the beneficial effect is obtained with a daily intake of 250 mg of omega 3 fatty acids. Such amount can be consumed as part of a balanced diet”. This claim has already been approved by the EFSA (2009; 2010).

''Table 3: Price levels (€/kg, and £/kg for the UK) by fish species for each country''

{| class="wikitable" style="width: 100%;"
|-
!  
! scope="col" | Trout
! scope="col" | Herring
! scope="col" | Salmon
! scope="col" | Seabream
! scope="col" | Seabass
! scope="col" | Cod
! scope="col" | Pangasius
|-
! colspan="8" scope="row" | France
|-
| Price + 30%
| 16.64
| 12.87
| 19.37
| 14.95
| 18.59
| 19.37
| 11.05
|-
| Avg. price
| 12.80
| 9.90
| 14.90
| 11.50
| 14.30
| 14.90
| 8.50
|-
| Price -30%
| 8.96
| 6.93
| 10.43
| 8.05
| 10.01
| 10.43
| 5.95
|-
! colspan="8" scope="row" | Spain
|-
| Price + 30%
| 7.76
| 15.47
| 16.73
| 12.83
| 14.35
| 15.60
| 6.80
|-
| Avg. price
| 5.97
| 11.90
| 12.87
| 9.87
| 11.04
| 12.00
| 5.23
|-
| Price -30%
| 4.18
| 8.33
| 9.01
| 6.91
| 7.73
| 8.40
| 3.66
|-
! colspan="8" scope="row" | Italy
|-
| Price + 30%
| 13.66
| 12.87
| 19.63
| 14.07
| 15.37
| 15.87
| 7.28
|-
| Avg. price
| 10.51
| 9.90
| 15.10
| 10.82
| 11.82
| 12.21
| 5.60
|-
| Price -30%
| 7.36
| 6.93
| 10.57
| 7.57
| 8.27
| 8.55
| 3.92
|-
! colspan="8" scope="row" | Germany
|-
| Price + 30%
| 15.05
| 14.12
| 21.89
| 21.71
| 21.84
| 21.78
| 6.83
|-
| Avg. price
| 11.58
| 10.86
| 16.84
| 16.70
| 16.80
| 16.75
| 5.25
|-
| Price -30%
| 8.11
| 7.60
| 11.79
| 11.69
| 11.76
| 11.73
| 3.68
|-
! colspan="8" scope="row" | UK (€/kg)
|-
| Price + 30%
| 21.83
| 6.81
| 20.97
| 28.09
| 30.73
| 20.68
| 13.48
|-
| Avg. price
| 16.79
| 5.24
| 16.13
| 21.61
| 23.64
| 15.91
| 10.37
|-
| Price -30%
| 11.75
| 3.67
| 11.29
| 15.13
| 16.55
| 11.14
| 7.26
|-
! colspan="8" scope="row" | UK (£/kg)
|-
| Price + 30%
| 19.32
| 6.03
| 18.56
| 24.86
| 27.20
| 18.30
| 11.93
|-
| Avg. price
| 14.86
| 4.64
| 14.27
| 19.12
| 20.92
| 14.08
| 9.18
|-
| Price -30%
| 10.40
| 3.25
| 9.99
| 13.39
| 14.64
| 9.86
| 6.42
|}

We have decided to exclude the attribute origin; indeed, this attribute has already been deeply studied in the literature (Carlucci et al., 2015). Moreover, a huge effect of the domestic origin has been documented: 145% WTP by Stefani et al. (2012), 108% by Mauracher et al. (2013), 100% by McClenachan et al. (2016). We have evaluated that this effect might overwhelm the impact of other attributes on the consumers’ choices. Therefore, since other attributes have been studied much less, we have preferred to exclude the origin from the experiment.

=== 2.3 Measures ===

Apart the choice experiment, the questionnaire included the following items: sociodemographics, frequency of consumption of fish, past consumption, level of responsibility in fish purchasing and cooking, fish choice motives, attitude towards environmental concerns, attitude towards health concerns, self-efficacy, trust, and attitude towards ready-to-cook fish. The survey questionnaire was developed and revised based on input from qualitative analysis and pre-tests. The questionnaire has been submitted online and was approx. 15 minutes long. The items with the asterisk (*) are common “bridge questions” with the survey performed in Task 5.4. The English version of the questionnaire is reported in the Appendix (see Appendix A4); the partners have translated the English version of the questionnaire in their national language (i.e. Italian, French, German and Spanish). Their versions were checked using a back-translation method to avoid semantic variance between countries.

The frequency of consumption of fish was measured by the following item: “Please indicate how often you consume fish (fresh, frozen, canned, smoked, ready to eat, etc.) at home, at restaurants and other food outlets (canteens, bars, etc.): Almost every day; 3-4 times a week; 1 or 2 times a week; 2-3 times a month; Once a month or less; Few times a year; Never” (*). This question has been replicated for every species considered in the experiment (salmon, trout, seabass, seabream, herring, cod, and pangasius). Past consumption was assessed by the following 7-point scaled item: “In the past 3 years has your fish consumption: strongly decreased – strongly increased” (*).

We have assessed the level of responsibility in fish purchasing and cooking by asking respondents to indicate the level of involvement in their household in fish purchasing, and in preparing and cooking fish (Not at all involved/Somewhat involved/Fairly involved/Completely involved).

Then we asked respondents to indicate the importance of each of the following attributes when purchasing fish: general appearance (*), free of smell (*), value for money (*), sustainability certification (*), easy to cook (*), low in calories (*), not previously frozen, wild caught, domestic origin, days since catch/harvest, organic certification, price (fish choice motives).

Attitude towards environmental concerns was assessed with two items (7-point scale, from ‘‘strongly disagree” to ‘‘strongly agree”): “I believe that fishing has negative consequences on marine resources” (*), “I believe that fish farming has negative consequences on the environment” (*).

We have measured attitude towards health concerns with two items (7-point scale, from ‘‘strongly disagree” to ‘‘strongly agree”): “I believe that eating fish containing omega-3 fatty acids benefits my health” (*), “I believe that eating fish would expose myself to substances (e.g. mercury, antibiotics, etc.) risking negative consequences on my health” (*).

We assessed self-efficacy with two items, using a 7-point scale (from ‘‘strongly disagree” to ‘‘strongly agree”): “I feel confident in evaluating the quality of the fish before buying it” (*), “I feel confident in cooking fish” (*).

Trust was defined by asking respondents the level of agreement (using a 7-point scale, from ‘‘strongly disagree” to ‘‘strongly agree”) with the following five statements: “I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by a: Public authority (e.g., the national Government or the EU) / Fish farmer or fisherman / Fish processing industry / Retailer / Independent organization (e.g., an NGO)”.

Attitude towards ready-to-cook fish was measured with four items using a 7-point scale (from ‘‘strongly disagree” to ‘‘strongly agree”): “I believe that ready-to-cook products would alter the original fish characteristics” (*), “I prefer to eat ready-to-cook fish because it allows me to save time” (*), “Preferably, I spend as little time as possible on meal preparation” (*), and “I prefer to eat ready-to-cook fish because it does not smell”.

 

=== 2.4 Data collection and sample ===

Data for this study were collected in June 2017 through a nationwide online survey administered in the five countries (Italy, France, Spain, UK and Germany) by a third-party contractor using its consumer panel database. The sample in each country consisted of approximately 500 fish consumers (2,509 in total), representative of the national populations in at least three of the following criteria: age, gender, educational level and geographical macro-areas (e.g. in Italy: North, Centre, South). The main sample characteristics are reported in Table 4.

''Table 4: Sample characteristics.''

{| class="wikitable"
|-
|  
! colspan="2" scope="col" | France
! colspan="2" scope="col" | Germany
! colspan="2" scope="col" | Italy
! colspan="2" scope="col" | Spain
! colspan="2" scope="col" | UK
! colspan="2" scope="col" | Total
|-
! scope="row" | Gender
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
|-
| Males
| 256
| 51.1%
| 262
| 52.2%
| 250
| 49.6%
| 260
| 51.9%
| 254
| 50.7%
| 1282
| 51.1%
|-
| Females
| 245
| 48.9%
| 240
| 47.8%
| 254
| 50.4%
| 241
| 48.1%
| 247
| 49.3%
| 1227
| 48.9%
|-
! scope="row" | Age
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
|-
| 18-24
| 61
| 12.2%
| 56
| 11.2%
| 51
| 10.1%
| 56
| 11.2%
| 49
| 9.8%
| 273
| 10.9%
|-
| 25-34
| 91
| 18.2%
| 101
| 20.1%
| 98
| 19.4%
| 97
| 19.4%
| 121
| 24.2%
| 508
| 20.2%
|-
| 35-44
| 113
| 22.6%
| 99
| 19.7%
| 117
| 23.2%
| 132
| 26.3%
| 105
| 21.0%
| 566
| 22.6%
|-
| 45-54
| 117
| 23.4%
| 130
| 25.9%
| 127
| 25.2%
| 114
| 22.8%
| 118
| 23.6%
| 606
| 24.2%
|-
| 55+
| 119
| 23.8%
| 116
| 23.1%
| 111
| 22.0%
| 102
| 20.4%
| 108
| 21.6%
| 556
| 22.2%
|-
! scope="row" | Education
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
|-
| Lower secondary education or below
| 92
| 18.4%
| 86
| 17.1%
| 197
| 39.1%
| 181
| 36.1%
| 79
| 15.8%
| 635
| 25.3%
|-
| Upper secondary education
| 140
| 27.9%
| 97
| 19.3%
| 156
| 31.0%
| 65
| 13.0%
| 149
| 29.7%
| 607
| 24.2%
|-
| University or college below a degree
| 97
| 19.4%
| 191
| 38.0%
| 68
| 13.5%
| 75
| 15.0%
| 71
| 14.2%
| 502
| 20.0%
|-
| Bachelor's or equivalent level
| 88
| 17.6%
| 58
| 11.6%
| 41
| 8.1%
| 116
| 23.2%
| 133
| 26.5%
| 436
| 17.4%
|-
| Postgraduate MSc or PhD
| 84
| 16.8%
| 70
| 13.9%
| 42
| 8.3%
| 64
| 12.8%
| 69
| 13.8%
| 329
| 13.1%
|-
! scope="row" | Geographical area
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
|-
| Rural area
| 164
| 32.7%
| 100
| 19.9%
| 93
| 18.5%
| 52
| 10.4%
| 113
| 22.6%
| 522
| 20.8%
|-
| Small sized urban area
| 170
| 33.9%
| 187
| 37.3%
| 208
| 41.3%
| 144
| 28.7%
| 180
| 35.9%
| 889
| 35.4%
|-
| Large urban area
| 167
| 33.3%
| 215
| 42.8%
| 203
| 40.3%
| 305
| 60.9%
| 208
| 41.5%
| 1098
| 43.8%
|-
! scope="row" | Coastline
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
! n
!  %
|-
| Yes
| 160
| 31.9%
| 91
| 18.1%
| 215
| 42.7%
| 294
| 58.7%
| 184
| 36.7%
| 944
| 37.6%
|-
!  
! scope="col" | mean
! scope="col" | sd
! scope="col" | mean
! scope="col" | sd
! scope="col" | mean
! scope="col" | sd
! scope="col" | mean
! scope="col" | sd
! scope="col" | mean
! scope="col" | sd
! scope="col" | mean
! scope="col" | sd
|-
! scope="row" | BMI
! 25.2
! 5.6
! 26.8
! 6.9
! 25.2
! 5.2
! 25.5
! 4.8
! 31.2
! 15.5
! 26.8
! 8.9
|-
| Persons in household (n)
| 2.6
| 1.3
| 2.4
| 1.2
| 3.0
| 1.2
| 3.2
| 1.2
| 2.8
| 1.6
| 2.8
| 1.3
|-
| < 18 years (n)
| 0.7
| 1.0
| 0.4
| 0.7
| 0.6
| 0.8
| 0.8
| 0.9
| 0.7
| 1.2
| 0.6
| 1.0
|-
| > 60 years (n)
| 0.4
| 0.7
| 0.4
| 0.7
| 0.5
| 0.8
| 0.4
| 0.7
| 0.3
| 0.7
| 0.4
| 0.7
|- style="text-align: center;"
! scope="row" | Total (n)
| colspan="2" | 501
| colspan="2" | 502
| colspan="2" | 504
| colspan="2" | 501
| colspan="2" | 501
| colspan="2" | 2509
|}

=== 2.5 The experimental design ===

The experimental design resulted in 9 blocks of 8 choice sets with 7 product profiles plus the “no choice” option. Figure 1 shows an example of the layout of the choice set.

[[File:Wtp_figure_1.jpg|Figure 1: Example of choice set.]] ''Figure 1: Example of choice set.''

 

== Models ==

=== 3.1 Descriptive analysis ===

The median values of fish consumption is reported in Table 5. In our samples, fish is more frequently consumed in Italy, France and Spain: ‘‘3-4 times a week” as a median value. As a median value, pangasius, herring and trout are the fish species less consumed in every country, whilst cod and salmon are those more consumed. Seabass and seabream are frequently consumed in the Mediterranean countries (Italy and Spain, in particular).

''Table 5: Frequency of fish consumption (median values).''

{| class="wikitable"
|-
!  
! Italy
! France
! Germany
! Spain
! UK
|-
! scope="2" | Trout
| Few times a year
| Few times a year
| Few times a year
| Few times a year
| Few times a year
|-
! scope="row" | Herring
| Few times a year
| Few times a year
| Few times a year
| Few times a year
| Never
|-
! scope="row" | Salmon
| Once a month
| Once a month
| Once a month
| Once a month
| Once a month
|-
! scope="row" | Seabass
| Once a month
| Few times a year
| Never
| Once a month
| Few times a year
|-
! scope="row" | Seabream
| Once a month
| Few times a year
| Never
| Once a month
| Never
|-
! scope="row" | Cod
| 2-3 times a month
| Once a month
| 2-3 times a month
| 2-3 times a month
| 2-3 times a month
|-
! scope="row" | Pangasius
| Few times a year
| Never
| Few times a year
| Few times a year
| Never
|-
! scope="row" | Fish
| 3-4 times a week
| 3-4 times a week
| 2-3 times a week
| 3-4 times a week
| 2-3 times a week
|}

Overall, 40% of the respondents increased fish consumption in the past 3 years, 16% decreased fish consumption in the same period, and 44% maintained the same level. The share of those who increased fish consumption is higher in the UK (45%) and Italy (43%), whilst the quota of those who decreased fish consumption is higher in France (20%), Germany (17%) and Spain (17%) (Figure 2).

[[File:Wtp_figure_2.jpg|Figure 2: Evolution of fish consumption in the past 3 years.]] ''Figure 2: Evolution of fish consumption in the past 3 years.''

The level of involvement is high in all countries both for fish purchasing (83% are completely or fairly involved) and for fish preparing and cooking (79%). The level of involvement is higher in the UK, respectively, 86% and 84% (Figure 3).

[[File:Wtp_figure_3.jpg|Figure 3: Level of involvement in fish purchasing in your household.]] ''Figure 3: Level of involvement in fish purchasing in your household.''

[[File:Wtp_figure_4.jpg|Figure 4: Level of involvement in your household when preparing and cooking fish.]] ''Figure 4: Level of involvement in your household when preparing and cooking fish.''

Table 6 shows the fish choice motives expressed by the participants. Value for money, price and general appearance are the most important attributes in every country. However, in Italy wild caught and days since catch/harvest (likely as a proxi of freshness) are more important than price. Easy to cook is ranked as another important attribute in fish selection, in particular in France, UK and Germany. Sustainability certification is ranked as 5th and 6th aspect in fish selection, respectively, in Germany and Spain. Table 7 shows the level of agreement on the attitudinal beliefs attitude towards environmental concerns (AE), attitude towards health concerns (AH), self-efficacy (SE), trust in information about sustainable production (TI), attitude towards ready-to-cook fish (AR). The results about the attitudinal beliefs are also displayed in Figures 5-9.

''Table 6: Relative importance of different aspects in fish selection (1 = Not at all important; 7 = Extremely important).''

{| class="wikitable"
|-
|  
! colspan="2" scope="col" | France
! colspan="2" scope="col" | Germany
! colspan="2" scope="col" | Italy
! colspan="2" scope="col" | Spain
! colspan="2" scope="col" | UK
! colspan="2" scope="col" | Total
|-
! scope="row" | Fish choice motives
! scope="col" | Mean
! scope="col" | sd
! scope="col" | Mean
! scope="col" | sd
! scope="col" | Mean
! scope="col" | sd
! scope="col" | Mean
! scope="col" | sd
! scope="col" | Mean
! scope="col" | sd
! scope="col" | Mean
! scope="col" | sd
|-
| Value for money
| 5.63
| 1.24
| 5.15
| 1.39
| 5.61
| 1.17
| 5.62
| 1.27
| 5.33
| 1.42
| 5.47
| 1.31
|-
| Price
| 5.57
| 1.24
| 5.10
| 1.34
| 5.31
| 1.25
| 5.44
| 1.29
| 5.29
| 1.42
| 5.34
| 1.32
|-
| General appearance
| 5.43
| 1.49
| 5.19
| 1.48
| 5.66
| 1.38
| 5.38
| 1.47
| 5.01
| 1.65
| 5.33
| 1.51
|-
| Free of smell
| 4.81
| 1.64
| 4.77
| 1.64
| 5.17
| 1.48
| 5.34
| 1.49
| 4.90
| 1.76
| 5.00
| 1.62
|-
| Easy to cook
| 5.09
| 1.44
| 4.87
| 1.49
| 4.99
| 1.35
| 4.97
| 1.44
| 5.00
| 1.49
| 4.98
| 1.44
|-
| Days since catch/harvest
| 5.01
| 1.51
| 4.39
| 1.63
| 5.36
| 1.43
| 5.25
| 1.46
| 4.70
| 1.67
| 4.94
| 1.58
|-
| Sustainability certification
| 4.80
| 1.48
| 4.81
| 1.59
| 5.14
| 1.36
| 5.09
| 1.45
| 4.65
| 1.72
| 4.90
| 1.54
|-
| Domestic origin
| 5.01
| 1.47
| 4.13
| 1.57
| 5.26
| 1.42
| 4.97
| 1.49
| 4.35
| 1.68
| 4.74
| 1.59
|-
| Wild caught
| 4.77
| 1.44
| 4.01
| 1.47
| 5.39
| 1.34
| 4.74
| 1.49
| 4.33
| 1.64
| 4.65
| 1.55
|-
| Organic certification
| 4.60
| 1.45
| 4.04
| 1.69
| 4.94
| 1.45
| 5.00
| 1.47
| 3.92
| 1.77
| 4.50
| 1.64
|-
| Not previously frozen
| 4.54
| 1.61
| 3.88
| 1.55
| 5.11
| 1.54
| 4.81
| 1.58
| 4.16
| 1.70
| 4.50
| 1.66
|-
| Low in calories
| 4.28
| 1.61
| 3.89
| 1.65
| 4.45
| 1.61
| 4.62
| 1.50
| 4.16
| 1.77
| 4.28
| 1.65
|}

''Table 7: Level of agreement on the following attitudinal beliefs: attitude towards environmental concerns (AE), attitude towards health'' concerns (AH), self-efficacy (SE), trust in information about sustainable production (TI), attitude towards ready-to-cook fish (AR).

{| class="wikitable" style="width: 98%"
|-
! colspan="2" scope="col" |  
! colspan="2" scope="col" | France
! colspan="2" scope="col" | Germany
! colspan="2" scope="col" | Italy
! colspan="2" scope="col" | Spain
! colspan="2" scope="col" | UK
! colspan="2" scope="col" | Total
|-
! scope="row" style="width: 50%;" | Fish choice motives
! scope="row" | Att
! scope="row" | Mean
! scope="row" | sd
! scope="row" | Mean
! scope="row" | sd
! scope="row" | Mean
! scope="row" | sd
! scope="row" | Mean
! scope="row" | sd
! scope="row" | Mean
! scope="row" | sd
! scope="row" | Mean
! scope="row" | sd
|-
| I believe that fishing has negative consequences on marine resources.
| AE
| 4.73
| 1.43
| 4.39
| 1.41
| 4.02
| 1.53
| 4.39
| 1.52
| 4.27
| 1.41
| 4.36
| 1.48
|-
| I believe that fish farming has negative consequences on the environment.
| AE
| 4.38
| 1.47
| 3.79
| 1.44
| 3.74
| 1.51
| 3.88
| 1.66
| 4.14
| 1.44
| 3.98
| 1.52
|-
| I believe that eating fish containing omega-3 fatty acids benefits my health.
| AH
| 5.40
| 1.34
| 5.41
| 1.22
| 5.57
| 1.27
| 5.69
| 1.35
| 5.42
| 1.30
| 5.50
| 1.30
|-
| I believe that eating fish would expose myself to substances (e.g. mercury, antibiotics, etc.) risking negative consequences on my health.
| AH
| 3.99
| 1.53
| 3.79
| 1.42
| 3.95
| 1.50
| 4.19
| 1.61
| 3.64
| 1.56
| 3.91
| 1.54
|-
| I feel confident in evaluating the quality of the fish before buying it.
| SE
| 4.85
| 1.25
| 4.47
| 1.25
| 4.85
| 1.23
| 5.06
| 1.38
| 4.76
| 1.39
| 4.80
| 1.32
|-
| I feel confident in cooking fish.
| SE
| 4.97
| 1.28
| 4.88
| 1.33
| 5.11
| 1.29
| 5.38
| 1.32
| 5.14
| 1.48
| 5.09
| 1.35
|-
| I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by a public authority (e.g., the Government or the EU)
| TI
| 4.49
| 1.43
| 4.68
| 1.39
| 4.79
| 1.47
| 5.00
| 1.54
| 4.88
| 1.46
| 4.77
| 1.47
|-
| I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by a fish farmer or fisherman
| TI
| 4.71
| 1.38
| 4.53
| 1.35
| 4.65
| 1.37
| 4.85
| 1.36
| 4.69
| 1.39
| 4.68
| 1.37
|-
| I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by a fish processing industry
| TI
| 3.97
| 1.51
| 3.91
| 1.44
| 4.43
| 1.41
| 4.65
| 1.47
| 4.47
| 1.45
| 4.29
| 1.49
|-
| I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by a retailer
| TI
| 4.19
| 1.39
| 4.16
| 1.36
| 4.30
| 1.42
| 4.47
| 1.47
| 4.48
| 1.33
| 4.32
| 1.40
|-
| I would trust the information provided about the sustainable fish production practices (fishing or farming) if they were certified by an independent organization (e.g., an NGO)
| TI
| 4.89
| 1.34
| 4.81
| 1.34
| 4.91
| 1.41
| 4.96
| 1.52
| 4.93
| 1.38
| 4.90
| 1.40
|-
| I believe that ready-to-cook products would alter the original fish characteristics
| AR
| 4.91
| 1.32
| 4.45
| 1.15
| 4.47
| 1.25
| 4.95
| 1.39
| 4.52
| 1.21
| 4.66
| 1.28
|-
| I prefer to eat ready-to-cook fish because it allows me to save time
| AR
| 3.89
| 1.66
| 4.49
| 1.34
| 4.03
| 1.46
| 4.03
| 1.65
| 4.34
| 1.58
| 4.15
| 1.56
|-
| Preferably, I spend as little time as possible on meal preparation
| AR
| 3.74
| 1.64
| 4.35
| 1.45
| 3.92
| 1.53
| 3.82
| 1.71
| 4.14
| 1.56
| 3.99
| 1.60
|-
| I prefer to eat ready-to-cook fish because it does not smell
| AR
| 3.39
| 1.60
| 4.19
| 1.36
| 3.62
| 1.60
| 3.59
| 1.68
| 3.98
| 1.56
| 3.75
| 1.59
|}

''Note: all items are scored on the scale: 1 = Strongly disagree; 7 = Strongly agree.''

In general consumers are more warried about the negative consequences of fishing on marine resources, than those of fish farming on the environment (Figure 5). The concern is higher in France and lower in Italy.

[[File:Wtp_figure_5.jpg|Figure 5: Attitude towards environmental concerns.]] ''Figure 5: Attitude towards environmental concerns.''

In general, respondents believe that fish consumption has more benefits than risks (Figure 6). The benefits are more appreciated in Spain, as well as the risks of negative consequences.

[[File:Wtp_figure_6.jpg|Figure 6: Attitude towards health concerns.]] ''Figure 6: Attitude towards health concerns.''

In general consumers are more confident in cooking fish than in evaluating the quality of the fish before buying it (Figure 7).

[[File:Wtp_figure_7.jpg|Figure 7: Self-efficacy.]] ''Figure 7: Self-efficacy.''

Consumers’ trust in information provided about the sustainable fish production is higher for independent organizations and public authorities, than for industries and retailers. Trust for farmers and fishermen is higher than trust for industry and retailers in every country. In France, the trust for fish farmers or fishermen is higher than for the public authority (Figure 8).

[[File:Wtp_figure_8.jpg|Figure 8: Trust for information about sustainable fish production]] ''Figure 8: Trust for information about sustainable fish production.''

In general, consumers show a rather negative perception about ready-to-cook products, in terms of loss of original characteristics. The preference for ready-to-cook fish products because of saving time is lower than the risk of alter the original fish characteristics (Figure 9). This difference is much larger in France and Spain, while is lower in the UK. Only in Germany consumers’ preference for ready-to-cook fish products is higher than the risk of alter the original fish characteristics.

[[File:Wtp_figure_9.jpg|Figure 9: Attitude towards ready-to-cook fish.]] ''Figure 9: Attitude towards ready-to-cook fish.''

Once having performed the choice experiment, the respondents had to state how they believed in the benefits of sustainability certification to the environment and society, and how they believed in the nutrition and health claim. The results are reported in Figure 10 and 11. The belief strength is generally higher for the sustainability certification scheme, while, for both labels, is lower in France compared to Spain, Italy and UK.

[[File:Wtp_figure_10.jpg|Figure 10: Belief strength about the sustainability label.]] ''Figure 10: Belief strength about the sustainability label.''

Note: “We assume you have read the definition of sustainability certification above. On a scale of 0-100, to what extent do you believe in the benefits of such certification to the environment and society? (e.g., 0 = completely unbelievable; 50 = neutral; 100 = completely believable)

[[File:Wtp_figure_11.jpg|Figure 11: Belief strength about the nutritional and health claim.]] ''Figure 11: Belief strength about the nutritional and health claim.''

Note: “In the marketplace, some producers provide health benefit information from consuming their products. On a scale of 0-100, to what extent do you believe such health benefit claims? (e.g., 0 = completely unbelievable; 50 = neutral; 100 = completely believable).

 

=== 3.2 The choice experiment results ===

Two different models were estimated:

*the first one with fish species-specific effects (FSSE); this is needed for obtaining WTP

specific for the 7 species;

*the second one with random price effect (RPE) models; this is needed for

segmentation.

 

=== 3.2.1 Model specification and estimation ===

According to Lancaster’s consumer theory (1966), consumer utility stems from product attributes, not the products themselves. In other words, consumer utility can be separated into part-worth utilities. The part-worth utilities equal consumers’ preference for corresponding attributes. In marketing research, the product attributes are classified into extrinsic and intrinsic attributes (Zeithaml, 1988; Olsen et al., 2008). Regardless of whether consumers are exposed to these attributes, they may be important signals of product quality and determinants of consumer preference.

The overall utility that a consumer obtains from consuming a seafood species j (Uj) can be expressed as:

[[File:Wtp_eq_1.JPG|center|Equation 1.]]

It is generally assumed that an individual would choose a product alternative if the utility derived from this alternative is maximized compared to the other alternatives:

[[File:Wtp_eq_2.JPG|center|Equation 2.]]

When facing a “basket” of seafood products, consumers assign a random utility to each product alternatives and select the one with the highest derived utility. Assuming that the stochastic components εj have independent and identical distributed (iid) forms, the probability of a consumer i choosing a fish product j(P( yij = 1 ) given by the multinomial logit (MNL) model (McFadden, 1974), is expressed in the following equation:

[[File:Wtp_eq_3.JPG|center|Equation 3.]]

The MNL model presented in equation (3) is the basic choice model and has been approved to have several disadvantages such as assuming iid of the error and assuming the homogeneity of consumers’ preference. To overcome the limitations of MNL, there many advanced discrete choice models suggested such as the mixed logit models (random coefficient, scaled-multinomial logit, and generalized-multinomial logit) and the latent class model (LCM) (see Fiebig et al., 2010; Greene & Hensher, 2003). We estimated two types of models in this report to elicit the consumers’ WTP for fish attributes that are specific to particular fish species and for individual consumers, named as fish speciesspecific effect model (FSSE) and random (i.e price) parameter effect model. The fish species-specific effect (FSSE) model (fish j), is expressed as:

[[File:Wtp_eq_4.JPG|center|Equation 4.]]

where β parameters are estimated for the j-th fish species and for the attributes production method (i.e. Method, as wild caught vs. farmed fish), product format (i.e. Format, as whole fish/round cut, fillet or ready-to-cook), nutritional and health claim (i.e. Health, as with/without nutritional and health claim), and sustainability label (i.e. Sustain, as with/without sustainability certification). The Random price effect (RPE) model is specified so that the price coefficients includes two components, such as the average effect of price and the individual variance of price effects, expressed as:

[[File:Wtp_eq_5.JPG|center|Equation 5.]]

where αj, βk are fixed-effect coefficients, γ3 is random coefficient of price estimated for individual i. The specification of FSSE allows us to calculate the willingness to pay (WTP) for each of seven fish species in the choice experiment, while random price effect model allows us to elicit the WTP of each fish attributes at individual consumers’ level. The WTP for a non-monetary attribute is the price premium that consumers are willing to pay for obtaining a desired attribute level. The WTP for an attribute level A (e.g. health) from FSSE model in equation (4) is calculated as:

[[File:Wtp_eq_6.JPG|center|Equation 6.]]

where 𝑊𝑇𝑃Aj is the price premium paid for obtaining a desired level of attribute A (i.e., product with health claim) of the fish j, and β𝐴𝑗 and β5𝑗 are the estimated coefficients of attribute A and price attributes of fish j. Similarly, the WTP for attribute A (not specific to fish species) at consumers' individual level (𝑊𝑇𝑃𝐴i) is calculated from model in equation (5) is:

[[File:Wtp_eq_7.JPG|center|Equation 7.]]

We estimate the WTP specific to fish species with expectation that consumers‘ preference for fish quality attributes depends in specific species (Thong et al., 2015). For instance, consumers may prefer filleted cod to the whole fish cod, but they may prefer whole fish herring to the filleted herring. The WTP for fish quality attributes are calculated at individual consumers because the nature of heterogeneity of preference. The random price effect model also allows us to obtain choice probability for fish species at the individual consumer‘s level. The individual consumers‘ choice probability thus will be used for segmentations that are actionable for marketing strategy and developing the decision support system (DSS). The segments are derived in every country using SAS macros, and three parameter criterion: cubic clustering criterion (Sarle, 1983), Pseudo-F statistics (Calinski and Harabasz, 1974), and Pseudo-t squared statistics (Duda and Hart, 1973).

 

== Reports & Data ==

----

===Data===

===='''Italy'''====

Table 8 reports the coefficients estimates for models with fish species-specific effect (FSSE)
in the Italian sample.
The higher coefficient reported for seabass indicate that this species is the most preferred by
the Italian consumers, followed by cod and seabream, while the least preferred is herring. Wild
caught alternative is the most preferred comparted to the farm-raised fish for all species, with
higher incidence for cod and seabass. Ready-to-cook products are preferred compared to
whole or round cut in the case of cod, herring and pangasius, while is less preferred for salmon
and seabream. Fish fillet is preferred than ready-to-cook products for salmon, seabream and
cod, while is less preferred for trout and seabass. The sustainability label is generally
appreciated for all species, where the effect is higher for cod, seabream, pangasius and trout.
The nutritional and health claim is also generally appreciated, where higher scores are found
for seabream, pangasius and cod.
The willingness to pay is directly derived from these results, applying the formula (6). The
results are shown in Table 9, where the price premium (in €/kg) and the marginal WTP (in %
above or below the average price in Table 3) are reported. Considering the production method,
the higher relative WTP has been found in the case of wild salmon, compared to the farmraised
alternative (+48%). Again the higher marginal WTP for format attribute is found for
salmon fillet and round cut compared to the ready-to-cook alternative (respectively, +70% and
+38%). The higher WTP for the sustainability scheme was found for cod (+27%), while the
WTP for nutritional and health claim is higher for seabream (+27%).

''Table 8: Fish Species-Specific Effect (FSSE) Model, β (mean and standard deviation) - Italy. ''
[[File:Wtp_table_8.JPG|center|WTP Table 8.]]

''Table 9: Italian consumers' WTP a price premium (in €/kg and % above or below the average
market price) for specific fish attributes, based on the estimates of the FSSE model.''
[[File:Wtp_table_9.JPG|center|WTP Table 9.]]

The random price effect (RPE) model, able to estimate the price coefficient for every single
consumer, resulted in the mean effects (and standard deviation) reported in Table 10. The
attribute effects, in this case, are computed without the interaction with the species (i.e. on
average for all species). The higher utility score was found for wild caught fishes compared to
the farm-raised ones, and for the sustainability label and nutritional and health claims. The
WTP estimates, based on these effects, are reported in Table 11. These estimates are the
mean values estimated for each consumer in the sample.

''Table 10: Random Price Effect (RPE) model, β (mean and standard deviation) - Italy. ''
[[File:Wtp_table_10.JPG|center|WTP Table 10.]]

Table 11: Italian consumers' WTP (in €/kg) for fish species and attributes, based on the
estimates of the RPE model.''
[[File:Wtp_table_11.JPG|center|WTP Table 11.]]

The choice probability for fish species is reported in Table 12. This probability is very similar
using both models, indicating the robustness of the effects across the models. Seabream,
seabass and salmon exhibit the higher choice probability, while herring and pangasius and
trout the lowest.

Table 12: Choice probability for fish species (mean value, standard deviation, minimum and
maximum) with Fish Species-Specific Effect (FSSE) and Random Price Effect (RPE) models
- Italy.''
[[File:Wtp_table_12.JPG|center|WTP Table 12.]]

We have derived five different segments, based on choice probabilities, shown in Table 13.
The first cluster is the largest (36% of the sample), and exhibits a higher WTP in general for
all fish species and attributes. It is indeed one of the least sensitive to price changes. Mostly
composed by females, middle aged, high educated and with high income level, living in a
medium-large family. The second segment (12% of the sample) exhibits a low WTP, compared
to the other segments, and a high sensitivity to price changes. It is made of females (61%),
with lower education level, mostly living in two people families. The third segment is the second
large one (30%), and expressed a medium WTP for all species, and a medium-high WTP for
sustainability label and wild-caught fishes. It shows a low sensitivity with price changes. It is
mostly composed by men (53%), middle-high aged, both low and high educated, with medium
income and large family units (> three people). The fourth segment, representing 20% of the
sample, shows slightly higher WTP values compared to the third one, only with a higher
sensitivity with price changes. It is mostly composed by men (58%), younger, with lower
educational level, and lower income (even if the higher income level is well represented), and
living in larger family units. The fifth sample is the smallest (3%), and exhibits a low WTP for
all species and attributes, and high price sensitivity.

Table 13: Segmentation of the Italian market, based on individuals’ choice probabilities.''
[[File:Wtp_table_13.JPG|center|WTP Table 13.]]

===='''France'''====

Table 14 reports the coefficients estimates in the French sample for models with fish speciesspecific
effect (FSSE).
The higher β coefficient reported for seabream, cod and seabass indicate that these species
are the most preferred by the French consumers, while the least preferred are herring and
pangasius. Wild caught alternative is preferred comparted to the farm-raised fish for all
species, with higher incidence for seabream. Ready-to-cook products are preferred compared
to whole or round cut for all species, except with salmon. Fish fillet is preferred than ready-tocook
products for salmon and cod, while is less preferred for pangasius. The sustainability
label is generally appreciated by consumers, with higher effects for seabass and pangasius.
The nutritional and health claim is appreciated for seabass, whilst the other effects are less
significant.
The willingness to pay results, applying the formula (8), are shown in Table 15 where the price
premium (in €/kg) and the marginal WTP (in % above or below the average price in Table 3)
are reported. Considering the production method, the higher relative WTP has been found in
the case of wild salmon, compared to the farm-raised alternative (+58% compared to average
market price); high premiums have been also estimated for wild seabream (+34%) and wild
cod (+33%). The higher marginal WTP for format attribute is found for salmon fillet and round
cut compared to the ready-to-cook alternative (respectively, +58% and +48%). Round cut
pangasius is the least accepted, with a WTP for ready-to-cook alternative of 72%. Significant
price premiums are also estimated for ready-to-cook cod (35%) and herring (33%), compared
to, respectively, round cut and whole alternatives. The higher price premium for the
sustainability scheme was found for salmon (+23%), seabass (+20%) and pangasius (+17%);
the WTP for nutritional and health claim is higher for seabass (+13%).

Table 14: Fish Species-Specific Effect (FSSE) Model, β (mean and std. deviation) - France. ''
[[File:Wtp_table_14.JPG|center|WTP Table 14.]]

Table 15: French consumers' WTP a price premium (in €/kg and % above or below the average market price) for specific fish attributes, based on the estimates of the FSSE model. ''
[[File:Wtp_table_15.JPG|center|WTP Table 15.]]

The random price effects (RPE) model results (mean and standard deviation) are reported in
Table 16 where the β coefficients are shown. The higher utility score was found for salmon
and cod, and for wild caught fishes compared to the farm-raised ones. To a lesser extent the
β coefficients are also positive for the fillets compared to the ready-to-cook alternatives, and
for the sustainability label.
The WTP estimates, based on these effects, are reported in Table 17; the higher premiums
are associated with salmon and cod (respectively, 24.6 and 20.6 €/kg), and with wild-caught
fishes (3.2 €/kg). The relatively low willingness to pay of French consumers for both
sustainability label and nutritional and health claim can be partially explained by their weak
belief strength in the benefits of sustainability certification to the environment and society, and
in the nutrition and health claim.

Table 16: Random Price Effect (RPE) model, β (mean and standard deviation) - France. ''
[[File:Wtp_table_16.JPG|center|WTP Table 16.]]

Table 17: French consumers' WTP (in €/kg) for fish species and attributes, based on the estimates of the RPE model.''
[[File:Wtp_table_17.JPG|center|WTP Table 17.]]

The choice probability for fish species is reported in Table 18. This probability is very similar
using both models, indicating the robustness of the effects across the models. Salmon, cod
and seabream exhibit the higher choice probability, while pangasius and herring the lowest.

Table 18: Choice probability for fish species (mean value, standard deviation, minimum and maximum) with Fish Species-Specific Effect (FSSE) and Random Price Effect (RPE) models - France. ''
[[File:Wtp_table_18.JPG|center|WTP Table 18.]]

Finally, we have derived six different segments, based on choice probabilities, shown in Table
19. The first two segments (CL1 and CL2), representing overall 45% of the sample, have the
largest WTP scores for all fish species and attributes, including a higher WTP for ready-tocook
fishes compared to whole alternatives. These two clusters are less sensitive to price
changes. The first segment is mostly composed by younger males, highly educated and with
higher income level, living in two-three people families. The second segment is mostly
composed by older females, highly educated and with higher income level, living in largersized
families (four people). The third segment (29% of the sample) exhibits an average WTP,
compared to the other segments. It is mostly made of males (53%), middle-high aged, less
educated and with lower income, mostly living alone. The fourth and the fifth segments,
representing 9% and 5% of the sample, show low price premiums compared to the other ones,
exhibiting a higher sensitivity with price changes. Segment four is mostly composed by young
females (64%), with lower education and income, living either alone or in larger families (four
people or more). Segment six, representing 13% of the sample, exhibits a medium-low
willingness to pay premium for all species, but with low sensitivity with price change. It is mostly
composed by young males with medium educational level, and high income, living in larger
family units (three and more components).

Table 19: Segmentation of the French market, based on individuals’ choice probabilities.''
[[File:Wtp_table_19.JPG|center|WTP Table 19.]]

===='''Germany'''====

Table 20 reports the coefficients estimates in the German sample for models with fish speciesspecific
effect (FSSE), with and without beliefs.
Cod, salmon, trout and seabass reported the higher β coefficients, indicating that these species
are the most preferred by German consumers. Wild caught alternative is the most preferred
comparted to the farm-raised fish for all species, with higher β coefficient for seabass. Readyto-cook
products are generally preferred compared to whole (or round cut) fishes and fillets,
except for salmon, where fillet is preferred than ready-to-cook product. The sustainability label
is generally appreciated for all species, with more significant effects where found for seabass
and seabream. The nutritional and health claim reported higher coefficients for seabream and
herring.
The willingness to pay results, applying the formula (8), are shown in Table 21. Wild-caught
seabass exhibits the highest premium compared to the farm-raised alternative (+51% above
the average market price), followed by wild-caught salmon (+35%) and seabream (+32%). As
said before, the ready-to-cook products are generally preferred, with highest premiums found
for pangasius, cod and seabass, compared to the whole or round cut fish. Consumers are
willing to pay 38% price premium for salmon fillets compared to ready-to-cook products. The
higher marginal WTP for the sustainability label was found for seabream (+53%), pangasius
(49%) and seabass (42%). The WTP for nutritional and health claim is higher for pangasius
(+44%) and seabream (+30%).

Table 20: Fish Species-Specific Effect (FSSE) Model, β (mean and std. deviation) - Germany. ''
[[File:Wtp_table_20.JPG|center|WTP Table 20.]]

Table 21: German consumers' WTP a price premium (in €/kg and % above or below the
average market price) for specific fish attributes, based on the estimates of the FSSE model. ''
[[File:Wtp_table_21.JPG|center|WTP Table 21.]]

The RPE model effects (β coefficients mean and standard deviation) are reported in Table 22.
The higher utility score was found for salmon, trout and cod, and for wild-caught fishes
compared to the farm-raised ones and for ready-to-cook products compared to whole or round
cut fishes. The β coefficients are also significant for the sustainability label and nutritional and
health claim. The WTP estimates, based on these effects, are reported in Table 23; the higher
premiums are associated with salmon and trout (respectively, 28.5 and 22.6 €/kg), and with
ready-to-cook (2.7 €/kg compared to the whole alternative) and wild-caught fishes (2.4 €/kg).

Table 22: Random Price Effect (RPE) model, β (mean and standard deviation) - Germany. ''
[[File:Wtp_table_22.JPG|center|WTP Table 22.]]

Table 23: German consumers' WTP (in €/kg) for fish species and attributes, based on the
estimates of the RPE model.''
[[File:Wtp_table_23.JPG|center|WTP Table 23.]]

Table 24 shows the choice probability for fish species. This probability is higher for salmon,
trout and pangasius, while is lower for seabream and seabass.

Table 24: Choice probability for fish species (mean value, standard deviation, minimum and
maximum) with Fish Species-Specific Effect (FSSE) and Random Price Effect (RPE) models
- Germany.''
[[File:Wtp_table_24.JPG|center|WTP Table 24.]]

We have derived four different segments, based on choice probabilities, shown in Table 25.
The first cluster, representing 28% of the sample, is the one with the highest willingness to pay
for all species and attributes, including the ready-to-cook alternatives. It is almost equally
composed by young males and females, with medium-to-high educational level, and high
incomes, mostly living with small family units (one or two members). Segment two is the
smallest one (13.5%). It reports a low willingness to pay for all species and attributes,
compared to the other segments. This segment is made by young and old people (middle aged
less represented), with medium educational level, and high income, living in large family units
(three people or more). The third segment is the largest (32%); it exhibits a medium willingness
to pay for species and attributes. It is mostly composed by males, middle-old aged, average
education, high income, and living in families with two people. Finally, the fourth segment
(26%), reports a low willingness to pay for all species and attributes. It is made by middle-age
females (59%), with low educational level, middle income and living in small family units.

Table 25: Segmentation of the German market, based on individuals’ choice probabilities. ''
[[File:Wtp_table_25.JPG|center|WTP Table 25.]]

===='''UK'''====

Table 26 reports the coefficients estimates in the UK sample for models with fish speciesspecific
effect (FSSE).
The high coefficients reported for salmon and cod indicate that these species are the most
preferred by the UK consumers, while the least preferred are pangasius and seabass,
exhibiting a negative β coefficient which denotes that these species decrease the consumers’
utility. Wild caught alternative are generally preferred, in particular seabass and salmon.
Ready-to-cook products are preferred compared to while or round cut for all fish species,
except for salmon. Fish fillet is preferred than ready-to-cook products for salmon and
seabream, while it is less preferred for trout and pangasius. The sustainability label is mostly
appreciated for herring and seabream, whilst it is detrimental for consumers’ utility in the case
of pangasius. The nutritional and health claim is mostly appreciated for pangasius, salmon and
trout.
Table 10 shows the WTP estimates, in £/kg and as a % of the average price, applying the
formula (8). The results show a +48% price premium consumers are willing to pay for wildcaught
seabass compared to farmed alternative. The higher marginal WTP for format attribute
have been found for ready-to-cook products, compared to whole/round cut fish, in the case of
herring (81%), seabass (49%), cod (37%), trout (33%) and seabream (30%). Salmon fillet is
preferred compared to the ready-to-cook alternative (+44%). The higher WTP for the
sustainability scheme was found for herring (+62%), while the WTP for nutritional and health
claim is higher for pangasius (+26%).

Table 26: Fish Species-Specific Effect (FSSE) Model, β (mean and standard deviation) – UK.''
[[File:Wtp_table_26.JPG|center|WTP Table 26.]]

Table 27: UK consumers' WTP a price premium (in £/kg, €/kg (5) and % of the average market
price) for specific fish attributes, based on the estimates of the FSSE model. ''
[[File:Wtp_table_27.JPG|center|WTP Table 27.]]
''(5) The exchange rate used is 1 GB £ = 1.16 €.''

The RPE model results are reported in Table 28, where the β coefficients (mean and standard
deviation) are shown.

Table 28: Random Price Effect (RPE) model, β (mean and standard deviation) - UK.''
[[File:Wtp_table_28.JPG|center|WTP Table 28.]]

Table 29: UK consumers' WTP (in £/kg and €/kg (6)
) for fish species and attributes, based on the
estimates of the RPE model.''
[[File:Wtp_table_29.JPG|center|WTP Table 29.]]
''6 The exchange rate used is 1 GB £ = 1.16 €.''

The higher utility score was found for salmon and cod, and for wild caught fishes compared to
the farm-raised ones. Ready-to-cook products are generally preferred compared to the
whole/round cut alternatives. To a lesser extent the β coefficients are also positive for the fillets
compared to the ready-to-cook alternatives, and for the sustainability label.
The WTP estimates, based on these effects, are reported in Table 29; the higher premiums
for fish species are associated with salmon and cod (respectively, 23.4 and 21.8 €/kg). For the
attributes, wild-caught fishes carry the higher premiums (1.8 €/kg), followed by ready-to-cook
products compared to whole alternative (1.4 €/kg), and by fish fillets compared to ready-tocook
ones (1.1 €/kg).
The choice probability, reported in Table 30, indicate that salmon and cod are the most chosen
alternatives, while pangasius, seabream and trout are the least preferred ones.

Table 30: Choice probability for fish species (mean value, standard deviation, minimum and
maximum) with Fish Species-Specific Effect (FSSE) and Random Price Effect (RPE) models
- UK. ''
[[File:Wtp_table_30.JPG|center|WTP Table 30.]]

We have derived four different segments for the UK market, based on choice probabilities
(Table 31). The first segment (13%) is the one with the lowest WTP for all species and
attributes, and the one more sensitive with price changes. It shows, compared to the other
segments, a higher incidence of middle-aged females, with low education and low income,
living in larger family units. Segment 2 is the largest one (41% of the sample), showing,
compared to the other segment a medium-high WTP. Younger males are more represented,
with higher educational level and income, and living in families with three or four members.
The third segment (27%) shows low estimates of premium prices; it is mostly composed by
females, with medium income level and education, living in small family units. Segment 4 (19%)
is the one with the highest estimated WTP; middle-aged and older females are more
represented, as well as middle educated and income levels, and mostly living in families with
two members.

Table 31: Segmentation of the UK market, based on individuals’ choice probabilities. ''
[[File:Wtp_table_31.JPG|center|WTP Table 31.]]

===='''Spain'''====

Table 32 reports the coefficients estimates in the Spanish sample for models with fish speciesspecific
effect (FSSE), with and without beliefs.
Seabass, seabream and cod are the species with the highest β coefficients in the FSSE model,
indicating a stronger preference of Spanish consumers for these products, while pangasius is
the least preferred one. Wild-caught alternative are generally appreciated, while wild-caught
seabass carrying the highest utility. Ready-to-cook products are preferred compared to while
or round cut in the case of cod, pangasius and herring, while it is less preferred for salmon and
seabream. This result is very similar to the Italian case. Fish fillets are generally preferred than
ready-to-cook products apart from trout and pangasius. The sustainability label coefficient
carrying the higher utility for consumers was found for trout, herring and seabream. The
nutritional and health claim is generally appreciated, where higher scores are found for
pangasius.
The price premiums (in €/kg and % of the average price) that Spanish consumers are willing
to pay for species and attributes, estimated with formula (8), are shown in Table 33. The higher
relative WTP has been found in the case of wild-caught seabass, compared to the farm-raised
alternative (+19%). Salmon fillet carries the higher premium compared to ready-to-cook
alternative (+53%), whilst ready-to-cook trout is preferred than the fillet alternative, showing a
47% WTP. Consumers are willing to pay a premium for ready-to-cook pangasius compared to
round cut and fillets, respectively, +36% and 32% premium. The higher WTP for the
sustainability label and nutritional and health claim was found for trout (respectively, +33% and
+37%) and pangasius (respectively, +30% and +68%).

Table 32: Fish Species-Specific Effect (FSSE) Model, β (mean and standard deviation) - Spain.''
[[File:Wtp_table_32.JPG|center|WTP Table 32.]]

Table 33: Spanish consumers' WTP a price premium (in €/kg and % above or below the
average market price) for specific fish attributes, based on the estimates of the FSSE model. ''
[[File:Wtp_table_33.JPG|center|WTP Table 33.]]

The RPE model effects (β coefficients mean and standard deviation) are reported in Table 34.
The higher utility score was found for salmon, seabream, seabass and cod, and for wild-caught
fishes compared to the farm-raised ones. The β coefficients are also significant for the
sustainability label and nutritional and health claim. The WTP estimates, based on these
effects, are reported in Table 35; the higher premiums for species are associated with salmon
(mean premium 20.7 €/kg), seabream (18.4 €/kg) and cod (18.1 €/kg). The nutritional and
health claim carries the highest premium among the attributes, with 1.1 €/kg.

Table 34: Random Price Effect (RPE) model, β (mean and standard deviation) - Spain. ''
[[File:Wtp_table_34.JPG|center|WTP Table 34.]]

Table 35: Spanish consumers' WTP (in €/kg) for fish species and attributes, based on the
estimates of the RPE model.''
[[File:Wtp_table_35.JPG|center|WTP Table 35.]]

Table 36 shows the choice probability for fish species. This probability is higher for salmon,
seabream and trout, while is lower for herring and pangasius.

Table 36: Choice probability for fish species (mean value, standard deviation, minimum and
maximum) with Fish Species-Specific Effect (FSSE) and Random Price Effect (RPE) models
- Spain.''
[[File:Wtp_table_36.JPG|center|WTP Table 36.]]

We have derived seven different segments, based on choice probabilities, shown in Table 37.
The first cluster, which is the larger one (21%), shows medium price premiums, compared to
the other clusters, for species and attributes. It is mostly made by young females, highly
educated, with high income and relatively medium-large family units (four people). Segment 2
(18% of the sample), showing the highest WTPs, is composed by young males, with high
income, living in large family units (four people or more). Segment 3 shows medium-high WTP
estimates too (19% of the sample), is relatively more representative of older females, with
lower income level, living in smaller family units. The fourth segment (19% of the sample)
shows an average WTP for species and attributes. It is mostly composed by middle-aged
males, less educated and with lower income. Segments 5, 6 and 7 are all exhibiting lower
premiums estimates for species and attributes.

Table 37: Segmentation of the Spanish market, based on individuals’ choice probabilities.''
[[File:Wtp_table_37.JPG|center|WTP Table 37.]]

===Appendix===

====Synthesis of the qualitative phase====

''Table A1: Familiarity, attributes, barriers, and format for fish species and countries, as retrieved from the qualitative phase (Task 4.1)''

[[File:Wtp_table_a1.JPG|center|WTP Table A1.]]

====Preliminary list of attributes====

''Table A2: Preliminary list of attributes and levels by species.''

[[File:Wtp_table_a2.JPG|center|WTP Table A2.]]

====Pictures of the format attribute====
''Table A3: Set of pictures of the format attribute, by species in each country.''

=====France=====
[[File:Wtp_table_a3_france.png|center|WTP Table A3 - France.]]

=====Germany=====
[[File:Wtp_table_a3_germany.png|center|WTP Table A3 - Germany.]]

=====Italy=====
[[File:Wtp_table_a3_italy.png|center|WTP Table A3 - Italy.]]

=====Spain=====
[[File:Wtp_table_a3_spain.png|center|WTP Table A3 - Spain.]]

=====UK=====
[[File:Wtp_table_a3_uk.png|center|WTP Table A3 - UK.]]

===The questionnaire===

'''Appendix A4: The questionnaire in the English version. (5 pages)'''
[[File:Wtp_question_1.JPG|center|WTP questionnaire page 1.]]
[[File:Wtp_question_2.JPG|center|WTP questionnaire page 2.]]
[[File:Wtp_question_3.JPG|center|WTP questionnaire page 3.]]
[[File:Wtp_question_4.JPG|center|WTP questionnaire page 4.]]
[[File:Wtp_question_5.JPG|center|WTP questionnaire page 5.]]

== References & Readings ==

----

===Conclusions===

The activity performed in Task 4.4, resulting in this Deliverable (D4.7), investigated consumer
demand and choice behaviour for fresh fish using an online choice experiment. In particular,
we examined consumer preferences in five countries for different fish alternative species and
attributes, using a labelled choice experiment (LCE). The results in terms of part-worth
associated with the single attributes allowed to estimate consumers’ willingness to pay (WTP)
for the salient product characteristics. The heterogeneous choices and preferences across
countries and species suggested the application of a model where the attribute part-worth were
estimated separately for every species in every country (fish species-specific effects model –
FSSE). Using a random price effect (RPE) model we estimated the effects and WTP for
attributes at consumers’ individual level; the individual consumers‘ choice probability so
estimated thus was used for segmentations in every country.
These results are actionable for marketing strategy and useful input in the developing of the
decision support system (PrimeDSS). In particular, using the WTP results of the FSSE model
it will be possible to estimate, in the five countries, the consumers’ willingness to pay a premium
for specific species-related attributes cumulated in a product profile with certain characteristics.
In other words, the DSS user, by selecting the preferred characteristics of the given species in
a specific country, will retrieve the estimated consumers’ willingness to pay for that product,
based on the estimated model on the data collected. Given the representativeness of the
sample in every country, this result will provide stakeholder with a clear guidance about the
(hypothetical) consumers’ preferences for each product profile.
Similarly, the segmentation performed using the RPE model will provide DSS users with more
details about the characteristics of the market segment more attracted by the given product
profile. In addition, RPE model effects will enable us to estimate price elasticities, in which
cross price elasticities among fish species are not constant. With these outcome it will be
possible to develop competitiveness clouds and vulnerability index.
Finally, the present activity have been implemented in parallel with the survey in Task 5.4, with
a number of common questions (the “bridge questions”) leaving the possibly to combine the
results of both surveys in a more powerful tool to be implemented in the PrimeDSS.
The results of WTP and price elasticity for markets and segments across the five surveyed
countries, as well as the possibility to combine the survey in Tasks 4.4 and 5.4, will be further
investigated in Tasks 5.4 and 5.5, and eventually used as an input for the PrimeDSS
development in WP6 of the project.'

===Acknowledgement===

We gratefully acknowledge the Primefish project partners for having provided feedback and
helpful input to the present research. In particular, we thank Birgit Hagen, Emilia Cubero
Dudinskaya and Antonella Carcagnì (University of Pavia, Italy), José Luis Santiago CastroRial,
(Centro Tecnológico del Mar - Fundación CETMAR, Spain), Dimitar Taskov (University
of Stirling, United Kingdom), Sterenn Lucas (Institut National de la Recherche Agronomique –
INRA, France), Bjorn Suckow (TTZ, Germany), and Olga Untilov (Universite de Savoie,
France).

===References===

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introduction of new organic products. The case of the Mediterranean sea bass
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willingness to pay for quality attributes of fresh seafood: A labeled latent class model.
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Tailor-Made Seafood Products. Improving seafood products for the consumer.
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WP4

2018-10-24T13:08:33Z

Jacandrade:

= Work Package 4: Products, consumers and seafood market trends =

----

----

 

== General information ==

----

=== PRODUCT AND CONSUMER TRENDS ===

WP4 will analyse the impact of consumer behaviour, market trends, innovation and product development in the seafood market. Work undertaken will be carried out in close co-operation with industry partners and key stakeholders. As a first step, micro-economic tools will be used to analyse how factors such as income, own prices and prices of substitute goods affect the demand for the chosen species. For this purpose, complete and/or partial systems of demand will be estimated. Results will highlight fish consumption within the consumers' diets, depending on country and types of consumers and will be used to simulate the effects of various price policies. In a second stage, past and current consumer preference trends will be analysed and the acceptability of fish products examined by looking at consumption in local, niche and global markets. The specific area of demand stimulation or manipulation through health, label and certification claims on one hand and negative press reports on the other hand will be analysed quantitatively where possible and compared with consumer acceptability of products using Conjoint Analysis. Finally, a database of successes and failures in product development and consumer behaviour will be used as a background material for trend research, yielding insights into product innovation and which product characteristics best fit consumers’ preferences. The outcome of the WP will be an overview of current and future trends and consumer behaviour in local, European and international seafood markets (SO4).

 

== Deliverables ==

=== [[Deliverable_4.1|D4.1 - Industry study cases report: A collection of marketing successes and failures in the World based on clever product innovation and/or marketing activities]] ===

Innovation is a ‘good, service or idea that is perceived by someone as new’. It is widely acknowledged that innovation is required for the growth of output and productivity and is also seen as a key to business success in a competitive environment. In 2012, the food and drink manufacturing industry in the European Union was the largest manufacturing sector in terms of value of the output with 15% of the total manufacturing turnover. However, it is widely perceived as not highly innovative. In addition, the commonly reported figures for new food product failure are between 70% and 90%. (Click title to read more)

=== [[Deliverable_4.7|D4.7 - Choice modelling report on innovative features and the consumers’ willingness to pay]] ===

The objective of this study was to investigate consumer demand and choice behaviour for
fresh fish at the retail market. In particular, we examined consumer preferences for different
fish alternative species, as well as different attributes, using a labelled choice experiment
(LCE). The outcomes allow to elicit consumers’ preferences and willingness to pay (WTP)
for the salient attributes of a variety of fresh fish species in the retail market.(Click title to read more)

== Links & Resources ==

----

*[http://www.primefish.eu/wp4-products-consumers-and-seafood-market-trends More] information on Work Package 4.
*Main project [http://www.primefish.eu website]
*[http://primefish.eu/project#WP4 WP4 Consortium]

Deliverable 4.1

2018-10-24T12:39:49Z

Jacandrade:

= Deliverable 4.1 - Industry study cases report: A collection of marketing successes and failures in the World based on clever product innovation and/or marketing activities =

----

----

== Executive Summary ==

----

Innovation is a ‘good, service or idea that is perceived by someone as new’. It is widely acknowledged that innovation is required for the growth of output and productivity and is also seen as a key to business success in a competitive environment. In 2012, the food and drink manufacturing industry in the European Union was the largest manufacturing sector in terms of value of the output with 15% of the total manufacturing turnover. However, it is widely perceived as not highly innovative. In addition, the commonly reported figures for new food product failure are between 70% and 90%. The present report was developed through a mixed research method – a combination of qualitative and quantitative analysis. The quantitative analysis used data from the Global New Product Development (GNPD) Database provided by Mintel (market intelligent agency) and focused on innovation of food product containing seafood as major ingredients in 25 European countries. The innovation in the database can be from five different launch types: a totally new product, a new packaging, a new recipe, an extension of the range and a product relaunch. Secondly, an explorative multiple case study analysis was performed based on 17 cases of innovative seafood products (4 failures and 13 successes) balancing the different types of innovations, claims, fish species, markets and successful/failed products as much as possible. All the selected cases have at least one product based mainly on one of the following fish species: salmon, trout, seabream, seabass, cod, pangasius or herring. Multiple data sources were used to develop the case studies: archives, interviews, questionnaires, and observations. The case analysis was structure along a common framework derived from literature review on food/fish innovations. Cod innovations increase across the European market, even if the share of cod over all seafood products is decreasing. It shows an orientation of cod innovation over sustainable claims (SC) (65.26% of SC is environmentally friendly product, as MSC label). An important part of cod innovations is frozen. Herring innovative products are mainly produced in Germany and East European countries. Even if the number of innovation for this species increases at a lower rate than for others species, innovative herring products with sustainable claims don’t follow the same path and increase faster than all seafood innovation in this positioning. Products containing trout are not the most innovative seafood products, only a few references have been listed in the database used. The number of sustainable innovations increased slower than for other species. Salmon is an important species due to the number of innovations. Many companies on the salmon market are major retailers on the European market, and only few salmon specialized companies are present among the most innovative companies. The use of sustainable claims increases, but this increase is not significantly different to the average increase of all others species on the European market. Pangasius is not a widespread fish in Europe, and it represents only 0.67% of seafood innovation. Nonetheless, pangasius products have a clear positioning on naturalness and sustainability, probably in order to thwart the poor perception of this fish on the European market. Seabass products are not numerous on the market, but many firms are interested in its commercialization. Some of them as a diversification, others as a central specie to develop further. A large majority of seabass products is positioned in such a way on the market to help in the acceptance of transformed seabass. Indeed, it is a species usually consumed fresh, without any transformation.

The key driver for innovation, whether product or process, was the pursuit of larger market share or sustained competitiveness. The companies have demonstrated awareness of growing market demands in “convenient” fish products, but the way they respond to these demands varied by the firm scale. Both large-scale and small-scale companies’ mainly responded to internal stimuli for innovation based on the company developed business strategies and consumer research. Bigger companies tended to pass a clear message on their product quality to consumers, focusing on the product convenience and health. Smaller firms tried to occupy the niche market by targeting narrower consumer groups with very specific preferences. Innovation process has also varied between different firm scales. While in small company this was typically triggered by either current staff members or external institutions like universities, larger companies had dedicated R&D department for new innovation generation. Big companies also usually followed structured product development models as part of a wider innovation strategy, whereas small companies introduced innovation through “trial and error”. No correlation has been found between the product success and the innovation process strategy per se. Nevertheless, ‘customer pull’ type of projects are expected to be more successful as they are more tailored the specific needs and wants of the end consumers. While due to sampling limitations, no major generalisations could be made about the wider industry, the results of the cases investigated point towards the need for a purposeful and goal-oriented approach to innovation, with strong leadership and an intellectual inputs from various sources. There was a strong indication that a new seafood product has to be a good ‘fit’ for the intended market, implying the need for clear understanding of the market (whether through marketing research or other means) and target consumer.

== Introduction ==

----

In 2012, the food and drink manufacturing industry in the European Union was the largest manufacturing sector in terms of value of the output with 15% of the total manufacturing turnover. It also remains one of the largest in terms of employment and number of companies, the large majority of which are small and medium scale enterprises (SMEs) (ECSIP Consortium, 2016).

Within the food and drink industry, the seafood processing sector had the smallest share of turnover in 2012. With 3570 companies, it occupied 0.01% of the total number of companies in the food sector (ECSIP Consortium, 2016). Nevertheless, the enterprises operating in the EU food and drink industry are a vital link in the supply chain, enabling wider economic activity and employment (Traill & Grunert, 1997).

In the context of globalisation and increased competition on domestic and foreign markets, innovation is seen as a key pathway to creating and sustaining competitive advantage at the firm level as well as stimulating wider economic growth (Porter, 1985, 1990). Indeed, one of the five targets of the Europe 2020 strategy is 3% of the GDP of the EU to be invested in R&D, a tool for innovation (EC, 2016). The food and drink industry, however, has been scored as a low-medium R&D intensity sectors, a group of sectors with R&D intensity between 1% and 2% of net sales, which comes at the background of companies in the automobile and electronics industries with R&D investment of more than 20% (Hernández et al., 2014). Nevertheless, as we will see below, this may not necessarily mean lack or a low level of innovation.

=== What is innovation? ===

Innovation is a ‘good, service or idea that is perceived by someone as new’(Grunert et al., 1997). According to the same authors, innovation may be related to invention but not all product innovations are based on inventions. New product could merely be an improved existing product. Schumpeter (1939) distinguishes between five types of innovation: introduction of new products; introduction of new methods of production; opening of new markets; development of new sources of supply for raw materials or other inputs and creation of new market structures in an industry. Similarly, The Oslo Manual on collecting and interpreting innovation data distinguishes between four innovation areas: product, process, marketing and organisation (OECD, 2005). In the context of the food industry, innovation can include new products, new types of packaging (including both the physical characteristics of packaging and the contents of information on it, new recipe (new flavours, new additives, conservation methods), range extension, re-launch, new marketing methods and implementation of a new or significantly improved logistical process (ECSIP Consortium, 2016).

The focus of this study is primarily on product innovation. However, the distinction between product and process innovation is not always clear-cut, since product and process innovation are often dependent on each other. Process innovation has been defined as “an investment into a company’s skills, resources and competences, which allows the company to introduce cost-saving changes in the production processes but also to introduce new technology which allows the production of a range of products quite different from the existing one” (Grunert et al., 1997). Modern market pressures have pushed food processing companies to move away from a focus of process improvement and cost reduction alone, which used to be the norm in the past, towards creating products that meet the consumer demands more successfully, where product innovation plays a key role (Fortuin & Omta, 2009). In the present-day food industry the introduction of new products is seen as an essential element of competition between companies (Grunert et al., 1997).

=== Why look at innovation ===

It is widely acknowledged that innovation is required for the growth of output and productivity. Schumpeter (1939) argues that economic development is driven by innovation through a process of replacement of old technologies with new, which he labels “creative destruction”. But innovation is also seen as a key to business success. A large study by the American Management Association, involving 1396 executives from large multinational companies showed that more than 90% of the participants believed innovation to be important or extremely important for the long-term success of the company and that this will still be the case in ten years’ time (AMA, 2006).

However, unsuccessful innovation may be even more harmful than no innovation, given the high costs associated with it (Traill & Grunert, 1997). The commonly reported figures for new food product failure are between 70% and 90% (Stewart-Knox & Mitchell, 2003). However, as pointed out by Grunert et al. (1997) those figures may be overstated since the definition of success, usually measured by the period which a product has been on the market, is not standard, and indeed a product may be successful even though short lived, depending on its intended function. For example, a range of products can be introduced by a company to diffuse the success of a new product launch by a competitor, being consequently withdrawn but nevertheless strategically successful. Similarly, the definition of a new product varies among authors. It has been argued that if a new product is ‘one that is new to the consumer’ only 7-25% of food products launched can be considered truly novel (Rudolph, 1995).

=== Aims and objectives ===

In this report we mainly aim at addressing four research questions:

Q1: How has the seafood innovation developed over time in general and for the selected species?

Q2: What drives product innovation at the company level?

Q3: What factors determine the focus of innovation?

Q4: What factors are responsible for success or failure in product innovation?

 

== Methods ==

----

The present report was developed through a mixed research method – a combination of qualitative and quantitative analysis. The combination of data types can be highly synergistic. Quantitative evidence can indicate relationships which may not be salient to the researcher, while qualitative data are useful for understanding the rationale underlying the relationships showed in the quantitative data or suggested through theory (Eisenhardt 1989).

The report starts out with an analysis of The Global New Products Databased (GNPD) which is constructed by Mintel, a market intelligence agency, working across 34 countries. The main objective of GNPD is to provide data giving the depth of resources necessary to track trends in product innovation and retail success. Product innovation are tracked on shop and online across 62 of the world’s major economies; and around 33,000 new products a month are added into the database. Eighty fields of information ranging from companies information and flavour to packaging and positioning are noted. This database allows access to the products characteristics, the marketing positioning and the type of launches. However, it only concerns packed products. It provides detailed data on new products launched in the food, beverage, beauty and personal care, healthcare, household goods and pet care markets.

The innovation taken into account into the database can be from five different launch types: a totally new product, a new packaging, a new recipe, an extension of the range and a product relaunch. The product has to be claimed as “new” to be picked up. A new product corresponds to a new line or a new family of products for the brand, this kind of launch is brand depending. This also includes brand products that are launched in a new country where the product was not commercialized (Mintel International Group Ltd. 2012). A new packaging is based on the visual aspect of the product, it corresponds to product labelled as '''new look''', '''new size''' or '''new packaging''' (Mintel International Group Ltd. 2012). A new recipe concerns the new ingredients formulation of an existing product. An extension of the range depends of the brand line; it is assigned when an innovation is the horizontal extension of an existing line (Mintel International Group Ltd. 2012). Finally, a relaunch is assigned to an innovation when it is indicated on the product packaging or when a secondary information source informs consumers (trade show, website or press). It is also assigned when the product has been both reformulated and it has a new package (Mintel International Group Ltd. 2012). Thus, there are mainly product and marketing innovations valorised in this database, as major process or social innovations are not necessarily highlighted to shopper.

For this analysis on European Seafood market, we looked at food product containing seafood as major ingredients (seafood has to be in the five main ingredients to be selected for this analysis). The European market as delimited (and covered) by Mintel concerns 25 countries: Germany, Austria, Belgium, Croatia, Denmark, Spain, Finland, France, Greece, Hungary, Ireland, Italia, Norway, Netherland, Poland, Portugal, Czech Republic, Romania, United Kingdom, Russia, Slovakia, Sweden, Swiss, Turkey and Ukraine.

Secondly the report focus on a primarily qualitative analysis - an explorative multiple case study analysis where the unit of analysis is the firm, although special attention is also given to one of the main successful or unsuccessful company’s products. The research strategy of case studies was chosen because it focused on understanding the dynamics present within single settings, at numerous levels of analysis, and can be used to accomplish various aims, ranging from providing a description to generating theory (Eisenhardt, 1989).

The cases were identified from secondary data (e.g. newspapers, company sites, specialized literature, innovation awards, etc.). Then, a first stage selection based on careful cross-checks with databases such as Lexis Nexis4 and GNPD, resulted in 60 proposed cases (9 product failures and 51 successful products). From them, 17 were selected (4 failures and 13 successes) for in-depth studies, in order to provide a detailed view on the successful – or unsuccessful – industry practice /or learnings.

All the selected cases belong to the seafood industry and have at least one product based mainly on one of the following fish species: salmon, trout, seabream, seabass, cod, pangasius or hearing. Moreover, the final selection of the cases was done balancing the different types of innovations, claims, fish species, markets and successful/failed products, among the cases. The selected cases can be observed in the Table 1.

''Table 1.Case studies general information''

{| class="wikitable" style="width: 100%;"
|-
! Case
! Innovation
! Major claim
! Fish species
! Markets
! Launching year
! Success/failure
|-
| A
|
*New packing
*New recipe

|
*Convenience

| Salmon, Seabass, Seabream
| UK
| 2010
| Success
|-
| B
|
*New recipe

|
*Quality and tradition

| Herring
| France
| 2012
| Failure
|-
| C
|
*New product
*New recipe
*Extension range

|
*Natural
*Health

| Salmon
| United States, Canada, European Union
| 2014
| Success
|-
| D
|
*New product
*New process

|
*Quality and taste

| Salmon
| Italy
| 2000
| Success
|-
| E
|
*New product
*Extension range

|
*Convenience

| Salmon, Cod
| United States
| 2014-2015
| Success
|-
| F
| *New product
| *Natural
*Health
*Local

| Trout
| Italy
| 1989
| Success
|-
| G
|
*New product
*New recipe

|
*Convenience
*Health

| Trout
| Italy
| 2015
| Failure
|-
| H
|
*New product

|
*Convenience
*Natural

| Trout
| Italy, Switzerland
| n.d
| Success
|-
| I
|
*New product
*New recipe

|
*Convenience
*Health

| Seabass
| Italy
| 2011
| Success
|-
| J
|
*New product
*New recipe

|
*Convenience

| Pangasius
| Europe, Asia and USA
| 2005
| Success
|-
| K
|
*New process

|
*Quality

| Trout
| UK
| 2008
| Success
|-
| L
|
*New Product

|
*Convenience

| Salmon
| Spain
| 2013
| Success
|-
| M
|
*New product

|
*Convenience

| Salmon, cod, seabass, seabream
| Europe
| n.d
| Success
|-
| N
|
*New Product

|
*Convenience

| SeaBream
| Greece, Russia
| n.d
| Failure
|-
| O
|
*New product

|
*Natural
*Health
*Gourmet

| SeaBass
| Croatia, Italy, Germany
| 2011
| Failure
|-
| P
|
*New process

|
*Quality

| Salmon
| Norway
| n.d
| Success
|-
| Q
|
*New product

|
*Quality

| Cod
| Germany
| n.d
| Success
|}

From the selected cases, 13 are product innovations, frequently related to new recipes (4 cases) or to an extension of product range (2 cases). There is also one case in which the new product development is related to a new process. Among the claims, the most common ones are convenience (9 products), health (5 products), high quality (5 products) or natural (4 products). Less common claims include taste or gourmet (2 products) and the ‘local’ claim (1 product). Regarding the fish species, 3 of the analyzed products are based on several fish species (salmon, cod, seabass and seabream). The rest of the products are focused on one particular specie: salmon (5 products), trout (4 products), seabass (2 products), seabream (1 product), cod (1 product) and pangasius (1 product).

Following the selection of the cases, multiple types of data compilation are used to develop the case studies: archives, interviews, questionnaires, and observations (Yin 1994). The case analysis was structure along a common framework derived from literature review on food/fish innovations. The major areas were developed in a semi-structured interview guideline, sent with instructions to all partners. The guide included information as aspects of company general information, market structure, innovative practices, innovation inside the firm, sources of innovation, success/failure perception, and more detailed information on the selected successful/fail product.

All firms were contacted by phone and additional information was sent via e-mail by local researchers. The semi-structured interviews were developed at the firms in their local language in order to enhance understanding. The interviews were carried by one or two local researchers, and when possible, these were recorded. The interviews were reinforced with additional secondary data collection and analysis. Then, based on the interview material and secondary data, a cross case analysis is performed with the objective of identifying commonalities and differences between the firms, operative markets, species, and successful/failure outcomes.

The analysis of the information is done through a cross-case analysis. All the results are presented based on the analysed case studies. Additionally, the report offers some comparisons of the qualitative and quantitative results. The general framework used for the analysis is divided into three main levels even though these clearly interrelate and interact: 1. Innovative potential at the supra-company level - the wider environment 2. Company’s innovative potential 3. Influences on innovation success at the project level When investigating at the innovative potential at the supra-company level – i.e. the wider environment we look for factors like market structure/characteristics, the firm’s perspective on consumer trends (needs/wants), value chain organization and regulation.

When looking at the innovative activity at the company level we looked for factors like company size, resource availability and experience. Further firm strategy and orientation, capabilities and relationships with other companies/institutions where investigated.

Finally, when it comes to each of the selected case products, the material was analysed based on factors such as; source of the innovation, innovation strategy, organisation of the NPD (individuals, relations, management involvement, etc), type of innovation (incremental, radical, ‘originality’), market and consumer knowledge, process of new product development and perception of success and effect on performance.

 

== Background: literature review ==

----

The EU food industry is a dynamic arena affected by wider socio-economic processes. To remain competitive in the modern world, food manufacturers must develop capacity to innovate quickly and effectively as reliance on a stable range of traditional foods can no longer ensure business success (Grunert et al., 1997). The following discussion starts with an overview of the major trends in the industry, particularly as they relate to pressures on the industry to innovate. It then proceeds with a review of the factors deemed important for the success or failure of new food products.

=== Drivers of innovation – the bigger picture ===

Over the last several decades, significant changes in the patterns of food consumption have been observed in industrialised countries, with inevitable influence on the rate and direction of product innovation. The drivers for these changes will be examined from different perspectives, which however, are inherently related to and reinforcing each other.

==== Economic factors ====

Generally, growing disposable incomes in industrialised countries has translated into changes in the patterns of expenditure on food, such that an overall higher level of expenditure on food, through consumption of higher quality and more diversified foods rather than higher quantity, can be observed (Traill, 1997). When it comes to seafood, however, the development of consumer prices has played a similarly important role in determining consumption trends. Since price is often cited among the main barrier to consumption of fish and seafood (Birch, Lawley, & Hamblin, 2012; Liu, Bui, & Leach, 2013; Myrland, Trondsen, Johnston, & Lund, 2000; Trondsen, Scholderer, Lund, & Eggen, 2003; Verbeke & Vackier, 2005), a decrease in their prices relative to other sources of protein can act as a driver for consumption and overall expansion of the market. Indeed, good illustrations of this are shrimp, salmon, tilapia and pangasius, all of which are internationally traded commodities whose real prices have declined over time due to increased and more efficient production methods (Asche, Bjørndal, & Young, 2001). For example, shrimp and salmon have been leading the international farmed seafood market for almost three decades, with current real prices a third of what they were three decades ago (Asche, Roll, & Trollvik, 2009). However, relative prices of close substitutes remain still important for consumers. This is particularly true at times of economic recession, when clear declines in seafood consumption can be seen as consumers ‘trade down’ the food basket (Seafish, 2015).

 

==== Consumer concerns ====

A wide array of non-economic factors is also at play in determining the trends in food consumption. Increasingly, these relate to ‘intangible’ aspects of the product, such as ethical and sustainable sourcing.

===== '''Diet and health''' =====

As the populations of many industrialized countries are becoming older, richer, more educated and more health conscious, the demand for food that promotes health and well-being is growing (FAO, 2008). Seafood has often been promoted as a having a variety of positive health properties. Because of that, seafood, and especially oily fish, can also be seen as a functional food (Gormley, 2006), a fast growing market with high opportunities for innovation (Khan, Grigor, Winger, & Win, 2013). However, risks of eating fish linked to contamination with carcinogens has also been communicated to the public (Sidhu, 2003). As a result there is a general confusion over the right choice of seafood (Oken et al., 2012), the individual choice whether to consume fish or not being eventually dependent on the type and accuracy of information consumers are exposed to (Burger & Gochfeld, 2009).

 

===== '''Environmental concerns''' =====

Consumers, as well as major distributors, are increasingly concerned about the sustainability and risk of depletion of marine stocks. While the range of fish and seafood products labelled as sustainably sourced is expanding and the demand for sustainable seafood products is rising (Roheim, 2009), there is a debate whether this is due to genuine consumer demand or due to influences by NGOs and branding strategies by retailers (Gutierrez & Thornton, 2014). Gulbrandsen (2006) and Bush et al (2013) for example argue that most markets for eco-labelled forestry and fisheries products have been created as a result of pressure by environmental groups on consumer-facing corporations, rather than resulting from consumer demand. In any case, consumers have as a result an increasing abundance and diversity of certified seafood product to choose from. Increasingly, consumer behaviour is shaped by the growing popularity of sustainable seafood guides, such as Monterey Bay Aquarium’s Seafood Watch and MCS Good fish (Roheim, 2009). However, the availability of too much information from different sources, with sometimes conflicting advice can lead to consumer confusion and even negatively impact consumption (Oken et al., 2012; Roheim, 2009). The issue whether demand is genuinely ‘consumer driven’ or resulting from a ‘retailer push’ would remain nevertheless important to the performance of new seafood products on this market.

===== '''Production methods and safety''' =====

Consumers have become increasingly concerned about the ways in which food is produced, with ranging attitudes towards the use of certain new food technologies (Grunert et al., 1997). More stringent demands for assurance concerning safety is yet another high-profile issue that has emerged in recent years and shaping consumption patterns. As a result a variety of safety certifications have been developed which have become requirements by supermarket chains. European retailers for example increasingly expect supplies to comply with quality standards such as BRC and IFS, as well as traceability (CBI, 2015).

==== Societal change ====

Significant increase in the demand for convenience food can be attributed to increased participation of women in the work force (Traill, 1997). Due to factors such as time pressure, there is a strong rise in the demand for products that are ready to eat or require little preparation before serving (Brunner, van der Horst, & Siegrist, 2010). And while fish has been widely considered inconvenient because of the time and skills required for preparation (Olsen, Scholderer, Brunsø, & Verbeke, 2007), the current wide availability and expanding market for value added convenience seafood sets a new norm of how fish is consumed (Olsen, 2004). For example, the development of vacuum packed, pre-cooked mussels with sauce has been highly successful on the UK market, driven by the convenience, longer shelf life and versatility. In 2008 the ratio of Scottish produced mussels going to fresh counter market and to value added market were 70% to 30% respectively with a combined value of £6 million while in 2015 the ratio was 25% to 75% respectively with combined value of £15 million (Cameron, 2015). The trend in expanding value added seafood markets presents a vast opportunity for innovation in the field, with particular reference to younger generations.

Further, according to Olsen (2003) frequency of seafood consumption is positively correlated with chronological age, mediated by attitudes toward eating seafood, health involvement and perceived convenience. Markets where population is aging, and the number of one-person single households is growing, such as the UK and other European countries, present an opportunity for innovation tailored to this particular consumer group.

==== Availability of food products ====

The increase in the global supply of seafood over the last few decades, combined with technological innovations, has facilitated the international orientation of the seafood industry. In particular, progress in storage and preservation and improved logistics leading to lower costs have allowed international trade to grow (Asche, Bellemare, Roheim, Smith, & Tveteras, 2015). An increased range of raw material available to processors has stimulated experimentation with new species and served as a basis for a wide variety of seafood product innovations. Notable examples are pangasius, tilapia and shrimp.

==== Food retailing ====

Food retailing in Europe has become concentrated in the hands of leading multiple retailers with inevitable impact on innovation not only for processors but throughout the value chain (Murray & Fofana, 2002). One of the most powerful tools of retailers exerting control on the value chain is their ‘private label’ products (Bunte et al., 2011). It is generally accepted that private labels utilize markets created by branded products, by ‘imitating’ successful products. Private label products require little advertising as they rely on the image of the store, thus they are well placed to compete on price with the highly advertised branded products, pushing leading manufacturers to innovate even faster. At the same time, ‘private labels’ provide an opportunity for small and medium scale enterprises to supply the market while avoiding the prohibitive costs of developing a recognised brand (Traill, 1997).

=== Factors for success in innovation ===

A considerable amount of insight on the key success and failure factors in new product performance has been published in the late twentieth century. This has led to the generation of a plethora of factors deemed critical for successful innovation, often cited with contradictory outcomes (Balachandra & Friar, 1997; Grunert et al., 1997). The discrepancies could partly be explained by the lack of methodological standardisation in the study designs and definition of key variables, but also by the contextual differences. The vast majority of these studies focus on high-tech industries such as electronics, biotechnology, or pharmaceutical (Fortuin, Batterink, & Omta, 2007). The number of foodrelated studies on innovation is considerably smaller, while regarding seafood it is negligible. While drawing from a wider industrial base, the following synthesis will review the factors with higher relevance to the food industry, wherever possible illustrating with examples from the seafood sector.

==== Enabling environment ====

Porter (1990) argues that government policies play a key role in determining the competitiveness of enterprises as they directly influence the factors responsible for competitive advantage, with inevitable influences on innovation potential. Indeed, as pointed by Lindkvist & Sánchez (2008), prohibitive regulations have had a negative impact on the innovative activities and overall competitiveness of the Norwegian salt fish producers on the Spanish market. In particular, laws not allowing the processors to own fishing vessels have resulted in a fragmentation of the value chain and low level of control over the quality and timing of raw material supply. This has been further exacerbated by prohibitions on the use of chemicals other than ascorbic salts in the process of salting fish, leading to products of perceived inferior quality compared to the phosphate and antioxidant treated Icelandic products.

==== At the company level ====

===== '''Interaction with other companies''' =====

Innovation capabilities at the company level can be influenced by the existence of clusters of companies producing interrelated products and having high level of coordination between their activities, thus exploiting a larger pool of skills and enhancing their innovative power. The same advantages can be exploited in a network of companies, not necessarily physically clustered together (Grunert et al., 1997).

In a similar fashion, vertical cooperation can bring advantages to the innovative activities of the firm in the form of generation of market intelligence by sharing of information between downstream and upstream members, increasing the firm’s portfolio of competences and improving cross-functional communication.

However, it has been argued that the inflexibility created by committing to a few partners may act as an impediment to market intelligence generation and competence expansion. Similarly, increased levels of bureaucracy, especially in connection with large retail chains with emphasis on price instead of differentiation, may inhibit upstream innovation. In such cases, the choice of co-operation partners becomes a crucial issue.

In addition to regulations, a lack of cooperation in innovation and market development, due to mistrust and protection of self-interests, between producers of salt cod in Norway has been cited as a central factor for the loss of market share to Icelandic producers on the Spanish market (Lindkvist, 2010).

The role a company plays in the supply chain can directly influence its innovative potential. Harmsen & Traill (1997) show that the seafood company ‘Royal Greenland’ increased considerably its innovation activities when it expanded its customer base from food service to retail. Similarly, Christensen et al. (2011) find that firms delivering directly to end users were more likely to be innovative than those delivering to the processing or wholesale links of the value chain.

===== '''Size of company''' =====

Size of the company has been a central variable in much of the literature on innovation activity at the company level. The neo-Schumpeterian view maintains that large companies are more innovative than small companies, largely because of better resource base; human and financial (Grunert et al., 1997). In fact, previous research has shown that small firms face the liability of smallness (Aldrich and Auster, 1986; Freeman et al., 1983), that refers to the limited access to financial resources and competitive human capital. Such constrains might generate a limited market power and a small customer base (Carson, 1985), as the firms are unknown to their potential customers (Gaddefors and Anderson, 2008). Thus, these companies must devote several resources to building an identity, but the process is lengthy and costly (Gruber, 2004).

An alternative view, argues that SMEs tend to be market makers while large companies tend to be imitators, if the potential market volume allows large scale production. It has also been argued that SMEs are more prone to innovate because of organisational and behavioural characteristics allowing them to react to market changes more quickly e.g. little bureaucracy, high commitment and motivation by managers, higher exposure to competition, lower innovation costs, higher R&D efficiency. Similarly, it has been hypothesised that radical innovation is more typical of small and medium scale companies because it does not fit with the pragmatic philosophy of larger companies which are looking for a systematic innovation process. Nevertheless, according to Grunert et al. (1997), there is no consensus in the literature regarding the influence of firm size on its innovativeness.

===== '''Orientation of the company''' =====

Innovative activity can be seen as pertaining to a particular innovation or to the company in general. When it comes to particular innovations, it has the dimension of how new it is to the market and how new it is from a technological point of view. Innovation at the company level can be broken down to innovation speed, innovation willingness, innovation capacity and innovation quality (Grunert et al., 1997).

Earle (1997) argues that successful innovation is reliant on innovation-oriented company and positively reactive environment. It is the company’s strategic decision whether to pursue an innovation course or not. A firm may take either reactive or proactive approach in innovation to either avoid losing market share to an innovative competitor or to gain strategic market position relative to its competitors.

Depending on their involvement with innovation activities companies can be divided into innovative (or prospectors); improvers, getting involved once the initial products have been already developed;

‘me too’ companies, copying what others have already introduced on the market; and ‘die hard’ ignoring innovation altogether (Earle, 1997; Fortuin et al., 2007). The spectrum can be illustrated again by Icelandic companies producing salt cod for the Spanish market at one end and their Norwegian counterparts at the other (Larsen, 2014; Lindkvist, 2010).

Grunert et al. (1997) presents a further nuanced picture of innovation at the company level by providing two different perspectives: the first linking innovation with technological change, the driving force of economic growth, which is linked to, and can be measured by, R&D activities. As such the food industry could be classified as a low-tech industry due to the small R&D to sales ratios typically reported. In this view innovation could be regarded as a ‘technology push’.

On the other hand, from a marketing perspective, innovation can also be viewed as an activity required for fulfilling the unfilled needs and wants of potential customers using the skills, competences and resources of the company, often referred to as ‘market-orientation’ of the company, or ‘demand pull’. This view maintains that R&D activities do not guarantee innovative success alone, but only in interaction with the needs in the market (Gupta, Raj, & Wilemon, 1986).

As seen before, the food industry is generally considered as one with a low R&D expenditure. Indeed, Harmsen, Grunert, & Declerck (2000) in a series of case studies from the food industry showed that R&D is of minor importance in the innovation process, but innovative activities are nevertheless carried out. This was supported by findings by Avermaete et al. (2004) from a study on small-scale food manufacturers and by Christensen, Dahl, Eliasen, Nielsen, & Østergaard (2011) from a wider sectorial analysis. This has led Harmsen et al. (2000) to revise the framework proposed by Grunert et al. (1997) by focusing greater attention on ‘market orientation’ and ‘competencies’ and their interaction as explanatory factors for success. In their revised framework, orientation was seen as relating to ‘product’, ‘process’ and ‘market’, rather than simply markets. Competencies of the firm relate to the types of orientation but all three types, albeit to different degrees, were required for successful innovation. In-house capabilities of the work force were found to be strong determinants of innovation, particularly in small food firms (Avermaete et al., 2004). That is where the culture of the company and its vision are critical to successful innovation. It has been suggested than unconventional individuals rather than conventional science or engineering are central to innovation success. However, without entrepreneurial spirit and openness, new ideas by such individuals can be dismissed.

==== At the project level ====

There is a great number of studies identifying performance factors and Ernst (2002) provides an extensive review of the topic. Here we focus on some of the most often cited groups of factors, particularly as they relate to the food industry and over which there seems to be some level of consensus.

Among others, the success and failure of new food products has been related to the process of new product development (Stewart-Knox & Mitchell, 2003). The process comprises five to eight steps spanning from idea generation to launch activities, going through screening, research, development and testing. The sequence in which those activities are undertaken has been linked to success in the past. For example (Cooper & Kleinschmidt, 1987) argue that companies which taking a stepwise approach were more successful. However, in later publications the same authors show that concurrent, overlapping, flexible approach has better potential than a simplistic stepwise model (Cooper & Kleinschmidt, 2007). The common ground is the requirement for repeated evaluation throughout the process.

Market and consumer knowledge and retailer involvement in the process of new food product development has also been highlighted as a factors critical for success (Kristensen, Ostergaard, & Juhl, 1998; Stewart-Knox & Mitchell, 2003). Similarly, the involvement (as well as its intensity and quality), of the final consumer during the process of product development has been claimed to have positive impact on the outcome of innovation (Gruner & Homburg, 2000). Hoban (1998) has shown that new product developers in the USA rely heavily on retailer customers for market information, and few draw on other sources of information, consequently the retailer involvement has become increasingly important but does not guarantee success. The importance of gathering of information from a variety of independent sources, including retailers, suppliers, research centres, consumers, prior to the development of new products has been emphasized as a unique to the food industry (Stewart-Knox & Mitchell, 2003). Similarly, in a number of publications Cooper emphasizes the importance of market research up-front of the initiation of the process of product development (G. R. Cooper & Cooper, 1994; R. G. Cooper, 1999; R. Cooper, 1996). However, McGinnis & Ackelsberg (1983) note that market analysis can limit the innovators to existing markets with small incremental innovations rather than direct them to undeveloped markets with major innovations. Therefore, a careful balance must be maintained between market analysis and thinking ‘out of the box’ (Balachandra & Friar, 1997). Furthermore, good market analysis is dependent on the quality of data, but as the same authors have pointed out, analysing customer needs may not yield accurate information as the needs may not be known by the customers themselves. In an earlier paper (Balachandra, 1984) suggests the need for an existence of a strong market, instead of a potential market, as the difficulties associated with consumer research can be thus avoided.

Most prospector organise the innovation processes, including new product development, in projects where different functional areas of the firm are represented in cross-functional teams co-operating throughout the process (Fortuin et al., 2007). As Robert G Cooper (1999) points out important decisions as to whether to initiate a project, terminate or redirect it are rarely based on a systematic analysis of the factors determining success or failure, but rather on the experience of the team.

Overall, factors linked to product development strategy, indicate the need for a purposeful and goaloriented approach to product development and balanced technological and market-related aspects, as well as a synergy with existing activities (Earle, 1997).

Although often pointed out as a critical factor for success in wider industrial innovation (Ernst, 2002), involvement of senior management throughout the process of food product development has not been consistently shown to be critical for success (Stewart-Knox & Mitchell, 2003), perhaps in part due to the variety of sizes of companies investigated in different studies and the different roles senior management play in them. In an UK study (Stewart-Knox, Parr, Bunting, & Mitchell, 2003), involvement of senior management seemed to be unrelated, while in Denmark (Kristensen et al., 1998) it was found to be a determinant for success.

Similarly, the rate of new product introduction has also been shown to drive success in opposing directions. Higher rate of introduction implies the growth stage of a product, therefore a higher chance of success, but at the same time greater intensity of competition – a negative factor for commercial success (Balachandra & Friar, 1997).

Generally, original products seem to be more successful than adapted products, because food products market can become quickly overcrowded, although that may be context specific (StewartKnox & Mitchell, 2003). And despite that the failure rate for truly new food products has been shown to be as low as only 25% (Hoban, 1998), only a small proportion of new food products are truly novel (Rudolph, 1995).This may be due to a fear of failure of a new product and taking the ‘safe’ approach of redeveloping old products, which however, only perpetuates the problem of high rate of product failure.

 

== Results & Data ==

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=== Results from GNDP and discussion ===

Between 2000 and 2015, 22,406 seafood products have been launched on the European Market (based on Mintel’s Global New Products Database (GNPD), 2016). Over this period, the average repartition by launch type is: 44.16% new varieties, 38.64% new products, 11.72% new packaging, 2.99% new formulations, and 2.49% product relaunches. As new formulation and relaunch are not very frequent strategies, we will regroup these two types of launch for further analyses (which is logical as a part of relaunch is reformulated products). Behind the type of launch we can underline several types of innovation strategies. First, new product tries to develop a new market answering to new needs. In this case, the innovation can be considered as a breakthrough innovation and it is the most risky innovation for firms. New packaging, new variety and new formulation are more adaptation or renovation innovation, and even if not without risk, they are supported by an existing market.

[[File:Sfs fig 1.png|center|Figure 1]] ''Figure 1. Products repartition over type of launch. Source: GNPD, 22,406 Observations''

Thus, we can observe that the strategy of innovation has evolved over the period (see Figure 1 ). The part of totally new products as decreased, in favour of new variety and new packaging. In a very competitive global market, as two third of innovation disappeared within the first two years (Aurier & Sirieix, 2009), firms seems to favour adaptation and renovation, with a decrease in risk- taking.

These choices over type of launch can also be linked to the product positioning strategy. Different product positioning can be used to match products with consumer’s expectations. This positioning claims can be related to sustainable claims (e.g. organic, environmentally friendly products and eco- labelled), convenience claims (e.g. Ease of Use and Microwaveable), natural claims (e.g. No additives/Preservatives and GMO Free), health claims (e.g. Antioxidant and Vitamin/Mineral Fortified) or other claims (e.g. Fair Trade, Kasher and Premium). Between 2000 and 2015, 63.76% of seafood innovations have at least one claim, the number of products without any claim is continuously decreasing over the period considered. No claim products represent 69.64% of product launched in 2000 and only 28.27% in 2015. Most used positioning is sustainable (28.14% of seafood products over the period) and convenience claims (28.19% of seafood products over the period), which correspond to main consumers concerns in regard of fish consumption. Indeed the convenience in fish product is an important restraint to fish consumption: some consumers do not have the knowledge to prepare unprocessed fish, and fish is not viewed as an easy product to buy, to conserve and to cook (Brunsø et al., 2008). Furthermore, the convenience positioning is a more general food tendency leading to less cooking times and more easy-to-eat/easy-to-cook products. In regards of the sustainable concerns, this issue is important for seafood industries as some stocks are over exploited (FAO, 2014). And, as for convenience claims, sustainable claims on seafood products respond to a more general tendency on sustainability of food production, illustrated by the increase of organic products on shops shelves all across European countries.

[[File:Sfs fig 2.png|center|Figure 2]] ''Figure 2. Repartition of claims by type of launch (%) between 2000 and 2015. Source: GNPD, 22,406 observations (New product: 8,657; New Packaging: 2,627; New Formulation: 1,228; New Variety: 9,894)''

We observe different strategies over the different type of launch (see Figure 2 ). First, we assume that the choice of the product positioning can be either previous to the choice of launch either viewed as an opportunity after the choice of launch type. In the case of new product, the share of products without any product positioning is the most important compared to others categories, while this share is the lower for new formulation. In the case of totally new product, the innovation has been created for answer to new consumer needs, with probably less expectations in terms of product positioning, which can explain the higher share of products without claims. When a firm chooses to relaunch a product or to change the formulation it is generally to fit more to consumer’s expectation with no major change. In this situation the use of claims is an easy way to communicate on product characteristics, as convenience or sustainable dimension of the product. Those characteristics are either non-existent before the change either already existent but were not claimed to the consumer. The same opportunity occurs with a new variety or a new packaging: this innovation strategy of renovation/adaptation is a chance to expand the line to new positioning, to reach more consumers. In regards of the repartition of innovation across Europe, countries with more innovations are France, United-Kingdom, Spain and Germany, representing 54% of innovations. Nonetheless, it is complicated to go on some deeper conclusion, as there is a possible bias on the shopping execution by Mintel across countries, as well as some differences on the seafood market size across those countries. It is more interesting to look at the country of origin of the innovative firms, as well as the repartition of innovation between national brand and private brand ( Table 1 ).

''Table 1. Top 10 of innovative firms. Source: GNPD; 22,406 observations.''

{| class="wikitable" style="width: 100%;"
|-
! Firm
! Firm Type
! Firm Nationality
! Number of products
! Percentage
|-
| Lidl
| Retailer
| Germany
| 833
| 3.72
|-
| Marks&Spencer
| Retailer
| United-Kingdom
| 734
| 3.28
|-
| Tesco
| Retailer
| United-Kingdom
| 497
| 2.22
|-
| Aldi
| Retailer
| Germany
| 354
| 1.58
|-
| Findus
| Manufacturer
| United-Kingdom
| 304
| 1.36
|-
| Iglo
| Manufacturer
| United-Kingdom
| 261
| 1.16
|-
| Carrefour
| Retailer
| France
| 250
| 1.12
|-
| Picard
| Retailer
| France
| 245
| 1.09
|-
| Asda
| Retailer
| United-Kingdom
| 239
| 1.07
|-
| Auchan
| Retailer
| France
| 232
| 1.04
|}

If the majority of innovation are from national brand companies (61.82% of innovations between 200 and 2015), the top 10 company are for the most part retailer, with private brand products. They represent 17.64% of seafood innovation. Only two manufacturers reach the top 10: Findus and Iglo, generally the two leaders in the seafood market. We underline that most of those companies use more claims that other companies (the average of products with at least one claim is 63.66% for the entire sample - Table 2 ).

''Table 2. Top 10 of innovative firms - products positioning. Source: GNPD; 22,406 observations.''

{| class="wikitable" style="width: 100%;"
|-
! Firm
! Percentage of products with at least one claim.
! Percentage of products with sustainable claim.
! Percentage of products with natural claim.
! Percentage of products with health claim.
! Percentage of products with convenience claim.
! Percentage of products with other claim.
|-
| Lidl
| 59.78**
| 28.93
| 3.48***
| 4.68***
| 16.33***
| 27.01***
|-
| Marks & Spencer
| 79.97***
| 57.36***
| 23.02***
| 6.21***
| 41.83***
| 15.53
|-
| Tesco
| 84.51***
| 44.06***
| 28.57***
| 15.69*
| 29.58
| 41.45***
|-
| Aldi
| 68.93**
| 41.53***
| 17.51
| 9.89*
| 22.60**
| 20.90***
|-
| Findus
| 72.37***
| 49.01***
| 21.38
| 13.49
| 40.79***
| 8.88***
|-
| Iglo
| 90.04***
| 74.33***
| 52.87***
| 16.09
| 32.57
| 18.39
|-
| Carrefour
| 47.20***
| 10.80***
| 6.40***
| 6.40***
| 24.40
| 14.80
|-
| Picard
| 68.57
| 21.63**
| 0***
| 2.04***
| 53.88***
| 6.94***
|-
| Asda
| 82.01***
| 33.05*
| 53.14***
| 48.95***
| 23.01*
| 34.31***
|-
| Auchan
| 62.07
| 19.83***
| 9.48***
| 1.72***
| 29.74
| 28.88***
|-
| All companies
| 63.66
| 28.14
| 17.86
| 13.05
| 28.19
| 15.67
|}

''Mean comparison test (t-test): significant at *10%, **5%, ***1%''

Companies using more claims are positioning more than average in at least two claims. For example, “Marks & Spencer” has more products with claims than the average, and that is for sustainable, natural, health and convenience claims. Only other claim isn’t used significantly more by “Marks & Spencer”. Over the 10 companies, only two are using fewer claims than others: Lidl and Carrefour, two retailers companies. Some companies are specialized in one specific claim: Lidl uses less claims than other, excepted for other claim; Picard is not significantly different in claims use, excepted for convenience which is used significantly higher than average. Picard is a retailer, with a premium positioning over the frozen distribution network, selling almost exclusively its one private brand. This convenience positioning can be linked with the product storage, as frozen products communicate more on convenience, e.g. the use of microwave to defrost the product. The two manufacturers present in this top 10 use more claims than average. Iglo is more positioned on sustainable (almost 75% of its products) and natural (around 50% of its products). On its side Findus, although on sustainable claim too, is well positioned on convenience claim.

In the GNPD, the seafood storage can be refrigerated (38.19% of innovations), frozen (31.39%) or ambient (30.41%). There is slightly more products with at least one claim in the frozen category and slightly less in refrigerated ( Table 3 ). There is more convenience claim in frozen category while there is less health claim. This can be explained by two main reasons. For the convenience claim, as said before, frozen products are intrinsically linked with this positioning (e.g: rapid defrost). Then, the frozen products can be perceived as less healthy than fresh one, and in that case this claim is not sought by consumer. Inversely, there is less convenience claim in ambient category while there is more health (as well as more sustainable and natural claims). In this category, there is less intrinsic need to claim on convenience (e.g. can technology has not changed so must from consumer side, there is not so much “more easy to open”). Furthermore, the fatty fish (as sardine and mackerel) are more often commercialized in can, thus in ambient (77% of bluefish), while the lean fish (as cod and pollock) are more often commercialized in frozen (cod 52%, pollock 77.24%). Yet, fatty fish are rich in omega 3, which can be pointed to the consumer through health claim, which could explain, at least partially, the difference between storage.

''Table 3. Repartition of claims by storage. Source: GNPD; 22,406 observations''

{| class="wikitable" style="width: 100%;"
|-
!  
! Percentage of products with at least one claim.
! Percentage of products with sustainable claim.
! Percentage of products with natural claim.
! Percentage of products with health claim.
! Percentage of products with convenience claim.
! Percentage of products with other claim.
|-
| Refrigerated
| 62.95*
| 24.55***
| 18.88*
| 12.64
| 27.72
| 18.21***
|-
| Frozen
| 65.07**
| 28.96*
| 15.92
| 10.87***
| 33.88***
| 16.12
|-
| Ambient
| 63.21
| 31.87***
| 18.63*
| 15.82***
| 22.96***
| 12.02***
|}

''Mean comparison test (t-test): significant at *10%, **5%, ***1%''

We can look at the species mainly used in the seafood innovation in European market. The recognition of species is not easy as there is no obligation for transformed products in Europe to clearly identify the kind of fish used in the product. Thus, 14.57% of seafood innovation cannot be linked to a specific species ( Table 4 ). The seafood ingredients are presented on the product as fish or seafood. Furthermore, the scientific name is almost never specified, which makes the distinction between close species (between tunas for example) complicated. Nonetheless, regarding general fish species, we have some interesting result. The most important species in terms of innovation are Salmon (20.37% of seafood innovation contains salmon), Crustaceans (17.17% of seafood innovation contains crustaceans) and Tuna (15.65% of seafood innovation contains tuna). Those species correspond to the more consumed species in Europe: Salmon and shrimps are part of the main seafood consumed in France (FranceAgriMer (2014)), salmon is also largely consumed in Belgium and Netherland (Brunsø, 2008) while tuna is largely consumed in Spain (Brunsø, 2008). The species with the greatest number of products with at least one claim are the Pangasius, the Haddock and the Seabass. Behind those three species, there is different reality. Pangasius is not a common species in Europe; it is not an endogenous one as Pangasius is mostly raised in Asia. To thwart a poor image of this fish in Europe, it’s seems that companies tried to communicate on the sustainability, as it is the species with the most important share of sustainable claim. For the Haddock and the Seabass, the positioning is mostly on sustainability/naturality and convenience. The convenience claims are also mainly used for the shellfish and the mussel, underling a need for consumer to be helped in the way to consume shellfish (cleaning & cooking). The products with the smallest claim use are the bluefish products (Clupeidae, mackerel, and anchovy), generally commercialized in can, well known from consumer, and already easy to use.

''Table 4. Repartition of seafood innovation in regards of the species. Source: GNPD; 22,406 observations''

{| class="wikitable" style="width: 100%;"
|-
! Species
! Number of products
! Frequency on European market (%)
! Percentage of products with at least one claim.
! Percentage of products with sustainable claim.
! Percentage of products with natural claim.
! Percentage of products with health claim.
! Percentage of products with convenience claim.
! Percentage of products with other claim.
|-
| Bluefish
| 1970
| 8.79
| 51.88
| 21.32
| 11.78
| 13.76
| 14.47
| 11.88
|-
| Trout
| 437
| 1.95
| 58.12
| 20.82
| 12.36
| 11.44
| 22.88
| 20.59
|-
| Cephalopods
| 1097
| 4.89
| 52.87
| 10.76
| 14.49
| 8.84
| 33.18
| 10.85
|-
| Herring
| 917
| 409
| 57.25
| 35.88
| 20.83
| 8.29
| 8.94
| 8.40
|-
| Cod
| 1508
| 6.73
| 69.50
| 33.02
| 23.41
| 15.58
| 34.15
| 14.32
|-
| Crustaceans
| 3848
| 17.17
| 59.69
| 21.52
| 16.09
| 10.50
| 30.93
| 16.32
|-
| Flatfish
| 273
| 1.22
| 62.64
| 37.00
| 12.45
| 10.99
| 23.08
| 14.65
|-
| Haddock
| 327
| 1.46
| 83.49
| 40.98
| 29.97
| 20.49
| 32.11
| 25.08
|-
| Shellfish
| 999
| 4.46
| 64.16
| 20.22
| 14.51
| 10.11
| 41.34
| 17.42
|-
| Mussel
| 724
| 3.23
| 64.64
| 18.78
| 15.19
| 14.78
| 44.75
| 9.53
|-
| Pangasius
| 149
| 0.66
| 75.84
| 47.65
| 14.77
| 16.11
| 34.23
| 22.15
|-
| Pollock
| 1608
| 7.18
| 75.81
| 38.99
| 23.69
| 19.22
| 41.85
| 15.67
|-
| Salmon
| 4565
| 20.37
| 67.19
| 29.40
| 17.85
| 11.11
| 29.16
| 21.56
|-
| Seabass
| 91
| 0.41
| 82.42
| 28.57
| 29.67
| 14.29
| 45.05
| 21.98
|-
| Tuna
| 3506
| 15.65
| 66.12
| 40.25
| 15.74
| 13.72
| 23.05
| 12.18
|-
| Seafood
| 3265
| 14.7
| 60.31
| 13.32
| 22.39
| 12.96
| 29.68
| 15.62
|-
| Freshwater Fish
| 263
| 1.17
| 63.50
| 17.49
| 21.67
| 10.65
| 33.46
| 15.59
|-
| Other fish* (species specified)
| 376
| 1.67
| 60.11
| 16.22
| 22.87
| 18.35
| 29.26
| 16.49
|}

''*Species representing less than % of innovations have been gather in one category, except Pangasius.''

=== Results from GNPD by species ===

==== COD ====

Innovations for products containing Cod follow the same path as global seafood products, and the number of innovation increases over years ( Figure 3 ). One thousand five hundred and eight (1,508) products have been launched over the period (2000-2015), which represents 6.73% of total seafood innovations. The share of innovation with cod over all seafood innovations is decreasing across European countries, especially in Czech Republic. The only country with an increasing share of cod innovations is Figure 3. Innovations by claims Source: GNPD; 1,508 Observations Sweden. Most of them are a new variety extending existing range (47%) or a totally new product (34%). There is also more reformulation in cod innovations than for others species. As seafood in general, majority of innovation containing cod have at least one claim (69.50% of products). The positioning is mainly convenience (34.15%), sustainable (33.02%) and natural (23.15%). At the European level, the number of innovations with sustainable claims is increasing faster than for other species, but this rate is slower for any other claims, showing a market tendency of cod products over sustainability .

[[File:Sfs fig 3.png|center|Figure 3]] ''Figure 3. Innovations by claims Source: GNPD; 1,508 Observations''

We observe that at the European level the five most innovative companies for cod products are from United-Kingdom (Marks & Spencer, Findus, Tesco, Iglo) or Germany (Lidl) ( Table 5 ), and belong to the top 10 firms in seafood innovations. Distribution of innovation among firm is more concentrated for sustainable and natural claims, but can be considered as weak as companies on the top 5 share only 33.99% of innovations maximum. The major companies are present over all positioning; most of them are retailer companies. Only no claims products bring companies less innovative compared to the previous one (Delabli and Sagit).

''Table 5. Major firms by claims (for Cod products). Source: GNPD, 1,508 observations''

{| class="wikitable" style="width: 100%;"
|-
!  
! Top 5 firms
! Nbr of products
! Share of top5 firms
|-
| All cod
| Marks & Spencer, Findus, Tesco, Lidl, Iglo
| 1508
| 18.97
|-
| Sustainable Claims
| Marks & Spencer, Findus, Lidl, Iglo, Birds Eye
| 498
| 32.33
|-
| Natural Claims
| Birds Eye, Marks & Spencer, Iglo, Asda, Tesco
| 353
| 33.99
|-
| Convenience Claims
| Marks & Spencer, Findus, Picard, Lidl, Tesco
| 515
| 19.61
|-
| Health Claims
| Asda, Marks & Spencer, Tesco, Findus, Iglo
| 235
| 26.38
|-
| Other Claims
| Tesco, Lidl, Sainsbury’s, Birds Eye, Coop
| 216
| 27.78
|-
| No claims
| Findus, Marks & Spencer, Bofrost, Delabli, Sagit
| 460
| 14.13
|}

Some categories of foods are more represented under some positioning than other ( Figure 4 ). The share of child food represents 2.51% for all cod products and increases to 6.51% under natural claims, more that for sustainable claims (3.21%). The most important category, processed fish, represents 66.51% of all cod products, which is the same as for all observations seafood product (66.01% is processed fish), and stay stable over claims/no claims products. The result for meals shows a more important share of convenience claims products compared to all cod products. In regards of the conditioning, cod products are mainly frozen products (52.29%) and refrigerated (35.43%). The repartition between private label and national label are a little more in favour of private brand (41.38%) than for seafood as an all.

''Figure 4. Repartition of innovations by food categories Source: GNPD; 1,508 observations'' [[File:Sfs fig 4.png|center|Figure 4]]

To conclude, cod innovations increase across European market, even if the share of cod over all seafood products is decreasing. Still, the cod products drive sustainable innovation as its contribution to this marketing positioning is increasing faster than others species. It shows an orientation of cod innovation over sustainable claims (SC) (65.26% of SC is environmentally friendly product, as MSC label). An important part of cod innovations is frozen.

''Figure 5. Distribution of innovations containing Cod across Europe. Source: GNPD—1,508 Observations'' [[File:Sfs fig 5.png|center|Figure 5]] Legend: Darker green = most important number of innovations, lighter green =less important number of innovations (white=no observations for cod, stripes countries are not into the GNPD database). S (N/H/C/O): Country with the most important share of sustainable (natural/ health/ convenience/ other) claims on its cod products.

==== Herring ====

Innovations for products containing Herring follow the same path as overall seafood products, and the number of innovation increases over years ( Figure 6 ). Nine hundred and seventeen (917) products have been launched over the period (2000-2015), which represents 4.09% of total seafood innovations. The share of innovation with herring over all seafood innovations is decreasing across European countries, meaning the number of herring innovations increases slower than all seafood innovation. Most of them are totally new product (42%) or new variety (43%). As seafood products in general, majority of innovation containing herring has at least one claim (57.27%). Positioning is mainly sustainable (35.88%) and natural (20.83%). Convenience claim is underrepresented on herring innovations compared to overall seafood innovation (8.94% vs 28.19%). Nonetheless, the increase of convenience (as well as for natural) claims is faster for herring than for other species, meaning this situation may change within a few years.

[[File:Sfs fig 6.png|center|Figure 6]] ''Figure 6. Innovations by claims. Source: GNPD, 917 observations''

Looking at the innovation for herring products, we can see that at the European level the five most innovative companies for herring products are from Germany and Poland ( Table 6 ). A large majority of the companies in the top five, regardless of the claims, are from Germany. The others are from Russia, Poland, Belarus and Sweden. A majority of leading companies are manufacturer. The herring products represent more than 50% of innovation for the top five firms (except for Lidl): 75.76% of innovation by Nadler Feinkost (Germany, Manufacturer) contains herring.

''Table 6. Major firms by claims (for Herring products). Source: GNPD, 917 observations''

{| class="wikitable" style="width: 100%;"
|-
!  
! Top 5 firms
! Nbr of products
! Share of top5 firms
|-
| All herring
| Appel Feinkost, Lidl, Homann Feinkost, Lisner, Nadler Feinkost
| 917
| 18.65
|-
| Sustainable Claims
| Appel Feinkost, Lidl, Aldi Nord, Nadler Feinkost, Aldi
| 329
| 29.79
|-
| Natural Claims
| Homann Feinkost, Aldi Nord, Edmund Merl, Nadler & Appel Feinkost
| 191
| 28.80
|-
| Convenience Claims
| Santa Bremor, Russkoye More, PKP Meridia, Lisner, Homann Feinkost
| 515
| 31.71
|-
| Health Claims
| Appel Feinkost, Larsen Danish Seafood, Aldi, H. Kuhlmann, NR Fish
| 76
| 34.21
|-
| Other Claims
| Appel Feinkost, H.Kuhlmann, Kaufland Warenhande, Lisner, Abba Seaf.
| 77
| 27.27
|-
| No claims
| Appel Feinkost, Abba Seaf., Lisner, Lidl, Homann Feinkost
| 392
| 14.13
|}

Some categories of foods are more represented under some positioning than other ( Figure 7 ). First, there is no child food or soup containing herring. A large majority of herring innovations are processed fish (87.35% versus 66.01% for all seafood innovations), and Meals (10.14%). Beside some savoury spread products, other categories with herring are almost inexistent. The repartition over claims is quite the same as for all herring products, only the repartition on health claims favours meals products. In regards of the conditioning, herring innovations are mainly refrigerated (65.46%) and only few references are frozen (2.19% versus 31.39% for all seafood products). The share of national brand over private label is higher for herring than for all seafood products (77.21% versus 61.82%).

[[File:Sfs fig 7.png|center|Figure 7]] ''Figure 7. Repartition of innovations by food categories Source: GNPD; 917 observations''

To conclude, herring innovative products are mainly produced in Germany and East European countries. Even if the number of innovation for this species increases at a lower rate than for others species, innovative herring products with sustainable claims don’t follow the same path and increase faster than all seafood innovation in this positioning. Despite an absence of firms on the major innovative one (for herring products), the UK market is well positioned on other and health claims.

[[File:Sfs fig 8.png|center|Figure 8]] ''Figure 8 Distribution of innovations containing Herring across Europe. Source: GNPD—917 Observations'' Legend: Darker green = most important number of innovations, lighter green =less important number of innovations (white=no observations for herring, stripes countries are not into the GNPD database). S (N/H/C/O): Country with the most important share of sustainable (natural/ health/ convenience/ other) claims on its herring products.

==== Trout ====

Innovations for products containing Trout follow the same path as global seafood products ( Figure 9 ), and the number of innovation increases over years. Four hundred and thirty seven (437) products have been launched over the period (2000-2015), which represents 1.95% of total seafood innovations. Despite a few references, the share of innovations with Trout over all seafood innovations is decreasing, for all countries. For trout, most of them are totally new products (42%) or a new variety extending an existing range (44%). As seafood products in general, majority of innovation containing trout have at least one claim (58.12% of products). The positioning is mainly convenience (22.88%) sustainable (20.82%), and other claims (20.59%). Nonetheless, the number of innovations with sustainable claims is increasing slowly compared to other species, leading Trout to be the less innovative species in regards of sustainability at the European level. Only the number of products with natural claims is increasing a tiny bit faster than for others species. Despite few references, Swiss is the country with the faster increase of innovation with trout.

[[File:Sfs fig 9.png|center|Figure 9]] ''Figure 9 Innovation by claims Source: GNPD; 437 observations''

Looking at the innovation for trout products, we can see that at the European level the five most innovative companies for trout products are from Germany (Lidl, Gottfried Friedrichs), France (Aqualande, Carrefour) and UK (Marks & Spencer) ( Table 7 ). Two of those innovative firms are retailers. The trout innovations are not in a concentrate market as the top 5 firms represent only 16.02% of the innovation. Looking at the positioning scale, the east countries companies are well represented, especially on the natural claims (Russkoye More — Russia, Amstor— Ukraine).

''Table 7. Major firms by claims (for Trout products). Source: GNPD, 437 observations''

{| class="wikitable" style="width: 100%;"
|-
!  
! Top 5 firms
! Nbr of products
! Share of top5 firms
|-
| All trout
| Lidl, Gottfried Friedrichs, Aqualande, Marks & Spencer, Carrefour - CMI
| 437
| 16.02
|-
| Sustainable Claims
| Aqualande, HiPP, Marks & Spencer, Distriborg, Monoprix
| 91
| 23.08
|-
| Natural Claims
| Aqualande, Russkoye More, Amstor, Fischzucht Alexander Quester,HiPP
| 54
| 22.22
|-
| Convenience Claims
| Lidl, Marks & Spencer, Labeyrie, Nestle, PKP Meridian
| 100
| 19.00
|-
| Health Claims
| Aqualande, HiPP, PKP Meridian, Nestle, Saarioinen
| 50
| 40.00
|-
| Other Claims
| Lidl, Gottfried Friedrichs, Aldi, Carrefour – CMI, Marks & Spencer
| 90
| 30.00
|-
| No claims
| Gottfried Friedrichs, Lidl, Aldi, Bofrost, Vejle Seafood
| 183
| 16.39
|}

Some categories of foods are more represented under some positioning than other ( Figure 10 ). Indeed baby food represent only 2.98% of products innovation containing trout but represent 18% of products with health claims and around 9% for sustainable and natural. Furthermore, all baby food containing trout have a marketing positioning. Meals and meal centers category more presents 13% of trout products with convenience claims when it represents only 6.41% of all trout products. The trout based product are mainly processed fish, 82.61% which is higher than for all seafood innovation, as only 66.01% of seafood innovation are processed fish. In regards of the conditioning 77.35% of trout products are refrigerated (versus 38.19% for all seafood products). The repartition between private label and national label is identical to the seafood category as an all, that to say around 61% of products innovation from national brand.

[[File:Sfs fig 10.png|center|Figure 10]] ''Figure 10. Repartition of innovations by food categories Source: GNPD, 437 observations''

To conclude, products containing trout are not the most innovative seafood products, few references have been listed in the database used. The number of sustainable innovations increased slower than for other species, but faster for natural innovations even if the coefficient is weak. The most innovative firms are not necessarily the same than for seafood in general, and the most innovative countries (number of products) are not the most strategic on market differentiation through the use of claims.

[[File:Sfs fig 11.png|center|Figure 11]] ''Figure 11 Repartition of innovations with trout across Europe. Source: GNPD; 437 observations'' Legend: Darker green = most important number of innovations, lighter green =less important number of innovations (white=no observations for trout, stripes countries are not into the GNPD database). S (N/H/C/O): Country with the most important share of sustainable (natural/health/convenience/other) claims on its trout products.

 

==== Salmon ====

Innovations for products containing Salmon follow the same path than global seafood products, and the number of innovation increases over years ( Figure 12 ). The salmon is the most important species in seafood innovation. Four thousand five hundred and sixty five (4,565) products have been launched over the period (2000-2015), which represents 20.37% of total seafood innovations. On the period, the share of innovation with salmon over all seafood innovations is stable at the European level, but it increases in Ukraine, Ireland, Denmark and it decreases in Turkey, UK and Portugal. Most of them are a new variety extending existing range (46%) or a totally new product (38%) As seafood in general, majority of innovation containing salmon have at least one claim (67.10% of products) and the share of salmon innovation with claims increases, the fastest increase being for Ukrainian market. The positioning is mainly sustainable (29.40%), convenience (29.16%), and other (21.56%) Only convenience and other claims increase slower for salmon than for other species, but the share of these claims is already high for salmon products.

[[File:Sfs fig 12.png|center|Figure 12]] ''Figure 12. Innovations by claims. Source: GNPD, 4,565 observations''

Innovative salmon products are mainly support by firms from the top 10 of most innovative firms ( Table 2 & Table 8 ) as Marks & Spencer, Lidl, Aldi and Tesco. Only two companies on most important innovative firms are not retailers (Labeyrie and Nestlé), and all of them are major companies in Europe. For a large majority, salmon represents one third of their innovation. Only the companies Labeyrie is specialised in Salmon, as this species represents 85% of the brand new products.

''Table 8. Major firms by claims (for Salmon products). Source: GNPD, 4,565 observations''

{| class="wikitable" style="width: 100%;"
|-
!  
! Top 5 firms
! Nbr of products
! Share of top5 firms
|-
| All salmon
| Marks & Spencer, Lidl, Labeyrie, Tesco, Aldi 4
| 565
| 16.23
|-
| Sustainable Claims
| Marks & Spencer, Tesco, Labeyrie, Waitrose, Lidl 1
| 342
| 26.75
|-
| Natural Claims
| Marks & Spencer, Labeyrie, Tesco, Asda, Iglo
| 815
| 21.23
|-
| Convenience Claims
| Marks & Spencer, Labeyrie, Tesco, Picard, Waitrose 1
| 331
| 18.48
|-
| Health Claims
| Asda, Marks & Spencer, Albert Heijn, Tesco, Nestle
| 507
| 20.12
|-
| Other Claims
| Lidl, Tesco, Marks & Spencer, Labeyrie, Aldi
| 984
| 25.30
|-
| No claims
| Lidl, Marks & Spencer, Labeyrie, Aldi, Picard 1
| 498
| 14.13
|}

Some categories of foods are more represented under some positioning than other ( Figure 13 ). The repartition of food categories across claims is consistent for salmon products, and is consistent with seafood in general. Only the repartition changes for health claim, as the share of child food increases (7% versus 1.38% for all salmon products) at the depend of all others categories; and the repartition for convenience claim, as the share of meals increases (31% versus 18% for all salmon products). In regards of the conditioning 64,65% of trout products are refrigerated (versus 38.19% for all seafood products). The repartition between private label and national label is close to the seafood category as an all, that to say around 57.44% of products innovation from national brand (versus 61.82% for all seafood).

[[File:Sfs fig 13.png|center|Figure 13]] ''Figure 13 Repartition of innovations by food categories Source: GNPD, 4,565 observations''

To conclude, salmon is an important species due to the number of innovations, but the share of salmon is relatively stable over the period. Major companies in salmon market are major retailers in the European market, and only few salmon specialized companies, as Labeyrie, are present among the most innovative companies. The use of sustainable claims increases, but this increase is not significantly different than the average increase of all others species in the European market.

[[File:Sfs fig 14.png|center|Figure 14]] ''Figure 14. Repartition of innovations with salmon across Europe. Source: GNPD; 4,565 observations'' Legend: Darker green = most important number of innovations, lighter green =less important number of innovations (white=no observations for salmon, stripes countries are not into the GNPD database). S (N/H/C/O): Country with the most important share of sustainable (natural/health/convenience/ other) claims on its trout products.

==== Pangasius ====

Innovations for products containing pangasius follow the same path as global seafood products ( Figure 15 ). Nonetheless, the number of products with pangasius launched in Europe is still very low as only 149 products have been launched over the period, that to say only 0.67% of total seafood innovations. The share of innovation with pangasius over all seafood is decreasing over the period. Most of them are a new variety extending existing range (48%) or a totally new product (41%). There is less new packaging in pangasius innovations than for others species, but there is more range extension. As seafood in general, majority of innovation containing pangasius have at least one claim (75.84% of products). The positioning is mainly sustainable (47.65%), convenience (34.23%) and other (23.15%). At the European level, the share of pangasius innovation with claims is stable, only Belgium market shows an increase in this share. The share of products with natural and sustainable claims increase, but with a slow slope and at a lower rate than others species.

[[File:Sfs fig 15.png|center|Figure 15]] ''Figure 15 Innovations by claims Source: GNPD, 149 observations''

The innovation for pangasius products come mainly from two firms from the top 10 of innovative firms: Lidl and Aldi (both retailers and German). The top five firms are well represented on the majority of claims (besides natural and no claims). The firms in the pangasius market are mostly major companies where innovations with pangasius represent less than 5% of the firm innovation. However, some companies with only few innovations (less than 5) are specialized on pangasius innovations (Seamark, Alfredo Foods or DM Drogerie Markt).

''Table 9. Major firms by claims (for Pangasius products). Source: GNPD, 149 observations''

{| class="wikitable" style="width: 100%;"
|-
!  
! Top 5 firms
! Nbr of products
! Share of top5 firms
|-
| All pangasius
| Lidl, Aldi, Young’s, Queens Products, Albert Heijn
| 149
| 30.20
|-
| Sustainable Claims
| Lidl, Young’s, Aldi, Queens Products, Okoland
| 71
| 49.30
|-
| Natural Claims
| DM Drogerie Markt., Okoland, Tesco, Young’s, ATB Market
| 22
| 54.55
|-
| Convenience Claims
| Lidl, Aldi, Queens Products, Tesco, Albert Heijn
| 51
| 41.18
|-
| Health Claims
| Adli, DM Drogerie Markt., Young’s, Albert Heijn, Alfredo Foods
| 24
| 54.17
|-
| Other Claims
| Young’s, Lidl, Albert Heijn, DM Drogerie Markt., Seamark
| 33
| 45.45
|-
| No claims
| Appel Feinkost, Bofrost, Dia, Frost Invest, Iceland
| 36
| 27.78
|}

Some categories of foods are more represented under some positioning than other. First, there are no side and soup products with pangasius in it. The majority of pangasius products are processed fish (more than for all seafood, 80% versus 66%) and meals (less than for all seafood, 11% versus 17%). Another category is more important for pangasius than for all seafood being the child food sector (4% versus 1%) and it is even greater for natural claim (27% versus 4%) and sustainable claim (8.5% versus 1.8%). As said before, the important share of natural and sustainable claims on pangasius products is a way to thwart a poor image of this fish in Europe. As it is in line with the general consumer expectation on the child food market this result is not surprising. The majority of pangasius innovations are frozen (70%) or fresh (19%). The share of national brand and private label are quiet similar (53.69% and 46.31% respectively), which shows a more important representation of private label than for all seafood (38%).

[[File:Sfs fig 16.png|center|Figure 16]] ''Figure 16. Repartition of innovations by food categories Source: GNPD, 149 observations''

To conclude, pangasius is not a widespread fish in Europe, and it represents only 0.67% of seafood innovation. Nonetheless, pangasius products have a clear positioning on naturalness and sustainability, probably in order to thwart the poor perception of this fish in European market.

[[File:Sfs fig 17.png|center|Figure 17]] ''Figure 17. Repartition of innovations with pangasius across Europe. Source: GNPD; 149 observations'' Legend: Darker green = most important number of innovations, lighter green =less important number of innovations (white=no observations for pangasius, stripes countries are not into the GNPD database). S (N/H/C/O): Country with the most important share of sustainable (natural/ health/ convenience/other) claims on its trout products.

==== Seabass & Seabream ====

Innovations for products containing seabass and seabream (thereafter seabass) follow the same path than global seafood products, and the number of innovation increases over years. However, only 91 innovative products have been launched during 2000-2015 in the European market, which represents 0.41% of total seafood innovations. The small number of innovation underlines the fact that seabass is not commonly transformed, it is generally consumed (bought by end consumer) as whole fresh. If the number of product increases, the share of innovation with seabass over all seafood innovations decreases. Most of them are a new variety (48%) or a totally new product (45%). There is less new packaging in seabass innovations than for others species (2% versus 11.72%). A large majority of innovation containing seabass have at least one claim (82.42% of products). The positioning is mainly health (85.71%), other (78.02%) and sustainable (71.43%). At the European level, the share of seabass products with claims increases, especially in Turkey. The use of health claims increases faster for seabass than the average of other species, and it is also true for the use of sustainable claims.

[[File:Sfs fig 18.png|center|Figure 18]] ''Figure 18. Innovations by claims Source: GNPD, 91 observations''

A lot of firms are on the seabass market, they are either major companies on the seafood market or minor players. We can distinguish three strategies. Major retailer seafood firms, as M&S, are on the seabass market but this species represents less than 1% of their innovation. Thus, this choice can be interpreted as a diversification but with not much risk taking. We find intermediate firms, as Guyader, for which seabass represents 4 to 10% of firm’s products. Finally, there are also some small companies, as Coldfish: seabass can represent 100% of their innovations. Those companies are manufacturers, mainly from Italia and Turkey, and in this case the bet on seabass products success is more important .

''Table 10. Major firms by claims (for Seabass products). Source: GNPD, 91 observations''

{| class="wikitable" style="width: 100%;"
|-
!  
! Top 5 firms
! Nbr of products
! Share of top5 firms
|-
| All Sea Bass/Bream
| Marks & Spencer, Picard, Lidl, Nuova Azzurro, Plasmon Dietetici Alim.
| 91
| 25.27
|-
| Sustainable Claims
| Plasmon Dietetici Alim., Marks & Spencer, Iglo, Picard, Tesco
| 26
| 53.85
|-
| Natural Claims
| Marks & Spencer, Plasmon Dietetici Alim., Coldfish, Guyader, Iglo
| 27
| 48.15
|-
| Convenience Claims
| Marks & Spencer, Lidl, Salmon Club, Dardanel Onentas, Gea
| 41
| 34.15
|-
| Health Claims
| Plasmon Dietetici Al., Çamli Yem Besicilik, Appetais, Coop It., DImar
| 13
| 61.54
|-
| Other Claims
| Picard, Iglo, Arctic Royal, Auchan, Coop Italia
| 20
| 40.00
|-
| No claims
| Aldi, Marks & Spencer, Bioresurs, Bofrost ,Concept Cool V.
| 16
| 43.75
|}

Some categories of food are more represented under some positioning than other. First, there is no soup, no side and no other categories with seabass. The overall repartition of seabass leads to more processed fish (75.82% versus 66.01%) and child food (5.49% versus 1.03%), and less meals (9.89% versus 17.08%), the difference being stronger for sustainable (80.76%, 11.53% and 3.84% respectively). The health claims gives pride of place to child food (around 30%). In regards of the conditioning, seabass products are mainly frozen products (50.55%) and refrigerated (36.26%). The repartition between private label and national label are a more in favour of national brand (58.24%).

[[File:Sfs fig 19.png|center|Figure 19]] ''Figure 19. Repartition of innovations by food categories Source: GNPD, 91 observations''

To conclude, seabass products are not numerous on the market, but many kind of firms are interested in its commercialization. Some of them as a diversification, others as a central species to developed. A large majority of seabass products has a market positioning to help the acceptation of transformed seabass. Indeed, it is a species usually consumed fresh, without any transformation.

[[File:Sfs fig 20.png|center|Figure 20]] ''Figure 20. Repartition of innovations with seabass across Europe. Source: GNPD; 91 observations'' Legend: Darker green = most important number of innovations, lighter green =less important number of innovations (white=no observations for seabass, stripes countries are not into the GNPD database). S (N/H/C/O): Country with the most important share of sustainable (natural/ health/ convenience/ other) claims on its trout products

=== Results from case studies and discussion ===

==== Innovative potential at the supra-company level ====

When investigating the selected case material i.e. the products and the approaches chosen by the associated companies it can be observed that companies to a large extend are i) aware of the consumer trends of wanting more convenient product i.e. more ready-to-cook and ii) respond to it, but to a different extent. In part this might be as commented by one of the cases, related to the markets behaving differently i.e. in southern Europe it is still an issue that consumers wants to see the whole fish – “to see the fish in the eyes” (a matter of checking for freshness), while for norther Europe this is not so much an issue.

Some products does also claim an added value through being marinated or having other added features making it a different taste experience and also as above being more ready to eat i.e. more prepared for the plate.

Further the products have common features also based on external expectations as claiming quality and also sustainability i.e. quality in respect of taking responsibility for the environment and/or ecological balance in the nature. Other orientations driven by market or consumer trends are being oriented towards i.e. claiming a healthy product. And, only one of the selected products has a price claim which also could be regarded as an external drive i.e. a significant proportion of the customers expecting food stuff to be offered at an affordable price. Also, on the other hand, premium price claims might be related to a player wanting to show superiority of the product.

The market price of raw material i.e. whole fish might also as commented by at least one case, negatively affect the willingness and/or felt need for innovation i.e. if selling raw material is more profitable than processed products. But, refraining from taking part in the innovative development might be risky with respect to access to future market share i.e. if larger volumes of the market are moving into processed seafood. And, it is e.g. observed from the Mintel data base that Turkish industry has a higher innovation degree than EU producing countries, and at the same time it is observed that the majority of the growth in the seabass and seabream markets, especially in Northern Europe – with more processed products, is taken by Turkish exports to EU.

There are also some examples of products being driven by new technologies becoming available i.e. processing technology and or technological equipment.

The relation in importance between the external drivers and internal drivers seems to be relatively different where in some companies one is mainly responding to major external trends as a basic strategy, while in others there is a strong internal drive for developing the production and the products. The material might indicate that the latter is more present in private family owned small and medium sized enterprises, while for larger enterprises e.g. stock market or investor owned companies, innovation comes as a result of a decided strategy based on market/consumer trend analysis. The material might also indicate that smaller companies to a larger degree claim that continuous innovation is important for staying in business and/or growing.

Often the justifications for providing the new product is a presence of an unsatisfied market i.e. a market demand, and the trend of customers asking for a more convenient product is highly present in most of the cases investigated. Also, to a large degree, successes is claimed to be based on ability to satisfy the market. Few cases report to have made a product not being demanded, but still becoming a success when customers see the positive attributes of it.

A few of the selected products has place of origin or the history of origin, as a major attribute, but this way of promoting products seems to be less developed than e.g. convenience of a product, and also may be, less than within other food product sectors like the livestock industry.

When addressing future development the important features pointed at for seafood innovations seems primarily to be addressing the need for convenient products; however, also addressing consumer trends among younger people is commented as a key strategy.

==== Company’s innovative potential ====

===== '''Company size and resource availability''' =====

According to the analysed cases, larger and smaller companies present some commonalities and some differences regarding their innovation practices. Additionally, some finding match with the literature, while other results do not. For example, both type of firms do product, and process innovation, which could be both classified as incremental (for a definition see (Balachandra and Friar, 1997) but with different levels of originality. It was not possible to establish a correlation between firm size and innovation activity. Nevertheless, their innovation styles, source of ideas and development differ. Small firms had a slightly higher tendency for process innovation than the larger firms. However, larger firms launched more ‘new products’ to the market than small ones. While a larger firm can launch until five to ten ‘new products’ a year; smaller firms declare to launch until three or four ‘new products’ per year.

There are also important differences on how small and large firms define a new product. While large firms base this definition on the customer, on stimulating the demand and the purchasing/acquisition activities; small firms focus more on the novelty dimension. Only one small firm made reference to the consumers, by defining a new product as that one that allows the firm to reach current non consumers. This shows how both type of firms have different focus and approached when developing innovations. Large firms keep a clear target, to get the customer to buy the product and to generate a profit, no matter if the innovation is really ‘new’ or just an adaptation. Small firms, on the other hand, focused more on actually generating new things, something that was not in the market. This could be seen in two possible ways. On one hand, it can show how more innovative oriented are small firms than large ones. One the other hand, it might show the lack of a clear product definition and target customer so that to create products for which there is no existing market.

Big companies usually followed a more structured product development model, part of a wider innovation strategy with budget allocated for innovation activities, whereas in small companies the process was described often as “trial and error”. Nevertheless, in both small and big companies, success has been achieved regardless of the presence or a lack of a clear model. In fact, large firms tend to focus on internal innovation and to be customer driven. The small firm’s innovation process is also internally driven and by its customers, however, the way it is develop is different. Smaller firms do not have a clear R&D department. In fact, in some cases, these companies associate with external partners as universities and research institutions in order to cover the lack of a R&D and develop new ideas for key innovations. Small firms also base more their innovations on the available resources that can come from within the company (CEO/entrepreneur and workers) or from external sources (suppliers and distributors). Regarding their in-house innovation, it is usually developed though the interaction of different people at diverse positions in the company. The entrepreneur or the CEO has a key role in this process, while the other managers/workers bring their expertise into the development of the new product. Moreover, frequently the first trials of the product are done at the internal level of the firm, between other workers or even with family members. Innovation can be also driven by the available/developed technology within the firm.

Concerning the innovation coming from external sources, several small companies report that they have received ideas for new products from their suppliers or the retailers that distribute their products. Innovative ideas from suppliers usually come in the form of new raw material or the availability of a different fish species. Then the firm takes over and develops the possible product according to their objectives or ideas. Retailers, on the other hand, are more direct in the way they bring innovative ideas to the firm. In some of the cases, small firms reported to have un-formal suggestions from the retailers regarding possible interesting products for the company. In other cases, retailers directly contacted the firm and explicitly requested the elaboration or development of some private brand products. Sometimes this ‘new products’ are based on one of the small company’s products, in other situations, the idea can come directly from the retailer.

Taking in consideration that 8 from the top 10 innovative firms are actually retailers, this fact provides some evidence on a key relationship between small and large retailers for the generation of innovation, in which small firms might have a bigger role than thought. For small firms, this becomes a way of promoting their product among retailers and other business in order to create business to business relationships. However, it is also a risky move, as the retailer might change their mind and change provider. To face this risk, many small firms are moving towards also developing a direct contact with the final customer, through local markets promotion, social media, sampling displays, etc. There is an on-going debate about the role of retailer’s own label products in competition with new branded products. It has been argued by experts that innovation comes from brand producers which are used by retailers for creating new markets, consequently exploited by the retailers own brand fully or partially. This statement was confirmed by several of the cases investigated here, particularly as it related to reward on investment, since innovation requires significant investment, so without consumer loyalty, the rewards to the innovator can diminish considerably.

In fact, given the lack of financial resources, small firms are not able to sustain big investments in R&D, product line expansions and marketing campaigns, while large firms can. Large firms are able to afford different kinds of promotional campaigns (including TV) and then monitor their results. Smaller firms lean more on public relations through social media, trade fairs and direct interaction with the customer. However, many of them do not track the results of these activities. Also, small firms tend to rely more on their experience, particularly the experience of the founder or CEO.

Large firms also have more resources and a more defined structure in the way they research and develop innovations. However, small firms are also quite innovative, regardless their limited financial resources. Small firms lean more on the capabilities of their staff, founder/CEO and previous experiences. In fact, it was observed that in some cases the development of new products based on existing products/inventions but in different industries (e.g. beef or poultry).

===== '''Firm’s strategy and orientation''' =====

All the analysed firms declared to be high quality oriented, however, the type of claim to sustain this quality varies among them. Although, in general terms there is a trend towards producing products based on the health claim, there are also differences concerning the size of the firm. Large firms tend to have a clear message on what a higher quality means, usually focused on health claims or convenience. Sustainability and natural claims also are common among large firms. Small firms tend to enhance a lot the focus on quality as their main point of differentiation with other competitors, but their claims vary. The most popular claim among small firms is artisanal production, followed by health and premium products. Artisanal in this context is seen as a good and bad point. On one hand, it offers a traditional product with traditional methods, something that brings sentiment (‘home-made’) or as it was before. On the other hand, some firms perceived also as a limitation, as usually is not linked to innovation or technology driven production.

In general, smaller firms tend to offer a wider variety on the use of claims. This also can be seen as a result of their strategy. These firms target niche markets, so they tend to focus on particular sectors of the market, trying to target customer with certain preferences (environmental friendly, natural, gluten free, etc.). One interesting and recent trend is to differentiate their product as a ‘local’ or ‘regional’ product. In some cases, the ‘local’ argument is used for key inputs in the breeding of the fish, which enhances their product attributes because of the inputs involved (e.g. the fresh water in the area). Other firms, have used the ‘local’ claim as a way to refer to high quality, as Europe in general has quite strict production norms. However, this last approach is mainly used only by firms at the regional level, and either way it might vary according to the market. Some small firms have currently certifications mainly because this is the only way the company can sell their products. This is mainly the case for business to business, as high quality processors or distributors, also look for high quality inputs or products.

In fact, large firms have more certifications than smaller firms. This makes sense, as large firms are also more internationally oriented (small firms prefer close markets) and to sell high quality products in international markets, a certification would provide the guarantee of such quality. Additionally, in the last years, a common way of expansion for large firms, has been through acquisitions. This has allowed them not only to enter new geographical markets, but also to integrate their value chain. This definitely has proven to be advantageous for them, as they are able to ensure traceability and quality from the start of the value chain, a limitation that some small firms have expressed (not being able to find the right quality inputs).

===== '''Firm capabilities''' =====

There are important differences on how small and large firms perceived their main capabilities. It becomes quite clear that large firms have developed more their market research and consumer communication capabilities. Small firms are still trying to do so, but there is a lack of monitoring their activities and their results. Also there is a general lack of access to resources to implement some market research methods. However, some small firms are trying to get some customer information in different ways. For example, through direct contact with their customers at the sale point, by developing and improving their website to be customer friendly or by trying to obtain such information through their retailers. Only one small company among the selected, actually does customer trials. Additionally, small firms enhance more on their knowledge as one of their key capabilities. This matches the literature, as in small firms the founder/manager tend to be a central figure that drives the firm. Moreover, the staff is usually highly involved in many decisions, and roles might overlap. For example, in several cases the founder or the quality managers were also in charge of the design of the packing. Regarding the search of opportunities, trends and information, there were no important differences regarding the size of the firm or the fish species. Neither for the skilled workers, as both type of firms also considered as a key capability.

===== '''Relationship with other companies/institutions''' =====

The most common kind of relationship with other firms is the one that ensures some kind of vertical integration in the value chain. This relationship might be with a supplier, in order to ensure certain quality or availability of the product, or with a distributor or exporter/importer, in order to guaranty the delivery to the customer under the right circumstances. There are also some R&D relations among the firms and research institutions or universities. This s mainly the case for small firms, but some large firms also practice this approach. For small firms, it is also more common to have informal agreements or partnerships with other companies or manufacturers.

==== Innovation at the project level ====

===== '''Drivers for innovation''' =====

In most of the cases the main driver for innovation, whether product or process, was the pursuit of larger market share or sustained competitiveness. Accordingly, for successful cases an increase in the overall performance of the firm was reported, albeit to varying degrees. However, in a case of a small scale producer, a clear innovation strategy has been followed with constant introduction of value added products, even though the company admitted, they were not bringing extra profit for the time being. The reasons for that could be found in a longer-term and outward-looking business strategy in which innovation is seen as a key competitive advantage for the future. This move was believed to be also the result of a strong and transformative leadership after the company’s acquisition by a larger agri-business.

Interestingly, however, one case went against the general pattern in terms of drivers of innovation. In this case of an unsuccessful product by a large-scale company, primarily focused on production of raw material, the innovative product (based on process innovation) was abandoned because of better financial performance achieved by selling non-value added products. The market at which the product was launched had a preference for whole fish rather than fillets, so no significant premium could be obtained through value addition product to justify the cost of production. In addition, in order to enter the multiple retail channel, relatively large volume of the product was required, which the company considered too risky provided the low price. The company seemed to be aware of a trend for growing markets for convenience products but in the short term found it more profitable to limit itself to providing non-value added products. From a global value chain perspective this process has been labelled ‘downgrading’ (Ponte and Ewert, 2009). And while traditionally, ‘upgrading’ has been associated with actions aimed at ‘moving up the value chain’, through producing higher value-added products or acquiring more sophisticated functions, in the broader sense abandonment of such functions or products in order to ‘reach a better deal’, including a balance between rewards and risk, could also be considered a form of upgrading. In this case, a link between the scale of production (economies of scale) and level of value addition, dictated by market conditions, could be established.

===== '''Source of innovation''' =====

In small companies, new product development was triggered typically by the senior managerial team, often including the owners of the business themselves. Two general patterns of idea generation were observed: (a) the idea originated from within the enterprise and (b) or from external sources. In the first case, the company develops new products based on perceived strong market demand, or due to experimentation with new, improved or existing production processes. Only a proportion of the developed products reach the stage of market launch. In the second case, sources of innovation could be clients, most commonly, research institutions and development agencies. When the new product characteristics were defined by the client a varying level of input into the design of the new product was still coming from within the company as it experimented with alternative product forms. One of the unsuccessful cases came from a company (B) which was ‘requested’ to produce a ready-to-cook meal with particular specifications which were believed by the retailer to lead to success. At the end, the failure was attributed to the inappropriate selection of fish species as the main ingredient by the producer, leading to ‘customers didn’t like the taste’. At the same time a ‘sister product’ by the same company, with alternative fish species but utilizing the same concept, was successful. Another unsuccessful case of a ready-to-cook meal however, came from innovative activity fully originating within the company. As with other new products, it was led by the owner and associates from the company without a clear strategy or preceding marketing research. And although it was designed to fit within the broader market for healthy and natural products, the approach resembled ‘shooting in the dark’ and its lack of success was believed to be caused by being ‘boring’ and ‘lacking emotion’.

In a case of a large export company ideas for new value added product development came from external agencies closer to the final EU market, which was believed to be strongly linked to the success of those products since the company was experiencing limitations with ‘consumer understanding’ being physically distanced from the market, complicated by providing products completely new to the market. In another case of a large European-based highly successful provider of branded value added products, innovation was partly outsourced to an external agency. The success of the product was believed to be due to satisfying a need for convenience as well as bringing awareness through advertising.

The source of product innovation observed here could be classified as ‘company push’, (whether the focus lay on the product or on the process of innovation) and ‘customer pull’, when the concept of the new product is provided by a client. This classification at the product level, could be seen as an elaboration of the existing typology of technology ‘push’ and ‘market pull’ regarding the orientation of a company e.g. (Grunert et al., 1997). Thus, at the project level we could distinguish between two types of product initiation. It could be reasoned that ‘customer pull’ type of projects would meet with more success as they are based on demand experienced by the seller, and are thus closely linked to the needs and wants of the end consumers. Similarly, the investment required for such innovation could be expected to be significantly smaller, given that the associated unsuccessful projects for each successful one are avoided. On the other hand, providing products to customer’s specifications usually means marketing under private label. And while this can increase the volume of production, it may lead also limited options for branding and imposition of too much control by the retailer over the processor. The influence of quality specification on value chain governance, the power of retailers and distribution of benefits has been examined by (Ponte and Gibbon, 2005) and applied to wine production in South Africa (Ponte, 2009). As seen in the results here, the level of ‘flexibility’ a producer has when receiving specifications for a new product would play a role in the chance for success of the product. The more flexible the request is, the more it resembles an in-house new product development process.

===== '''Justification of launch''' =====

In all cases, successful products were launched in expectation of a positive reaction from the market. And while in all cases the innovators could cite a reason for launch of the particular product, the level of detail in their reasoning varied. In a case of an unsuccessful product only broad trend in the market – growing health consciousness was cited. On the other hand, a significant proportion of the successful products targeted a particular barrier to fish consumption according to the consumer’s perception, e.g. bones, ease of preparation, lack of cooking knowledge. Generally, successful products were characterised by a more careful ‘tailoring’ of the product to the needs of the market where they were launched. On the other hand, too much ‘tailoring’ was partly blamed to be the reason for loss of brand identity and therefore market failure in a case where a domestically successful product was launched in a foreign market. However, the unsuitability of the market for this particular concept may have also played a role, as stated by representative from the distribution channel, linking again to the importance of market understanding.

===== '''Market research''' =====

As seen above, this appeared to be an important factor for the success of new projects. The level of investment and extent of market research varied, usually with size of enterprise and resource availability, but good understanding of consumer needs was not necessarily achieved in the standard ‘scientific’ way. In cases of small companies, typically ‘mini’ consumer research was conducted with members of the staff. That is also where ideas for new products were often generated. For example, in one case of a small company, it was reported that it is the women workers who propose the ideas for new recipes. However, it can be argued that basing the research on too small a sample, particularly composed of closely associated people could introduce a level of bias as to what the real consumer needs are on a bigger scale. In another case, the founder of the enterprise achieved good consumer understanding by working at a different job, close to a large number of end consumer. He applied his insight understanding of the consumer needs into an improved production process, leading to a successful product. A clearer idea of the target consumer appeared to be associated with more success, particularly when the product was tailored to that particular customer group’s perceived needs. However, there were highly successful cases for which the target customer was a very large group, e.g. domestic consumes, ‘anybody who likes fish’ or young consumers. In those cases a characteristic of the product usually removed a barrier to consumption.

However, since successful cases of both types were present, the size of the sample cannot be directly linked to the performance of products. Suffice to say, it is recommendable that the scope of marketing research conducted should be relevant to the size and coverage of the intended market.

===== '''Originality''' =====

Virtually all, but one, of the companies interviewed considered themselves innovative. However, all cases investigated could be characterised as having medium to low level of originality. None of the products was truly new to the market and there was no major ‘invention’ present. In most of the cases ‘newness’ came from combining familiar concepts in a new way, e.g. different species of fish in an existing recipe. Here, 'borrowing' of ideas from the wider food industry was present to a considerable extent. Improvement or variations upon existing concepts was the other level of originality, e.g. new recipe. Combining improved concepts in a new way, provided yet another level of originality, e.g. new recipe for a sauce in a combination with a different species of fish. In terms of processes, in several of the cases improvements in existing processes or an application of technology in a new manner was serving as a basis for new product development. At the end, the products were improved to better suit the needs of the consumers, but were not radically new. The level of newness was important in determining whether a product would enter a new market or an established market. However, none of the products investigated were imitators either, but in two of the cases ‘copying’ of the concept by retailers and reintroducing the product under new label was cited as a problem by producers.

===== '''Innovation process''' =====

The level of resource involvement again varied according to size of the company. A team of trained chefs and a dietician working together in a multi-disciplinary team including dedicated R&D members was described in one successful large scale company case. In another large company, the success of products was attributed mostly to the help of an external agency. The involvement of human resource in the development process in small companies was primarily focused on senior management and staff members with multiple functions. However, involvement of external sources such as research institutions and business partners was also reported by small companies. It was noted that in all cases, the process was not limited to an R&D team but wider human resource pool was utilised. Strong leadership and dedication on the side of management throughout the process was found to be highly positive for the success of innovation products. In a case of a family-owned small scale company, the highly proactive management approach combined with strong marketing capability was believed to be a key success factor for the product. In general, the strong management involvement was found to be important in SMEs.

Similarly, involvement of end consumer in the process was found in all success cases. End consumers were involved usually at the prototype testing stage of the process. However, in small companies, this was limited again to the immediate surroundings of the developers – family, friends, staff, with the limitations associated with such approach discussed above.

===== '''Advertising and promotional activities''' =====

In small companies the promotional activities were often limited to marketing efforts by the owner who would engage with potential clients to promote products which have successfully passed the development and prototype testing stage. Accepted products would be advertised through local media sources (newspapers, magazines, radio, TV) or the participation of a company representative at social events. Considerable advertising effort and expenditure was reported in one of the highly successful large scale companies. TV advertising campaigns at this company were run annually and online and social media advertising continuously, tailored to the like of younger consumers. TV campaigns were reported to be successful in recruiting new consumers in the long term. The company is also building awareness through the organisation of events where consumers are encouraged to participate. It is the company’s strategy to educate consumers, with particular focus on young generations. On the other hand, a highly successful product from a small scale company was completely dependent on the promotional activity by the owners and their direct engagement with customers.

== References & Readings ==

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=== Conclusions and Recommendations ===

While due to sampling limitations, no major generalisations could be made about the wider industry, the results of the cases investigated point towards the need for a purposeful and goal-oriented approach to innovation, with strong leadership and intellectual input from various sources. The most successful companies were highly ‘market oriented’. They had identified unsatisfied consumer needs, targeted a barrier to fish consumption, or exploited a growing market trend. All unsuccessful cases had the similar feature of not matching with the consumer needs, either completely or to a level below which production was unprofitable.

There was a strong indication that a new seafood product has to be a good ‘fit’ for the intended market, implying the need for a clear understanding of the market (whether through marketing research or other means) and target consumer .

=== References ===

AMA. (2006). The Quest For Innovation: A Global Study of Innovation Management 2006-2016.

Asche, F., Bellemare, M. F., Roheim, C., Smith, M. D., & Tveteras, S. (2015). Fair Enough? Food Security and the International Trade of Seafood. World Development, 67(289760), 151–160. [http://doi.org/10.1016/j.worlddev.2014.10.013 http://doi.org/10.1016/j.worlddev.2014.10.013]

Asche, F., Bjørndal, T., & Young, J. A. (2001). Market interactions for aquaculture products. Aquaculture Economics & Management, 5(March), 303–318. [http://doi.org/10.1080/13657300109380296 http://doi.org/10.1080/13657300109380296]

Asche, F., Roll, K. H., & Trollvik, T. (2009). New Aquaculture Species—the Whitefish Market. Aquaculture Economics & Management, 13(2), 76–93. [http://doi.org/10.1080/13657300902881641 http://doi.org/10.1080/13657300902881641]

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Deliverable 4.1

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= Deliverable 4.1 - Industry study cases report: A collection of marketing successes and failures in the World based on clever product innovation and/or marketing activities =

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== Executive Summary ==

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Innovation is a ‘good, service or idea that is perceived by someone as new’. It is widely acknowledged
that innovation is required for the growth of output and productivity and is also seen as a key to
business success in a competitive environment. In 2012, the food and drink manufacturing industry in
the European Union was the largest manufacturing sector in terms of value of the output with 15% of
the total manufacturing turnover. However, it is widely perceived as not highly innovative. In addition,
the commonly reported figures for new food product failure are between 70% and 90%.
The present report was developed through a mixed research method – a combination of qualitative
and quantitative analysis. The quantitative analysis used data from the Global New Product
Development (GNPD) Database provided by Mintel (market intelligent agency) and focused on
innovation of food product containing seafood as major ingredients in 25 European countries. The
innovation in the database can be from five different launch types: a totally new product, a new
packaging, a new recipe, an extension of the range and a product relaunch. Secondly, an explorative
multiple case study analysis was performed based on 17 cases of innovative seafood products (4
failures and 13 successes) balancing the different types of innovations, claims, fish species, markets
and successful/failed products as much as possible. All the selected cases have at least one product
based mainly on one of the following fish species: salmon, trout, seabream, seabass, cod, pangasius or
herring. Multiple data sources were used to develop the case studies: archives, interviews,
questionnaires, and observations. The case analysis was structure along a common framework derived
from literature review on food/fish innovations.
Cod innovations increase across the European market, even if the share of cod over all seafood
products is decreasing. It shows an orientation of cod innovation over sustainable claims (SC) (65.26%
of SC is environmentally friendly product, as MSC label). An important part of cod innovations is frozen.
Herring innovative products are mainly produced in Germany and East European countries. Even if the
number of innovation for this species increases at a lower rate than for others species, innovative
herring products with sustainable claims don’t follow the same path and increase faster than all
seafood innovation in this positioning. Products containing trout are not the most innovative seafood
products, only a few references have been listed in the database used. The number of sustainable
innovations increased slower than for other species. Salmon is an important species due to the number
of innovations. Many companies on the salmon market are major retailers on the European market,
and only few salmon specialized companies are present among the most innovative companies. The
use of sustainable claims increases, but this increase is not significantly different to the average
increase of all others species on the European market. Pangasius is not a widespread fish in Europe,
and it represents only 0.67% of seafood innovation. Nonetheless, pangasius products have a clear
positioning on naturalness and sustainability, probably in order to thwart the poor perception of this
fish on the European market. Seabass products are not numerous on the market, but many firms are
interested in its commercialization. Some of them as a diversification, others as a central specie to
develop further. A large majority of seabass products is positioned in such a way on the market to help
in the acceptance of transformed seabass. Indeed, it is a species usually consumed fresh, without any
transformation.

The key driver for innovation, whether product or process, was the pursuit of larger market share or
sustained competitiveness. The companies have demonstrated awareness of growing market
demands in “convenient” fish products, but the way they respond to these demands varied by the firm
scale. Both large-scale and small-scale companies’ mainly responded to internal stimuli for innovation
based on the company developed business strategies and consumer research. Bigger companies
tended to pass a clear message on their product quality to consumers, focusing on the product
convenience and health. Smaller firms tried to occupy the niche market by targeting narrower
consumer groups with very specific preferences.
Innovation process has also varied between different firm scales. While in small company this was
typically triggered by either current staff members or external institutions like universities, larger
companies had dedicated R&D department for new innovation generation. Big companies also usually
followed structured product development models as part of a wider innovation strategy, whereas
small companies introduced innovation through “trial and error”. No correlation has been found
between the product success and the innovation process strategy per se. Nevertheless, ‘customer pull’
type of projects are expected to be more successful as they are more tailored the specific needs and
wants of the end consumers.
While due to sampling limitations, no major generalisations could be made about the wider industry,
the results of the cases investigated point towards the need for a purposeful and goal-oriented
approach to innovation, with strong leadership and an intellectual inputs from various sources.
There was a strong indication that a new seafood product has to be a good ‘fit’ for the intended market,
implying the need for clear understanding of the market (whether through marketing research or other
means) and target consumer.

== Introduction ==

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In 2012, the food and drink manufacturing industry in the European Union was the largest manufacturing sector in terms of value of the output with 15% of the total manufacturing turnover. It also remains one of the largest in terms of employment and number of companies, the large majority of which are small and medium scale enterprises (SMEs) (ECSIP Consortium, 2016).

Within the food and drink industry, the seafood processing sector had the smallest share of turnover in 2012. With 3570 companies, it occupied 0.01% of the total number of companies in the food sector (ECSIP Consortium, 2016). Nevertheless, the enterprises operating in the EU food and drink industry are a vital link in the supply chain, enabling wider economic activity and employment (Traill & Grunert, 1997).

In the context of globalisation and increased competition on domestic and foreign markets, innovation is seen as a key pathway to creating and sustaining competitive advantage at the firm level as well as stimulating wider economic growth (Porter, 1985, 1990). Indeed, one of the five targets of the Europe 2020 strategy is 3% of the GDP of the EU to be invested in R&D, a tool for innovation (EC, 2016). The food and drink industry, however, has been scored as a low-medium R&D intensity sectors, a group of sectors with R&D intensity between 1% and 2% of net sales, which comes at the background of companies in the automobile and electronics industries with R&D investment of more than 20% (Hernández et al., 2014). Nevertheless, as we will see below, this may not necessarily mean lack or a low level of innovation.

=== What is innovation? ===

Innovation is a ‘good, service or idea that is perceived by someone as new’(Grunert et al., 1997). According to the same authors, innovation may be related to invention but not all product innovations are based on inventions. New product could merely be an improved existing product. Schumpeter (1939) distinguishes between five types of innovation: introduction of new products; introduction of new methods of production; opening of new markets; development of new sources of supply for raw materials or other inputs and creation of new market structures in an industry. Similarly, The Oslo Manual on collecting and interpreting innovation data distinguishes between four innovation areas: product, process, marketing and organisation (OECD, 2005). In the context of the food industry, innovation can include new products, new types of packaging (including both the physical characteristics of packaging and the contents of information on it, new recipe (new flavours, new additives, conservation methods), range extension, re-launch, new marketing methods and implementation of a new or significantly improved logistical process (ECSIP Consortium, 2016).

The focus of this study is primarily on product innovation. However, the distinction between product and process innovation is not always clear-cut, since product and process innovation are often dependent on each other. Process innovation has been defined as “an investment into a company’s skills, resources and competences, which allows the company to introduce cost-saving changes in the production processes but also to introduce new technology which allows the production of a range of products quite different from the existing one” (Grunert et al., 1997). Modern market pressures have pushed food processing companies to move away from a focus of process improvement and cost reduction alone, which used to be the norm in the past, towards creating products that meet the consumer demands more successfully, where product innovation plays a key role (Fortuin & Omta, 2009). In the present-day food industry the introduction of new products is seen as an essential element of competition between companies (Grunert et al., 1997).

=== Why look at innovation ===

It is widely acknowledged that innovation is required for the growth of output and productivity. Schumpeter (1939) argues that economic development is driven by innovation through a process of replacement of old technologies with new, which he labels “creative destruction”. But innovation is also seen as a key to business success. A large study by the American Management Association, involving 1396 executives from large multinational companies showed that more than 90% of the participants believed innovation to be important or extremely important for the long-term success of the company and that this will still be the case in ten years’ time (AMA, 2006).

However, unsuccessful innovation may be even more harmful than no innovation, given the high costs associated with it (Traill & Grunert, 1997). The commonly reported figures for new food product failure are between 70% and 90% (Stewart-Knox & Mitchell, 2003). However, as pointed out by Grunert et al. (1997) those figures may be overstated since the definition of success, usually measured by the period which a product has been on the market, is not standard, and indeed a product may be successful even though short lived, depending on its intended function. For example, a range of products can be introduced by a company to diffuse the success of a new product launch by a competitor, being consequently withdrawn but nevertheless strategically successful. Similarly, the definition of a new product varies among authors. It has been argued that if a new product is ‘one that is new to the consumer’ only 7-25% of food products launched can be considered truly novel (Rudolph, 1995).

=== Aims and objectives ===

In this report we mainly aim at addressing four research questions:

Q1: How has the seafood innovation developed over time in general and for the selected species?

Q2: What drives product innovation at the company level?

Q3: What factors determine the focus of innovation?

Q4: What factors are responsible for success or failure in product innovation?

== Methods ==

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The present report was developed through a mixed research method – a combination of qualitative and quantitative analysis. The combination of data types can be highly synergistic. Quantitative evidence can indicate relationships which may not be salient to the researcher, while qualitative data are useful for understanding the rationale underlying the relationships showed in the quantitative data or suggested through theory (Eisenhardt 1989).

The report starts out with an analysis of The Global New Products Databased (GNPD) which is constructed by Mintel, a market intelligence agency, working across 34 countries. The main objective of GNPD is to provide data giving the depth of resources necessary to track trends in product innovation and retail success. Product innovation are tracked on shop and online across 62 of the world’s major economies; and around 33,000 new products a month are added into the database. Eighty fields of information ranging from companies information and flavour to packaging and positioning are noted. This database allows access to the products characteristics, the marketing positioning and the type of launches. However, it only concerns packed products. It provides detailed data on new products launched in the food, beverage, beauty and personal care, healthcare, household goods and pet care markets.

The innovation taken into account into the database can be from five different launch types: a totally new product, a new packaging, a new recipe, an extension of the range and a product relaunch. The product has to be claimed as “new” to be picked up. A new product corresponds to a new line or a new family of products for the brand, this kind of launch is brand depending. This also includes brand products that are launched in a new country where the product was not commercialized (Mintel International Group Ltd. 2012). A new packaging is based on the visual aspect of the product, it corresponds to product labelled as '''new look''', '''new size''' or '''new packaging''' (Mintel International Group Ltd. 2012). A new recipe concerns the new ingredients formulation of an existing product. An extension of the range depends of the brand line; it is assigned when an innovation is the horizontal extension of an existing line (Mintel International Group Ltd. 2012). Finally, a relaunch is assigned to an innovation when it is indicated on the product packaging or when a secondary information source informs consumers (trade show, website or press). It is also assigned when the product has been both reformulated and it has a new package (Mintel International Group Ltd. 2012). Thus, there are mainly product and marketing innovations valorised in this database, as major process or social innovations are not necessarily highlighted to shopper.

For this analysis on European Seafood market, we looked at food product containing seafood as major ingredients (seafood has to be in the five main ingredients to be selected for this analysis). The European market as delimited (and covered) by Mintel concerns 25 countries: Germany, Austria, Belgium, Croatia, Denmark, Spain, Finland, France, Greece, Hungary, Ireland, Italia, Norway, Netherland, Poland, Portugal, Czech Republic, Romania, United Kingdom, Russia, Slovakia, Sweden, Swiss, Turkey and Ukraine.

Secondly the report focus on a primarily qualitative analysis - an explorative multiple case study analysis where the unit of analysis is the firm, although special attention is also given to one of the main successful or unsuccessful company’s products. The research strategy of case studies was chosen because it focused on understanding the dynamics present within single settings, at numerous levels of analysis, and can be used to accomplish various aims, ranging from providing a description to generating theory (Eisenhardt, 1989).

The cases were identified from secondary data (e.g. newspapers, company sites, specialized literature, innovation awards, etc.). Then, a first stage selection based on careful cross-checks with databases such as Lexis Nexis4 and GNPD, resulted in 60 proposed cases (9 product failures and 51 successful products). From them, 17 were selected (4 failures and 13 successes) for in-depth studies, in order to provide a detailed view on the successful – or unsuccessful – industry practice /or learnings.

All the selected cases belong to the seafood industry and have at least one product based mainly on one of the following fish species: salmon, trout, seabream, seabass, cod, pangasius or hearing. Moreover, the final selection of the cases was done balancing the different types of innovations, claims, fish species, markets and successful/failed products, among the cases. The selected cases can be observed in the Table 1.

''Table 1.Case studies general information''

{| class="wikitable" style="width: 100%;"
|-
! Case
! Innovation
! Major claim
! Fish species
! Markets
! Launching year
! Success/failure
|-
| A
|
*New packing
*New recipe
|
*Convenience
| Salmon, Seabass, Seabream
| UK
| 2010
| Success
|-
| B
|
*New recipe
|
*Quality and tradition
| Herring
| France
| 2012
| Failure
|-
| C
|
*New product
*New recipe
*Extension range
|
*Natural
*Health
| Salmon
| United States, Canada, European Union
| 2014
| Success
|-
| D
|
*New product
*New process
|
*Quality and taste
| Salmon
| Italy
| 2000
| Success
|-
| E
|
*New product
*Extension range
|
*Convenience
| Salmon, Cod
| United States
| 2014-2015
| Success
|-
| F
| *New product
| *Natural
*Health
*Local
| Trout
| Italy
| 1989
| Success
|-
| G
|
*New product
*New recipe
|
*Convenience
*Health
| Trout
| Italy
| 2015
| Failure
|-
| H
|
*New product
|
*Convenience
*Natural
| Trout
| Italy, Switzerland
| n.d
| Success
|-
| I
|
*New product
*New recipe
|
*Convenience
*Health
| Seabass
| Italy
| 2011
| Success
|-
| J
|
*New product
*New recipe
|
*Convenience
| Pangasius
| Europe, Asia and USA
| 2005
| Success
|-
| K
|
*New process
|
*Quality
| Trout
| UK
| 2008
| Success
|-
| L
|
*New Product
|
*Convenience
| Salmon
| Spain
| 2013
| Success
|-
| M
|
*New product
|
*Convenience
| Salmon, cod, seabass, seabream
| Europe
| n.d
| Success
|-
| N
|
*New Product
|
*Convenience
| SeaBream
| Greece, Russia
| n.d
| Failure
|-
| O
|
*New product
|
*Natural
*Health
*Gourmet
| SeaBass
| Croatia, Italy, Germany
| 2011
| Failure
|-
| P
|
*New process
|
*Quality
| Salmon
| Norway
| n.d
| Success
|-
| Q
|
*New product
|
*Quality
| Cod
| Germany
| n.d
| Success
|}

From the selected cases, 13 are product innovations, frequently related to new recipes (4 cases) or to an extension of product range (2 cases). There is also one case in which the new product development is related to a new process. Among the claims, the most common ones are convenience (9 products), health (5 products), high quality (5 products) or natural (4 products). Less common claims include taste or gourmet (2 products) and the ‘local’ claim (1 product). Regarding the fish species, 3 of the analyzed products are based on several fish species (salmon, cod, seabass and seabream). The rest of the products are focused on one particular specie: salmon (5 products), trout (4 products), seabass (2 products), seabream (1 product), cod (1 product) and pangasius (1 product).

Following the selection of the cases, multiple types of data compilation are used to develop the case studies: archives, interviews, questionnaires, and observations (Yin 1994). The case analysis was structure along a common framework derived from literature review on food/fish innovations. The major areas were developed in a semi-structured interview guideline, sent with instructions to all partners. The guide included information as aspects of company general information, market structure, innovative practices, innovation inside the firm, sources of innovation, success/failure perception, and more detailed information on the selected successful/fail product.

All firms were contacted by phone and additional information was sent via e-mail by local researchers. The semi-structured interviews were developed at the firms in their local language in order to enhance understanding. The interviews were carried by one or two local researchers, and when possible, these were recorded. The interviews were reinforced with additional secondary data collection and analysis. Then, based on the interview material and secondary data, a cross case analysis is performed with the objective of identifying commonalities and differences between the firms, operative markets, species, and successful/failure outcomes.

The analysis of the information is done through a cross-case analysis. All the results are presented based on the analysed case studies. Additionally, the report offers some comparisons of the qualitative and quantitative results. The general framework used for the analysis is divided into three main levels even though these clearly interrelate and interact: 1. Innovative potential at the supra-company level - the wider environment 2. Company’s innovative potential 3. Influences on innovation success at the project level When investigating at the innovative potential at the supra-company level – i.e. the wider environment we look for factors like market structure/characteristics, the firm’s perspective on consumer trends (needs/wants), value chain organization and regulation.

When looking at the innovative activity at the company level we looked for factors like company size, resource availability and experience. Further firm strategy and orientation, capabilities and relationships with other companies/institutions where investigated.

Finally, when it comes to each of the selected case products, the material was analysed based on factors such as; source of the innovation, innovation strategy, organisation of the NPD (individuals, relations, management involvement, etc), type of innovation (incremental, radical, ‘originality’), market and consumer knowledge, process of new product development and perception of success and effect on performance.

 

== Background: literature review ==

----

The EU food industry is a dynamic arena affected by wider socio-economic processes. To remain competitive in the modern world, food manufacturers must develop capacity to innovate quickly and effectively as reliance on a stable range of traditional foods can no longer ensure business success (Grunert et al., 1997). The following discussion starts with an overview of the major trends in the industry, particularly as they relate to pressures on the industry to innovate. It then proceeds with a review of the factors deemed important for the success or failure of new food products.

=== Drivers of innovation – the bigger picture ===

Over the last several decades, significant changes in the patterns of food consumption have been observed in industrialised countries, with inevitable influence on the rate and direction of product innovation. The drivers for these changes will be examined from different perspectives, which however, are inherently related to and reinforcing each other.

==== Economic factors ====

Generally, growing disposable incomes in industrialised countries has translated into changes in the patterns of expenditure on food, such that an overall higher level of expenditure on food, through consumption of higher quality and more diversified foods rather than higher quantity, can be observed (Traill, 1997). When it comes to seafood, however, the development of consumer prices has played a similarly important role in determining consumption trends. Since price is often cited among the main barrier to consumption of fish and seafood (Birch, Lawley, & Hamblin, 2012; Liu, Bui, & Leach, 2013; Myrland, Trondsen, Johnston, & Lund, 2000; Trondsen, Scholderer, Lund, & Eggen, 2003; Verbeke & Vackier, 2005), a decrease in their prices relative to other sources of protein can act as a driver for consumption and overall expansion of the market. Indeed, good illustrations of this are shrimp, salmon, tilapia and pangasius, all of which are internationally traded commodities whose real prices have declined over time due to increased and more efficient production methods (Asche, Bjørndal, & Young, 2001). For example, shrimp and salmon have been leading the international farmed seafood market for almost three decades, with current real prices a third of what they were three decades ago (Asche, Roll, & Trollvik, 2009). However, relative prices of close substitutes remain still important for consumers. This is particularly true at times of economic recession, when clear declines in seafood consumption can be seen as consumers ‘trade down’ the food basket (Seafish, 2015).

 

==== Consumer concerns ====

A wide array of non-economic factors is also at play in determining the trends in food consumption. Increasingly, these relate to ‘intangible’ aspects of the product, such as ethical and sustainable sourcing.

===== '''Diet and health''' =====

As the populations of many industrialized countries are becoming older, richer, more educated and more health conscious, the demand for food that promotes health and well-being is growing (FAO, 2008). Seafood has often been promoted as a having a variety of positive health properties. Because of that, seafood, and especially oily fish, can also be seen as a functional food (Gormley, 2006), a fast growing market with high opportunities for innovation (Khan, Grigor, Winger, & Win, 2013). However, risks of eating fish linked to contamination with carcinogens has also been communicated to the public (Sidhu, 2003). As a result there is a general confusion over the right choice of seafood (Oken et al., 2012), the individual choice whether to consume fish or not being eventually dependent on the type and accuracy of information consumers are exposed to (Burger & Gochfeld, 2009).

 

===== '''Environmental concerns''' =====

Consumers, as well as major distributors, are increasingly concerned about the sustainability and risk of depletion of marine stocks. While the range of fish and seafood products labelled as sustainably sourced is expanding and the demand for sustainable seafood products is rising (Roheim, 2009), there is a debate whether this is due to genuine consumer demand or due to influences by NGOs and branding strategies by retailers (Gutierrez & Thornton, 2014). Gulbrandsen (2006) and Bush et al (2013) for example argue that most markets for eco-labelled forestry and fisheries products have been created as a result of pressure by environmental groups on consumer-facing corporations, rather than resulting from consumer demand. In any case, consumers have as a result an increasing abundance and diversity of certified seafood product to choose from. Increasingly, consumer behaviour is shaped by the growing popularity of sustainable seafood guides, such as Monterey Bay Aquarium’s Seafood Watch and MCS Good fish (Roheim, 2009). However, the availability of too much information from different sources, with sometimes conflicting advice can lead to consumer confusion and even negatively impact consumption (Oken et al., 2012; Roheim, 2009). The issue whether demand is genuinely ‘consumer driven’ or resulting from a ‘retailer push’ would remain nevertheless important to the performance of new seafood products on this market.

===== '''Production methods and safety''' =====

Consumers have become increasingly concerned about the ways in which food is produced, with ranging attitudes towards the use of certain new food technologies (Grunert et al., 1997). More stringent demands for assurance concerning safety is yet another high-profile issue that has emerged in recent years and shaping consumption patterns. As a result a variety of safety certifications have been developed which have become requirements by supermarket chains. European retailers for example increasingly expect supplies to comply with quality standards such as BRC and IFS, as well as traceability (CBI, 2015).

==== Societal change ====

Significant increase in the demand for convenience food can be attributed to increased participation of women in the work force (Traill, 1997). Due to factors such as time pressure, there is a strong rise in the demand for products that are ready to eat or require little preparation before serving (Brunner, van der Horst, & Siegrist, 2010). And while fish has been widely considered inconvenient because of the time and skills required for preparation (Olsen, Scholderer, Brunsø, & Verbeke, 2007), the current wide availability and expanding market for value added convenience seafood sets a new norm of how fish is consumed (Olsen, 2004). For example, the development of vacuum packed, pre-cooked mussels with sauce has been highly successful on the UK market, driven by the convenience, longer shelf life and versatility. In 2008 the ratio of Scottish produced mussels going to fresh counter market and to value added market were 70% to 30% respectively with a combined value of £6 million while in 2015 the ratio was 25% to 75% respectively with combined value of £15 million (Cameron, 2015). The trend in expanding value added seafood markets presents a vast opportunity for innovation in the field, with particular reference to younger generations.

Further, according to Olsen (2003) frequency of seafood consumption is positively correlated with chronological age, mediated by attitudes toward eating seafood, health involvement and perceived convenience. Markets where population is aging, and the number of one-person single households is growing, such as the UK and other European countries, present an opportunity for innovation tailored to this particular consumer group.

==== Availability of food products ====

The increase in the global supply of seafood over the last few decades, combined with technological innovations, has facilitated the international orientation of the seafood industry. In particular, progress in storage and preservation and improved logistics leading to lower costs have allowed international trade to grow (Asche, Bellemare, Roheim, Smith, & Tveteras, 2015). An increased range of raw material available to processors has stimulated experimentation with new species and served as a basis for a wide variety of seafood product innovations. Notable examples are pangasius, tilapia and shrimp.

==== Food retailing ====

Food retailing in Europe has become concentrated in the hands of leading multiple retailers with inevitable impact on innovation not only for processors but throughout the value chain (Murray & Fofana, 2002). One of the most powerful tools of retailers exerting control on the value chain is their ‘private label’ products (Bunte et al., 2011). It is generally accepted that private labels utilize markets created by branded products, by ‘imitating’ successful products. Private label products require little advertising as they rely on the image of the store, thus they are well placed to compete on price with the highly advertised branded products, pushing leading manufacturers to innovate even faster. At the same time, ‘private labels’ provide an opportunity for small and medium scale enterprises to supply the market while avoiding the prohibitive costs of developing a recognised brand (Traill, 1997).

=== Factors for success in innovation ===

A considerable amount of insight on the key success and failure factors in new product performance has been published in the late twentieth century. This has led to the generation of a plethora of factors deemed critical for successful innovation, often cited with contradictory outcomes (Balachandra & Friar, 1997; Grunert et al., 1997). The discrepancies could partly be explained by the lack of methodological standardisation in the study designs and definition of key variables, but also by the contextual differences. The vast majority of these studies focus on high-tech industries such as electronics, biotechnology, or pharmaceutical (Fortuin, Batterink, & Omta, 2007). The number of foodrelated studies on innovation is considerably smaller, while regarding seafood it is negligible. While drawing from a wider industrial base, the following synthesis will review the factors with higher relevance to the food industry, wherever possible illustrating with examples from the seafood sector.

==== Enabling environment ====

Porter (1990) argues that government policies play a key role in determining the competitiveness of enterprises as they directly influence the factors responsible for competitive advantage, with inevitable influences on innovation potential. Indeed, as pointed by Lindkvist & Sánchez (2008), prohibitive regulations have had a negative impact on the innovative activities and overall competitiveness of the Norwegian salt fish producers on the Spanish market. In particular, laws not allowing the processors to own fishing vessels have resulted in a fragmentation of the value chain and low level of control over the quality and timing of raw material supply. This has been further exacerbated by prohibitions on the use of chemicals other than ascorbic salts in the process of salting fish, leading to products of perceived inferior quality compared to the phosphate and antioxidant treated Icelandic products.

==== At the company level ====

===== '''Interaction with other companies''' =====

Innovation capabilities at the company level can be influenced by the existence of clusters of companies producing interrelated products and having high level of coordination between their activities, thus exploiting a larger pool of skills and enhancing their innovative power. The same advantages can be exploited in a network of companies, not necessarily physically clustered together (Grunert et al., 1997).

In a similar fashion, vertical cooperation can bring advantages to the innovative activities of the firm in the form of generation of market intelligence by sharing of information between downstream and upstream members, increasing the firm’s portfolio of competences and improving cross-functional communication.

However, it has been argued that the inflexibility created by committing to a few partners may act as an impediment to market intelligence generation and competence expansion. Similarly, increased levels of bureaucracy, especially in connection with large retail chains with emphasis on price instead of differentiation, may inhibit upstream innovation. In such cases, the choice of co-operation partners becomes a crucial issue.

In addition to regulations, a lack of cooperation in innovation and market development, due to mistrust and protection of self-interests, between producers of salt cod in Norway has been cited as a central factor for the loss of market share to Icelandic producers on the Spanish market (Lindkvist, 2010).

The role a company plays in the supply chain can directly influence its innovative potential. Harmsen & Traill (1997) show that the seafood company ‘Royal Greenland’ increased considerably its innovation activities when it expanded its customer base from food service to retail. Similarly, Christensen et al. (2011) find that firms delivering directly to end users were more likely to be innovative than those delivering to the processing or wholesale links of the value chain.

===== '''Size of company''' =====

Size of the company has been a central variable in much of the literature on innovation activity at the company level. The neo-Schumpeterian view maintains that large companies are more innovative than small companies, largely because of better resource base; human and financial (Grunert et al., 1997). In fact, previous research has shown that small firms face the liability of smallness (Aldrich and Auster, 1986; Freeman et al., 1983), that refers to the limited access to financial resources and competitive human capital. Such constrains might generate a limited market power and a small customer base (Carson, 1985), as the firms are unknown to their potential customers (Gaddefors and Anderson, 2008). Thus, these companies must devote several resources to building an identity, but the process is lengthy and costly (Gruber, 2004).

An alternative view, argues that SMEs tend to be market makers while large companies tend to be imitators, if the potential market volume allows large scale production. It has also been argued that SMEs are more prone to innovate because of organisational and behavioural characteristics allowing them to react to market changes more quickly e.g. little bureaucracy, high commitment and motivation by managers, higher exposure to competition, lower innovation costs, higher R&D efficiency. Similarly, it has been hypothesised that radical innovation is more typical of small and medium scale companies because it does not fit with the pragmatic philosophy of larger companies which are looking for a systematic innovation process. Nevertheless, according to Grunert et al. (1997), there is no consensus in the literature regarding the influence of firm size on its innovativeness.

===== '''Orientation of the company''' =====

Innovative activity can be seen as pertaining to a particular innovation or to the company in general. When it comes to particular innovations, it has the dimension of how new it is to the market and how new it is from a technological point of view. Innovation at the company level can be broken down to innovation speed, innovation willingness, innovation capacity and innovation quality (Grunert et al., 1997).

Earle (1997) argues that successful innovation is reliant on innovation-oriented company and positively reactive environment. It is the company’s strategic decision whether to pursue an innovation course or not. A firm may take either reactive or proactive approach in innovation to either avoid losing market share to an innovative competitor or to gain strategic market position relative to its competitors.

Depending on their involvement with innovation activities companies can be divided into innovative (or prospectors); improvers, getting involved once the initial products have been already developed;

‘me too’ companies, copying what others have already introduced on the market; and ‘die hard’ ignoring innovation altogether (Earle, 1997; Fortuin et al., 2007). The spectrum can be illustrated again by Icelandic companies producing salt cod for the Spanish market at one end and their Norwegian counterparts at the other (Larsen, 2014; Lindkvist, 2010).

Grunert et al. (1997) presents a further nuanced picture of innovation at the company level by providing two different perspectives: the first linking innovation with technological change, the driving force of economic growth, which is linked to, and can be measured by, R&D activities. As such the food industry could be classified as a low-tech industry due to the small R&D to sales ratios typically reported. In this view innovation could be regarded as a ‘technology push’.

On the other hand, from a marketing perspective, innovation can also be viewed as an activity required for fulfilling the unfilled needs and wants of potential customers using the skills, competences and resources of the company, often referred to as ‘market-orientation’ of the company, or ‘demand pull’. This view maintains that R&D activities do not guarantee innovative success alone, but only in interaction with the needs in the market (Gupta, Raj, & Wilemon, 1986).

As seen before, the food industry is generally considered as one with a low R&D expenditure. Indeed, Harmsen, Grunert, & Declerck (2000) in a series of case studies from the food industry showed that R&D is of minor importance in the innovation process, but innovative activities are nevertheless carried out. This was supported by findings by Avermaete et al. (2004) from a study on small-scale food manufacturers and by Christensen, Dahl, Eliasen, Nielsen, & Østergaard (2011) from a wider sectorial analysis. This has led Harmsen et al. (2000) to revise the framework proposed by Grunert et al. (1997) by focusing greater attention on ‘market orientation’ and ‘competencies’ and their interaction as explanatory factors for success. In their revised framework, orientation was seen as relating to ‘product’, ‘process’ and ‘market’, rather than simply markets. Competencies of the firm relate to the types of orientation but all three types, albeit to different degrees, were required for successful innovation. In-house capabilities of the work force were found to be strong determinants of innovation, particularly in small food firms (Avermaete et al., 2004). That is where the culture of the company and its vision are critical to successful innovation. It has been suggested than unconventional individuals rather than conventional science or engineering are central to innovation success. However, without entrepreneurial spirit and openness, new ideas by such individuals can be dismissed.

==== At the project level ====

There is a great number of studies identifying performance factors and Ernst (2002) provides an extensive review of the topic. Here we focus on some of the most often cited groups of factors, particularly as they relate to the food industry and over which there seems to be some level of consensus.

Among others, the success and failure of new food products has been related to the process of new product development (Stewart-Knox & Mitchell, 2003). The process comprises five to eight steps spanning from idea generation to launch activities, going through screening, research, development and testing. The sequence in which those activities are undertaken has been linked to success in the past. For example (Cooper & Kleinschmidt, 1987) argue that companies which taking a stepwise approach were more successful. However, in later publications the same authors show that concurrent, overlapping, flexible approach has better potential than a simplistic stepwise model (Cooper & Kleinschmidt, 2007). The common ground is the requirement for repeated evaluation throughout the process.

Market and consumer knowledge and retailer involvement in the process of new food product development has also been highlighted as a factors critical for success (Kristensen, Ostergaard, & Juhl, 1998; Stewart-Knox & Mitchell, 2003). Similarly, the involvement (as well as its intensity and quality), of the final consumer during the process of product development has been claimed to have positive impact on the outcome of innovation (Gruner & Homburg, 2000). Hoban (1998) has shown that new product developers in the USA rely heavily on retailer customers for market information, and few draw on other sources of information, consequently the retailer involvement has become increasingly important but does not guarantee success. The importance of gathering of information from a variety of independent sources, including retailers, suppliers, research centres, consumers, prior to the development of new products has been emphasized as a unique to the food industry (Stewart-Knox & Mitchell, 2003). Similarly, in a number of publications Cooper emphasizes the importance of market research up-front of the initiation of the process of product development (G. R. Cooper & Cooper, 1994; R. G. Cooper, 1999; R. Cooper, 1996). However, McGinnis & Ackelsberg (1983) note that market analysis can limit the innovators to existing markets with small incremental innovations rather than direct them to undeveloped markets with major innovations. Therefore, a careful balance must be maintained between market analysis and thinking ‘out of the box’ (Balachandra & Friar, 1997). Furthermore, good market analysis is dependent on the quality of data, but as the same authors have pointed out, analysing customer needs may not yield accurate information as the needs may not be known by the customers themselves. In an earlier paper (Balachandra, 1984) suggests the need for an existence of a strong market, instead of a potential market, as the difficulties associated with consumer research can be thus avoided.

Most prospector organise the innovation processes, including new product development, in projects where different functional areas of the firm are represented in cross-functional teams co-operating throughout the process (Fortuin et al., 2007). As Robert G Cooper (1999) points out important decisions as to whether to initiate a project, terminate or redirect it are rarely based on a systematic analysis of the factors determining success or failure, but rather on the experience of the team.

Overall, factors linked to product development strategy, indicate the need for a purposeful and goaloriented approach to product development and balanced technological and market-related aspects, as well as a synergy with existing activities (Earle, 1997).

Although often pointed out as a critical factor for success in wider industrial innovation (Ernst, 2002), involvement of senior management throughout the process of food product development has not been consistently shown to be critical for success (Stewart-Knox & Mitchell, 2003), perhaps in part due to the variety of sizes of companies investigated in different studies and the different roles senior management play in them. In an UK study (Stewart-Knox, Parr, Bunting, & Mitchell, 2003), involvement of senior management seemed to be unrelated, while in Denmark (Kristensen et al., 1998) it was found to be a determinant for success.

Similarly, the rate of new product introduction has also been shown to drive success in opposing directions. Higher rate of introduction implies the growth stage of a product, therefore a higher chance of success, but at the same time greater intensity of competition – a negative factor for commercial success (Balachandra & Friar, 1997).

Generally, original products seem to be more successful than adapted products, because food products market can become quickly overcrowded, although that may be context specific (StewartKnox & Mitchell, 2003). And despite that the failure rate for truly new food products has been shown to be as low as only 25% (Hoban, 1998), only a small proportion of new food products are truly novel (Rudolph, 1995).This may be due to a fear of failure of a new product and taking the ‘safe’ approach of redeveloping old products, which however, only perpetuates the problem of high rate of product failure.

== Results & Data ==

----
===Results from GNDP and discussion===

Between 2000 and 2015, 22,406 seafood products have been launched on the European
Market (based on Mintel’s Global New Products Database (GNPD), 2016). Over this period, the average
repartition by launch type is: 44.16% new varieties, 38.64% new products, 11.72% new packaging,
2.99% new formulations, and 2.49% product relaunches. As new formulation and relaunch are not very
frequent strategies, we will regroup these two types of launch for further analyses (which is logical as
a part of relaunch is reformulated products). Behind the type of launch we can underline several types
of innovation strategies. First, new product tries to develop a new market answering to new needs. In
this case, the innovation can be considered as a breakthrough innovation and it is the most risky
innovation for firms. New packaging, new variety and new formulation are more adaptation or
renovation innovation, and even if not without risk, they are supported by an existing market.

[[File:Sfs_fig_1.png|center|Figure 1]]
''Figure 1. Products repartition over type of launch. Source: GNPD, 22,406 Observations''

Thus, we can observe that the strategy of innovation has evolved over the period (see Figure
1 ). The part of totally new products as decreased, in favour of new variety and new packaging. In a
very competitive global market, as two third of innovation disappeared within the first two years
(Aurier & Sirieix, 2009), firms seems to favour adaptation and renovation, with a decrease in risk-
taking.

These choices over type of launch can also be linked to the product positioning strategy. Different
product positioning can be used to match products with consumer’s expectations. This positioning
claims can be related to sustainable claims (e.g. organic, environmentally friendly products and eco-
labelled), convenience claims (e.g. Ease of Use and Microwaveable), natural claims (e.g. No
additives/Preservatives and GMO Free), health claims (e.g. Antioxidant and Vitamin/Mineral Fortified)
or other claims (e.g. Fair Trade, Kasher and Premium). Between 2000 and 2015, 63.76% of seafood
innovations have at least one claim, the number of products without any claim is continuously
decreasing over the period considered. No claim products represent 69.64% of product launched in
2000 and only 28.27% in 2015. Most used positioning is sustainable (28.14% of seafood products over
the period) and convenience claims (28.19% of seafood products over the period), which correspond
to main consumers concerns in regard of fish consumption. Indeed the convenience in fish product is
an important restraint to fish consumption: some consumers do not have the knowledge to prepare
unprocessed fish, and fish is not viewed as an easy product to buy, to conserve and to cook (Brunsø et
al., 2008). Furthermore, the convenience positioning is a more general food tendency leading to less
cooking times and more easy-to-eat/easy-to-cook products. In regards of the sustainable concerns,
this issue is important for seafood industries as some stocks are over exploited (FAO, 2014). And, as
for convenience claims, sustainable claims on seafood products respond to a more general tendency
on sustainability of food production, illustrated by the increase of organic products on shops shelves
all across European countries.

[[File:Sfs_fig_2.png|center|Figure 2]]
''Figure 2. Repartition of claims by type of launch (%) between 2000 and 2015. Source: GNPD, 22,406 observations (New product: 8,657; New Packaging: 2,627; New Formulation: 1,228; New Variety: 9,894)''

We observe different strategies over the different type of launch (see Figure 2 ). First, we
assume that the choice of the product positioning can be either previous to the choice of launch either
viewed as an opportunity after the choice of launch type. In the case of new product, the share of
products without any product positioning is the most important compared to others categories, while
this share is the lower for new formulation. In the case of totally new product, the innovation has been
created for answer to new consumer needs, with probably less expectations in terms of product
positioning, which can explain the higher share of products without claims. When a firm chooses to
relaunch a product or to change the formulation it is generally to fit more to consumer’s expectation
with no major change. In this situation the use of claims is an easy way to communicate on product
characteristics, as convenience or sustainable dimension of the product. Those characteristics are
either non-existent before the change either already existent but were not claimed to the consumer.
The same opportunity occurs with a new variety or a new packaging: this innovation strategy of
renovation/adaptation is a chance to expand the line to new positioning, to reach more consumers.
In regards of the repartition of innovation across Europe, countries with more innovations are
France, United-Kingdom, Spain and Germany, representing 54% of innovations. Nonetheless, it is
complicated to go on some deeper conclusion, as there is a possible bias on the shopping execution
by Mintel across countries, as well as some differences on the seafood market size across those
countries. It is more interesting to look at the country of origin of the innovative firms, as well as the
repartition of innovation between national brand and private brand ( Table 1 ).

''Table 1. Top 10 of innovative firms. Source: GNPD; 22,406 observations.''
{| class="wikitable" style="width: 100%;"
|-
!Firm
!Firm Type
!Firm Nationality
!Number of products
!Percentage
|-
|Lidl
|Retailer
|Germany
|833
|3.72
|-
|Marks&Spencer
|Retailer
|United-Kingdom
|734
|3.28
|-
|Tesco
|Retailer
|United-Kingdom
|497
|2.22
|-
|Aldi
|Retailer
|Germany
|354
|1.58
|-
|Findus
|Manufacturer
|United-Kingdom
|304
|1.36
|-
|Iglo
|Manufacturer
|United-Kingdom
|261
|1.16
|-
|Carrefour
|Retailer
|France
|250
|1.12
|-
|Picard
|Retailer
|France
|245
|1.09
|-
|Asda
|Retailer
|United-Kingdom
|239
|1.07
|-
|Auchan
|Retailer
|France
|232
|1.04
|}

If the majority of innovation are from national brand companies (61.82% of innovations
between 200 and 2015), the top 10 company are for the most part retailer, with private brand
products. They represent 17.64% of seafood innovation. Only two manufacturers reach the top 10:
Findus and Iglo, generally the two leaders in the seafood market. We underline that most of those
companies use more claims that other companies (the average of products with at least one claim is
63.66% for the entire sample - Table 2 ).

''Table 2. Top 10 of innovative firms - products positioning. Source: GNPD; 22,406 observations.''
{| class="wikitable" style="width: 100%;"
|-
!Firm
!Percentage of products with at least one claim.
!Percentage of products with sustainable claim.
!Percentage of products with natural claim.
!Percentage of products with health claim.
!Percentage of products with convenience claim.
!Percentage of products with other claim.
|-
|Lidl
|59.78**
|28.93
|3.48***
|4.68***
|16.33***
|27.01***
|-
|Marks & Spencer
|79.97***
|57.36***
|23.02***
|6.21***
|41.83***
|15.53
|-
|Tesco
|84.51***
|44.06***
|28.57***
|15.69*
|29.58
|41.45***
|-
|Aldi
|68.93**
|41.53***
|17.51
|9.89*
|22.60**
|20.90***
|-
|Findus
|72.37***
|49.01***
|21.38
|13.49
|40.79***
|8.88***
|-
|Iglo
|90.04***
|74.33***
|52.87***
|16.09
|32.57
|18.39
|-
|Carrefour
|47.20***
|10.80***
|6.40***
|6.40***
|24.40
|14.80
|-
|Picard
|68.57
|21.63**
|0***
|2.04***
|53.88***
|6.94***
|-
|Asda
|82.01***
|33.05*
|53.14***
|48.95***
|23.01*
|34.31***
|-
|Auchan
|62.07
|19.83***
|9.48***
|1.72***
|29.74
|28.88***
|-
|All companies
|63.66
|28.14
|17.86
|13.05
|28.19
|15.67
|}
''Mean comparison test (t-test): significant at *10%, **5%, ***1%''

Companies using more claims are positioning more than average in at least two claims. For
example, “Marks & Spencer” has more products with claims than the average, and that is for
sustainable, natural, health and convenience claims. Only other claim isn’t used significantly more by
“Marks & Spencer”. Over the 10 companies, only two are using fewer claims than others: Lidl and
Carrefour, two retailers companies. Some companies are specialized in one specific claim: Lidl uses less
claims than other, excepted for other claim; Picard is not significantly different in claims use, excepted
for convenience which is used significantly higher than average. Picard is a retailer, with a premium
positioning over the frozen distribution network, selling almost exclusively its one private brand. This
convenience positioning can be linked with the product storage, as frozen products communicate
more on convenience, e.g. the use of microwave to defrost the product. The two manufacturers
present in this top 10 use more claims than average. Iglo is more positioned on sustainable (almost
75% of its products) and natural (around 50% of its products). On its side Findus, although on
sustainable claim too, is well positioned on convenience claim.

In the GNPD, the seafood storage can be refrigerated (38.19% of innovations), frozen (31.39%)
or ambient (30.41%). There is slightly more products with at least one claim in the frozen category and
slightly less in refrigerated ( Table 3 ). There is more convenience claim in frozen category while there is
less health claim. This can be explained by two main reasons. For the convenience claim, as said before,
frozen products are intrinsically linked with this positioning (e.g: rapid defrost). Then, the frozen
products can be perceived as less healthy than fresh one, and in that case this claim is not sought by
consumer. Inversely, there is less convenience claim in ambient category while there is more health
(as well as more sustainable and natural claims). In this category, there is less intrinsic need to claim
on convenience (e.g. can technology has not changed so must from consumer side, there is not so
much “more easy to open”). Furthermore, the fatty fish (as sardine and mackerel) are more often
commercialized in can, thus in ambient (77% of bluefish), while the lean fish (as cod and pollock) are
more often commercialized in frozen (cod 52%, pollock 77.24%). Yet, fatty fish are rich in omega 3,
which can be pointed to the consumer through health claim, which could explain, at least partially, the
difference between storage.

''Table 3. Repartition of claims by storage. Source: GNPD; 22,406 observations''
{| class="wikitable" style="width: 100%;"
|-
!
!Percentage of products with at least one claim.
!Percentage of products with sustainable claim.
!Percentage of products with natural claim.
!Percentage of products with health claim.
!Percentage of products with convenience claim.
!Percentage of products with other claim.
|-
|Refrigerated
|62.95*
|24.55***
|18.88*
|12.64
|27.72
|18.21***
|-
|Frozen
|65.07**
|28.96*
|15.92
|10.87***
|33.88***
|16.12
|-
|Ambient
|63.21
|31.87***
|18.63*
|15.82***
|22.96***
|12.02***
|}
''Mean comparison test (t-test): significant at *10%, **5%, ***1%''

We can look at the species mainly used in the seafood innovation in European market. The
recognition of species is not easy as there is no obligation for transformed products in Europe to clearly
identify the kind of fish used in the product. Thus, 14.57% of seafood innovation cannot be linked to a
specific species ( Table 4 ). The seafood ingredients are presented on the product as fish or seafood.
Furthermore, the scientific name is almost never specified, which makes the distinction between close
species (between tunas for example) complicated. Nonetheless, regarding general fish species, we
have some interesting result. The most important species in terms of innovation are Salmon (20.37%
of seafood innovation contains salmon), Crustaceans (17.17% of seafood innovation contains
crustaceans) and Tuna (15.65% of seafood innovation contains tuna). Those species correspond to the
more consumed species in Europe: Salmon and shrimps are part of the main seafood consumed in
France (FranceAgriMer (2014)), salmon is also largely consumed in Belgium and Netherland (Brunsø,
2008) while tuna is largely consumed in Spain (Brunsø, 2008). The species with the greatest number of
products with at least one claim are the Pangasius, the Haddock and the Seabass. Behind those three
species, there is different reality. Pangasius is not a common species in Europe; it is not an endogenous
one as Pangasius is mostly raised in Asia. To thwart a poor image of this fish in Europe, it’s seems that
companies tried to communicate on the sustainability, as it is the species with the most important
share of sustainable claim. For the Haddock and the Seabass, the positioning is mostly on
sustainability/naturality and convenience. The convenience claims are also mainly used for the
shellfish and the mussel, underling a need for consumer to be helped in the way to consume shellfish
(cleaning & cooking). The products with the smallest claim use are the bluefish products (Clupeidae,
mackerel, and anchovy), generally commercialized in can, well known from consumer, and already
easy to use.

''Table 4. Repartition of seafood innovation in regards of the species. Source: GNPD; 22,406 observations''
{| class="wikitable" style="width: 100%;"
|-
!Species
!Number of products
!Frequency on European market (%)
!Percentage of products with at least one claim.
!Percentage of products with sustainable claim.
!Percentage of products with natural claim.
!Percentage of products with health claim.
!Percentage of products with convenience claim.
!Percentage of products with other claim.
|-
|Bluefish
|1970
|8.79
|51.88
|21.32
|11.78
|13.76
|14.47
|11.88
|-
|Trout
|437
|1.95
|58.12
|20.82
|12.36
|11.44
|22.88
|20.59
|-
|Cephalopods
|1097
|4.89
|52.87
|10.76
|14.49
|8.84
|33.18
|10.85
|-
|Herring
|917
|409
|57.25
|35.88
|20.83
|8.29
|8.94
|8.40
|-
|Cod
|1508
|6.73
|69.50
|33.02
|23.41
|15.58
|34.15
|14.32
|-
|Crustaceans
|3848
|17.17
|59.69
|21.52
|16.09
|10.50
|30.93
|16.32
|-
|Flatfish
|273
|1.22
|62.64
|37.00
|12.45
|10.99
|23.08
|14.65
|-
|Haddock
|327
|1.46
|83.49
|40.98
|29.97
|20.49
|32.11
|25.08
|-
|Shellfish
|999
|4.46
|64.16
|20.22
|14.51
|10.11
|41.34
|17.42
|-
|Mussel
|724
|3.23
|64.64
|18.78
|15.19
|14.78
|44.75
|9.53
|-
|Pangasius
|149
|0.66
|75.84
|47.65
|14.77
|16.11
|34.23
|22.15
|-
|Pollock
|1608
|7.18
|75.81
|38.99
|23.69
|19.22
|41.85
|15.67
|-
|Salmon
|4565
|20.37
|67.19
|29.40
|17.85
|11.11
|29.16
|21.56
|-
|Seabass
|91
|0.41
|82.42
|28.57
|29.67
|14.29
|45.05
|21.98
|-
|Tuna
|3506
|15.65
|66.12
|40.25
|15.74
|13.72
|23.05
|12.18
|-
|Seafood
|3265
|14.7
|60.31
|13.32
|22.39
|12.96
|29.68
|15.62
|-
|Freshwater Fish
|263
|1.17
|63.50
|17.49
|21.67
|10.65
|33.46
|15.59
|-
|Other fish* (species specified)
|376
|1.67
|60.11
|16.22
|22.87
|18.35
|29.26
|16.49
|}
''*Species representing less than % of innovations have been gather in one category, except Pangasius.''

=== Results from GNPD by species ===

==== COD ====

Innovations for products containing Cod follow the same path as global seafood products,
and the number of innovation increases over years ( Figure 3 ). One thousand five hundred and
eight (1,508) products have been launched over the period (2000-2015), which represents 6.73%
of total seafood innovations. The share of innovation with cod over all seafood innovations
is decreasing across European countries, especially in Czech Republic. The only country
with an increasing share of cod innovations is Figure 3. Innovations by claims Source: GNPD; 1,508 Observations
Sweden. Most of them are a new variety extending existing range (47%) or a totally new product (34%).
There is also more reformulation in cod innovations than for others species.
As seafood in general, majority of innovation containing cod have
at least one claim (69.50% of products). The positioning is mainly convenience (34.15%), sustainable
(33.02%) and natural (23.15%). At the European level, the number of innovations with sustainable
claims is increasing faster than for other species, but this rate is slower for any other claims, showing
a market tendency of cod products over sustainability .

[[File:Sfs_fig_3.png|center|Figure 3]]
''Figure 3. Innovations by claims Source: GNPD; 1,508 Observations''

We observe that at the European level the five most innovative companies for cod products
are from United-Kingdom (Marks & Spencer, Findus, Tesco, Iglo) or Germany (Lidl) ( Table 5 ), and belong
to the top 10 firms in seafood innovations. Distribution of innovation among firm is more concentrated
for sustainable and natural claims, but can be considered as weak as companies on the top 5 share
only 33.99% of innovations maximum. The major companies are present over all positioning; most of
them are retailer companies. Only no claims products bring companies less innovative compared to
the previous one (Delabli and Sagit).

''Table 5. Major firms by claims (for Cod products). Source: GNPD, 1,508 observations''
{| class="wikitable" style="width: 100%;"
|-
!
!Top 5 firms
!Nbr of products
!Share of top5 firms
|-
|All cod
|Marks & Spencer, Findus, Tesco, Lidl, Iglo
|1508
|18.97
|-
|Sustainable Claims
|Marks & Spencer, Findus, Lidl, Iglo, Birds Eye
|498
|32.33
|-
|Natural Claims
|Birds Eye, Marks & Spencer, Iglo, Asda, Tesco
|353
|33.99
|-
|Convenience Claims
|Marks & Spencer, Findus, Picard, Lidl, Tesco
|515
|19.61
|-
|Health Claims
|Asda, Marks & Spencer, Tesco, Findus, Iglo
|235
|26.38
|-
|Other Claims
|Tesco, Lidl, Sainsbury’s, Birds Eye, Coop
|216
|27.78
|-
|No claims
|Findus, Marks & Spencer, Bofrost, Delabli, Sagit
|460
|14.13
|}

Some categories of foods are more represented under some
positioning than other ( Figure 4 ). The share of child food represents 2.51%
for all cod products and increases to 6.51% under natural claims, more that
for sustainable claims (3.21%). The most important category, processed
fish, represents 66.51% of all cod products, which is the same as for all observations
seafood product (66.01% is processed fish), and stay stable over claims/no claims products. The result
for meals shows a more important share of convenience claims products compared to all cod products.
In regards of the conditioning, cod products are mainly frozen products (52.29%) and refrigerated
(35.43%). The repartition between private label and national label are a little more in favour of private
brand (41.38%) than for seafood as an all.

''Figure 4. Repartition of innovations by food categories Source: GNPD; 1,508 observations''
[[File:Sfs_fig_4.png|center|Figure 4]]

To conclude, cod innovations increase across European market, even if the share of cod over
all seafood products is decreasing. Still, the cod products drive sustainable innovation as its
contribution to this marketing positioning is increasing faster than others species. It shows an
orientation of cod innovation over sustainable claims (SC) (65.26% of SC is environmentally friendly
product, as MSC label). An important part of cod innovations is frozen.

''Figure 5. Distribution of innovations containing Cod across Europe. Source: GNPD—1,508 Observations''
[[File:Sfs_fig_5.png|center|Figure 5]]
Legend: Darker green = most important
number of innovations, lighter green =less
important number of innovations (white=no
observations for cod, stripes countries are not
into the GNPD database). S (N/H/C/O): Country
with the most important share of sustainable
(natural/ health/ convenience/ other) claims
on its cod products.

====Herring====

Innovations for products containing Herring follow the same path as overall
seafood products, and the number of innovation increases over years ( Figure 6 ). Nine
hundred and seventeen (917) products have been launched over the period (2000-2015),
which represents 4.09% of total seafood innovations. The share of innovation with
herring over all seafood innovations is decreasing across European countries,
meaning the number of herring innovations increases slower than all seafood innovation.
Most of them are totally new product (42%) or new variety (43%). As seafood products in general,
majority of innovation containing herring has at least one claim (57.27%). Positioning is mainly
sustainable (35.88%) and natural (20.83%). Convenience claim is underrepresented on herring
innovations compared to overall seafood innovation (8.94% vs 28.19%). Nonetheless, the increase of
convenience (as well as for natural) claims is faster for herring than for other species, meaning this
situation may change within a few years.

[[File:Sfs_fig_6.png|center|Figure 6]]
''Figure 6. Innovations by claims. Source: GNPD, 917 observations''

Looking at the innovation for herring products, we can see that at the European level the five
most innovative companies for herring products are from Germany and Poland ( Table 6 ). A large
majority of the companies in the top five, regardless of the claims, are from Germany. The others are
from Russia, Poland, Belarus and Sweden. A majority of leading companies are manufacturer. The
herring products represent more than 50% of innovation for the top five firms (except for Lidl): 75.76%
of innovation by Nadler Feinkost (Germany, Manufacturer) contains herring.

''Table 6. Major firms by claims (for Herring products). Source: GNPD, 917 observations''
{| class="wikitable" style="width: 100%;"
|-
!
!Top 5 firms
!Nbr of products
!Share of top5 firms
|-
|All herring
|Appel Feinkost, Lidl, Homann Feinkost, Lisner, Nadler Feinkost
|917
|18.65
|-
|Sustainable Claims
|Appel Feinkost, Lidl, Aldi Nord, Nadler Feinkost, Aldi
|329
|29.79
|-
|Natural Claims
|Homann Feinkost, Aldi Nord, Edmund Merl, Nadler & Appel Feinkost
|191
|28.80
|-
|Convenience Claims
|Santa Bremor, Russkoye More, PKP Meridia, Lisner, Homann Feinkost
|515
|31.71
|-
|Health Claims
|Appel Feinkost, Larsen Danish Seafood, Aldi, H. Kuhlmann, NR Fish
|76
|34.21
|-
|Other Claims
|Appel Feinkost, H.Kuhlmann, Kaufland Warenhande, Lisner, Abba Seaf.
|77
|27.27
|-
|No claims
|Appel Feinkost, Abba Seaf., Lisner, Lidl, Homann Feinkost
|392
|14.13
|}

Some categories of foods are more represented under some
positioning than other ( Figure 7 ). First, there is no child food or soup
containing herring. A large majority of herring innovations are processed
fish (87.35% versus 66.01% for all seafood innovations), and Meals
(10.14%). Beside some savoury spread products, other categories
with herring are almost inexistent.
The repartition over claims is quite the same as for all herring products, only the repartition on health
claims favours meals products. In regards of the conditioning, herring innovations are mainly
refrigerated (65.46%) and only few references are frozen (2.19% versus 31.39% for all seafood
products). The share of national brand over private label is higher for herring than for all seafood
products (77.21% versus 61.82%).

[[File:Sfs_fig_7.png|center|Figure 7]]
''Figure 7. Repartition of innovations by food categories Source: GNPD; 917 observations''

To conclude, herring innovative products are mainly produced in Germany and East European
countries. Even if the number of innovation for this species increases at a lower rate than for others
species, innovative herring products with sustainable claims don’t follow the same path and increase
faster than all seafood innovation in this positioning. Despite an absence of firms on the major
innovative one (for herring products), the UK market is well positioned on other and health claims.

[[File:Sfs_fig_8.png|center|Figure 8]]
''Figure 8 Distribution of innovations containing Herring across Europe. Source: GNPD—917 Observations''
Legend: Darker green = most important number of innovations, lighter green =less important number of
innovations (white=no observations for herring, stripes countries are not into the GNPD database). S
(N/H/C/O): Country with the most important share of sustainable (natural/ health/ convenience/ other)
claims on its herring products.

====Trout====

Innovations for products containing Trout follow the same path as global seafood products
( Figure 9 ), and the number of innovation increases over years. Four hundred and thirty seven (437)
products have been launched over the period (2000-2015), which represents 1.95% of total
seafood innovations. Despite a few references, the share of innovations with Trout over all seafood
innovations is decreasing, for all countries. For trout, most of them are totally new products (42%)
or a new variety extending an existing range (44%).
As seafood products in general, majority of innovation containing trout have
at least one claim (58.12% of products). The positioning is mainly
convenience (22.88%) sustainable (20.82%), and other claims (20.59%). Nonetheless, the number of
innovations with sustainable claims is increasing slowly compared to other species, leading Trout to be
the less innovative species in regards of sustainability at the European level. Only the number of
products with natural claims is increasing a tiny bit faster than for others species. Despite few
references, Swiss is the country with the faster increase of innovation with trout.

[[File:Sfs_fig_9.png|center|Figure 9]]
''Figure 9 Innovation by claims Source: GNPD; 437 observations''

Looking at the innovation for trout products, we can see that at the European level the five
most innovative companies for trout products are from Germany (Lidl, Gottfried Friedrichs), France
(Aqualande, Carrefour) and UK (Marks & Spencer) ( Table 7 ). Two of those innovative firms are retailers.
The trout innovations are not in a concentrate market as the top 5 firms represent only 16.02% of the
innovation. Looking at the positioning scale, the east countries companies are well represented,
especially on the natural claims (Russkoye More — Russia, Amstor— Ukraine).

''Table 7. Major firms by claims (for Trout products). Source: GNPD, 437 observations''
{| class="wikitable" style="width: 100%;"
|-
!
!Top 5 firms
!Nbr of products
!Share of top5 firms
|-
|All trout
|Lidl, Gottfried Friedrichs, Aqualande, Marks & Spencer, Carrefour - CMI
|437
|16.02
|-
|Sustainable Claims
|Aqualande, HiPP, Marks & Spencer, Distriborg, Monoprix
|91
|23.08
|-
|Natural Claims
|Aqualande, Russkoye More, Amstor, Fischzucht Alexander Quester,HiPP
|54
|22.22
|-
|Convenience Claims
|Lidl, Marks & Spencer, Labeyrie, Nestle, PKP Meridian
|100
|19.00
|-
|Health Claims
|Aqualande, HiPP, PKP Meridian, Nestle, Saarioinen
|50
|40.00
|-
|Other Claims
|Lidl, Gottfried Friedrichs, Aldi, Carrefour – CMI, Marks & Spencer
|90
|30.00
|-
|No claims
|Gottfried Friedrichs, Lidl, Aldi, Bofrost, Vejle Seafood
|183
|16.39
|}

Some categories of foods are more represented under some positioning than
other ( Figure 10 ). Indeed baby food represent only 2.98% of products
innovation containing trout but represent 18% of products with health claims and
around 9% for sustainable and natural. Furthermore, all baby food containing trout
have a marketing positioning. Meals and meal centers category more presents 13%
of trout products with convenience claims when it represents only 6.41% of all trout
products. The trout based product are mainly processed fish, 82.61% which is higher than for all
seafood innovation, as only 66.01% of seafood innovation are processed fish. In regards of the
conditioning 77.35% of trout products are refrigerated (versus 38.19% for all seafood products). The
repartition between private label and national label is identical to the seafood category as an all, that
to say around 61% of products innovation from national brand.

[[File:Sfs_fig_10.png|center|Figure 10]]
''Figure 10. Repartition of innovations by food categories Source: GNPD, 437 observations''

To conclude, products containing trout are not the most innovative seafood products, few references
have been listed in the database used. The number of sustainable innovations increased slower than
for other species, but faster for natural innovations even if the coefficient is weak. The most innovative
firms are not necessarily the same than for seafood in general, and the most innovative countries
(number of products) are not the most strategic on market differentiation through the use of claims.

[[File:Sfs_fig_11.png|center|Figure 11]]
''Figure 11 Repartition of innovations with trout across Europe. Source: GNPD; 437 observations''
Legend: Darker green = most important number of innovations, lighter green =less
important number of innovations (white=no observations for trout, stripes countries are not
into the GNPD database). S (N/H/C/O): Country with the most important share of sustainable
(natural/health/convenience/other) claims on its trout products.

====Salmon====

Innovations for products containing Salmon follow the same path than global seafood
products, and the number of innovation increases over years ( Figure 12 ). The salmon is
the most important species in seafood innovation. Four thousand five hundred and
sixty five (4,565) products have been launched over the period (2000-2015), which represents
20.37% of total seafood innovations. On the period, the share of innovation with salmon
over all seafood innovations is stable at the European level, but it increases in Ukraine,
Ireland, Denmark and it decreases in Turkey, UK and Portugal. Most of them are a new variety
extending existing range (46%) or a totally new product (38%) As seafood in general, majority of
innovation containing salmon have at least one claim (67.10% of products) and the share of salmon
innovation with claims increases, the fastest increase being for Ukrainian market. The positioning is
mainly sustainable (29.40%), convenience (29.16%), and other (21.56%) Only convenience and other
claims increase slower for salmon than for other species, but the share of these claims is already high
for salmon products.

[[File:Sfs_fig_12.png|center|Figure 12]]
''Figure 12. Innovations by claims. Source: GNPD, 4,565 observations''

Innovative salmon products are mainly support by firms from the top 10 of most innovative
firms ( Table 2 & Table 8 ) as Marks & Spencer, Lidl, Aldi and Tesco. Only two companies on most
important innovative firms are not retailers (Labeyrie and Nestlé), and all of them are major companies
in Europe. For a large majority, salmon represents one third of their innovation. Only the companies
Labeyrie is specialised in Salmon, as this species represents 85% of the brand new products.

''Table 8. Major firms by claims (for Salmon products). Source: GNPD, 4,565 observations''
{| class="wikitable" style="width: 100%;"
|-
!
!Top 5 firms
!Nbr of products
!Share of top5 firms
|-
|All salmon
|Marks & Spencer, Lidl, Labeyrie, Tesco, Aldi 4
|565
|16.23
|-
|Sustainable Claims
|Marks & Spencer, Tesco, Labeyrie, Waitrose, Lidl 1
|342
|26.75
|-
|Natural Claims
|Marks & Spencer, Labeyrie, Tesco, Asda, Iglo
|815
|21.23
|-
|Convenience Claims
|Marks & Spencer, Labeyrie, Tesco, Picard, Waitrose 1
|331
|18.48
|-
|Health Claims
|Asda, Marks & Spencer, Albert Heijn, Tesco, Nestle
|507
|20.12
|-
|Other Claims
|Lidl, Tesco, Marks & Spencer, Labeyrie, Aldi
|984
|25.30
|-
|No claims
|Lidl, Marks & Spencer, Labeyrie, Aldi, Picard 1
|498
|14.13
|}

Some categories of foods are more represented under some
positioning than other ( Figure 13 ). The repartition of food categories
across claims is consistent for salmon products, and is consistent
with seafood in general. Only the repartition changes for health
claim, as the share of child food increases (7% versus 1.38% for all
salmon products) at the depend of all others categories; and the
repartition for convenience claim, as the share of meals increases (31% versus 18% for all salmon
products). In regards of the conditioning 64,65% of trout products are refrigerated (versus 38.19% for
all seafood products). The repartition between private label and national label is close to the seafood
category as an all, that to say around 57.44% of products innovation from national brand (versus
61.82% for all seafood).

[[File:Sfs_fig_13.png|center|Figure 13]]
''Figure 13 Repartition of innovations by food categories Source: GNPD, 4,565 observations''

To conclude, salmon is an important species due to the number of innovations, but the share
of salmon is relatively stable over the period. Major companies in salmon market are major retailers
in the European market, and only few salmon specialized companies, as Labeyrie, are present among
the most innovative companies. The use of sustainable claims increases, but this increase is not
significantly different than the average increase of all others species in the European market.

[[File:Sfs_fig_14.png|center|Figure 14]]
''Figure 14. Repartition of innovations with salmon across Europe. Source: GNPD; 4,565 observations''
Legend: Darker green = most important number of innovations, lighter green =less important number
of innovations (white=no observations for salmon, stripes countries are not into the GNPD database).
S (N/H/C/O): Country with the most important share of sustainable (natural/health/convenience/ other)
claims on its trout products.

====Pangasius====
Innovations for products containing pangasius follow the same
path as global seafood products ( Figure 15 ). Nonetheless, the number of
products with pangasius launched in Europe is still very low as only 149
products have been launched over the period, that to say only 0.67% of total
seafood innovations. The share of innovation with pangasius over all
seafood is decreasing over the period.
Most of them are a new variety extending existing range (48%) or a
totally new product (41%). There is less new packaging in pangasius innovations than for others
species, but there is more range extension. As seafood in general, majority of innovation containing
pangasius have at least one claim (75.84% of products). The positioning is mainly sustainable (47.65%),
convenience (34.23%) and other (23.15%). At the European level, the share of pangasius innovation
with claims is stable, only Belgium market shows an increase in this share. The share of products with
natural and sustainable claims increase, but with a slow slope and at a lower rate than others species.

[[File:Sfs_fig_15.png|center|Figure 15]]
''Figure 15 Innovations by claims Source: GNPD, 149 observations''

The innovation for pangasius products come mainly from two firms from the top 10 of
innovative firms: Lidl and Aldi (both retailers and German). The top five firms are well represented on
the majority of claims (besides natural and no claims). The firms in the pangasius market are mostly
major companies where innovations with pangasius represent less than 5% of the firm innovation.
However, some companies with only few innovations (less than 5) are specialized on pangasius
innovations (Seamark, Alfredo Foods or DM Drogerie Markt).

''Table 9. Major firms by claims (for Pangasius products). Source: GNPD, 149 observations''
{| class="wikitable" style="width: 100%;"
|-
!
!Top 5 firms
!Nbr of products
!Share of top5 firms
|-
|All pangasius
|Lidl, Aldi, Young’s, Queens Products, Albert Heijn
|149
|30.20
|-
|Sustainable Claims
|Lidl, Young’s, Aldi, Queens Products, Okoland
|71
|49.30
|-
|Natural Claims
|DM Drogerie Markt., Okoland, Tesco, Young’s, ATB Market
|22
|54.55
|-
|Convenience Claims
|Lidl, Aldi, Queens Products, Tesco, Albert Heijn
|51
|41.18
|-
|Health Claims
|Adli, DM Drogerie Markt., Young’s, Albert Heijn, Alfredo Foods
|24
|54.17
|-
|Other Claims
|Young’s, Lidl, Albert Heijn, DM Drogerie Markt., Seamark
|33
|45.45
|-
|No claims
|Appel Feinkost, Bofrost, Dia, Frost Invest, Iceland
|36
|27.78
|}

Some categories of foods are more represented under some positioning than
other. First, there are no side and soup products with pangasius in it. The majority
of pangasius products are processed fish (more than for all seafood, 80% versus
66%) and meals (less than for all seafood, 11% versus 17%). Another category is more
important for pangasius than for all seafood being the child food sector (4%
versus 1%) and it is even greater for natural claim (27% versus 4%) and sustainable claim (8.5% versus 1.8%).
As said before, the important share
of natural and sustainable claims on pangasius products is a way to thwart a poor image of this fish in
Europe. As it is in line with the general consumer expectation on the child food market this result is
not surprising. The majority of pangasius innovations are frozen (70%) or fresh (19%). The share of
national brand and private label are quiet similar (53.69% and 46.31% respectively), which shows a
more important representation of private label than for all seafood (38%).

[[File:Sfs_fig_16.png|center|Figure 16]]
''Figure 16. Repartition of innovations by food categories Source: GNPD, 149 observations''

To conclude, pangasius is not a widespread fish in Europe, and it represents only 0.67% of
seafood innovation. Nonetheless, pangasius products have a clear positioning on naturalness and
sustainability, probably in order to thwart the poor perception of this fish in European market.

[[File:Sfs_fig_17.png|center|Figure 17]]
''Figure 17. Repartition of innovations with pangasius across Europe. Source: GNPD; 149 observations''
Legend: Darker green = most important number of innovations, lighter green =less
important number of innovations (white=no observations for pangasius, stripes countries
are not into the GNPD database). S (N/H/C/O): Country with the most important share of
sustainable (natural/ health/ convenience/other) claims on its trout products.

====Seabass & Seabream====

Innovations for products containing seabass and seabream
(thereafter seabass) follow the same path than global seafood products,
and the number of innovation increases over years. However, only 91
innovative products have been launched during 2000-2015 in the
European market, which represents 0.41% of total seafood innovations.
The small number of innovation underlines the fact that seabass is not commonly transformed, it is generally
consumed (bought by end consumer) as whole fresh. If the number of product increases, the share of
innovation with seabass over all seafood innovations decreases. Most of them are a new variety (48%)
or a totally new product (45%). There is less new packaging in seabass innovations than for others
species (2% versus 11.72%). A large majority of innovation containing seabass have at least one claim
(82.42% of products). The positioning is mainly health (85.71%), other (78.02%) and sustainable
(71.43%). At the European level, the share of seabass products with claims increases, especially in
Turkey. The use of health claims increases faster for seabass than the average of other species, and it
is also true for the use of sustainable claims.

[[File:Sfs_fig_18.png|center|Figure 18]]
''Figure 18. Innovations by claims Source: GNPD, 91 observations''

A lot of firms are on the seabass market, they are either major companies on the seafood
market or minor players. We can distinguish three strategies. Major retailer seafood firms, as M&S,
are on the seabass market but this species represents less than 1% of their innovation. Thus, this choice
can be interpreted as a diversification but with not much risk taking. We find intermediate firms, as
Guyader, for which seabass represents 4 to 10% of firm’s products. Finally, there are also some small
companies, as Coldfish: seabass can represent 100% of their innovations. Those companies are
manufacturers, mainly from Italia and Turkey, and in this case the bet on seabass products success is
more important .

''Table 10. Major firms by claims (for Seabass products). Source: GNPD, 91 observations''
{| class="wikitable" style="width: 100%;"
|-
!
!Top 5 firms
!Nbr of products
!Share of top5 firms
|-
|All Sea Bass/Bream
|Marks & Spencer, Picard, Lidl, Nuova Azzurro, Plasmon Dietetici Alim.
|91
|25.27
|-
|Sustainable Claims
|Plasmon Dietetici Alim., Marks & Spencer, Iglo, Picard, Tesco
|26
|53.85
|-
|Natural Claims
|Marks & Spencer, Plasmon Dietetici Alim., Coldfish, Guyader, Iglo
|27
|48.15
|-
|Convenience Claims
|Marks & Spencer, Lidl, Salmon Club, Dardanel Onentas, Gea
|41
|34.15
|-
|Health Claims
|Plasmon Dietetici Al., Çamli Yem Besicilik, Appetais, Coop It., DImar
|13
|61.54
|-
|Other Claims
|Picard, Iglo, Arctic Royal, Auchan, Coop Italia
|20
|40.00
|-
|No claims
|Aldi, Marks & Spencer, Bioresurs, Bofrost ,Concept Cool V.
|16
|43.75
|}

Some categories of food are more represented under some positioning than
other. First, there is no soup, no side and no other categories with seabass. The overall
repartition of seabass leads to more processed fish (75.82% versus 66.01%) and child food
(5.49% versus 1.03%), and less meals (9.89% versus 17.08%), the difference being stronger
for sustainable (80.76%, 11.53% and 3.84% respectively). The health claims gives pride of
place to child food (around 30%).
In regards of the conditioning, seabass products are mainly frozen products (50.55%) and refrigerated (36.26%). The
repartition between private label and national label are a more in favour of national brand (58.24%).

[[File:Sfs_fig_19.png|center|Figure 19]]
''Figure 19. Repartition of innovations by food categories Source: GNPD, 91 observations''

To conclude, seabass products are not numerous on the market, but many kind of firms are
interested in its commercialization. Some of them as a diversification, others as a central species to
developed. A large majority of seabass products has a market positioning to help the acceptation of
transformed seabass. Indeed, it is a species usually consumed fresh, without any transformation.

[[File:Sfs_fig_20.png|center|Figure 20]]
''Figure 20. Repartition of innovations with seabass across Europe. Source: GNPD; 91 observations''
Legend: Darker green = most important number of innovations, lighter green =less important
number of innovations (white=no observations for seabass, stripes countries are not into the
GNPD database). S (N/H/C/O): Country with the most important share of sustainable (natural/
health/ convenience/ other) claims on its trout products

===Results from case studies and discussion===

====Innovative potential at the supra-company level====

When investigating the selected case material i.e. the products and the approaches chosen by the
associated companies it can be observed that companies to a large extend are i) aware of the consumer
trends of wanting more convenient product i.e. more ready-to-cook and ii) respond to it, but to a
different extent. In part this might be as commented by one of the cases, related to the markets
behaving differently i.e. in southern Europe it is still an issue that consumers wants to see the whole
fish – “to see the fish in the eyes” (a matter of checking for freshness), while for norther Europe this is
not so much an issue.

Some products does also claim an added value through being marinated or having other added
features making it a different taste experience and also as above being more ready to eat i.e. more
prepared for the plate.

Further the products have common features also based on external expectations as claiming quality
and also sustainability i.e. quality in respect of taking responsibility for the environment and/or
ecological balance in the nature. Other orientations driven by market or consumer trends are being
oriented towards i.e. claiming a healthy product. And, only one of the selected products has a price
claim which also could be regarded as an external drive i.e. a significant proportion of the customers
expecting food stuff to be offered at an affordable price. Also, on the other hand, premium price claims
might be related to a player wanting to show superiority of the product.

The market price of raw material i.e. whole fish might also as commented by at least one case,
negatively affect the willingness and/or felt need for innovation i.e. if selling raw material is more
profitable than processed products. But, refraining from taking part in the innovative development
might be risky with respect to access to future market share i.e. if larger volumes of the market are
moving into processed seafood. And, it is e.g. observed from the Mintel data base that Turkish industry
has a higher innovation degree than EU producing countries, and at the same time it is observed that
the majority of the growth in the seabass and seabream markets, especially in Northern Europe – with
more processed products, is taken by Turkish exports to EU.

There are also some examples of products being driven by new technologies becoming available i.e.
processing technology and or technological equipment.

The relation in importance between the external drivers and internal drivers seems to be relatively
different where in some companies one is mainly responding to major external trends as a basic
strategy, while in others there is a strong internal drive for developing the production and the products.
The material might indicate that the latter is more present in private family owned small and medium
sized enterprises, while for larger enterprises e.g. stock market or investor owned companies,
innovation comes as a result of a decided strategy based on market/consumer trend analysis. The
material might also indicate that smaller companies to a larger degree claim that continuous
innovation is important for staying in business and/or growing.

Often the justifications for providing the new product is a presence of an unsatisfied market i.e. a
market demand, and the trend of customers asking for a more convenient product is highly present in
most of the cases investigated. Also, to a large degree, successes is claimed to be based on ability to
satisfy the market. Few cases report to have made a product not being demanded, but still becoming
a success when customers see the positive attributes of it.

A few of the selected products has place of origin or the history of origin, as a major attribute, but this
way of promoting products seems to be less developed than e.g. convenience of a product, and also
may be, less than within other food product sectors like the livestock industry.

When addressing future development the important features pointed at for seafood innovations
seems primarily to be addressing the need for convenient products; however, also addressing
consumer trends among younger people is commented as a key strategy.

====Company’s innovative potential====

====='''Company size and resource availability'''=====

According to the analysed cases, larger and smaller companies present some commonalities and some
differences regarding their innovation practices. Additionally, some finding match with the literature,
while other results do not. For example, both type of firms do product, and process innovation, which
could be both classified as incremental (for a definition see (Balachandra and Friar, 1997) but with
different levels of originality. It was not possible to establish a correlation between firm size and
innovation activity. Nevertheless, their innovation styles, source of ideas and development differ.
Small firms had a slightly higher tendency for process innovation than the larger firms. However, larger
firms launched more ‘new products’ to the market than small ones. While a larger firm can launch until
five to ten ‘new products’ a year; smaller firms declare to launch until three or four ‘new products’ per
year.

There are also important differences on how small and large firms define a new product. While large
firms base this definition on the customer, on stimulating the demand and the purchasing/acquisition
activities; small firms focus more on the novelty dimension. Only one small firm made reference to the
consumers, by defining a new product as that one that allows the firm to reach current non consumers.
This shows how both type of firms have different focus and approached when developing innovations.
Large firms keep a clear target, to get the customer to buy the product and to generate a profit, no
matter if the innovation is really ‘new’ or just an adaptation. Small firms, on the other hand, focused
more on actually generating new things, something that was not in the market. This could be seen in
two possible ways. On one hand, it can show how more innovative oriented are small firms than large
ones. One the other hand, it might show the lack of a clear product definition and target customer so
that to create products for which there is no existing market.

Big companies usually followed a more structured product development model, part of a wider
innovation strategy with budget allocated for innovation activities, whereas in small companies the
process was described often as “trial and error”. Nevertheless, in both small and big companies,
success has been achieved regardless of the presence or a lack of a clear model. In fact, large firms
tend to focus on internal innovation and to be customer driven. The small firm’s innovation process is
also internally driven and by its customers, however, the way it is develop is different. Smaller firms
do not have a clear R&D department. In fact, in some cases, these companies associate with external
partners as universities and research institutions in order to cover the lack of a R&D and develop new
ideas for key innovations. Small firms also base more their innovations on the available resources that
can come from within the company (CEO/entrepreneur and workers) or from external sources
(suppliers and distributors). Regarding their in-house innovation, it is usually developed though the
interaction of different people at diverse positions in the company. The entrepreneur or the CEO has
a key role in this process, while the other managers/workers bring their expertise into the
development of the new product. Moreover, frequently the first trials of the product are done at the
internal level of the firm, between other workers or even with family members. Innovation can be also
driven by the available/developed technology within the firm.

Concerning the innovation coming from external sources, several small companies report that they
have received ideas for new products from their suppliers or the retailers that distribute their products.
Innovative ideas from suppliers usually come in the form of new raw material or the availability of a
different fish species. Then the firm takes over and develops the possible product according to their
objectives or ideas. Retailers, on the other hand, are more direct in the way they bring innovative ideas
to the firm. In some of the cases, small firms reported to have un-formal suggestions from the retailers
regarding possible interesting products for the company. In other cases, retailers directly contacted
the firm and explicitly requested the elaboration or development of some private brand products.
Sometimes this ‘new products’ are based on one of the small company’s products, in other situations,
the idea can come directly from the retailer.

Taking in consideration that 8 from the top 10 innovative firms are actually retailers, this fact provides
some evidence on a key relationship between small and large retailers for the generation of
innovation, in which small firms might have a bigger role than thought. For small firms, this becomes
a way of promoting their product among retailers and other business in order to create business to
business relationships. However, it is also a risky move, as the retailer might change their mind and
change provider. To face this risk, many small firms are moving towards also developing a direct
contact with the final customer, through local markets promotion, social media, sampling displays, etc.
There is an on-going debate about the role of retailer’s own label products in competition with new
branded products. It has been argued by experts that innovation comes from brand producers which
are used by retailers for creating new markets, consequently exploited by the retailers own brand fully
or partially. This statement was confirmed by several of the cases investigated here, particularly as it
related to reward on investment, since innovation requires significant investment, so without
consumer loyalty, the rewards to the innovator can diminish considerably.

In fact, given the lack of financial resources, small firms are not able to sustain big investments in R&D,
product line expansions and marketing campaigns, while large firms can. Large firms are able to afford
different kinds of promotional campaigns (including TV) and then monitor their results. Smaller firms
lean more on public relations through social media, trade fairs and direct interaction with the
customer. However, many of them do not track the results of these activities. Also, small firms tend to
rely more on their experience, particularly the experience of the founder or CEO.

Large firms also have more resources and a more defined structure in the way they research and
develop innovations. However, small firms are also quite innovative, regardless their limited financial
resources. Small firms lean more on the capabilities of their staff, founder/CEO and previous
experiences. In fact, it was observed that in some cases the development of new products based on
existing products/inventions but in different industries (e.g. beef or poultry).

====='''Firm’s strategy and orientation'''=====

All the analysed firms declared to be high quality oriented, however, the type of claim to sustain this
quality varies among them. Although, in general terms there is a trend towards producing products
based on the health claim, there are also differences concerning the size of the firm. Large firms tend
to have a clear message on what a higher quality means, usually focused on health claims or
convenience. Sustainability and natural claims also are common among large firms. Small firms tend
to enhance a lot the focus on quality as their main point of differentiation with other competitors, but
their claims vary. The most popular claim among small firms is artisanal production, followed by health
and premium products. Artisanal in this context is seen as a good and bad point. On one hand, it offers
a traditional product with traditional methods, something that brings sentiment (‘home-made’) or as
it was before. On the other hand, some firms perceived also as a limitation, as usually is not linked to
innovation or technology driven production.

In general, smaller firms tend to offer a wider variety on the use of claims. This also can be seen as a
result of their strategy. These firms target niche markets, so they tend to focus on particular sectors of
the market, trying to target customer with certain preferences (environmental friendly, natural, gluten
free, etc.). One interesting and recent trend is to differentiate their product as a ‘local’ or ‘regional’
product. In some cases, the ‘local’ argument is used for key inputs in the breeding of the fish, which
enhances their product attributes because of the inputs involved (e.g. the fresh water in the area).
Other firms, have used the ‘local’ claim as a way to refer to high quality, as Europe in general has quite
strict production norms. However, this last approach is mainly used only by firms at the regional level,
and either way it might vary according to the market. Some small firms have currently certifications
mainly because this is the only way the company can sell their products. This is mainly the case for
business to business, as high quality processors or distributors, also look for high quality inputs or
products.

In fact, large firms have more certifications than smaller firms. This makes sense, as large firms are also
more internationally oriented (small firms prefer close markets) and to sell high quality products in
international markets, a certification would provide the guarantee of such quality. Additionally, in the
last years, a common way of expansion for large firms, has been through acquisitions. This has allowed
them not only to enter new geographical markets, but also to integrate their value chain. This definitely
has proven to be advantageous for them, as they are able to ensure traceability and quality from the
start of the value chain, a limitation that some small firms have expressed (not being able to find the
right quality inputs).

====='''Firm capabilities'''=====

There are important differences on how small and large firms perceived their main capabilities. It
becomes quite clear that large firms have developed more their market research and consumer
communication capabilities. Small firms are still trying to do so, but there is a lack of monitoring their
activities and their results. Also there is a general lack of access to resources to implement some
market research methods. However, some small firms are trying to get some customer information in
different ways. For example, through direct contact with their customers at the sale point, by
developing and improving their website to be customer friendly or by trying to obtain such information
through their retailers. Only one small company among the selected, actually does customer trials.
Additionally, small firms enhance more on their knowledge as one of their key capabilities. This
matches the literature, as in small firms the founder/manager tend to be a central figure that drives
the firm. Moreover, the staff is usually highly involved in many decisions, and roles might overlap. For
example, in several cases the founder or the quality managers were also in charge of the design of the
packing. Regarding the search of opportunities, trends and information, there were no important
differences regarding the size of the firm or the fish species. Neither for the skilled workers, as both
type of firms also considered as a key capability.

====='''Relationship with other companies/institutions'''=====

The most common kind of relationship with other firms is the one that ensures some kind of vertical
integration in the value chain. This relationship might be with a supplier, in order to ensure certain
quality or availability of the product, or with a distributor or exporter/importer, in order to guaranty
the delivery to the customer under the right circumstances. There are also some R&D relations among
the firms and research institutions or universities. This s mainly the case for small firms, but some large
firms also practice this approach. For small firms, it is also more common to have informal agreements
or partnerships with other companies or manufacturers.

====Innovation at the project level====

====='''Drivers for innovation'''=====

In most of the cases the main driver for innovation, whether product or process, was the pursuit of
larger market share or sustained competitiveness. Accordingly, for successful cases an increase in the
overall performance of the firm was reported, albeit to varying degrees. However, in a case of a small
scale producer, a clear innovation strategy has been followed with constant introduction of value
added products, even though the company admitted, they were not bringing extra profit for the time
being. The reasons for that could be found in a longer-term and outward-looking business strategy in
which innovation is seen as a key competitive advantage for the future. This move was believed to be
also the result of a strong and transformative leadership after the company’s acquisition by a larger
agri-business.

Interestingly, however, one case went against the general pattern in terms of drivers of innovation. In
this case of an unsuccessful product by a large-scale company, primarily focused on production of raw
material, the innovative product (based on process innovation) was abandoned because of better
financial performance achieved by selling non-value added products. The market at which the product
was launched had a preference for whole fish rather than fillets, so no significant premium could be
obtained through value addition product to justify the cost of production. In addition, in order to enter
the multiple retail channel, relatively large volume of the product was required, which the company
considered too risky provided the low price. The company seemed to be aware of a trend for growing
markets for convenience products but in the short term found it more profitable to limit itself to
providing non-value added products. From a global value chain perspective this process has been
labelled ‘downgrading’ (Ponte and Ewert, 2009). And while traditionally, ‘upgrading’ has been
associated with actions aimed at ‘moving up the value chain’, through producing higher value-added
products or acquiring more sophisticated functions, in the broader sense abandonment of such
functions or products in order to ‘reach a better deal’, including a balance between rewards and risk,
could also be considered a form of upgrading. In this case, a link between the scale of production
(economies of scale) and level of value addition, dictated by market conditions, could be established.

====='''Source of innovation'''=====

In small companies, new product development was triggered typically by the senior managerial team,
often including the owners of the business themselves. Two general patterns of idea generation were
observed: (a) the idea originated from within the enterprise and (b) or from external sources. In the
first case, the company develops new products based on perceived strong market demand, or due to
experimentation with new, improved or existing production processes. Only a proportion of the
developed products reach the stage of market launch. In the second case, sources of innovation could
be clients, most commonly, research institutions and development agencies. When the new product
characteristics were defined by the client a varying level of input into the design of the new product
was still coming from within the company as it experimented with alternative product forms. One of
the unsuccessful cases came from a company (B) which was ‘requested’ to produce a ready-to-cook
meal with particular specifications which were believed by the retailer to lead to success. At the end,
the failure was attributed to the inappropriate selection of fish species as the main ingredient by the
producer, leading to ‘customers didn’t like the taste’. At the same time a ‘sister product’ by the same
company, with alternative fish species but utilizing the same concept, was successful. Another
unsuccessful case of a ready-to-cook meal however, came from innovative activity fully originating
within the company. As with other new products, it was led by the owner and associates from the
company without a clear strategy or preceding marketing research. And although it was designed to
fit within the broader market for healthy and natural products, the approach resembled ‘shooting in
the dark’ and its lack of success was believed to be caused by being ‘boring’ and ‘lacking emotion’.

In a case of a large export company ideas for new value added product development came from
external agencies closer to the final EU market, which was believed to be strongly linked to the success
of those products since the company was experiencing limitations with ‘consumer understanding’
being physically distanced from the market, complicated by providing products completely new to the
market. In another case of a large European-based highly successful provider of branded value added
products, innovation was partly outsourced to an external agency. The success of the product was
believed to be due to satisfying a need for convenience as well as bringing awareness through
advertising.

The source of product innovation observed here could be classified as ‘company push’, (whether the
focus lay on the product or on the process of innovation) and ‘customer pull’, when the concept of the
new product is provided by a client. This classification at the product level, could be seen as an
elaboration of the existing typology of technology ‘push’ and ‘market pull’ regarding the orientation
of a company e.g. (Grunert et al., 1997). Thus, at the project level we could distinguish between two
types of product initiation. It could be reasoned that ‘customer pull’ type of projects would meet with
more success as they are based on demand experienced by the seller, and are thus closely linked to
the needs and wants of the end consumers. Similarly, the investment required for such innovation
could be expected to be significantly smaller, given that the associated unsuccessful projects for each
successful one are avoided. On the other hand, providing products to customer’s specifications usually
means marketing under private label. And while this can increase the volume of production, it may
lead also limited options for branding and imposition of too much control by the retailer over the
processor. The influence of quality specification on value chain governance, the power of retailers and
distribution of benefits has been examined by (Ponte and Gibbon, 2005) and applied to wine
production in South Africa (Ponte, 2009). As seen in the results here, the level of ‘flexibility’ a producer
has when receiving specifications for a new product would play a role in the chance for success of the
product. The more flexible the request is, the more it resembles an in-house new product development
process.

====='''Justification of launch'''=====

In all cases, successful products were launched in expectation of a positive reaction from the market.
And while in all cases the innovators could cite a reason for launch of the particular product, the level
of detail in their reasoning varied. In a case of an unsuccessful product only broad trend in the market
– growing health consciousness was cited. On the other hand, a significant proportion of the successful
products targeted a particular barrier to fish consumption according to the consumer’s perception,
e.g. bones, ease of preparation, lack of cooking knowledge. Generally, successful products were
characterised by a more careful ‘tailoring’ of the product to the needs of the market where they were
launched. On the other hand, too much ‘tailoring’ was partly blamed to be the reason for loss of brand
identity and therefore market failure in a case where a domestically successful product was launched
in a foreign market. However, the unsuitability of the market for this particular concept may have also
played a role, as stated by representative from the distribution channel, linking again to the
importance of market understanding.

====='''Market research'''=====

As seen above, this appeared to be an important factor for the success of new projects. The level of
investment and extent of market research varied, usually with size of enterprise and resource
availability, but good understanding of consumer needs was not necessarily achieved in the standard
‘scientific’ way. In cases of small companies, typically ‘mini’ consumer research was conducted with
members of the staff. That is also where ideas for new products were often generated. For example,
in one case of a small company, it was reported that it is the women workers who propose the ideas
for new recipes. However, it can be argued that basing the research on too small a sample, particularly
composed of closely associated people could introduce a level of bias as to what the real consumer
needs are on a bigger scale. In another case, the founder of the enterprise achieved good consumer
understanding by working at a different job, close to a large number of end consumer. He applied his
insight understanding of the consumer needs into an improved production process, leading to a
successful product. A clearer idea of the target consumer appeared to be associated with more
success, particularly when the product was tailored to that particular customer group’s perceived
needs. However, there were highly successful cases for which the target customer was a very large
group, e.g. domestic consumes, ‘anybody who likes fish’ or young consumers. In those cases a
characteristic of the product usually removed a barrier to consumption.

However, since successful cases of both types were present, the size of the sample cannot be directly
linked to the performance of products. Suffice to say, it is recommendable that the scope of marketing
research conducted should be relevant to the size and coverage of the intended market.

====='''Originality'''=====

Virtually all, but one, of the companies interviewed considered themselves innovative. However, all
cases investigated could be characterised as having medium to low level of originality. None of the
products was truly new to the market and there was no major ‘invention’ present. In most of the cases
‘newness’ came from combining familiar concepts in a new way, e.g. different species of fish in an
existing recipe. Here, 'borrowing' of ideas from the wider food industry was present to a considerable
extent. Improvement or variations upon existing concepts was the other level of originality, e.g. new
recipe. Combining improved concepts in a new way, provided yet another level of originality, e.g. new
recipe for a sauce in a combination with a different species of fish. In terms of processes, in several of
the cases improvements in existing processes or an application of technology in a new manner was
serving as a basis for new product development. At the end, the products were improved to better suit
the needs of the consumers, but were not radically new. The level of newness was important in
determining whether a product would enter a new market or an established market. However, none
of the products investigated were imitators either, but in two of the cases ‘copying’ of the concept by
retailers and reintroducing the product under new label was cited as a problem by producers.

====='''Innovation process'''=====

The level of resource involvement again varied according to size of the company. A team of trained
chefs and a dietician working together in a multi-disciplinary team including dedicated R&D members
was described in one successful large scale company case. In another large company, the success of
products was attributed mostly to the help of an external agency. The involvement of human resource
in the development process in small companies was primarily focused on senior management and staff
members with multiple functions. However, involvement of external sources such as research
institutions and business partners was also reported by small companies. It was noted that in all cases,
the process was not limited to an R&D team but wider human resource pool was utilised.
Strong leadership and dedication on the side of management throughout the process was found to be
highly positive for the success of innovation products. In a case of a family-owned small scale company,
the highly proactive management approach combined with strong marketing capability was believed
to be a key success factor for the product. In general, the strong management involvement was found
to be important in SMEs.

Similarly, involvement of end consumer in the process was found in all success cases. End consumers
were involved usually at the prototype testing stage of the process. However, in small companies, this
was limited again to the immediate surroundings of the developers – family, friends, staff, with the
limitations associated with such approach discussed above.

====='''Advertising and promotional activities'''=====

In small companies the promotional activities were often limited to marketing efforts by the owner
who would engage with potential clients to promote products which have successfully passed the
development and prototype testing stage. Accepted products would be advertised through local media
sources (newspapers, magazines, radio, TV) or the participation of a company representative at social
events. Considerable advertising effort and expenditure was reported in one of the highly successful
large scale companies. TV advertising campaigns at this company were run annually and online and
social media advertising continuously, tailored to the like of younger consumers. TV campaigns were
reported to be successful in recruiting new consumers in the long term. The company is also building
awareness through the organisation of events where consumers are encouraged to participate. It is
the company’s strategy to educate consumers, with particular focus on young generations. On the
other hand, a highly successful product from a small scale company was completely dependent on the
promotional activity by the owners and their direct engagement with customers.

== Tool Overview ==

----

== References & Readings ==

----

===Conclusions and Recommendations===

While due to sampling limitations, no major generalisations could be made about the wider industry,
the results of the cases investigated point towards the need for a purposeful and goal-oriented
approach to innovation, with strong leadership and intellectual input from various sources.
The most successful companies were highly ‘market oriented’. They had identified unsatisfied
consumer needs, targeted a barrier to fish consumption, or exploited a growing market trend. All
unsuccessful cases had the similar feature of not matching with the consumer needs, either completely
or to a level below which production was unprofitable.

There was a strong indication that a new seafood product has to be a good ‘fit’ for the intended market,
implying the need for a clear understanding of the market (whether through marketing research or
other means) and target consumer .

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WP4

2018-10-24T12:37:37Z

Jacandrade: Created page with "= Work Package 4: Products, consumers and seafood market trends = ---- ----   == General information == ---- === PRODUCT AND CONSUMER TRENDS === WP4 will analyse t..."

= Work Package 4: Products, consumers and seafood market trends =

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== General information ==

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=== PRODUCT AND CONSUMER TRENDS ===

WP4 will analyse the impact of consumer behaviour, market trends, innovation and product development in the seafood market. Work undertaken will be carried out in close co-operation with industry partners and key stakeholders. As a first step, micro-economic tools will be used to analyse how factors such as income, own prices and prices of substitute goods affect the demand for the chosen species. For this purpose, complete and/or partial systems of demand will be estimated. Results will highlight fish consumption within the consumers' diets, depending on country and types of consumers and will be used to simulate the effects of various price policies. In a second stage, past and current consumer preference trends will be analysed and the acceptability of fish products examined by looking at consumption in local, niche and global markets. The specific area of demand stimulation or manipulation through health, label and certification claims on one hand and negative press reports on the other hand will be analysed quantitatively where possible and compared with consumer acceptability of products using Conjoint Analysis. Finally, a database of successes and failures in product development and consumer behaviour will be used as a background material for trend research, yielding insights into product innovation and which product characteristics best fit consumers’ preferences. The outcome of the WP will be an overview of current and future trends and consumer behaviour in local, European and international seafood markets (SO4).

== Deliverables ==

=== [[Deliverable_4.1|D4.1 - Industry study cases report: A collection of marketing successes and failures in the World based on clever product innovation and/or marketing activities]] ===

Innovation is a ‘good, service or idea that is perceived by someone as new’. It is widely acknowledged
that innovation is required for the growth of output and productivity and is also seen as a key to
business success in a competitive environment. In 2012, the food and drink manufacturing industry in
the European Union was the largest manufacturing sector in terms of value of the output with 15% of
the total manufacturing turnover. However, it is widely perceived as not highly innovative. In addition,
the commonly reported figures for new food product failure are between 70% and 90%. (Click title to read more)

=== [[Deliverable_4.2|D4.2 - Demand analysis model]] ===

== Links & Resources ==

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*[http://www.primefish.eu/wp4-products-consumers-and-seafood-market-trends More] information on Work Package 4.
*Main project [http://www.primefish.eu website]
*[http://primefish.eu/project#WP4 WP4 Consortium]

Deliverable 5.4

2018-10-24T11:55:29Z

Jacandrade: Created page with "= Demand analysis model = ---- ---- == Executive Summary == ---- Some consumers expect clean and clear labels, transparency from manufacturers and highest safety while ot..."

= Demand analysis model =

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== Executive Summary ==

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Some consumers expect clean and clear labels, transparency from manufacturers and highest safety
while others value great taste, sensory appeal and premium quality. Others are relying on branded
products and exhibit loyalty, again others may shop in non-traditional channels for food and purchase
based on price. In order to address such consumer diversity and to succeed in a highly competitive
marketplace, firms must understand differences in consumer preferences and behaviour in order to
address them efficiently. New products (and existing ones) must be connected to consumers’ wants
and expectations in order to be placed and marketed strategically and successfully. Many companies
struggle with innovation and new product commercialization as is evident in failure rates of new
food/drinks products as high as 70-80 %.
The value that consumers give to the same product and the expectations they have with regard to it
are different because they are influenced by many factors, e.g. socio-demographic, psychological
characteristics of the person and their surroundings. Segmentation is an approach to better
understand differences and commonalities in consumer behaviour as it helps to identify homogeneous
subgroups of consumers and to efficiently address them. The concept of segmentation thus accounts
for the idea that a business cannot serve the entire market(s) with a single set of marketing policies
because there are disparities among consumers and disparities among countries. One size does not fit
all – but one size may fit the same segment in more than one country.
Surveying representative samples of consumers from Italy, Spain, France, Germany and the UK
regarding their motivations and preferences for fish, the study also collected data on
sociodemographic and consumption patterns garnering a total of 4000 usable questionnaires.
Latent class analyses indicate clear and distinctive segment profiles for the single countries and for
total Europe which give actionable insight for the firms’ new product development/marketing
decisions. The study also identifies segments that cut across the different nations as well as groups of
consumers that are idiosyncratic to just one or a few countries: the findings thus support the existence
of similarities across the European fish market that would allow the fish industry to target the so-called
”pan-European segments” with an almost standardized marketing program.
Examples of cross-national segments include ”cooking artists“, a group of ”indifferent“ fish consumers,
and “ healthy & environmentally conscious” consumers. Of note, while the segment preferences,
expected benefits and behaviour are similar, they may differ substantially in segment size and socio-
demographic characteristics.
The “knowledgeable local ecologist” is an example of a consumer type present only in the UK, and only
in the UK/EU segmentation the combination of “healthy convenience” is uncovered. Convenience is
coupled with price considerations, or taste in Italy, or brand loyalty in Germany, illustrating the many
facets of consumer “convenience” - expectations. As is the case with convenience, the overly
important theme of health (“it can’t be any higher” - Verbeke et al., 2008) is also appreciated in a
multitude of different combinations. Overall, we construct from 7 (Italy) to 5 (UK) segments in each
country and 11 EU-wide segments and indicate segment size and segment trend.

While already the segment profiles by themselves are highly informative, an additional dimension is
obtained by matching the firm’s product(s) with the most attractive segment. The success analysis
model is obtained through multinomial logistic regression, which provides the identification of the
best fit between the segments identified in the various markets and/or Europe and the product
attributes. The firm, in this case, receives clear guidance on which segment(s) to target. A comparison
of product characteristics and the “ideal“ profile as indicated by the segment also gives valuable advice
regarding whether and how to improve the product or marketing program.

== Introduction ==

----

Consumers are too numerous, dispersed, and varied in their buying requirements to make it possible
to serve all efficiently and in the same manner. At the same time, in today’s competitive landscape,
companies follow more and more customized approaches to serve and satisfy the consumers which
again drives their ever more differentiated wants. As a consequence, markets become “demassified”,
dissolving more and more into “micromarkets”, characterized by different consumers purchasing
different products in different distribution channels and attending to different communication
channels. Segmentation aims at identifying such micro markets, i.e. groups of consumers that share
the same expectations and behavioural patterns. The identification of the most attractive micromarkets,
i.e. segment(s), for the company and its products therefore is imperative not only for
successful commercialization but also for new product development.

Following a strategic approach to markets, the company distinguishes the major market segments
based on the profiling of different consumer groups along their wants, consumption and purchasing
behaviour; socio-demographic characteristics etc.; targets one or more of these segments; and
develops products (and marketing programs) tailored to the profile and expectations of each selected
segment.Tailoring starts with an understanding of the customers and providing them with the
product and service they expect but, importantly, embraces also price, distribution and
communication efforts to reach the target segment efficiently. The firm focus is on the buyers whom
they have the greatest chance of satisfying. Having satisfied customers is at the basis for company
success and the first step to repeat purchase and customer loyalty.

Evidence for new product development or new product commercialization success factors shows that
the analyses of market segments, targeting, positioning and the alignment with the firms’ offer and
resources are crucial to both new product development and new product commercialization (e.g.
Montoya-Weiss & O’Driscoll, 2000; Florén et al., 2017).
It follows that segmentation helps companies to navigate an increasingly competitive market, to
understand their customers better, to develop offerings that satisfy specific wants, and to address
diversity in an efficient manner.

The approach to developing a robust model to analyze the likelihood that new seafood product
launches will be successful follows this perspective. We develop both country specific consumer
segmentations in Italy, Germany, France, Spain and the UK, as well as an overarching European
segmentation useful for companies that are innovating and developing new fish products or have fish
products on offer and would like to improve their commercialization. The segmentations are based on
latent class analyses of representative samples of consumers (800 in each of the five countries) who
replied to an online survey in June-July 2017.

Although the segment profiles by themselves are informative, the methodology used contains an
additional step in order to help the company select the most appropriate target(s). In this second
stage, multinomial regression matches product (and firm) attributes with the most attractive
consumer segment(s). A comparison of the segment, i.e. consumer profile, with the product attributes
will further inform the company on how to improve the product and/or its marketing effort in order to
tailor more closely to segment wants and characteristics and ultimately launch and
commercialize successfully. Figure 1 gives an overview of the success analysis model.

'''Figure 1: The success analysis model at a glance'''
[[File:psc_fig_1.JPG |center| Figure 1: The success analysis model at a glance]]

== Methods ==

----

===Survey design===

Based on the objective of consumer segmentation, a questionnaire including socio-demographic,
geographic, psychographic and benefits/behavioural dimensions of consumers and their behaviour
was designed. It is built on previous literature (e.g. Ailawadi et al., 2001; Candel, 2001; Pieniak et al.,
2007; Verbeke et al., 2007; Verbeke and Vackier, 2005), on studies on consumer behaviour regarding
fish related products (EUMOFA, 2016; European Commission, 2016; ISMEA, 2014) and on qualitative
insight gained through explorative in-depth interviews with fish consumers in each of the countries
under study (performed in task 4.1.). Constant interaction with partners in all countries ensured
equivalence and adaptation of the questionnaire in case culturally-specific measures were needed.
The questionnaire was developed in English and cross-checked with a native English speaker from the
partner in the United Kingdom, to ensure the right use of words and concepts from the local culture.
Then, the questionnaire was translated to each of the languages of the remaining countries (Spanish,
Italian, French and German) and back-translated. The translators and back-translators were bilingual
in the target language and English.

The survey instrument was administered online. In order to keep the time to complete the
questionnaire manageable, different flows along the questionnaire were developed so that only
relevant questions and options were displayed. On average, the time needed to complete the
questionnaire was around 11 minutes, in line with recommendations regarding length of online
questionnaires.

===Constructs and Measures - Segmentation criteria===

Market segments are large identifiable groups consisting of individuals that are characterized by
homogenous buying attitudes, preferences, purchasing power, usage patterns etc. Any of these
characteristics can be used to segment markets and to profile the consumers in the respective
segments.
We use combinations of sociodemographic, psychographic, benefit and behavioural criteria to build
and profile segments. Demographic variables have obvious potential as segmentation criteria. The
most commonly used variables include gender, age, income level, and educational achievement.
Frequently, use is made of a battery of demographic variables when delineating market segments.
Psychographic segmentation involves using "lifestyle" factors in the segmentation process.
Appropriate criteria are usually of an inferred nature and concern consumer interests and perceptions
of "way of living" in regard to work and leisure habits. Critical dimensions of lifestyle thus include
activities, interests, and opinions. In the food context examples include interest in cooking, looking for
new ways or recipes to cook etc. (e.g. Grunert et al., 1993). Behavioural variables pay attention to
patterns of consumption (e.g. low-medium-high usage rates) or loyalty with respect to brand/products
among others. Behaviourally defined segments may focus on a specific aspect of behaviour which is
not broad enough to be defined as a "lifestyle". Benefit segmentation aims at proactively defining an
(unfilled) need.

We apply a domain-specific segmentation base and integrate it with some general segmentation
bases; this is pragmatic and relevant for identifying within-country segments but also in order to
identify cross-country segments and related commonalities and differences.
The major segmentation categories with respective variables (illustrative) are show in Figure 2 .

'''Figure 2: Profiling consumer segments along socio-demographic, geographic, behavioural/benefit- and psychographic criteria'''
[[File:Psc_fig_2.JPG |center| Figure 2: Profiling consumer segments along socio-demographic, geographic, behavioural/benefit- and psychographic
criteria]]

In general, operationalization followed extant literature and market studies (e.g. ISMEA 2014;
EUMOFA 2017), the results from the explorative in-depth interviews, a pre-test (done in Italy with 91
respondents) and an iterative discussion with international researchers from the countries under
study. Seven point Likert-scales were used throughout the questionnaire. All Likert-scale questions
followed Friedman et al.’s(1993) recommendations on setting the negative statements on the left side
to avoid the “left side bias” generated by the positive statement. We briefly describe the criteria and
their measurement next (for more details please see the questionnaire in Appendix 1).

===='''Consumer sociodemographic data'''====

The sociodemographic variables we use include: age, gender, employment status, family composition,
education and income. Age is measured as a continuous variable from 18 years onwards. Family size
and structure are measured through two questions: first, respondents were asked to report the
number of people living in their household (including themselves). Since the presence of children or
elderly has been shown to be a major determinant of fish consumption and consumption patterns in
earlier studies, respondents then were asked to indicate also the age of each family member and
whether the member consumes fish.

Employment status is measured through a single selection question including the following categories:
full-time, part-time, self-employed, homemaker, retired, student, unemployed, other.
The education levels are based on ISCED (UNESCO, 2012) and are re-arranged in the following way:
less than primary, primary and lower secondary education (ISCED levels 0-2); upper secondary (ISCED
level 3); university or college below a degree (ISCED levels 4-5); bachelor (ISCED level 6); Postgraduate
(ISCED levels 7-8). The income variable was introduced with options representing income levels from
very low to very high. Country-specific ranges were set for each income level (using secondary data
from e.g. Deutsches Statistisches Bundesamt, 2017; European Commission, 2016; Eurostat, 2017) and
allowance was also made for the fact that the UK has its own currency.

===='''Consumer geographic data'''====
To account for potentially varying consumer profiles within each country, the geographical variables
are measured through three questions. In the first one, respondents were asked to identify in which
type of geographical area they live: urban (more than 50.001 inhabitants), intermediate (between
5.000 and 50.000 inhabitants), rural (less than 4.999 inhabitants). In the second one, respondents were
asked to specify if they lived in an area with a coastline or not. In the third question, respondents
reported their macro-geographical region of residence in their country according to the NUT3
classification (Eurostat, 2013).

===='''Benefits and behavioural measures'''====
The benefits and behavioural measures we include are consumer involvement in buying fish, places of
acquisition, fish attributes important to the selection, fish- and overall food expenditure, situations for
fish consumption, sources of information and past/expected future consumption behaviour.
Consumer involvement was used for screening as we included only those people who were at least
fairly involved in their household’s fish purchasing process.

Consumption frequency (i.e. usage rate) was based on Thong & Solgaard (2017) (never, few times a
year, once a month, 2-3 times a month, 1-2 times a week, 3-4 times a week, almost every day) and
included total fish consumption (i.e. fish consumption also in restaurants, canteens etc.), fish
consumption by species (salmon, cod, seabass, seabream, herring, trout, pangasius) and by formats.
Moreover, the usage rate was used for screening as only fish consumers were included in the survey.

The fish purchasing places and usage occasions were taken from the results of the explorative in-depth
interviews and a continuous interaction with international researchers from the countries under study
(e.g. at home, for a barbecue, at the restaurant, at the supermarket, online, at the fishmonger).
We asked not only for the preferences of the attributes of the fish the consumers buy, but also for
their importance to the purchase in order to account for the fact that consumers usually have to make
a choice across attributes.

Food and fish products expenditure was measured through an open question in which the respondents
were asked first to report their monthly expense on food related products and second, their expenses
on fish products.

In order to understand the use of information sources, we asked respondents to report the frequency
of consulting various information sources (e.g. family members, fish seller, supermarkets and in-store
promotion, advertising, social media, medical advice, labels and information on the packaging of the
product etc.).

Regarding past/future consumption, a new measure was developed based on the explorative in-depth
interviews and on some previous qualitative studies (European Commission, 2016; ISMEA, 2014). We
asked respondents to report changes (increase/decrease) in fish consumption over the past three
years/expected for the next three years. If changes were reported, we also asked to indicate the reason
for the change (e.g. income, available time for cooking, fish prices, health awareness, variety of
choices). Importantly, this information was used to estimate the future segment trend, i.e. stable,
increasing, or declining.

===='''Psychographics'''====
The psychographic dimension includes attitudes, preferences, consumption motives and lifestyle.
Attitudes refer to the degree to which a person has a favourable or unfavourable evaluation towards
a product or behaviour. Following literature, the measure of consumer attitudes included bipolar
adjectives such as items regarding the source of the fish (wild/farmed), the price (expensive/cheap),
formats (frozen/fresh) and production level (processed/unprocessed) and other bipolar pairs such as
branded/unbranded, organic/not organic, natural/enhanced and EU origin/Outside EU origin.

Additionally, based on the exploratory in-depth interviews and the feedback of the international
research team, the following adjectives were also added: local-origin/national-origin, familiar products
or producers/new products or producers, traditional products/products for special dietary needs.
Consumer motives as well as attitudes are extremely important in consumer research as they explain
the reasons behind consumer behaviours. We included quality and sensory appeal motivation items,
health motives as well as items related to price sensitivity and convenience motives and items related
to ethical and environmental concerns.

Life style includes factual and procedural knowledge, based on subjective perceptions and experiences
which encourage enduring dispositions to behave in certain ways. Life style might transcend individual
products, but may be also specific to a product class (Grunert et al., 1993). In the present study, general
and fish specific items were included, e.g. I like to try new recipes, I always inform myself on the
nutrients I can assimilate from fish. We included convenience lifestyle items, ethical and environmental
and health items together with novelty and innovativeness statements. Self-efficacy items (e.g.
regarding the knowledge, evaluation and the preparation of fish) are present too.

===Sample===
The average apparent fish consumption per capita in the EU is the second highest in the world (at
around 22 kg/capita/year), and some individual EU Member States are among the highest fish consuming
countries in the world (EEA, 2016). The five selected nations under study had the highest
household expenditure and volume in fishery and aquaculture products in 2015, representing in total
the 72% of all consumer expenditures. Their importance is underlined also with the fact that they
covered around 86 % of the total EU fresh fish consumption in volume and 85 % in value in 2015
(EUMOFA, 2016).

Within-country representativeness was ensured using a stratified random sample (Lohr, 2010), which
is more likely to produce a representative sample (Reynolds et al., 2003). Each country was divided
into different stratums for the sociodemographic variables described earlier, where the percentages
of the sample assigned to each sociodemographic stratum were established based on the total
distribution of the population of each country. The percentages for age, gender and geographical
regions were obtained from Eurostat (2017) and were established based on the population between
18 to 74 years old in 2016. Age was divided into five stratums: 18-24 years old, 25-34 years old, 35-44
years old, 45-55 years old and >=55 years old. The geographical regions stratums were defined
according to the NUT3 European classification of small regions (Eurostat, 2013).
Representativeness of the education categories from the ISCED outlined earlier in the countries was
established according to the OECD (2016, p. 43) as this source provided a more detailed classification
than Eurostat (2017). The measures were based on the population between 18 to 64 years old.

===Data collection===

The target samples were 800 adults aged 18 and older from Italy, Germany, France, Spain and United
Kingdom. The respondents had to be fish consumers (no restrictions on frequency) of at least one of
the target species (salmon, cod, seabream, seabass, herring, trout, and pangasius) and be fairly or
completely involved in the fish buying process in their households. The data was collected through an
online survey developed on the Qualtrics platform. Before collecting survey data, a pilot test of the
survey was performed with partners and with 91 Italian fish consumers. The feedback provided was
used to improve the questionnaire. The final version of the questionnaire was launched in parallel in
all five countries to ensure data collection equivalence (Hult et al., 2008). The data collection took a
month, from June 23rd until July 24th, 2017.

Respondents were selected from a market research panel with qualifying demographic characteristics.
They were sent an invitation to fill in with information on questionnaire length and the available
incentives. Each sample stratum from the panel base was proportioned to the general population and
then randomized before the survey was deployed. To exclude duplication and to ensure validity, every
IP address was checked using a sophisticated digital fingerprint and deduplication technology
(Qualtrics, 2014).

All data were collected through the online survey. Although online questionnaires present many
advantages such as reduced cost, time and access to unique populations they also have some
limitations such as the access to older and less educated consumer groups (Wright, 2006). For this
reason, some of the stratums percentages originally defined for education and age had to be slightly
modified, to reach the target of 800 respondents per country in a reasonable time frame. The changes
were always done by increasing mainly the percentage of respondents in the closest categories from
the one with the low quota response. On average, respondents took 11.4 minutes to complete the
questionnaire.

In total, 4414 completed and usable questionnaires were collected, from which 4000 were
representative for each country (800 responses per country) and sample stratum, according to the age,
gender, education level and macro-geographical area. The main sample characteristics are reported
in Table 1.

'''Table 1: Sample characteristics'''
[[File:psc_tab_1.JPG |center| Table 1: Sample characteristics]]

===Statistical Methods===
===='''Exploratory and Confirmatory Factor Analysis (EFA – CFA) for questionnairevalidation'''=====

We followed the commonly used combination of exploratory factor analysis (EFA) and confirmatory
factor analysis (CFA) to validate our questionnaire. Construct validity of the items of the questionnaire
is investigated firstly with EFA to uncover the factor pattern underlying the questionnaire, and then
CFA is used to validate the factor structure provided by EFA. We performed factor analysis i) overall
and ii) within country (stratified analysis). Finally, we performed a multi-group confirmative factor
analysis to assess the measurement invariance (i.e. configural, weak and
strong invariance) (Meredith, 1993) between countries.

Factor analyses were performed using R (R Core Team, 2015) and the R-packages polycor (Fox, 2016),
paran (Dinno, 2012), psych (Revelle, 2017) and lavaan (Rosseel, 2015).

All results confirm validity of our survey instrument: the EFA statistics, i.e. eigenvalue >1 and Horn’s
parallel analysis, identified seven factors for Europe and each individual country. By CFA, only the items
with high factor loadings were retained (83,3%) to maintain factor consistency. Overall, CFA fit indices
were adequate for both European and for single country analyses. Indices of unidimensionality
(AVE>0.2), reliability (omega>0.7) and general factor validity (rho>0.8) were satisfactory for each
factor, and the item–factor correlations (>0.4) proved high-quality specific factor validity for all items.
In addition, the indices were also satisfying in the CFAs stratified by country and in the multi-group
analysis, by retaining the same items. Finally, concerning multi-group analysis, the testing of the
measurement invariance showed a weak invariance, i.e. the factor loadings are equal across countries
(results are available upon request).

===='''Latent Class Analysis (LCA) and multinomial logistic regression for segmentation and for matching consumer segmentations with products/firms'''====

Latent class analysis (LCA) can be viewed as a special case of model–based clustering for multivariate
discrete data. It is assumed that each observation comes from one of a number of classes, groups or
subpopulations, with its own probability distribution. The overall population thus follows a finite
mixture model. When observed, data take the form of categorical responses as, for example, in
consumer behaviour surveys, it is often of interest to identify and characterize clusters of similar
individuals.

In the context of marketing research, one will typically interpret the latent number of mixture
components as clusters or segments. In fact, LCA provides a powerful tool and the state-of-the-art
technique to identify market segments. In line with our objective, latent class analysis has been
suggested as a model-based tool for regular market segmentation (Wedel & Kamakura, 2000) and
international market segmentation (Steenkamp & ter Hofstede, 2002).

In the following we describe the standard latent class model and its parameter estimation and we
report the problem of model selection and goodness of fit criteria. Subsequently, we present the
extension of the basic model which permits the inclusion of covariates to predict latent class
membership. We discuss three-step approaches for LCA with covariates. Lastly, we present the
empirical application.

===='''The formal models of LCA'''====
Let 𝑋 represent the latent variable and 𝑌𝑙 one of the L observed or manifest variables, where 1 ≤ 𝑙 ≤
𝐿. Moreover, let C be the number of latent classes and 𝐷𝑙
the number of levels of 𝑌𝑙. A particular latent class is enumerated by the index x, x = 1, 2, ..., C, and a
particular value of 𝑌𝑙 by 𝑦𝑙, 𝑦𝑙= 1, 2, ..., 𝐷𝑙.

The vector notation Y and y is used to refer to a complete response pattern.
The basic idea underlying any type of LC model is that the probability of obtaining response pattern y,
𝑃(𝐘 = 𝐲), is a weighted average of the C class-specific probabilities 𝑃(𝐘 = 𝐲|𝑋 = 𝑥); that is,

[[File:psc_eq_1.JPG |center| equation 1 ]]

Here, 𝑃(𝑋 = 𝑥) denotes the proportion of persons belonging to LC 𝑥.
In the classical LC model, this basic idea is combined with the assumption of local independence. The
𝐿 manifest variables are assumed to be mutually independent within each LC, which can be
formulated as follows:

[[File:psc_eq_2.JPG |center| equation 2 ]]

After estimating the conditional response probabilities 𝑃(𝑌𝑙 = 𝑦𝑙
|𝑋 = 𝑥), comparing these
probabilities between classes shows how the classes differ from each other, which can be used to
name the classes. Combining the two basic equations (1) and (2) yields the following model for
𝑃(𝐘 = 𝐲) marginal probability:

[[File:psc_eq_3.JPG |center| equation 3 ]]

The model is formulated for nominal indicators 𝑌𝑙 and consequently a multinomial logit distribution
is hypothesized for the conditional probability to obtain 𝑦𝑙
to l-th, given the affiliation to the latent
class x, 𝑃(𝑌𝑙 = 𝑦𝑙
|𝑋 = 𝑥).
The conditional probability is parameterized as follows

[[File:psc_eq_4.JPG |center| equation 4 ]]

Where the linear term 𝜂𝑦𝑙
|𝑥 = 𝛽𝑦𝑙 + 𝛽𝑦𝑙𝑥, the parameter 𝛽𝑦𝑙
is the intercept and 𝛽𝑦𝑙𝑥 is the effect of
the latent variable X on the indicator 𝑌𝑙.

In the same way, the probability associated with the latent variable X has a nominal logit distribution:

[[File:psc_eq_5.JPG |center| equation 5 ]]

Similarly to cluster analysis, one of the purposes of LC analysis might be to assign individuals to latent
classes. The probability of belonging to LC x – often referred to as posterior membership probability
– can be obtained by the Bayes rule,

[[File:psc_eq_6.JPG |center| equation 6 ]]

The most common classification rule is modal assignment, which amounts to assigning each
individual to the LC with the highest 𝑃(𝑋 = 𝑥|𝐘 = 𝐲).

The parameters of LC models are typically estimated by means of maximum likelihood (ML):

[[File:psc_eq_7.JPG |center| equation 7 ]]

Where i is a particular pattern of response, I is the number of all potential patterns of response,
(𝐼 =∏ 𝐷𝑙𝐿𝑙=1) and 𝑃(𝐘 = 𝐲𝑖).
Among the most popular numerical methods for solving the Maximum Likelihood Estimation (MLE)
problem is the Expectation-Maximization (EM) algorithm (Dempster et al., 1977). The EM algorithm
treats the estimation of LC model parameters as an estimation problem similar to those for missing
data (i.e. multiple imputation). More details about the model and the parameter estimation are
provided in Lazarsfeld and Henry (1968), Goodman (1974); Haberman (1979), Clogg (1995), Agresti
(2002) and Bartholomew, Knott and Moustaki (2011).

An advantage of LCA as compared with other clustering techniques is the variety of tools available for
assessing model fit and for determining the appropriate number of latent classes. In some applications,
the number of latent classes will be selected for primarily theoretical reasons. In other cases, however,
the analysis may be of a more exploratory nature, with the objective being to locate the best fitting or
most parsimonious model. The researcher may then begin by fitting a complete “independence”
model with C = 1, and then iteratively increase the number of latent classes by one until a suitable fit
has been achieved.

Parsimony criteria seek to strike a balance between over- and under-fitting the model to the data by
penalizing the log-likelihood by a function of the number of parameters being estimated. The two most
widely used parsimony measures are the Bayesian information criterion, or BIC (Schwartz 1978) and
Akaike information criterion, or AIC (Akaike 1973). Preferred models are those that minimize values of
the BIC and/or AIC.

BIC will usually be more appropriate for basic latent class models because of their relative simplicity
(Lin and Dayton 1997; Forster 2000). Calculating Pearson’s χ2 goodness of fit and likelihood ratio chisquare
(G2 ) statistics for the observed versus predicted cell counts is another method to help
determine how well a particular model fits the data (Goodman 1970). The entropy of a model is also
used as a model selection criterion, either by itself or together with other statistics.

===='''Latent class with covariates (using multinomial logistic regression)'''====

In most LC analysis applications, one not only wishes to build a measurement or classification model
based on a set of responses, but also to relate the class membership to explanatory variables. In a
more explanatory study, one may wish to build a predictive or structural model for class membership
whereas in a more descriptive study the aim would be to simply profile the latent classes by
investigating their association with external variables (Vermunt, 2010). The latent class regression
model (LCRM) generalizes the basic latent class model by permitting the inclusion of covariates to
predict individuals' latent class membership (Dayton and Macready, 1988; Hagenaars and
McCutcheon, 2002).

In the LCA literature two ways for dealing with covariates have been proposed: a one-step and a threestep
approach. The former involves simultaneous estimation of the LC (measurement) model of
interest with a logistic regression (structural) model in which the latent classes are related to a set of
covariates. An alternative estimation procedure that is sometimes used is called the “three-step"
approach: estimate the basic latent class model, calculate the predicted posterior class membership
probabilities and then use these values as the dependent variable(s) in a regression model with the
desired covariates. Since the one-step presents certain disadvantages – for example, it limits the
number of covariates that can be considered in the model (Vermunt, 2010) - we use the three-step
approach in order to avoid such limitation. In a subsequent step, this allows us to predict the consumer
segment and perform a matching between segmentation and firms’ characteristics, in order to detect
the best segment for the firm. According to this, the causal relationship firm-to-consumer segment will
be explained by multinomial logistic regression models where the consumer segment will be the
dependent variable and the selected covariates (i.e. organic, wild, cheap etc.) will be the choice
factors. Theoretical details and the generic equation of the multinomial logistic regression model are
reported in Agresti (2002). LCA and multinomial regression were performed using poLCA (Linzer &
Lewis, 2011) and nnet (Venables et al., 2002) R-packages (R Core Team, 2017), respectively.

== Models ==

----

===Matching segments and products/firms via multinomial logistic regression===

Multinomial regression was employed not only to integrate segment information (please see paragraph 3.2.), but is also employed in a subsequent step for the match of segment (demand) and product/firm (supply side). The company interested in an identification of the most attractive consumer segment for the firm’s offering, i.e. the match of segment profile and product characteristics, will select the variables which best describe the product, e.g. wild/farmed, species, branded/unbranded, claims used (Omega 3, new recipe, easy-to-cook etc.) and choose the target country (France, Italy, Germany, Spain, UK).

Once the company has selected the variables (X) – for our example in Figure 4 below – Spain (market), salmon (species), traditional preparation, branded, wild, origin, omega 3 (claims), the estimated coefficients of multinomial logistic regression will be employed:

[[File:psc_eq_8.JPG |center| equation 8 ]]

where 𝑖 = 1,…,𝑘 − 1, k = number of classes discovered by LCA, r = reference class, X is the design matrix (with the independent variables) and  i is the coefficients vector for the modality logit i Finally, we compute the membership probabilities 𝑝̂𝑖 = 𝑒𝑋𝛽 1+𝑒𝑋𝛽 (by coefficients) for each i class in order to obtain the results in terms of best class, i.e. the best membership probability, in other terms, the “best” segment. From the algorithm we obtain the association between product characteristics and the segment, according to the best fit (highest membership probability).
Such a fit leads to success in this segment (i.e. market). Additionally, the model will indicate – based on firm and product characteristics - which product or marketing elements should be improved and/or added to increase the fit, and it will yield an estimate about segment (i.e. market) size and segment growth. Such information is essential because the fit is a necessary, but not sufficient, condition for sustainable product/firm success. Of course, the segment must be economically
attractive and it must be accessible for the firm. The segments’ profiles provide also details on how to best access the segment, e.g. which communication and media to use, whether to innovate through packaging or through product features etc.

This step corresponds to targeting, i.e. the selection of the most attractive market segment(s) for the firm and informs about positioning, i.e. the overall marketing program to address the segment needs.
Here follows an example on how the match is actually set (Figure 4). In this example case for Spain, the best fitting segment is the fourth: “360 degree health (nutritional digestive and inclusive health)” with probability membership equal to 0.80. This segment (360 degree-health) however is present also in EU.

'''Figure 4: Graphic results of the match between product firm and consumer segments'''

[[File:Psc_fig_4.JPG |center| Figure 4]]

===Conclusions===

A LCA was conducted using a sample of 4000 representative responses collected from fish consumers involved in fish purchasing in five European countries, i.e. Italy, France, Spain, Germany and the UK. We identify distinct and meaningful segments for the single countries and an overarching European segmentation. Segment profiles include expected benefits, usage patterns, sociodemographic information etc. of the segments’ consumers.

Our findings show segments that cut across various countries (e.g. cooking artists, the group of indifferent consumers) but also groups that are idiosyncratic to one or a very few countries only (e.g. the local connoisseurs; the local ecologist in the UK; the convenience & health oriented cluster).

The segmentation profiles are valuable for new product development and commercialization activities in general as they provide firms with a better understanding of their primary markets as well as with a comparison with other markets and segments. Armed with insight on expected benefits and reasons for fish choice and actual consumption behaviour, firms get actionable input regarding the key decision of selection of country market(s) and/or consumer segment(s) and respective positioning and marketing programs. The model, however, goes a step further and proposes the “best” match (i.e. targeting) of segment with company offering (through multinomial regression). The match will further be developed in the decision support system (PrimeDSS) in WP6.

Using the results of the segmentation and the algorithm for matching consumer profiles with product/company attributes in five countries and in Europe, the DSS user will get clear advice on which segment(s) to target and indications of whether and how to improve the product or the marketing program (also internationally).

Finally, the present activity has been implemented in parallel with the survey in Task 4.6, with a number of common questions (the “bridge questions”) opening further avenues of development. The combination of the surveys bears potential to develop an even more powerful tool to be implemented in the PrimeDSS.

The results of the segmentation across the five surveyed countries and EU jointly with the algorithm for match as well as the possibility to combine the survey in Tasks 4.4 and 5.4, will be further investigated and eventually used as an input for the PrimeDSS development in WP6 of the project.

== Reports &Data ==

----

===Descriptive analysis===

As shown in table 2, in our samples, fish is more frequently consumed in Italy, Spain and France (1-2 times a week) as a median value. The most consumed fish species across countries are salmon and cod. A significant consumption of herring is recorded only in Germany (2-3 times a month). Seabream and seabass are mostly consumed in Italy and Spain.

Among all nations, France has a higher median frequency of trout consumption (2-3 times a month). Pangasius has a median frequency of consumption that is completely irrelevant (median value corresponds to '' never '').

'''Table 2: Median values of fish consumption'''
[[File:Psc_tab_2.JPG |center| Table 2]]

In Table 3 frequencies of consumption by species in the various countries are broken down further.
Salmon is least frequently consumed in Spain and the UK where 28 % and 25 % of consumers report
consuming salmon only 1-2 times a week. The corresponding frequency is 26-30 % in France, Italy
and Germany.

Consumption of seabream is most frequent in Spain and Italy, where around 20 % of consumers have
seabream at least 1-2 times a week. In the UK, only 4 % of consumers have seabream once a week or
more often. A similar practice is to be observed for consumption of seabass; around 20 % of consumers
in Italy and Spain have seabass at least 1-2 times a week, while the corresponding frequency in the
other three countries is much lower, even as low as 1 % in Germany.

Consumption frequency of trout is comparable in all countries except Germany where percentages are
slightly higher (17 %, 2-3 time a month). Cod is most popular in Italy and in the UK (1-2 times a week),
in Spain the consumption of cod varies between 1-2 times a week and 2-3 times a month; in France
and Germany cod is consumed less frequently (2-3 times a month) with the lowest – 16 % -
consumption in Germany.

Herring is consumed mainly in Germany where 22 % indicate that they consume herring 2-3 times a
month, and a further 13 % 1-2 times a week. France and the UK are similar in frequency but the
percentage of those who consume herring is much lower. In Italy and Spain just a few consume herring.
Pangasius, as compared to the other species, is the least consumed, as already evidenced by the 0
median shown above.

'''Table 3: Frequency of consumption for species in the various countries'''
[[File:Psc_tab_3.JPG |center| Table 3]]

In Italy, the favorite formats of fish species consumption are: fresh fillet and smoked for salmon; whole
fish for seabream, seabass and trout; frozen fillet for cod; and smoked and canned for herring.

In France the favourite format for seabream, seabass, trout and cod is fresh fillet whereas smoked is
preferred for salmon and herring. In Germany the favourite formats are: fresh fillet for salmon,
seabream and seabass; smoked for trout; frozen fillet for cod and canned for herring. In UK the
favourite formats are: fresh fillet for salmon, seabream, seabass and trout; frozen and fresh fillet for
cod and smoked for herring. Ready to eat/read-to-cook products are mainly consumed in Germany
and UK (for further details on the choice of fish formats by species in the various countries please see
Table 4).

'''Table 4: Percentage of choice of fish formats by species by country'''
[[File:Psc_tab_4_1.JPG |center| Table 4 part 1]]
[[File:Psc_tab_4_2.JPG |center| Table 4 part 2]]

Looking into the main sources of information, in general, European consumers consult frequently
labels, and sometimes fish-seller, supermarket and in-store promotions, family and friends. In all
countries, labels are the most used source of information.

Italian consumers frequently consult the label, the fish-seller and the family, sometimes supermarket
in-store promotion and medical and friends’ advice. The Spanish consumers consult frequently fishseller
and label, occasionally supermarket in-store promotion and family, friends and doctor’s advice,
and rarely mass media. French and British consumers differ somewhat from consumers in Italy and
Spain, as they consult frequently label and sometimes supermarket in-store promotion, friends and
fish-seller and thus make use of fewer sources of information. Germans additionally consult family,
and, like Spanish consumers, they rarely attend to mass media. In none of the countries investigated,
consumers use scientific magazines, social networks or industry and non-governmental organizations
to learn about fish.

Table 5, below, shows the information behaviour in the single countries and in Europe.

'''Table 5: Maximum frequency for information sources by country'''
[[File:Psc_tab_5.JPG |center| Table 5]]

In Appendix 2, more descriptives are presented, for example the place of purchase, and consumption
situations by country (Table 11 and 12 respectively).

Overall, 42% of the respondents have maintained the same level fish consumption for the past 3 years,
13 % decreased fish consumption and 45 % increased fish consumption in the same period. The share
of those who increased fish consumption is higher in the UK (52 %) and Italy (48 %), whilst the quota
of those who decreased fish consumption is higher in France (19 %). Spain and Germany share the
same trend of fish consumption over time (please see figure 3).

'''Figure 3: The evolution of fish consumption over the past three years'''
[[File:Psc_fig_3.JPG |center| Figure 3]]

Table 6 shows a series of different aspects important for fish selection as expressed by the
respondents.

'''Table 6: Importance of different aspects in fish selection (1 = Not at all important; 7 = Extremely important)'''
[[File:Psc_tab_6.JPG |center| Table 6]]

Regarding the importance of the characteristics ascribable to the fish, it can be noted that in all
countries that the highest mean value of importance is associated with the items “value for money”,
“general appearance”, “texture”, “origin and traceability” of the product, to the endowment of a
“certification of sustainability” and to the “health-nutritional aspect”. Italy has the highest mean values
for environmental, health-nutritional and sensory aspects.

In general, consumers are more worried about the negative consequences of fishing on marine
resources, than those of fish farming on the environment. The concern is higher in France and
Germany. In general, respondents believe that fish consumption has more benefits than risks. The
benefits are more appreciated in Spain and Italy. In general, consumers have confidence in their own
ability to cook fish and evaluate the quality of the fish before buying it. Overall, consumers consider
"save time" and -"ready to cook" characteristics unimportant as well as the low price and branded
products (Table 7).

'''Table 7: Agreement with different statements in fish selection (1 = strongly disagree; 7 = strongly agree )'''
[[File:Psc_tab_7.JPG |center| Table 7]]
*Has a discounted price; ** I easily change my fish selection in case of discounts; the first one wants to measure the
importance that the application of a reduced price has on the purchaser and the second wants to measure how much the
consumer is susceptible to the effect of the discount.

===LCA segments===
Latent class analysis was performed on 42 items for the European consumer segmentation and 27
items for the single countries (please see Table 8 for the items). Using the information from EFA and
CFA we have been able to obtain a first selection of items to be included in the latent class analysis
(please see section 2.5.1.). A second selection of items was obtained on the basis of LCA: all those
items that had a high probability on the neutral modalities of the Likert scale were eliminated (e.g.
farming and fishing effect, save time item etc.) leading to a final selection of 27 items used in countryLCA.
The items, as discussed above, reflect established benefit-behavioural, and psychographic
segmentation criteria, useful to the identification and exploration of subgroups of consumers, i.e.
segments. In Table 8 the items and respective variable labels are reported. The items used for single
country analyses are marked with an asterisk. LCA were performed overall and stratified by country.
In each country individuals were assigned to one of the latent classes based on their highest posterior
probability of class membership derived from their response to the items.

In addition, for each country, the multinomial logistic regression model is applied to evaluate the
associations between classes predicted by LCA and predictors (i.e. independent variables). In
particular, the dependent variable (outcome) was the membership class predicted by LCA (i.e.
segment), while the independent variables were: family size, general consumption of fish, children
eating fish, age, grocery shopping (euro), single fish species consumption (i.e., salmon, seabream,
seabass, cod, trout, herring) (see Table 9 for details). If our segment profiles are meaningful, that is
explaining/able to predict actual consumption behaviour we should find a coherent pattern between
preferences/benefits expected in the various segments and their consumption and sociodemographic
combinations.

To gain degrees of freedom, the 7-point Likertscale for frequency of consumption of individual species
was rearranged into four categories (≤low, medium-low, medium-high, high) while the one for the
“general consumption” variable was collapsed into three (low, medium, high) categories. The age
variable was divided into five classes (i.e. [18-24), (25-34], (35-44], (45-54], >54). To take into account
the influence on consumption habits resulting from the presence of children (≤ 12 old years), a new
categorical variable has been constructed using information on the presence of children eating fish
“no” (children do not eat fish), “none” (no children in family) and “yes” (children eat fish). The class
"low consumption”, “young”, “consumers and no children in the family" group was used as the
reference category. As we will see in the following paragraph, the segment called “indifferent” is
present in all countries. For reasons of easy and best comparison, this segment has been chosen as the
reference category for the multinomial logistic regression.

'''Table 8: Items used in LCA models (single country – European segmentation)'''
[[File:Psc_tab_8.JPG |center| Table 8]]

The coefficients of the model are interpretable as expected outcome variation in odds ratio (OR) terms
(OR= exp (βj), from the reference category) per unit increase of the associated predictor, keeping fixed
the others in the built-in model. Concerning the results, in all countries, family, children
(<12 years) eating fish and grocery shopping variables were not statistically significant. The significance
of the remaining variables varies by country and by nature of the variables, in particular the level of
fish consumption by species and by age categories.

The results obtained from the multinomial logistic regression model (especially OR) and from the
calculation of descriptive statistics (mean value and relative frequencies in each class) are used to
characterize the consumer profile (market segment) in more detail (detailed results of the regression
are available on request).

To obtain an improved description of the segments, we calculate frequency and mean of some sociodemographics
(gender, family size, income, education), geography (presence of coastline and
urbanization) and consumption (i.e. usage) variables (general fish consumption, format of fish etc.),
preference for boneless, wild/farmed and traditional products. In case a variable was not statistically
significant in the multinomial logistic regression model, mean and frequency were calculated in order
to obtain all the information we needed to describe the segments.

'''Table 9: Variables names and measures'''
[[File:Psc_tab_9.JPG |center| Table 9]]

In a pre-processing step, we decided to transform 7-point into 6-points Likert scales by collapsing the
5 and 6 modalities, in order to increase segment interpretability. Since the number of latent classes
cannot be estimated as part of the LCA, we performed a LCA sensibility analysis by evaluating models
from 1 to 14 classes and defining the number of classes based on statistical and substantive
grounds. For the purpose of statistical model selection, we used the Bayesian information criterion
(BIC) and we considered the relative improvement in model fit (based on the log likelihood-function).
In addition, we evaluated the competing models in terms of usefulness and interpretability. Finally, we
found the 11-class model in Europe to allow an adequate representation of the data and to permit
good differentiation of the posterior probability classes (profiles or segments). Country analyses tend
to yield fewer classes, e.g. in Italy we have identified a 7-class model, in Spain and Germany 6 class
model, while in France and UK we have identified 5 class models.

Before we go into detailed country segment descriptions, a note on the interpretation of results is
appropriate. For reasons of parsimony, in the following we will only report the main characteristics
and patterns, as indicated by respondents, to support the construction of our segment profiles. The
profiles are complemented with some key sociodemographics and linked to consumption patterns. For
the full list of variables and detailed information (as well as probabilities of inclusion) please see
Appendix 3, Tables 13-18. Of note, the segment profile is a combination of items which the
respondents value highly and/or what they do not consider important. Members inside the segments
share the same profile while their profiles are distinct across the segments (i.e. within- group
homogeneity and statistically significant between-group heterogeneity). We turn now to a detailed
description of single country- and the overarching European segmentation.

====Italy====

We identify 7 distinct consumer segments in Italy, as reported in Table 11 (for all details please see
Appendix 3, Table 13).

Segment 1, the health & environmentally conscious consumer represents 13 % of the Italian
consumers(trend: stable). Members of this segment are willing to pay (second highest expenditure for
fish in Italy) for beneficial effects for both personal and environmental health. Predominantly women
aged 50 + value items such as environmentally friendly, sustainability and natural ingredients,
nutrients, easy-to digest characteristics highly. Appearance and traceability are also important to this
segment, pointing to critical evaluation and check of quality/safety issues related to fish. They prefer
wild fish, boneless and traditional recipes. Their favorite place of purchase is the supermarket/fish
monger which are also their sources of information. The segment’s usage rate is medium-high. Of note,
consumers here like all fish species (although they consume seabream and seabass most) and buy a
broad range of formats. The women and their small families (3 persons) reside in bigger urban centers,
with children who are grown up but still live at home.

The brand-convenience-taste consumers reflect only a small but growing portion of the Italian market
(7 %). This group of young consumers with small families declares to have a preferred brand and to
favor taste over nutritional aspects. Highly important to them are availability of the fish, new formats,
labels and omega 3. The consumers here also value fish products that take little time to prepare while
nutrients or sustainability claims are of no importance to them. Consistent with a brand buyer is also
the fact that these consumers are not self-efficacious– they rely instead on the familiarity and security
that comes with a preferred brand and label (another aspect of “convenience”). In line with this profile
is the supermarket as the only place of purchase, which is also, together with advertisements, the
segment’s main source of information. People in this group live predominantly in rural areas of the
country. The favorite species are salmon (ready-to-eat/to cook, fresh fillet), seabream (fresh fillet) and
cod (frozen fillet) with overall medium consumption and average expenditure.

The self-efficacious cooking artist, the third Italian cluster we describe, represents 14 % of Italian
consumers (trend: growing). Here we find the self-efficacious (all items that point to knowledge and
evaluation of fish score high) relatively young male who likes to cook, is creative in meal preparation
and looks for versatility. Consistent with the passion for cooking, saving time in meal preparation is
unimportant to him. He looks for healthy products (with traceability) but also for a reasonable pricequality
ratio. He and his partner (or small family) live in coastal/rural areas as well as in urban centers.
The favorite place of purchase is the supermarket or the fishmonger, the source of information is the
label or the advice from the fishmonger. Chooses predominantly seabream, seabass and cod in a wide
range of formats (except ready to eat). Fish expenditure is average, in line with the fact that those who
have more knowledge of fish can find more alternatives among available products.

The local connoisseur represents the biggest segment in Italy (24%/growing). This is the group of
consumers who know everything about fish (high values across self-efficacy items), use its versatility
and experiment with new formats or recipes. Relatively young women here (with small family) strongly
emphasize the health-nutritional aspect and underline easy digestion. This group of consumers also
favours local origin. They pay attention to environment and sustainability issues and indicate the
preference for a (local) brand or seller. Emphasizing value for money, they do not trade off quality for
price (but would instead go for a cheaper species or stock the fish in order to be flexible). They prefer
wild fish, are indifferent to bones, and are inclined to traditional preparation. Their consumption is
medium-high (mainly seabream, seabass, less cod and salmon in a wide range of formats) with an
expenditure that is the highest across all Italian segments. These consumers buy in the supermarket
or at the fishmonger and do not indicate any sources of information.

Price-wise convenience consumers (14%/stable) represented in segment 5 are very price conscious,
reflected also in their low expenditure on fish. People here are not knowledgeable about fish. They
strongly underline health, easy-to-cook characteristics and texture. In line with this profile is their fish
selection – they favor cod and salmon (fresh and frozen fillets but also canned, smoked, ready-tocook/ready-to
eat). Both genders aged 54 + are represented here, mainly living with one grown up
child in rural and urban areas. Preferably they buy in supermarkets which are, together with
advertisements, also the source of information.

Segment 6 is a representation of self-efficacious pragmatic fish consumers, a large (23%) and growing
segment with high fish expenditure. They value the health benefits of fish, look for conservation and
versatility. Preferences here bring together the health of both, individuals and the environment, added
is a strong emphasis on value for money. Although this segment is knowledgeable about fish and its
preparation, the profile seems to reflect a pragmatic instance of “having to eat and cook fish” without
related pleasure of doing so. In fact, this segment has only two favorite species, namely salmon and
cod, which they consume frequently, predominantly as fresh/frozen fillets. Women aged 45 + with
small families, medium-high education and income represent the sociodemographic profile of this
segment best.

Finally, the group of indifferent consumers is the smallest group of consumers (6%/stable),
represented by relatively young male with small family living in rural or intermediate areas of Italy.
Their favorite place of purchase is the supermarket. They consult the label or ads for fish information.
Species include seabream and salmon and their expenditure is among the lowest across the segments.

====Spain====
Latent class analysis identifies 6 segments in the Spanish market (for all details please see Appendix
3, Table 14).

Segment 1 represents brand/seller “dependent” high quality consumers who are not self-efficacious
(23%/growing). The preferred “brand“ here is either the shop/seller or the brand itself. Consumers do
not feel on the safe side regarding fish evaluation and preparation and thus rely on the trusted
seller/brand of whom they learn. They give importance to inclusive health (individual and
environment) and have a broad quality understanding for which they are ready to pay. This segment
shows high fish consumption and the highest expenditure for fish. Consistent with the fact that they
like to cook but do not indicate corresponding competence they go for a very limited range of species.
They buy in supermarkets or at the fishmonger and listen to the advice of the fishmonger or seller.
Women aged 46 + with small children (who eat fish) and low-medium education but relatively high
income best represent this group of consumers. Favorite species are seabream (whole/fresh fillet) and
cod (fresh/frozen fillet, dried).

Self-efficacious selfish brand buyer (23%/growing): also this group of consumers has a preferred
brand/seller but it is, as compared to segment 1, self-efficacious. It is “egoistic” in terms of health
orientation as only items which focus on individual health are important (while environmental
attention is unimportant) to this segment. Men around 55 here take care of their family which lives in
cities close to the coast. They are medium seabass and salmon consumers who spend relatively little
on fish.

The independent “good for me” connoisseur (9%, growing) values taste and nutrition equally.
Members of this segment love fish (sensory appeal) and they value its benefits for health. They crosscheck
on labels and expect a guaranteed origin. In line with this, the segments favorite species is wild
fresh seabass which is consumed in high quantities. Women aged 48, living with family in cities at the
coast are willing to spend for their selected premium seabass which they preferably buy at the
fishmonger or in the supermarket.

The consumers in the 4th and biggest (29 %, stable) segment in Spain are directed towards nutritionaldigestive
and inclusive health (360 degree-health). Consistent with this emphasis is the importance
given to origin and traceability. Value for money is crucial to this segment, and they value conservation.
Their medium-high fish consumption is reflected also in a relatively high fish expenditure mainly spent
on fresh seabream and salmon (fresh/smoked). Young women here take care of their families with
young children.

(Salmon) Cooking artists (9%/stable), very young couples (24 +), like to cook and trust in their
competence of fish (salmon) preparation, they are creative and experiment with new formats, and
they emphasize versatility. None of the health related items is of importance. The young couples go
mainly for wild salmon (medium –high consumption) in the supermarket. Salmon is the dominant
species they buy in all formats. Consistent with the artist stance is also the (low) use of an exotic species
such as herring. The main source of information is the seller.

The indifferent (7%/stable), with medium-low consumption of salmon and cod, spends little on fish.
Typically consumers here are young male, small family size, low education level living in urban centers
in the countryside.

====France====
In France, 5 distinctive segments are identified with LCA (for all details please see Appendix 3, Table
15).

The good for me health consumer represents 29 % of the French market (trend: stable) that expects
mainly health benefits from fish consumption and looks for guarantees in terms of sustainability
certifications and traceability. Predominantly consisting of male in their fifties, highly educated and
with high income, this segment appreciates “easy-to-cook” products and emphasizes value for money.
It is characterized by low-medium consumption and low expenditure for seabream (either fresh fillet
or ready-to-eat). Shopping for two, predominantly in supermarkets, these men use the label or the
seller for information.

The segment of the health oriented (selfish), (not creative) cook (23%/growing) is medium-high in fish
consumption and the highest in expenditure. Women aged around 45 highly value the health benefits
of fish, they like cooking and the variety and versatility that comes with many species and a wide range
of formats (herring, cod and seabream) in traditional preparations. They purchase in the supermarket
for a small family and take information from the label and the seller.
The cooking artist represents around a quarter of fish consumers in France (trend: stable). This profile
cuts across all ages, also the very young. They choose carefully, go for high quality for which they are
ready to pay and they consult many information sources. Health is not on the agenda of this segment
and they have no environmental concerns. They shop for seabream at the supermarket or at the
fishmonger. The couple prefers fresh, but they are flexible and willing to try different formats and
recipes.

Self-efficacious convenience consumer to whom, beyond inclusive health, convenience is central
(31%/stable). They give importance to each and every aspect and thus represents very demanding
consumers. This consumer critically checks the expected quality: reads labels and values certificates
and guarantees. Medium consumption of varied fish species and broad range of formats (reflecting
convenience), and second highest expenditure on fish. Relatively young women and men are
representing the class, living in the countryside/intermediate cities in small families.
The indifferent in France are the smallest group of consumers (7%/stable). The class is on a mediumlow
level in fish consumption and the lowest expenditure for trout, salmon and cod. Prefer mainly in
fresh and frozen formats. The segment is predominantly young singles or couple, living in the
countryside in smaller cities.

In all segments salmon and trout is consumed. The species mentioned above distinguish the segments
from this overall baseline consumption.

====Germany====

For the 6 segments constructed in Germany full details are depicted in Table 16, Appendix 3.

Among the 6 segments in Germany we identify the cooking artist (12%/stable) who is loyal to a
brand/seller and gives importance to local origin. Consumers in this segment share the characteristics
that cut across-countries for the cooking artist: they like to cook/are capable of preparing fish, value
versatility, are creative and ready to try new formats. Taste here clearly dominates nutritional aspects
(only Omega 3 is of importance). Consumers in this segment are not price sensitive, a fact reflected also in the highest fish expenditure across German segments. They
prefer fresh fish, medium usage rate, mainly salmon but also the more “exotic” seabream (the only
segment in Germany) and seabass. The class includes both genders, they are young, live with a small
family with smaller kids in cities in the countryside.

Healthy & environmentally-conscious consumers make up a third of the German market (growing).
To consumers in this segment, a healthy diet and a natural product and the texture are central. Health
here is inclusive of the environment, consumers value sustainability certification and put emphasis on
a guaranteed origin. They are not self-efficacious and thus trust their “seller/brand”, but also consult
the label and ask for guarantees. The group is ready to pay for the value they ask for, i.e. a healthy &
environmentally safe diet, which is reflected in high fish expenditure. The class includes both genders
aged over 54 involved in decisions and patterns of fish consumption (salmon, trout and seabass; fresh
and frozen); consistent with their health focus their consumption is medium high.

The convenience- brand loyal consumer (23%/growing), looks for value for money. Brands provide the
benefits she asks for: nutrients, sustainability certification, traceability, label. Ready-to-eat is
emphasized which together with fresh formats may satisfied her want for creativity. Predominantly
relatively young female living in a two-person-household in cities in the countryside with lower fish
expenditure and medium fish consumption represent this cluster best. The members of this segment
shop in supermarkets where they get information in-store, from the seller or from the label.
The fourth segment comprises healthy cooking artists who like variety. Being a premium segment in
terms of expenditure, this profile unites the cooking artist with a focus on health. Versatility is
important, but experimentation is also reflected in a broad range of species and formats. The sociodemographic
profile of women over 54, with medium high education, in 2 person-households, is very
much in line with this segment.

Cheap brand and taste consumer (16%/stable): People in this segment have learned the claims of
their preferred brand (but they are not knowledgeable about fish), omega 3 and tasty, they are priceconscious
and, overall, seem to go for an easy buy without much involvement or major decision
criteria. Fish here offers the best compromise between health and taste. No importance is given to
origin and traceability. Male in their forties (couple) spend little for medium-low consumption.
The indifferent present around 7 % of the market, predominantly young and single. Medium
consumption, relatively high expenditure and a broad range of species and formats.
Of note, herring is consumed in all segments. The species mentioned above distinguish the segments
from this overall baseline consumption.

====UK====

5 segments represent the British fish consumers best (for all details please see Appendix 3, Table 17).
Healthy convenience consumers (22 %, growing) have their focus on “easy” to cook, to stock, to use
(versatile). Health is also central, with a strong focus on digestion and environmental concern and the
request for traceability. The segment is characterized by medium consumption and highest
expenditure on fish across the segments. Women, aged above 50 with medium-high education and a
2-person household describe the segment best. Members of this segment appreciate wild fish; their
favorite species are seabream, seabass – fresh fillets, ready-to-eat, whole fish.

Selfish health & convenience consumers, the biggest segment (43 % , growing) are typically younger
couples with medium – low income but relatively high expenditure on fish. They are informed and are
consulting many information sources, do not trade off quality for price and are indifferent to brands,
origin and traceability. The focus is on health, but also easy to cook, versatility, and conservation are
important. Consume salmon and seabass in medium quantity. This segment is similar to segment 1 in
convenience but health is not inclusive and more focused on nutrients than on digestion and its
information behaviour is more extensive.

Cooking artist (8 %/stable trend). Similar to her counterparts in the other countries, the British cooking
artist likes to cook and to experiment with new formats. Taste is an important theme, while she is
indifferent to health and environmental concerns; dietary issues are not important. British cooking
artists are not really knowledgeable about fish. Women aged 44+ in small families with children eating
fish do best describe the sociodemographic characteristics. Prefer wild, favorite species seabream and
cod. Given the low income she really likes and spends (over proportionally) for fish.
Self-efficacious & local ecologist (13 %/growing segment) are very young singles or 2-person
households. They are knowledgeable and environmentally conscious. At the same time they give much
importance to the local context. The segment members enjoy cooking and they trust in their meal
preparation. Medium consumption of salmon, seabream, seabass, but with low expenditure.
The segment of indifferent (14 %, growing) is composed of young male, single or in a household of
two, and low to medium education. Prefer salmon and cod, ready to eat, ready to cook. Medium
consumers, low expenditure.

In all segments cod is consumed. The species mentioned above distinguish the segments from this
overall baseline consumption.

====Europe====
We construct 11 European segments which are briefly discussed here below (for all details please see
Appendix 3, Table 18 ).

The salmon fan segment (9 %/growing), in line with the only species it consumes, values highest omega
3, availability, versatility and value for money. These consumers also clearly favor taste over nutritional
aspects. Consumers here are women in their forties, living in households of two persons with medium
– high salmon consumption of all formats and relatively high expenditure. In terms of relative
composition, this segment is very prominent in the UK (29 %).

Segment two represents the self-efficacious inclusive health consumer, one of the largest EU
segments (17 %, growing): knowledgeable people who appreciate the health-nutritional aspect of fish.
Dietary considerations are not important (e.g. nr. of calories). Health includes the wellbeing of the
environment. People emphasize value for money, expect traceability and certification but are
indifferent with regard to organic products. Male and female consumers aged around 50, with medium
expenditure and fish consumption; favorite species are salmon, seabream, cod with wide variety of
formats. Germans make up 24 % of this segment.

Cooks with inclusive health focus (11%) characterize segment 3. They enjoy meal preparation (but are
neither creative nor knowledgeable of fish) and emphasize omega 3 and “easy-to-digest” attributes.
Their overall important theme is individual and environmental health, and, importantly, animal
welfare, which is cross-checked with label and certifications. The segment is not price sensitive and is
ready to pay for the expected value. Relatively young men here take care of small families who live in
urban centers in the countryside. Low-medium consumption, but relatively high expenditure on fish.
UK dominated with 27% of consumers in this segment (trend: stable).

Tasty and easy quality (8%). To this segment value for money is important as are “easy to cook” and
quick preparation of meals. Availability and conservation is stressed, emphasizing the
time/convenience posture of the segment. Taste and texture are valued more than health aspects. No
environmental concerns and also self-efficacy criteria are low/indifferent. Young male (early thirties)
with medium-high education take care of small families. They prefer wild over farmed and spend much
for taste and easy quality - high expenditure for medium-high fish consumption. Segment is mainly
populated by French, Spanish and Italians (trend: increasing).

Segment 5 is the 360 degree- health oriented segment (11%), which gives much importance to natural
fish products. Also “easy to digest” and nutrients are of utmost importance, as is the absence of smell
and a guaranteed origin. It is the only segment where people also have a concern regarding negative
effects of farming. Consistent with this preference they favor wild fish. The segment is characterized
by medium-high fish consumption with corresponding high expenditure. Women in their 50s in 2-
people households with medium education represent best the demographic profile of the segment.
Italians dominate this segment (trend: increasing ).

Segment 6, one of the smallest in EU (5 %), is characterizing the innovative brand buyer. Consumers
here have a favorite brand to which they are also loyal. “Claim”-related items are important but not
supported by corresponding factual knowledge. People here are also the only ones to underline new
dietary preparations (e.g. gluten free products), they prefer products that take little time for
preparation, and they emphasize conservation and versatility. Time, overall, is an important factor for
this group. The known brand is a response to this: choosing the familiar brand saves time in terms of
reflection/selection and it is a guarantee for satisfied expectations. Consumption of this segment is
high with corresponding highest expenditure across all segments. British, Italian and French women
around 45, with small families make up this segment (trend: increasing).

Indifferent: the majority of indifferent consumers is divided among UK (31 %) and France (27 %),
followed by Spain and Germany (15 % and 14 %, respectively), with a stable trend. Only 12 % of the
class is populated by Italian consumers. This segment is characterized by male and female aged 18-
40, with low education and medium-low consumption. Expenditure, not surprisingly, is the lowest.
Healthy convenience (6 %). Segment 8 consumers look for easy to cook meals that take little time to
prepare, appreciate conservation and general health/environmental benefits. Being demanding on all
dimensions, they are ready to pay for the corresponding products. As confirmed by high fish
expenditure, consumers do not trade off value for money. Here young dads with medium-high
education take care of their bigger families’ health by balancing it with the need to have meals easily
and quickly prepared (trend: stable). Only Italy is underrepresented (16 %) in this overall balanced
segment.

This group – the local – natural brand/seller (5 %) - values “local” and natural highly. More than
emphasizing the presence of positive nutrients and elements, consumers here emphasize the absence
of ingredients and substances. They are self-efficacious, trust a certain – local – brand or seller to whom
they are loyal. They also stress availability. Fish consumption is medium – low, expenditure is at the lower level across segments. The sociodemographic show relatively young men
and women in households of three holding a medium education level. German consumers account for
27 % of this small segment (trend: stable).

In this segment we find the cook with selfish health focus (8%) who likes taste and nutrition. Broader
health, dietary or environmental concerns are not considered important. Consistent with enjoying the
preparation and consumption of fish, this segment’s expenditure is medium-high with corresponding
high expenditure. Relatively young Spanish women in small households without children best describe
the consumers of this segment (trend: increasing).

Cooking artists (17 %, stable) are creative, like to experiment with new formats, like to cook and are
self-efficacious. No environmental and health concerns. Women in their fifties in small households (2-
3 members) with medium consumption and relatively low expenditure characterize this segment’s
demographic profile. The majority of the class is made of Italians, while the minority comes from UK.
Table 10 presents a summary of the segments identified in the single countries and in the “total” EU
countries under study. As is clear from this table and the discussion above, some segments are crossnational
or pan-European, while others are specific to a few/only one country.

'''Table 10: Overview of single country/EU segmentations'''
[[File:Psc_tab_10.JPG |center| Table 10]]

Firstly, in line with a well-established association of health and fish consumption (Verbeke et al., 2008),
we find many shades of health across segments and countries. Health in our segments is referred to
“egoistically”, i.e. in terms of personal health (nutrients; digestive health, low in calories); it is reflected
in inclusive health as mirrored in individual and environmental “health”, comprehensive of animal
welfare (item available only for the EU segmentation). The segment combinations emphasize multiple
facets, e.g. healthy & environmentally conscious consumers in Italy, Germany and EU, health-oriented
cooks in Italy and in France, a segment having a 360-degree health orientation in Spain and in the EU
and many more. Overall, however, animal welfare, or the negative consequences of farming or
overfishing are neglected themes for our respondents. Also, organic products do not emerge as being
important to any of the groups.

Secondly, in all countries except Italy we find a cooking artist (“a Masterchef”) who loves fish for its
culinary/sensory characteristics and is highly involved with cooking. Thirdly, a group of “indifferent”
fish consumers is present across all countries: consumers in these segments do not exhibit a clear
pattern of health-, convenience-, taste-related preferences. Still, these groups represent low to
medium fish consumers and, in some countries, large portions of the overall market.
However, these segments cutting across the nations are heterogeneous in terms of the relative size of
each segment and in terms of the demographic/consumption patterns as presented in Tables 14-18.
The cooking artist, for example, seems to be a Millennial couple in France and Spain (focused on
Salmon), while in Germany and the UK the artists are older (aged 34 + in Germany and 44 + in the UK)
and predominantly female in the UK. The group of indifferent fish consumers is very small in Italy,
France, Germany and Spain (6 % or 7 % respectively), while it climbs up to 14 % in in the UK. In Spain
and Italy, the indifferent are male in their late thirties, while in Germany and the UK this segment is
very young (aged 24) and growing.

Other general patterns concern the presence of “brand” buyers in various combinations. The
combination comes mainly with convenience and a trend-seeking attitude (innovation in EU), but also
with high-quality expectations and taste.

The simultaneous focus on health and convenience, a priori seen as incompatible in literature (Olsen
et al., 2009) is an interesting theme which emerges in the UK and in EU. With regard to other
differences, we do not find evidence of convenience in Spain, and price-oriented clusters exist only in
Italy and Germany. Italy and Germany show similar segments of healthy & environmentally conscious
consumers as well as health- instead of taste-oriented cooking artists. Spain and Italy have the
connoisseurs in common, people who derive benefit from highest quality and sensory /taste attributes
of fish. As one would expect, in these two markets self-efficacy as a general trait is much higher than
in the other countries under study.

Other segments, for example the self-efficacious local ecologist, a very young segment, is present only
in the UK, as is the price-oriented convenience buyer in Italy or the cheap brand & taste seeker in
Germany.

Commonalities across the markets may help interested firms identify avenues for international
expansion. Similarities enable the firm to address the segment needs with a more or less standardized
marketing program, and therefore offer a relatively straightforward way to achieve growth abroad.
Differences, instead, may point to emerging trends and may be used for inspiration for product
development and additional segments to come up with. For example, while the young “Masterchef”-
type of cooking artists and the “connoisseurs” appreciate taste and sensory appeal,
the “connoisseurs” are more traditional and do not enjoy creative cooking. They are also very different
regarding both the socio-demographic profile and the species they use. In general, young people
represent important portions of the market which need to be catered to as they present the market
opportunities of tomorrow.

The many shades of health also evidence how important positioning and marketing activities are in a
differentiated market. As mentioned above, health benefits may be associated with nutrition, diet,
digestion, absence of negative substances, environmental and animal health. It is important to
understand the differences: selfish health consumers will not value environmental claims while for
inclusive health consumers these are a must. Still, the theme of environmental health may be also
linked to personal health and safety so that firms should be wary about the risk of overemphasizing
environmental benefits over other benefits sought by the consumers. Care of purely environmental
items is stressed by only one segment across all countries (UK). Moreover, the above mentioned
combination of health and convenience shows an interesting theme. It illustrates that convenience
food producers should not only focus on the time/effort and taste dimension (or appeal to children)
but that healthy convenience is another facet of convenience food that is valuable in two countries
(Italy/UK) and in the overall EU segmentation. One remaining question is also whether and how to
convert portions of passive (indifferent) into active consumers, to further develop overall market
potential.

== References & Readings ==

----

===Acknowledgements===

Firstly, we are grateful to all PrimeFish partners that took part in the challenging process of survey
design and translation, namely: Sterenn Lucas and Olga Untilova from INRA and USav, José Luis
Santiago from CETMAR, Imke Matullat from TTZ, Dimitar Taskov and John Bostock from the University
of Sterling, Kolbrun Sveinsdottir from Matis. We thank the University of Parma team, and especially
Giovanni Sogari and Davide Menozzi, for their contribution to survey design and for collaboration with
regard to the “bridge questions” which may be used to further develop and combine the two surveys’
results in the PrimeDSS. We also are grateful to Andrew Baxter and Heiner Lehr from Syntesa for
support and collaboration regarding the segment/product (company) match to be implemented in [[WP6]].

A special “thank you” goes to Emilia Cubero Dudinskaya, the dedicated post doc researcher on
PrimeFish who has left our University at the beginning of December, for her contribution to this task
and the project tasks in more general.

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WP5

2018-10-24T11:51:57Z

Jacandrade:

= Work Package 5: Prediction models =

----

----

 

== General information ==

----

=== DEVELOPMENT OF SIMULATION AND PREDICTION TOOLS ===

In WP5 simulation models are developed to analyse how changes in supply and demand affect production planning, economic performance, supply chain relationships, value added, potential product success, market trends and developments and thus competitiveness as measured by the updated FACI developed in WP1. Simulations of “boom and bust” cycles will be carried out and common traits highlighted that facilitate the development of prediction models. Building on work undertaken in WP4, a set of product success indicators will be established designed to indicate probability of successful launches on a targeted seafood market. The outcome of this WP will be simulation/forecasting models for analysing changes in competitiveness, prediction of instability of demand and supply including that of warning signs for “boom and bust” cycles and for indication of potential for product innovation success (SO5).

== Deliverables ==

=== [[Deliverable_5.1|D5.1 - Fisheries and Aquaculture Competitiveness Index]] ===

The concept of competitiveness can be traced back to early writing on economics in the 17th and 18th centuries, but has become ever more urgent in the last decades with rapid improvements in transport and communication and a higher level of globalisation. Although competitiveness may be measured by single indicators, such as productivity of labour, a deeper understanding of the competitive standing of firms and countries can be gained by employing multi-dimensional measurements. Currently, the Global Competitiveness Index (GCI), developed and compiled by the World Economic Forum, is probably the most comprehensive index of its kind. The choice of methods depends on a variety of factors, including the perceived need for complexity, data availability and how the results are to be used. (Click title to read more)

=== [[Deliverable_5.4|D5.4 - Demand analysis model ]] ===

Some consumers expect clean and clear labels, transparency from manufacturers and highest safety
while others value great taste, sensory appeal and premium quality. Others are relying on branded
products and exhibit loyalty, again others may shop in non-traditional channels for food and purchase
based on price. In order to address such consumer diversity and to succeed in a highly competitive
marketplace, firms must understand differences in consumer preferences and behaviour in order to
address them efficiently. New products (and existing ones) must be connected to consumers’ wants
and expectations in order to be placed and marketed strategically and successfully. Many companies
struggle with innovation and new product commercialization as is evident in failure rates of new
food/drinks products as high as 70-80 %. (Click title to read more)

== Links & Resources ==

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*[http://www.primefish.eu/work-package-5-prediction-models More] information on Work Package 1.
*Main project [http://www.primefish.eu website]
*[http://primefish.eu/project#WP5 WP5 Consortium]

Deliverable 5.1

2018-10-24T11:45:36Z

Jacandrade: Created page with " = Deliverable 5.1 - Fisheries and Aquaculture Competitiveness Index = ---- ---- == Methods == ---- Currently, the Global Competitiveness Index (GCI) is probably the mos..."

= Deliverable 5.1 - Fisheries and Aquaculture Competitiveness Index =

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== Methods ==

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Currently, the Global Competitiveness Index (GCI) is probably the most comprehensive index of its kind. The index defines competitiveness as the set of institutions, policies and factors that determine the level of productivity of a country. The most recent analysis covers 138 countries, with a combined output representing 98% of the world GDP. The index, which is compiled annually by the World Economic Forum, combines 114 indicators that capture concepts that matter for productivity and long-term prosperity. As shown in the [[#cpi_structure|figure ]] below, these indicators are grouped into 12 pillars: institutions, infrastructure, macroeconomic environment, health and primary education, higher education and training, goods market efficiency, labour market efficiency, financial market development, technological readiness, market size, business sophistication, and innovation. These pillars are in turn organised into three sub-indexes: basic requirements, efficiency enhancers, and innovation and sophistication factors. The three sub-indexes are given different weights in the calculation of the overall Index, depending on each economy’s stage of development, as proxied by its GDP per capita and the share of exports represented by raw materials.

 
<div id="cpi_structure">[[File:Cpi structure.jpg|The structure of the Global Competitiveness Index. Source: WEF 2016.]]</div>
 

=== Fisheries and Aquaculture Competitiveness Index (FACI) ===

As outlined above, competitiveness can be measured in a number of ways, using both simple and more complex analytical tools. The choice of methods depends on a variety of factors, including the perceived need for complexity, data availability and how the results are to be used.

The FACI must be flexible enough to meet the needs of the two different end-users; industry and policymakers. With this in mind it was decided to develop two different kinds of competitiveness indexes; a firm-level FACI and a national-level FACI. The firm-level FACI is only intended to capture the views of operators of individual firms and therefore less complex. It is based on a survey which in the case of firms engaged in the harvesting, processing or marketing of wild capture fish consists of 40 questions, and in the case of aquaculture firms consists of 45 questions. The firms are able to access the [http://dss.primefish.eu/index.php/cpa firm-level FACI], complete the survey and then compare their answers to those provided by other operators. The degree of comparison will, of course, depend on the number of firms using the PrimeDSS, but provided the number of users is large enough, it would be possible to undertake comparison between firms in the same sectors both in the same country as well as between countries, as well as between different sectors. By thus benchmarking themselves against others, firms could gain a better understanding of their competitive standing.

The national-level FACI is modelled on the Fisheries Competitive Index (FCI) developed by the Directorate of Fresh Fish Prices in Iceland and the Norwegian College of Fishery Science at the University of Tromsø in 2004-2005 (Verðlagsstofa skiptaverðs, 2005). The FCI consists of 139 questions and observations which are split between six sub-indexes that make it possible to calculate scores both for the FCI as a whole as well as for individual sub-indexes. This further expands the use of the FCI. The index was applied to the Icelandic and Norwegian fish industries. The national-level FACI consists of 144 items, whereof 44 are taken from the WEF Global Competitiveness Index, 19 are based on data obtained from national, public sources and 81 are based on answers from a survey conducted among specialists in each country. Whereas the information taken from the GCI analyses the overall competitiveness of the nation, the other sources will throw light on the competitiveness of the fisheries and aquaculture sectors. The national-level FACI will therefore yield a comprehensive measure of competitiveness which takes both into account general conditions in the country as well as those that deal specifically with the sectors of interest.

According to Porter (1998, 2008), the nature of competition is embodied in five competitive forces; (1) the threat of new entrants, (2) the threat of substitute products or services, (3) the bargaining power of suppliers, (4) the bargaining power of buyers, and (5) the rivalry among the existing competitors. As shown in the [[#firmlevel-faci|figure]] below, these forces do interact with each other. Their strength may also vary but together they determine long-term industry profitability.

 
<div id="firmlevel-faci">[[File:FirmLevelFaci.jpg|The five competitive forces that determine industry competition. Source: Porter (1998).]]</div>
The threat of entry puts a cap on the profit potential of an industry. When the threat is high, incumbents must keep prices low or increase production capacity to deter new competitors. Within each industry there are usually some entry barriers that deter new firms from entering the market, and give the incumbents some advantages. These may include economies of scale, network effects, customer switching costs, capital requirements, unequal access to distribution channels, restrictive government policy, expected retaliation of incumbents, and some other advantages not related to size, such as favourable geographic locations, and established brand identities.

The power of suppliers varies between industries, but in general a supplier is more powerful if is more concentrated than the industry it sells to, the supplier group does not depend heavily on the industry it is selling to, the firms face switching costs for changing suppliers and the products offered by suppliers are somewhat differentiated.

Buyers can capture more value by forcing down prices, demanding better quality or improved service, and play industry partners against each other. Analogous to suppliers, buyers have more leverage if they are few and large, the industry’s products are similar so that there are ample substitution possibilities, and there are low switching costs.

A high threat of substitutes will reduce profitability by placing a ceiling on prices. A firm can, however, distance itself from others through product performance, marking or other means. High rivalry among existing competitors will reduce the profitability of the firms in an industry. The rivalry can take many forms, including price discounting, new product innovations, advertising campaigns and service and quality improvements. Rivalry will be especially high in cases where there are many competitors and no clear industry leader, industry growth is slow and exit barriers are high. Although some market/firm/industry characteristics may be regarded as only belonging to one specific force category, other characteristics could plausible be classified in two or more different ways. Thus, the value of an output brand could impact on the bargaining power of buyers, threats of substitutes and rivalry among existing competitors. The firm-level FACI builds heavily on the theories of Porter (1998), taking into considerations all five aspects of competition outlined above. As stated earlier, this index is mostly intended for operators of fisheries and aquaculture firms who wish to analyse the competitive standing of their firm. The index consists of 40 questions – 45 in the case of aquaculture – that together yield a solid measure of competitiveness. This deliverable yields the results of a survey that was put to firm operators, but once the PrimeDSS becomes operational it will be possible to access a computerised version of the firm-level FACI, complete the survey online and then obtain a measure of the competitiveness of the firm, both by analysing the data and comparing the competitive standing of the firm to that of other firms. Each questions uses a seven-level Likert scale. Nine of the survey questions refer to the category threat of new entrants. They are as follows

*Institutional barriers (f. ex. licenses, quotas, regulations, location restrictions, water treatment)
*Investment barriers in capital (vessels, equipment, buildings)
*Other form of barriers (marketing, R&D, knowledge)
*Economies-of-scale in production
*Utilisation of economies-of-scale
*Geographical location
*Level of uncertainty in business environment
*Local availability of highly skilled labour
*Availability of qualified experts

The first three items all refer to concrete barrier to entry, such as licenses, quotas, investment, and R&D. The next two refer to the existence and utilisation of economies-of-scale, but companies that produce at a large scale enjoy a cost advantages that new entrants may have difficulties in matching. Geographical location refers to the fact that some firms are well located in terms of cost and ability to meet customer demand. An uncertain business environment may make entry less attractive, and the availability of skilled employees will certainly impact on the threat of entry. The bargaining power of suppliers is analysed on the basis of the following eight questions for fisheries firms (10 for aquaculture firms):

*Bargaining power of suppliers
*Competition among the major suppliers (fisheries)
*Current quality of raw material (fisheries)
*Ability of prices for raw material to reflect changes in (fisheries)
*Quantity
*Quality
*Timing
*Ability of prices for seed to reflect changes in (aquaculture)
*Quantity
*Quality
*Timing
*Ability of prices for feed to reflect changes in (aquaculture)
*Quantity
*Quality
*Timing
*Comparative access to raw material (fisheries)
*Comparative access to seed (aquaculture)
*Comparative access to feed (aquaculture)
*Access to supplier networks

The term “raw material” refers to landings of catch sourced by processors. Catches are by far the most important input for firms engaged in processing and marketing of wild capture fish, while for aquaculture firms the most important inputs are seed and feed. The interest here is in how well prices for these inputs reflect changes in quantity, quality and timing. The term “comparative access” refers to how firms regards their access to inputs (raw material, feed, seed) compared to their competitors. The bargaining power of suppliers is also assessed using a direct question on that issue. The bargaining power of buyers is analysed in terms of eight characteristics:

*Customers´ sensitivity to changes in product price
*Value of brand
*Loyal buyers
*Bargaining power of buyers
*Ability of output prices to reflect changes in
*Quantity
*Quality
*Timing
*Diversification of marketing options

Good brand value and loyal buyers will combine to make customers rather insensitive to changes in product prices. The survey also has questions on how firms view the price sensitivity of product prices, i.e. whether the firms regard their product price inelastic or elastic, as well as whether the bargaining power of buyers is weak or strong. Diversification of marketing options refers to whether the firm depends on a single buyer for its product or many buyers. The bargaining power of buyers may also be affected by how well output prices reflect changes in quantity, quality and timing of sale

The bargaining power of buyers is very closely linked to the threat of substitute products or services. Some of the items listed under the bargaining power of buyers, such as customers’ sensitivity to price changes, brand value and consumer loyalty, could just as easily have been listed under substitutes. Here, only two items are classified in this category, namely:

*Production to a niche market
*Availability of substitutes

Customers in niche markets are often willing to pay a premium price for a product that well satisfies their needs. These markets are often characterised by a strong brand and consumer loyalty. The two survey questions here refer to whether the firm is producing to a niche market, and whether substitutes to the product are available in the market. Most of the survey questions in the firm-level FACI are here grouped under the heading “rivalry among existing competitors”. However, many of these items could equally well have been categorised differently. These questions are on the following topics:

*R&D collaboration with technology firms
*Importance of R&D for operation and possibility to increase value added
*Importance of innovation for competitive advantage
*Ability of firm’s part of the value chain to respond to changes in market conditions
*Ability of the whole value chain to respond to changes in market conditions
*Importance of third-party audited labels
*Strength of competitive strategy
*Market share of firm
*Level of cost leadership
*Sophistication of production technology compared to best practice
*Quality of sites for production facilities
*Flexibility to adapt to unpredictable events
*Ability of risk management and insurance to protect against unpredictable negative shocks
*Comparative seed costs (aquaculture)
*Comparative feed costs (aquaculture)
*Comparative production losses due to diseases or other causes (aquaculture)

The first three questions refer to R&D and innovation activities within the firm, to which degree they are done in close collaboration with high-tech firms, and how important they are for increased value added and competitive advantage. Flexibility of the value chain – both as regards the firm itself and the whole value chain – is also important for firms facing competition. Third-party labelling has become very important in the food industry, not least for fisheries and aquaculture. Labelling may open access to markets and also indicate sustainable and environmental friendly production. The market share of firms is important, as is the level of cost leadership. Firms are also asked to indicate how sophisticated their production facilities are compared to their competitors, and assess the quality of the sites used for their production facilities. Two questions refer to the ability of the firms to adjust to unpredictable events, and three questions focus on the costs of feed and seed relative to the firm’s competitors, and comparative production losses due to fish diseases and other causes.

The firm-level FAC yields both an overall score as well as a score for each of the five competitive forces where the former is calculated as the simple average of the other five scores.

=== National-level FACI ===

The national-level FACI is a comprehensive measure that includes both factors influencing each country’s overall competitiveness as well as factors that specifically relate to the fisheries and aquaculture sectors. Most of the indicators related to overall competitiveness are taken from the Global Competitiveness Index, published by the World Economic Forum (2016), but information on the other, more specific indicators was obtained through surveys and from public data collection agencies.

The national-level FACI consists of three pillars; (I) basic requirements, (II) efficiency enhancers, and (III) innovation and sophistication. In contrast to the firm-level FACI, the national-level FACI yields a weighted overall score for each country, as well as a weighted score for each pillar and the sub-indexes contain therein. Basic requirements weigh 30% of the total score, efficiency enhancers 50% and innovation and sophistication 20%.

[[File:NationalLevelFaci.jpg|center|Overall structure of the national-level FACI.]]

The first pillar – basic requirements – comprises elements that are essential if firms are to thrive in a competitive, international world. As noted by Acemoglu and Robinson (2012), economic prosperity depends above all on the inclusiveness of economic and political institutions, where inclusiveness is defined as the situation where a large number of people have a say in political decision-making. By contrast, extractive institutions allow a certain elite to rule over and exploit others, thus preventing firms from enjoying competition on a level playing field. As shown in Table 1, there are two subsections within the first pillar, institutions and infrastructure. Institutions are then further subdivided into public institutions and management of fisheries and aquaculture. Public institutions are then finally divided into property rights and public sector performance. There is just one indicator for property rights, namely property rights, but within public sector performance there are three indicators. Well defined and secure property rights are essential for any market-based activity, as are well functioning courts and legal system that make it easy for firms to challenge government actions and/or regulations. Transparent government policy making is also important. The burden of government regulation must however not become too great. For firms operating within the fisheries and aquaculture sectors, it is also important how well these activities are managed by policy makers.

 

''Table 1 Structure of the first pillar, Basic requirements.''

{|
|-
! Level
! Weight
! Source
|-
| style="width: 70%;" | 1st pillar: Basic requirements
| style="width: 15%;" | 30%
| style="width: 15%;" |  
|-
| . A. Institutions
| 75%
|  
|-
| .. I. Public institutions
| 33%
|  
|-
| ... 1. Property rights
| 50%
|  
|-
| .... 1.01 Property rights
| 100%
| WEF
|-
| ... 2. Public sector performance
| 50%
|  
|-
| .... 2.01 Burden of government regulation
| 33%
| WEF
|-
| .... 2.02 Efficiency of legal framework in challenging regulations
| 33%
| WEF
|-
| .... 2.03 Transparency of government policy making
| 33%
| WEF
|-
| .. II. Fisheries management
| 33%
|  
|-
| ... 3. Stability
| 33%
|  
|-
| .... 3.01 Transparency of fisheries management
| 33%
| Survey
|-
| .... 3.02 Objectives of fisheries management
| 33%
| Survey
|-
| .... 3.03 Stability of the allocation of fishing rights
| 33%
| Survey
|-
| ... 4. Research and advice
| 33%
|  
|-
| .... 4.01 Actual vs recommended fishing mortality
| 20%
| Data
|-
| .... 4.02 Extent of information gathering by marine research
| 20%
| Survey
|-
| .... 4.03 Information gathering by marine research
| 20%
| Survey
|-
| .... 4.04 Accuracy of forecasts of marine research
| 20%
| Survey
|-
| .... 4.05 Impact of marine research on investments and operation
| 20%
| Survey
|-
| ... 5. Monitoring and inspection
| 33%
|  
|-
| .... 5.01 Efficiency of the management system
| 50%
| Survey
|-
| .... 5.02 Illegal/excess catches
| 50%
| Survey
|-
| .. III. Aquaculture management
| 33%
|  
|-
| ... 6. Stability
| 50%
|  
|-
| .... 6.01 Transparency of aquaculture management
| 25%
| Survey
|-
| .... 6.02 Objectives of aquaculture management
| 25%
| Survey
|-
| .... 6.03 Stability of the allocation of the aquaculture licenses
| 25%
| Survey
|-
| .... 6.04 Efficiency of management - aquaculture
| 25%
| Survey
|-
| ... 7. Research and advice
| 50%
|  
|-
| .... 7.01 Extent of information gathering by research for aquaculture
| 100%
| Survey
|-
| . B. Infrastructure
| 25%
|  
|-
| .. I. Transport infrastructure
| 100%
|  
|-
| .... 8.01 Quality of overall infrastructure
| 20%
| WEF
|-
| .... 8.02 Communication network needs
| 20%
| Survey
|-
| .... 8.03 Communication network restrictions
| 20%
| Survey
|-
| .... 8.04 Cost of domestic transportation
| 20%
| Survey
|-
| .... 8.05
| Cost of cross-border transportation
| 20%
| Survey
|}

 

Table 1 also shows the weighing structure of the FACI. As noted above, the first pillar, Basic requirements, carries a weight of 30%, with institutions thereof weighing 75% and infrastructure weighing 25%. Within institutions, public institutions weigh 33%, fisheries management 33% and aquaculture management 33%. Within public institutions, property rights weigh and public sector performance each weigh 50%. Finally, each of the three indicators of public sector performance weighs 33%. The weight of each section and indicators is shown in the second-last column of Table 1, while the sources are shown in the last column of the table. WEF refers to the 2016-2017 Global Competitiveness Index carried out by the World Economic Forum, data refers to data collected from official sources, and survey refers to the survey carried out among experts in each country.

''Table 2 Structure of the second pillar, Efficiency enhancers. Subsections A-C.''

{|
|-
! Level
! Weight
! Source
|-
| style="width: 70%;" | 2nd pillar: Efficiency enhancers
| style="width: 15%;" | 50%
| style="width: 15%;" |  
|-
| . A. Higher education and training
| 5
|  
|-
| .. I. Quality of education
| 25%
|  
|-
| .... 1.01 Quality of the education system
| 33%
| WEF
|-
| .... 1.02 Quality of math and science education
| 33%
| WEF
|-
| .... 1.03 Quality of management schools
| 33%
| WEF
|-
| .. II. On-the-job training
| 75
|  
|-
| .... 2.01 Local availability of specialized training services
| 10%
| WEF
|-
| .... 2.02 Extent of staff training
| 10%
| WEF
|-
| .... 2.03 Training and education fisheries
| 30%
| Survey
|-
| .... 2.04 Training and education fish processing
| 30%
| Survey
|-
| .... 2.05 Training and education aquaculture
| 30%
| Survey
|-
| . B. Goods market efficiency
| 10%
|  
|-
| .. I. Competition
| 67%
|  
|-
| ... 3. Domestic competition
| 50%
|  
|-
| .... 3.01 Intensity of local competition
| 5%
| WEF
|-
| .... 3.02 Extent of market dominance
| 5%
| WEF
|-
| .... 3.03 Effect of taxation on incentives to invest
| 8%
| WEF
|-
| .... 3.04 Total tax rate
| 8%
| WEF
|-
| .... 3.05 Competition for fishing rights (quota)
| 15%
| Survey
|-
| .... 3.06 Market for fresh fish - fisheries
| 15%
| Survey
|-
| .... 3.07 Market for fresh fish - fish processing
| 15%
| Survey
|-
| .... 3.08 Competition between marketing/distributors - marketing
| 15%
| Survey
|-
| .... 3.09 Competition between companies that market and distribute seafood products
| 15%
| Survey
|-
| ... 4. Foreign competition
| 50%
|  
|-
| .... 4.01 Prevalence of non-tariff barriers
| 15%
| WEF
|-
| .... 4.02 Trade-weighted average tariff rate
| 15%
| WEF
|-
| .... 4.03 Current markets - free trade agreements
| 45%
| Survey
|-
| .... 4.04 Potential markets - free trade agreements
| 25%
| Survey
|-
| .. II. Quality of demand conditions
| 33%
|  
|-
| .... 5.01 Degree of customer orientation
| 10%
| WEF
|-
| .... 5.02 Buyer sophistication
| 10%
| WEF
|-
| .... 5.03 Product development - fish processing
| 40%
| Survey
|-
| .... 5.04 Product development - aquaculture processing
| 40%
| Survey
|-
| . C. Labour market efficiency
| 10%
|  
|-
| .. I. Flexibillity
| 25%
|  
|-
| .... 6.01 Flexibility of wage determination
| 33%
| WEF
|-
| .... 6.02 Hiring and firing practices
| 33%
| WEF
|-
| .... 6.03 Effect of taxation on incentives to work
| 33%
| WEF
|-
| .. II. Efficient use of talent
| 25%
|  
|-
| .... 7.01 Pay and productivity
| 10%
| WEF
|-
| .... 7.02 Reliance on professional management
| 10%
| WEF
|-
| .... 7.03 Productivity of fishermen
| 30%
| Data
|-
| .... 7.04 Wage system fisheries
| 30%
| Survey
|-
| .... 7.05 Productivity of employees fish processing
| 30%
| Data
|-
| .... 7.06 Wage system fish processing
| 30%
| Survey
|-
| .... 7.07 Productivity of labor aquaculture
| 30%
| Data
|-
| .... 7.08 Labour skills and productivity - aquaculture
| 30%
| Survey
|-
| .. III. Supply of labour
| 25%
|  
|-
| .... 8.01 Supply of qualified officers
| 20%
| Survey
|-
| .... 8.02 Supply of skilled fishermen
| 20%
| Survey
|-
| .... 8.03 Supply middle management fish processing
| 20%
| Survey
|-
| .... 8.04 Supply of skilled labour fish processing
| 20%
| Survey
|-
| .... 8.05 Supply middle management aquaculture
| 20%
| Survey
|-
| .... 8.06 Supply of skilled labour aquaculture
| 20%
| Survey
|-
| .. IV. Cost of labour
| 25%
|  
|-
| .... 9.01 Labour cost fisheries
| 50%
| Data
|-
| .... 9.02 Labour cost fish processing
| 50%
| Data
|-
| . D. Fisheries specific inputs
| 15%
|  
|-
| .. I. Property rights
| 20%
|  
|-
| .... 10.01 Permanency of fisheries rights.
| 50%
| Survey
|-
| .... 10.02 Transfers of fishing rights between firms
| 50%
| Survey
|-
| .. II. Capacity utilization
| 20%
|  
|-
| .... 11.01 Transfers of fishing rights between vessels
| 25%
| Survey
|-
| .... 11.02 Impact of quota system on capacity utilisation
| 25%
| Survey
|-
| .... 11.03 Stability of catch for the 5 most important species.
| 25%
| Data
|-
| .... 11.04 Impact of authorities on investment decisions
| 25%
| Survey
|-
| .. III. Cost items
| 30%
|  
|-
| .... 12.01 Special taxation fishing
| 50%
| Data
|-
| .... 12.02 Oil price
| 50%
| Data
|-
| .. IV. Profitability
| 30%
|  
|-
| .... 13.01 Profit margin
| 35%
| Data
|-
| .... 13.02 Capital turnover
| 20%
| Data
|-
| .... 13.03 Financial strength
| 15%
| Data
|-
| .... 13.04 Ability to use economies of scale
| 20%
| Survey
|-
| .... 13.05 Ability to use economies of scope
| 10%
| Survey
|-
| . E. Fish processing specific inputs
| 15%
|  
|-
| .. I. Capacity utilization
| 20%
|  
|-
| .... 14.01 Distribution of the catch within the year
| 50%
| Data
|-
| .... 14.02 Timing of wetfish availability
| 50%
| Survey
|-
| .. II. Cost items
| 30%
|  
|-
| .... 15.01 Cost of electricity
| 50%
| Data
|-
| .... 15.02 Supply and cost of fresh water - fish processing
| 50%
| Survey
|-
| .. III. Profitability
| 30%
|  
|-
| .... 16.01 Profit margin
| 35%
| Data
|-
| .... 16.02 Capital turnover
| 20%
| Data
|-
| .... 16.03 Financial strength
| 15%
| Data
|-
| .... 16.04 Ability to use economies of scale
| 20%
| Survey
|-
| .... 16.05 Ability to use economies of scope
| 10%
| Survey
|-
| . F. Aquaculture specific inputs
| 15%
|  
|-
| .. I. Property rights
| 20%
|  
|-
| .... 17.01 Transfers of licenses between firms - aquaculture
| 100%
| Survey
|-
| .. II. Capacity utilization
| 20%
|  
|-
| .... 18.01 Impact of regulations on capacity utilisation - aquaculture
| 100%
| Survey
|-
| .. III. Cost items
| 30%
|  
|-
| .... 19.01 Cost of electricity - aquaculture
| 15%
| Data
|-
| .... 19.02 Supply and cost of seedstocks
| 30%
| Survey
|-
| .... 19.03 Supply and cost of feed
| 55%
| Survey
|-
| .. IV. Profitability
| 30%
|  
|-
| .... 20.01 Profit margin
| 35%
| Data
|-
| .... 20.02 Capital turnover
| 20%
| Data
|-
| .... 20.03 Financial strength
| 15%
| Data
|-
| .... 20.04 Ability to use economies of scale
| 20%
| Survey
|-
| .... 20.05 Ability to use economies of scope
| 10%
| Survey
|-
| . G. Financial market development
| 5%
|  
|-
| .. I. Efficiency
| 100%
|  
|-
| .... 21.01 Financial services meeting business needs
| 33%
| WEF
|-
| .... 21.02 Financing through local equity market
| 33%
| WEF
|-
| .... 21.03 Ease of access to loans
| 33%
| WEF
|-
| . H. Technological readiness
| 15%
|  
|-
| .. I. Technological adoption
| 10%
|  
|-
| .... 22.01 Availability of latest technologies
| 50%
| WEF
|-
| .... 22.02 Firm-level technology absorption
| 50%
| WEF
|-
| .. II. Fisheries technology
| 30%
|  
|-
| .... 23.01 Technical level of vessels and mechnical equipment
| 33%
| Survey
|-
| .... 23.02 Fishing technology
| 33%
| Survey
|-
| .... 23.03 Processing technology on board
| 33%
| Survey
|-
| .. III. Fish processing technology
| 30%
|  
|-
| .... 24.01 General technology - fish processing
| 100%
| Survey
|-
| .. IV. Aquaculture technology
| 30%
|  
|-
| .... 25.01 General technology - aquaculture
| 100%
| Survey
|-
| . I. Market size
| 10%
|  
|-
| .. I. Domestic market size
| 50%
|  
|-
| .... 26.01 Domestic market size index
| 100%
| WEF
|-
| .. II. Foreign market size
| 50%
|  
|-
| .... 27.01 Foreign market size index
| 100%
| WEF
|}

 

The structure of the second pillar, efficiency enhancers, is similarly shown in Tables 2. This is a much more complex pillar than the first one, with nine subsections and 88 indicators. While some of the subsections here refer to areas mostly within the reach of government, such as higher education and training, other subsections deal with areas over which the firm themselves have more control, such as the access to and utilisation of inputs. Table 2 shows higher education and training, goods market efficiency and labour market efficiency, specific inputs used in fisheries, fish processing and aquaculture, financial market development, technological readiness and market size.

The structure of pillar III – innovation and business sophistication – is far simpler than that of the other two pillars. Here there are only two subsections, business sophistication and R&D innovation. There are 16 indicators within the former subsection and 10 within the latter. Most of these indicators refers to areas over which the firms have good control, but some are also related to areas there the government is more involved.

 

{|
|-
! Level
! Weight
! Source
|-
| style="width: 70%;" | 3rd pillar: Innovation and sophistication
| style="width: 15%;" | 20%
| style="width: 15%;" |  
|-
| . A. Business sophistication
| 50%
|  
|-
| .... 1.01 Local supplier quantity
| 3%
| WEF
|-
| .... 1.02 Local supplier quality
| 3%
| WEF
|-
| .... 1.03 State of cluster development
| 3%
| WEF
|-
| .... 1.04 Nature of competitive advantage
| 3%
| WEF
|-
| .... 1.05 Value chain breadth
| 3%
| WEF
|-
| .... 1.06 Control of international distribution
| 3%
| WEF
|-
| .... 1.07 Production process sophistication
| 3%
| WEF
|-
| .... 1.08 Extent of marketing
| 3%
| WEF
|-
| .... 1.09 Official marketing support - marketing
| 3%
| Survey
|-
| .... 1.10 Marketing operations - wild fisheries
| 11%
| Survey
|-
| .... 1.11 Marketing operations - aquaculture products
| 11%
| Survey
|-
| .... 1.12 Competition among major suppliers - fisheries
| 11%
| Survey
|-
| .... 1.13 Cooperation in the value chain - fisheries
| 11%
| Survey
|-
| .... 1.14 Cooperation in the value chain - fish processing
| 11%
| Survey
|-
| .... 1.15 Competition among major suppliers - fish processing
| 11%
| Survey
|-
| .... 1.16 Cooperation along the value chain - aquaculture
| 11%
| Survey
|-
| . B. R&D Innovation
| 50%
|  
|-
| .... 2.01 Capacity for innovation
| 8%
| WEF
|-
| .... 2.02 Quality of scientific research institutions
| 8%
| WEF
|-
| .... 2.03 Company spending on R&D
| 5%
| WEF
|-
| .... 2.04 University-industry collaboration in R&D
| 8%
| WEF
|-
| .... 2.05 Availability of scientists and engineers
| 8%
| WEF
|-
| .... 2.06 PCT patent applications
| 5%
| WEF
|-
| .... 2.07 R&D Fishing technology fisheries
| 15%
| Survey
|-
| .... 2.08 R&D Processing technology fisheries
| 15%
| Survey
|-
| .... 2.09 R&D Processing technology fish processing
| 15%
| Survey
|-
| .... 2.10 R&D - aquaculture equipment
| 15%
| Survey
|}

 

 

== Models ==

----

The concept of competitiveness can be traced back to early writing on economics in the 17th and 18th centuries, but has become ever more urgent in the last decades with rapid improvements in transport and communication and a higher level of globalisation. Although competitiveness may be measured by single indicators, such as productivity of labour, a deeper understanding of the competitive standing of firms and countries can be gained by employing multi-dimensional measurements. Currently, the Global Competitiveness Index (GCI), developed and compiled by the World Economic Forum, is probably the most comprehensive index of its kind. The choice of methods depends on a variety of factors, including the perceived need for complexity, data availability and how the results are to be used.

The Fisheries and Aquaculture Competitiveness Index (FACI) developed in this deliverable is modelled on the Fisheries Competitive Index (FCI) developed by the Directorate of Fresh Fish Prices in Iceland and the Norwegian College of Fishery Science at the University of Tromsø in 2004-2005. The FACI though expands on the FCI in two directions. First, by developing a national-level FACI that also includes aquaculture. Second, by designing a firm-level FACI that is intended to capture the views of operators of individual firms and is therefore less complex. The national-level FACI consists of 144 items, whereof 44 are taken from the WEF Global Competitiveness Index, 19 are based on data obtained from national, public sources and 81 are based on answers from a survey conducted among specialists in each country. Whereas the information taken from the GCI analyses the overall competitiveness of the nation, the other sources will throw light on the competitiveness of the fisheries and aquaculture sectors. The firm-level FACI is based on a survey which in the case of firms engaged in the harvesting, processing or marketing of wild capture fish consists of 40 questions, and in the case of aquaculture firms consists of 45 questions. In PrimeFish, a computerised decision support system (CPA) was developed that can be used by the industry and/or policymakers. The CPA is based on the FACI and a suit of simulation/forecasting models to be compiled in WP5 and developed as an operational web-based software tool. A computerised version of the FACI will therefore form a part of the PrimeDSS software.

The FACI was employed to analyse the competitiveness of three fisheries firms in Norway, one in Iceland and one in Newfoundland, and assess the competitive standing of Spain, Iceland, Norway and Vietnam. Newfoundland was also included in the national study, but the comparison is incomplete due to some gaps in the information collected. The firms in Newfoundland and Iceland were found to have a competitive edge over their Norwegian competitors, mostly due to their ability to fend of new entrants, flexible value-chains and high level of R&D development and innovation. At the national level, Iceland, Norway and Spain all ranked close to one another, with Vietnam at a competitive disadvantage. While some of the issues standing in the way of improved competitiveness can be traced to the general social issue facing firms, e.g. poor institutions and infrastructure, and can only be addressed through government, others lie within the realm of the firms, e.g. poor financial performance and inability to take advantage of economies-of-scale.

 

== Reports & Data ==

----

 

=== Firm-level FACI - Fisheries ===

As mentioned above, the firm-level FACI can both be applied to firms engaged in fisheries and aquaculture. This section only deals with the former, and compares results from one firm Iceland, one from Newfoundland and three Norwegian firms engaged in harvesting and processing of wild capture fish. Each firm’s scoring of individual indicators is presented in the table below:

''Questions and responses – firm level FACI – Threat of new entrants''

{| class="wikitable"
|-
! Theme
! Question
! Ice.1
! New1
! Nor1
! Nor2
! Nor3
|-
| style="width: 10%;" | Institutional barriers
| style="width: 65%;" | There are significant institutional barriers (f. ex. licenses, quotas, regulations) to entry in my industry (1=not at all; 7=make entry impossible)
| style="width: 5%;" | 7
| style="width: 5%;" | 7
| style="width: 5%;" | 3
| style="width: 5%;" | 5
| style="width: 5%;" | 7
|-
| Real capital barriers
| Entry into my industry requires investment in capital (vessels, equipment, buildings) that (1=does not deter entry at all; 7=deters entry completely)
| 5
| 7
| 4
| 4
| 5
|-
| Other investment barriers
| Entry into my industry requires other forms of investment (marketing, R&D, knowledge) that (1=does not deter entry at all; 7=deters entry completely)
| 5
| 6
| 4
| 3
| 6
|-
| Scale economics
| Does this type of production enjoy economies of scale (1=not at all; 7=to a huge degree)
| 7
| 6
| 5
| 6
| 2
|-
| Firm scale economics
| The firm takes advantage of its economies of scale (1=not at all; 7=completely)
| 7
| 6
| 5
| 5
| 1
|-
| Location
| The firm is well geographically located in terms of costs and ability to meet customer demand (1=not at all; 7=very well located)
| 4
| 5
| 5
| 3
| 7
|-
| Uncertainty
| How large uncertainty is there in your business environment? (1=none at all; 7=very great)
| 4
| 4
| 4
| 4
| 5
|-
| Labour availability
| High skilled labour in your company’s locations is (1=not readily available; 7=readily available)
| 6
| 2
| 6
| 6
| 6
|-
| Expert availability
| Qualified experts are (1=not readily available; 7=readily available)
| 6
| 6
| 2
| 3
| 5
|}

''Questions and responses – firm level FACI – Bargaining power of suppliers''

{| class="wikitable"
|-
! Theme
! Question
! Ice.1
! New1
! Nor1
! Nor2
! Nor3
|-
| style="width: 10%" | Supplier power
| style="width: 65%" | The bargaining power of suppliers is (1=weak; 7=strong)|
| style="width: 5%" | 5
| style="width: 5%" | 6
| style="width: 5%" | 5
| style="width: 5%" | 6
| style="width: 5%" | 4
|-
| Supplier competition
| Competition among the firm‘s major suppliers is (1=nonexistent; 7=fierce)
| 5
| 6
| 6
| 5
| 7
|-
| Quality raw material
| Quality of raw material is currently (1=poor; 7=excellent)
| 1
| 4
| 4
| 6
| 5
|-
| Quality and price
| How well do prices for raw materials reflect changes in Quality (1=not at all; 7=completely)
| 5
| 6
| 4
| 7
| 3
|-
| Quantity and price
| How well do prices for raw materials reflect changes in Quantity (1=not at all; 7=completely)
| 5
| 6
| 4
| 5
| 2
|-
| Timing and price
| How well do prices for raw materials reflect changes in Timing (1=not at all; 7=completely)
| 6
| 4
| 4
| 5
| 6
|-
| Access raw materials
| Compared to your most important competitors, your access to raw material is currently (1=very difficult; 7=very easy)
| 5
| 4
| 3
| 5
| 4
|-
| Supplier networks
| The firm has access to supplier networks (1=not at all; 7= very good access)
| 6
| 5
| 5
| 4
| 6
|}

''Questions and responses – firm level FACI – Bargaining power of buyers''

{| class="wikitable"
|-
! Theme
! Question
! Ice.1
! New1
! Nor1
! Nor2
! Nor3
|-
| style="width: 10%" | Product price sensitivity
| style="width: 65%" | My customers are sensitive to changes in product price (1=not at all; very much so)
| style="width: 5%" | 5
| style="width: 5%" | 7
| style="width: 5%" | 6
| style="width: 5%" | 6
| style="width: 5%" | 7
|-
| Brand value
| The brand of my product is valuable ?(1=not valuable at all; 7=immensely valuable)
| 4
| 6
| 4
| 5
| 5
|-
| Loyalty buyers
| The buyers of my product are loyal (1=not at all; 7=very much so)
| 7
| 7
| 3
| 4
| 5
|-
| Buyer power
| The bargaining power of buyers is (1=weak; 7=strong)
| 5
| 4
| 4
| 5
| 3
|-
| Quality and price
| How well do prices for your output reflect changes in Quality (1=not at all; 7=completely)
| 5
| 6
| 2
| 6
| 3
|-
| Quantity and price
| How well do prices for your output reflect changes in Quantity (1=not at all; 7=completely)
| 5
| 6
| 5
| 6
| 4
|-
| Timing and price
| How well do prices for your output reflect changes in Timing (1=not at all; 7=completely)
| 5
| 4
| 3
| 5
| 4
|-
| Diversification
| How diversified are the marketing options (does the firm depend on one buyer or many) (1=not at all; 7=very diversified)
| 6
| 5
| 5
| 4
| 6
|}

''Questions and responses – firm level FACI – Threat of substitute products or services''

{| class="wikitable"
|-
! Theme
! Question
! Ice.1
! New1
! Nor1
! Nor2
! Nor3
|-
| style="width: 10%" | Niche market
| style="width: 65%" | The firm is producing to a niche market (1=not all; 7=completely)
| style="width: 5%" | 4
| style="width: 5%" | 5
| style="width: 5%" | 2
| style="width: 5%" | 5
| style="width: 5%" | 4
|-
| Substitute availability
| There are substitutes to my products available in the market (1=not at all; 7=many substitutes exist)
| 5
| 5
| 5
| 4
| 3
|}

''Questions and responses – firm level FACI – Rivalry of existing competitors''

{| class="wikitable"
|-
! Theme
! Question
! Ice.1
! New1
! Nor1
! Nor2
! Nor3
|-
| style="width: 10%" | R&D collaboration
| style="width: 65%" | Research and development within the firm is done in close collaboration with technology firms (1=not at all; 7=completely)
| style="width: 5%" | 6
| style="width: 5%" | 4
| style="width: 5%" | 5
| style="width: 5%" | 1
| style="width: 5%" | 3
|-
| R&D importance
| How important is R&D for your operation and possibility to increase value added? (1=not important; 7=very important)
| 6
| 4
| 6
| 1
| 3
|-
| Innovation impact
| Innovation makes it possible for my firm to retain a competitive advantage (1=not at all; 7=highly)
| 6
| 6
| 5
| 3
| 3
|-
| Response market condition
| How capable is your part of the value chain of responding to changes in market conditions? (1=not capable; 7=very capable)
| 6
| 6
| 4
| 3
| 4
|-
| Value chain response
| How capable is your whole value chain of responding to changes in market conditions? (1=not capable; 7=very capable)
| 6
| 6
| 4
| 4
| 5
|-
| Importance audited labels
| How important are third-party audited labels to your operation (1=not important; 7=very important)
| 5
| 7
| 6
| 6
| 3
|-
| Competitive strategy
| The competitive strategy of my firm is (1=weak; 7=powerful)
| 6
| 5
| 5
| 4
| 3
|-
| Market share
| The market share of the firm is (1=less than 1%; 7=larger than 10%)
| 4
| 3
| 4
| 4
| 1
|-
| Cost leadership
| The firm is a cost leader (1=not at all; 7=very much so)
| 4
| 3
| 4
| 1
| 1
|-
| Technology sophistication
| How sophisticated is your production technology compared to best practice (1=not at all; 7=very sophisticated)
| 6
| 3
| 1
| 4
| 2
|-
| Production sites
| The firm has access to good sites for its production facilities (1=agree completely; 7=disagree completely)
| 6
| 5
| 5
| 4
| 6
|-
| Flexibility
| How much flexibility does your firm have in adapting to unpredictable events? (1=none at all; 7=complete flexibility)
| 4
| 3
| 5
| 3
| 4
|-
| Risk management
| To what extent does risk management and insurance protect against unpredictable negative shocks? (1=not at all; 7=completely)
| 5
| 5
| 2
| 4
| 3
|}

 

==== Total competitiveness ====

The scores for aggregated competitiveness for each of the sampled firms are presented in Figure 4. The Newfoundland and Icelandic firms receives scores of 5.2 and 5.1, while the Norwegian firms received considerably lower scores, or in the range 4.1-4.6.

[[File:Cpa figure4.png|Figure 4 Total competitiveness between sampled firms in the wildfish sector.]]
<div style="text-align: center;">''Figure 4 Total competitiveness between sampled firms in the wildfish sector''</div>
==== Competitive forces ====

By going one step beyond the total competitiveness score and looking at how the firms rank in terms of each competitive force, it is possible to gain a better insight into the firms’ competitive position. As shown in Figure 5, the Icelandic firm and the Newfoundland firm each score highest in two categories, with the difference between these two firms and the three Norwegian firms especially pronounced as regards the threat of new entrants and rivalry among competitors. The figure also reveals considerable differences between individual Norwegian firms.

[[File:Cpa figure5.png|Figure 5 First level of aggregation – firm level competitiveness.]]
<div style="text-align: center;">''Figure 5 First level of aggregation – firm level competitiveness''</div>
==== Individual indicators ====

Looking at the individual indicators for each competitive force can further illustrate differences and similarities among firms. In what follows the results are briefly discussed.

===== '''Threat of new entrants''' =====

Threat of new entrants is measured by nine individual indicators. Here the Icelandic and Newfoundland firms received the highest score. The survey reveals the existence of substantial barriers to entry, with the Icelandic firms in addition enjoying greater economies of scale and be able to take advantage of that position. The Newfoundland and Norwegian firms have a more advantageous location, but Newfoundland does not have as good access to qualified labour as the other four firms. Qualified experts are more readily available in Newfoundland and Iceland than in Norway.

[[File:Cpa figure6.png|center|Figure 6 Individual firm indicators – threat of new entrants.]]
<div style="text-align: center;">''Figure 6 Individual firm indicators – threat of new entrants.''</div>
 

===== '''Bargaining power of suppliers''' =====

Bargaining power of suppliers is measured through eight individual indicators. Here, one of the Norwegian firms performs much better than the firms in the survey (Figure 7). At the time of the survey, the quality of the raw material available to the Icelandic firm appears to have been very poor. Contrary to what could have been expected for a firm operating under an ITQ management system in fisheries, the relationship between price on the one hand and quality, quantity and timing is not as strong for the Icelandic firm as some of the Norwegian firms and the Newfoundland firm.

[[File:Cpa figure7.jpg|center|Figure 7 Individual firm indicators – bargaining power of suppliers.]]
<div style="text-align: center;">''Figure 7 Individual firm indicators – bargaining power of suppliers.''</div>
 

===== '''Bargaining power of buyers''' =====

The category bargaining power of buyers is measured through eight individual indicators. All the firms believe their buyers are quite sensitive to price changes, but do not regard their brand as particularly valuable (Figure 8). The customers of the Icelandic and Newfoundland firms are far more loyal but all firms rank the power of buyers as relatively similar. The firms have very different views on the relationship between output price and quality.

[[File:Cpa figure8.jpg|center|Figure 8 Individual firm indicators – bargaining power of buyers.]]
<div style="text-align: center;">''Figure 8 Individual firm indicators – bargaining power of buyers.''</div>
 

===== '''Threat of substitute products or services''' =====

The threat from substitutes is measured by two indicators. Both indicate the firms do have access to niche markets and that substitutes are available (Figure 9).

[[File:Cpa figure9.jpg|center|Figure 9 Individual firm indicators – threat of substitutes.]]
<div style="text-align: center;">''Figure 9 Individual firm indicators – threat of substitutes.''</div>
 

===== '''Rivalry among existing competitors''' =====

Rivalry among the existing firms is measured by 13 individual indicators (figure 10). Here the Icelandic firm performs better according to 10 of the indicators. According to the Icelandic firm, R&D collaboration is to a much higher degree conducted in close collaboration with technology firms, and R&D and innovation is regarded vital to maintain a competitive edge. The firm has also more sophisticated technology than its competitors. The Icelandic and Newfoundland value chains are also more flexible and better able to adjust to market condition.

[[File:Cpa figure10.jpg|center|Figure 10 Individual firm indicators – rivalry.]]
<div style="text-align: center;">''Figure 10 Individual firm indicators – rivalry.''</div>
[[File:Cpa figure11.jpg|center|Figure 11 Individual firm indicators – rivalry – last six indicators.]]
<div style="text-align: center;">''Figure 11 Individual firm indicators – rivalry – last six indicators.''</div>
 

=== National-level FACI ===

In the following sections the results from the competitiveness estimation are presented, first the aggregate scores, then the scores for each of the three main pillars (aggregation level 1) and then the score for the subsections within each pillar (aggregation level 2). All scoring is done using a seven step Likert scale. In some instances, data have not been available for certain countries. In particular, this applies to some of the hard data and most frequently for Newfoundland and Vietnam. When one indicator is missing, we have disregarded this from the calculation of the lowest aggregation level for the country in question. For Newfoundland, some themes had several indicators with missing data. Here we have not calculated aggregate level scoring, hence some tables have missing numbers for Newfoundland.

==== '''Aggregation level 1 and 2''' ====

The national-level FACI was applied to five countries; Norway, Iceland, Spain, Newfoundland and Vietnam. As Newfoundland-Labrador is not an independent country but one of the provinces that make up Canada, the WEF scores for Canada are used for Newfoundland. The hard data and survey is though only based on information from sources in Newfoundland. The data for Newfoundland has some gaps, but the data for the other four countries is almost complete. Because of this, no overall score is calculated for Newfoundland, but where possible scores are presented for individual pillars and subsections, as well as each indicator. Norway, Iceland and Spain all have a similar overall score of 4.8-4.9, while Vietnam gets a score of 3.9 (Table 5). The difference between the European countries and Vietnam is especially large in relation to pillar I, basic requirements, both as regards institutions and infrastructure. Norway and Iceland have a similar score for this first pillar, 4.9 and 5.0, with Spain receiving a score of 4.5. This is mostly due to the Nordic scores getting higher scores for their institutions, but Spain has better infrastructure. The European countries all receive similar scores for pillar II, Efficiency enhancers, and pillar III, Innovation and sophistication, with Vietnam lagging behind in both categories. Newfoundland ranks in between for innovation and sophistication, but due to the lack of data no overall score is calculated for Newfoundland for pillars I and II.

''Table 5 Total and first two category levels of competitiveness''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
|-
| style="width: 70%" | Total
| 4.8
| 4.9
| 4.8
|  
| 3.9
|-
| 1 Basic requirements
| 4.9
| 5.0
| 4.5
|  
| 3.5
|-
| 1.1 Institutions
| 5.2
| 5.1
| 4.3
|  
| 3.5
|-
| 1.2 Infrastructure
| 4.2
| 4.7
| 5.3
| 3.6
| 3.5
|-
| 2 Efficiency enhancers
| 4.8
| 4.8
| 4.9
|  
| 4,2
|-
| 2.1 Higher education and training
| 5.1
| 5.4
| 4.6
| 4.6
| 3.8
|-
| 2.2 Goods market efficiency
| 4.1
| 4.8
| 4.6
| 4.3
| 3.9
|-
| 2.3 Labour market efficiency
| 4.7
| 4.6
| 4.3
| 3,1
| 3,3
|-
| 2.4 Fisheries specific inputs
| 5.1
| 5.1
| 5.4
|  
| 4.9
|-
| 2.5 Fish processing specific inputs
| 4.1
| 5,8
| 5,0
| 2,3
| 3,6
|-
| 2.6 Aquaculture specific inputs
| 5.3
| 4,0
| 4.3
|  
| 4,1
|-
| 2.7 Financial market development
| 5.4
| 4.5
| 3.8
| 4.9
| 3.8
|-
| 2.8 Technological readiness
| 5.4
| 5.9
| 5.6
| 5.0
| 4.7
|-
| 2.9 Market size
| 4.6
| 2.7
| 5.6
| 5.6
| 5.2
|-
| 3 Innovation and sophistication
| 4.8
| 4.9
| 4.8
| 4.5
| 3.8
|-
| 3.1 Business sophistication
| 4.6
| 4.6
| 4.6
| 4.4
| 3.8
|-
| 3.2 R&D Innovation
| 4.9
| 5.2
| 5.1
| 4.7
| 3.7
|}

 

==== '''Pillar I Basic requirements''' ====

This section goes into detail on the two components of the first pillar – institutions and infrastructure. We first discuss the he institutions subsection consisting of sections on public institutions, fisheries management and aquaculture management. Subsequent sections discuss these areas again in more detail.Public institutions are much higher ranked in Norway and Iceland and Newfoundland than in Spain and Vietnam (Table 6). This is both due to stronger property rights in these countries and better public sector performance. Fisheries management scores highest in Iceland and Norway, but aquaculture management is considered better in Norway and Spain. Spain has the best infrastructure, followed by Iceland, Norway and Newfoundland and Vietnam having the lowest scores.

''Table 6 Basic requirements and two following aggregation levels of competitiveness''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
|-
| style="width: 70%" | 1 Basic requirements
| 4.9
| 5.0
| 4.5
|  
| 3.5
|-
| 1.1 Institutions
| 5.2
| 5.1
| 4.3
|  
| 3.5
|-
| 1.1.1 Public institutions
| 5.7
| 5.4
| 4.1
| 5.0
| 3.8
|-
| ........Property rights
| 6.2
| 5.8
| 4.7
| 5.4
| 4.0
|-
| ........Public sector performance
| 5.2
| 5.0
| 3.6
| 4.7
| 3.5
|-
| 1.1.2 Fisheries management
| 5.1
| 5.5
| 4.2
| 4.3
| 2.8
|-
| ........Stability
| 5.4
| 6.1
| 4.5
| 3.9
| 2.9
|-
| ........Research and advice
| 5.2
| 4.9
| 4.9
| 4.4
| 2.7
|-
| ........Monitoring and inspection
| 4.6
| 5.7
| 3.1
| 4.6
| 2.9
|-
| 1.1.3 Aquaculture management
| 4.7
| 4.3
| 4.6
|  
| 3.8
|-
| ........Stability
| 4.8
| 4.0
| 4.3
|  
| 4.2
|-
| ........Research and advice
| 4.6
| 4.6
| 4.8
|  
| 3.4
|-
| 1.2 Infrastructure
| 4.2
| 4.7
| 5.3
| 3.6
| 3.5
|-
| 1.2.1 Transport infrastructure
| 4.2
| 4.7
| 5.3
| 3.6
| 3.5
|}

 

===== '''Fisheries management''' =====

There is relatively large variation between the countries in the stability of fisheries management. It is considered very high in Iceland with Norway following with a score about 0,7 lower.Spain is almost a full point behind again and Newfoundland and Vietnam registering a significant lower stability (Table 7). Research and advice sees less variation between the European countries, with score slightly higher in Norway than in Iceland and Spain. Newfoundland and Vietnam again scores worst. Monitoring and inspection is best in Iceland, with Norway and Newfoundland receiving the same score. Spain and Vietnam have the lowest monitoring and inspection scores.

''Table 7 Fisheries management and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | '''1.1.2 Fisheries management'''
| 5.1
| 5.5
| 4.2
| 4.3
| 2.8
|  
|-
| ....Stability
| 5.4
| 6.1
| 4.5
| 3.9
| 2.9
|  
|-
| ''Transparency of fisheries management''
| 5.3
| 6.7
| 4.8
| 3.8
| 3.4
| Surv
|-
| ''Objectives of fisheries management''
| 5.2
| 5.8
| 3.9
| 3.6
| 3.3
| Surv
|-
| ''Stability of allocation of fishing rights''
| 5.7
| 5.8
| 4.8
| 4.2
| 2.0
| Surv
|-
| ....Research and advice
| 5.2
| 4.9
| 4.9
| 4.4
| 2.7
|  
|-
| ''Actual vs recommended fishing mortality''
| 6.2
| 2.2
| na
| na
| na
| Data
|-
| ''Extent of information gathered by research''
| 5.3
| 4.8
| 4.4
| 4.2
| 3.7
| Surv
|-
| ''Information gathering by marine research''
| 5.3
| 6.2
| 5.9
| 5.2
| 3.7
| Surv
|-
| ''Accuracy of forecasts by marine research''
| 4.9
| 5.4
| 4.8
| 4.8
| 2.8
| Surv
|-
| ''Impact of research on investments and operations''
| 4.3
| 5.8
| 4.6
| 3.4
| 3.4
| Surv
|-
| ....Monitoring and inspection
| 4.6
| 5.7
| 3.1
| 4.6
| 2.9
|  
|-
| ''Efficiency of management system''
| 5.9
| 6.1
| 4.3
| 3.6
| 2.6
| Surv
|-
| ''Illegal/excess catches''
| 3.4
| 5.2
| 2.0
| 5.5
| 3.1
| Surv
|}

 

===== '''Aquaculture management''' =====

Aquaculture is a major industry in Norway, Spain and Vietnam with Iceland being a relative newcomer. No data on aquaculture was available from Newfoundland. Stability is highest in Norway, with relatively small differences between the others. Norway’s leading position is due to generally higher scores on all the indicators. Apart from Vietnam, scoring the worst, there are relatively small differences between countries on in research and advice, but Spain in a slight lead (Table 8).

''Table 8 Aquaculture management and individual indicators''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 1.1.3 Aquaculture management
| 4.7
| 4.3
| 4.6
|  
| 3.8
|  
|-
| ....Stability
| 4.8
| 4.0
| 4.3
|  
| 4.2
|  
|-
| ''Transparency of aquaculture management''
| 4.9
| 4.6
| 4.3
|  
| 4.2
| Surv
|-
| ''Objectives of aquaculture management''
| 4.4
| 3.4
| 3.7
|  
| 4.2
| Surv
|-
| ''Stability of allocation of aquaculture licenses''
| 5.5
| 4.6
| 5.0
|  
| 4.8
| Surv
|-
| ''Efficiency of management - aquaculture''
| 4.5
| 3.5
| 4.3
|  
| 3.5
| Surv
|-
| ....Research and advice
| 4.6
| 4.6
| 4.8
|  
| 3.4
|  
|-
| ''Extent of information gathered by research''
| 4.6
| 4.6
| 4.8
|  
| 3.4
| Surv
|}

 

===== '''Infrastructure''' =====

Infrastructure in Spain appears to be far better than in any of the other four countries, not least because of relatively low transport costs (Table 9). Iceland and Spain receive similarly high scores for their communication systems. Norway in general scores wore than Spain for all indicators, but sees less costly transportation than Iceland. Both Newfoundland and Vietnam have poorer scores, with transportation costs and communication network needs scoring particularly badly for the former.

''Table 9 Fisheries management and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 1.2 Infrastructure
| 4.2
| 4.7
| 5.3
| 3.6
| 3.5
|  
|-
| ....Transport infrastructure
| 4.2
| 4.7
| 5.3
| 3.6
| 3.5
|  
|-
| ''Quality of overall infrastructure''
| 4.8
| 5.8
| 5.5
| 5.2
| 3.6
| WEF
|-
| ''Communication network needs''
| 3.8
| 5.6
| 5.3
| 3.0
| 3.5
| Surv
|-
| ''Communication network restrictions''
| 3.9
| 5.6
| 5.6
| 5.3
| 3.1
| Surv
|-
| ''Cost of domestic transportation''
| 4.0
| 3.2
| 5.3
| 2.3
| 3.5
| Surv
|-
| ''Cost of cross-border transportation''
| 4.4
| 3.6
| 4.6
| 2.3
| 3.8
| Surv
|}

 

==== '''Pillar II Efficiency enhancers''' ====

This pillar consists of a number of quite diverse subsections that measure the competitiveness of the country in terms of quality and efficiency of education, markets, inputs and technology. Norway, Iceland and Spain all receive a score of 4,8-4,9 for the pillar as a whole, but there are some important discrepancies (Table 10). Iceland receives the highest score for education and training, goods market efficiency, for inputs into harvesting and processing of wild capture fish, and technological readiness, but has an inefficient financial system and small markets. Norway has the best aquaculture sector while Spain, Newfoundland and Vietnam enjoy the largest markets.

''Table 10 Efficiency enhancers and two following aggregation levels of competitiveness''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
|-
| style="width: 65%" | 2 Efficiency enhancers
| 4.8
| 4.8
| 4.9
|  
| 4,2
|-
| 2.1 Higher education and training
| 5.1
| 5.4
| 4.6
| 4.6
| 3.8
|-
| 2.1.1 Quality of education
| 5.3
| 5.7
| 4.4
| 5.4
| 3.7
|-
| 2.1.2 On the job training
| 5.0
| 5.3
| 4.7
| 4.3
| 3.8
|-
| 2.2 Goods market efficiency
| 4.1
| 4.8
| 4.6
| 4.3
| 3.9
|-
| 2.2.1 Competition
| 4.1
| 5.0
| 4.6
| 4.3
| 4.2
|-
| ......''Domestic competition''
| 4.2
| 5.1
| 4.5
| 4.0
| 4.5
|-
| ......''Foreign competition''
| 4.1
| 4.9
| 4.6
| 4.6
| 3.9
|-
| 2.2.2 Quality of demand conditions
| 4.1
| 4.4
| 4.7
| 4.2
| 3.2
|-
| 2.3 Labour market efficiency
| 4.7
| 4.6
| 4.3
|  
| 3,3
|-
| 2.3.1 Flexibility
| 3.9
| 4.4
| 3.9
| 4.9
| 4.2
|-
| 2.3.2 Efficient use of talent
| 5,1
| 5,5
| 3.9
| 3,3
| 4,7
|-
| 2.3.3 Supply of labour
| 5.1
| 5.5
| 5.1
| 4.2
| 4.1
|-
| 2.3.4 Cost of labour
| 4.8
| 3.1
| 4.5
|  
|  
|-
| 2.4 Fisheries specific inputs
| 5.1
| 5.7
| 5.4
|  
| 4.9
|-
| 2.4.1 Property rights
| 5.4
| 6.2
| 5.4
| 2.8
| 6.1
|-
| 2.4.2 Capacity utilization
| 3.9
| 5.9
| 5,0
| 2.8
| 3,2
|-
| 2.4.3 Cost items
| 7.0
| 3.6
| 7.0
|  
| 7.0
|-
| 2.4.4 Profitability
| 3.8
| 5.2
| 4.2
| 2,2
| 3.1
|-
| 2.5 Fish processing specific inputs
| 4.1
| 5,8
| 5,0
|  
| 3,6
|-
| 2.5.1 Capacity utilization
| 2.9
| 4.0
| 5,5
| 2,5
| 3,8
|-
| 2.5.2 Cost items
| 5,3
| 6,8
| 5,7
| 4,3
| 3,7
|-
| 2.5.3 Profitability
| 3.7
| 5.9
| 3.9
|  
| 3.3
|-
| 2.6 Aquaculture specific inputs
| 5.3
| 4,0
| 4.3
|  
| 4,1
|-
| 2.6.1 Property rights
| 6.0
| 4.9
| 4.9
|  
| 1.3
|-
| 2.6.2 Capacity utilization
| 5.3
| 5.0
| 5.7
|  
| 4.8
|-
| 2.6.3 Cost items
| 4,6
| 5,1
| 4,6
|  
| 5,1
|-
| 2.6.4 Profitability
| 5.5
| 1.8
| 2.8
|  
| 4.6
|-
| 2.7 Financial market development
| 5.4
| 4.5
| 3.8
| 4.9
| 3.8
|-
| 2.7.1 Efficiency
| 5.4
| 4.5
| 3.8
| 4.9
| 3.8
|-
| 2.8 Technological readiness
| 5.4
| 5.9
| 5.6
| 5.0
| 4.7
|-
| 2.8.1 Technological adoption
| 6.3
| 6.2
| 5.1
| 5.7
| 4.3
|-
| 2.8.2 Fisheries technology
| 5.4
| 6.3
| 5.5
| 4.1
| 3.3
|-
| 2.8.3 Fish processing technology
| 4.1
| 6.6
| 5.9
| 4.5
| 5.0
|-
| 2.8.4 Aquaculture technology
| 6.3
| 4.6
| 5.4
| 6.0
| 5.8
|-
| 2.9 Market size
| 4.6
| 2.7
| 5.6
| 5.6
| 5.2
|-
| 2.9.1 Domestic market size
| 4.2
| 1.9
| 5.3
| 5.3
| 4.5
|-
| 2.9.2 Foreign market size
| 5.0
| 3.5
| 5.8
| 5.8
| 5.8
|}

 

===== '''Higher education and training''' =====

The category higher education and training consists of education and on-the-job training. Only the latter has indicators specific for the survey and is hence detailed in Table 11 below. Iceland scores slightly higher than Norway in this subsection, mainly because training and education in fish processing seems to be better in Iceland. Spain and Newfoundland have the same overall score. Vietnam appears to lag behind the other countries on all accounts. ''Table 11 On-the-job training and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.1 Higher education and training
| 5.1
| 5.4
| 4.6
| 4.6
| 3.8
|  
|-
| ....On the job training
| 5.0
| 5.3
| 4.7
| 4.3
| 3.8
|  
|-
| ''Local availability of specialized training services''
| 5.8
| 5.4
| 4.3
| 5.8
| 3.7
| WEF
|-
| ''Extent of staff training''
| 5.5
| 5.1
| 3.7
| 4.6
| 3.9
| WEF
|-
| ''Training and education fisheries''
| 4.6
| 5.4
| 5.1
| 3.8
| 3.8
| Surv
|-
| ''Training and education fish processing''
| 3.7
| 4.7
| 3.7
| 3.5
| 3.3
| Surv
|-
| ''Training and education aquaculture''
| 5.1
| 4.5
| 5.6
| 6.0
| 4.4
| Surv
|}

 

===== '''Goods market efficiency''' =====

Efficiency in the goods market appears to be quite similar in all five countries, although Iceland and Spain score higher than the other three countries (Table 12). Iceland enjoys a competitive advantage both as regards domestic and foreign competition. Taxes have a detrimental effect on competitiveness in Spain, while Vietnam suffers from lack of access to international markets due to tariffs and on-tariff barriers. The quality of demand conditions is best in Spain, but quite similar in Norway, Iceland and Newfoundland.

''Table 12 Goods market efficiency and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.2.1 Competition
| 4.1
| 5.0
| 4.6
| 4.3
| 4.2
|  
|-
| ....Domestic competition
| 4.2
| 5.1
| 4.5
| 4.0
| 4.5
|  
|-
| ''Intensity of local competition''
| 5.1
| 4.8
| 5.6
| 5.1
| 5.0
| WEF
|-
| ''Extent of market dominance''
| 4.7
| 3.8
| 4.1
| 5.4
| 3.6
| WEF
|-
| ''Effect of taxation on incentives to invest''
| 3.8
| 4.1
| 3.4
| 3.9
| 3.6
| WEF
|-
| ''Total tax rate''
| 3.5
| 4.1
| 2.2
| 5.7
| 3.5
| WEF
|-
| ''Competition for fishing rights (quota)''
| 3.8
| 5.3
| 4.3
| 1.8
| 2.0
| Survey
|-
| ''Market for fresh fish - fisheries''
| 5.1
| 6.3
| 4.5
| 3.0
| 5.4
| Survey
|-
| ''Market for fresh fish - fish processing''
| 2.4
| 5.0
| 4.8
| 3.8
| 5.2
| Survey
|-
| ''Competition between marketing/distributors - marketing''
| 5.2
| 4.7
| 5.5
| 5.7
| 5.4
| Survey
|-
| ''Competition between companies that market and distribute seafood products''
| 5.2
| 5.5
| 4.8
| 4.0
| 5.4
| Survey
|-
| ....Foreign competition
| 4.1
| 4.9
| 4.6
| 4.6
| 3.9
|  
|-
| ''Prevalence of non-tariff barriers''
| 4.6
| 4.3
| 4.5
| 4.5
| 3.9
| WEF
|-
| ''Trade-weighted average tariff rate''
| 5.2
| 5.3
| 4.0
| 5.3
| 2.3
| WEF
|-
| ''Current markets - free trade agreements''
| 4.3
| 5.4
| 4.8
| 4.5
| 4.6
| Surv
|-
| ''Potential markets - free trade agreements''
| 3.9
| 4.4
| 4.8
| 4.5
| 3.8
| Surv
|-
| 2.2.2 Quality of demand conditions
| 4.1
| 4.4
| 4.7
| 4.2
| 3.2
|  
|-
| ''Degree of customer orientation''
| 5.6
| 5.6
| 4.9
| 5.5
| 4.1
| WEF
|-
| ''Buyer sophistication''
| 4.6
| 4.1
| 3.3
| 4.4
| 3.5
| WEF
|-
| ''Product development - fish processing''
| 3.3
| 4.6
| 5.1
| 3.0
| 3.2
| Surv
|-
| ''Product development - aquaculture processing''
| 4.3
| 4.0
| 4.6
| 5.0
| 3.0
| Surv
|}

 

===== '''Labour market efficiency''' =====

Labour market efficiency is highest in Iceland and Norway, not least because of far higher productivity in harvesting and fish processing (Table 13). Supply of labour scores similarly in Iceland, Norway and Spain, but Newfoundland and Vietnam appear to be affected by the availability of good labour.

''Table 13 Labour market efficiency and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.3.2 Efficient use of talent
| 5,1
| 5,5
| 3.9
| 3,3
| 4,2
|  
|-
| ''Pay and productivity''
| 4.9
| 4.9
| 3.6
| 4.9
| 4.0
| WEF
|-
| ''Reliance on professional management''
| 6.2
| 5.5
| 4.7
| 5.8
| 3.6
| WEF
|-
| Productivity of fishermen
| 5.8
| 6.5
| 3.6
| na
| na
| Data
|-
| ''Wage system fisheries''
| 5.4
| 5.9
| 3.7
| 1.5
| 2.8
| Survey
|-
| Productivity of employees fish processing
| 3.9
| 5.8
| 2.7
| na
| na
| Data
|-
| ''Wage system fish processing''
| 4.1
| 4.9
| 3.3
| 1.7
| 6.0
| Survey
|-
| Productivity of labor aquaculture
| na
| na
| na
| na
| na
| Data
|-
| ''Labour skills and productivity - aquaculture''
| 5.8
| 4.7
| 5.8
| 5.5
| 6.0
| Survey
|-
| 2.3.3 Supply of labour
| 5.1
| 5.5
| 5.1
| 4.2
| 4.1
|  
|-
| Supply of qualified officers
| 5.0
| 6.0
| 4.1
| 4.0
| 3.2
| Survey
|-
| Supply of skilled fishermen
| 5.5
| 5.9
| 3.5
| 4.0
| 4.2
| Survey
|-
| Supply middle management fish processing
| 5.0
| 5.7
| 5.6
| 4.0
| 3.8
| Survey
|-
| Supply of skilled labour fish processing
| 4.1
| 5.2
| 5.5
| 3.0
| 4.0
| Survey
|-
| Supply middle management aquaculture
| 5.8
| 5.3
| 5.9
| 5.5
| 4.8
| Survey
|-
| Supply of skilled labour aquaculture
| 5.4
| 4.8
| 5.9
| 4.5
| 4.8
| Survey
|-
| 2.3.4 Cost of labour
| 4.8
| 3.1
| 4.5
| na
| na
|  
|-
| Labour cost fisheries
| 4.8
| 3.1
| 4.5
| na
| na
| Data
|-
| Labour cost fish processing
| na
| na
| na
| na
| na
| Data
|}

 

===== '''Fisheries specific inputs''' =====

The fisheries specific inputs score countries in terms of quality of the property rights in management, capacity utilisation, taxation and oil costs, and profitability. Iceland scores highly here, mainly because of the good quality of the property rights system employed in the harvesting sectors, high degree of capacity utilisation and profitability. However, taxation in the Icelandic fisheries erodes some of the competitive advantage. Newfoundland performs poorly in this subsection. ''Table 14 Fisheries specific inputs and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.4.1 Property rights
| 5.4
| 6.2
| 5.4
| 2.8
| 6.1
|  
|-
| ''Permanency of fisheries rights.''
| 5.8
| 5.9
| 3.8
| 1.8
| 6.2
| Survey
|-
| ''Transfers of fishing rights between firms''
| 5.0
| 6.4
| 7.0
| 3.8
| 6.0
| Survey
|-
| 2.4.2 Capacity utilization
| 3.9
| 5.9
| 3.8
| 2.8
| 3,2
|  
|-
| ''Transfers of fishing rights between vessels''
| 4.0
| 6.5
| 7.0
| 3.0
| 5.5
| Survey
|-
| ''Impact of quota system on capacity utilisation''
| 4.5
| 6.3
| 4.0
| 2.0
| 1.7
| Survey
|-
| ''Stability of catch for the 5 most important species.''
| 3.2
| 4.6
| na
| na
| 3.2
| Data
|-
| ''Impact of authorities on investment decisions''
| 4.1
| 6.1
| 4.0
| 3.3
| 2.4
| Survey
|-
| 2.4.2 Cost items
| 7.0
| 3.6
| 7.0
| na
| 7.0
|  
|-
| ''Special taxation fishing''
| 7.0
| 3.6
| 7.0
| na
| 7.0
| Data
|-
| ''Oil price''
| na
| na
| na
| na
| na
| Data
|-
| 2.4.3 Profitability
| 3.8
| 5.2
| 4.2
| 2,2
| 3.1
|  
|-
| ''Profit margin''
| 4.7
| 5.2
| 4.1
| na
| 2.0
| Data
|-
| Capital turnover
| 2.2
| 5.5
| 3.7
| na;
| 1.3
| Data
|-
| ''Financial strength''
| 2.9
| 4.3
| 6.3
| na
| 4.6
| Data
|-
| ''Ability to use economies of scale''
| 4.1
| 5.2
| 3.7
| 2.0
| 5.0
| Survey
|-
| ''Ability to use economies of scope''
| 4.3
| 6.1
| 3.8
| 2.7
| 5.0
| Survey
|}

 

===== '''Fish processing specific inputs''' =====

All the countries have rather low scores for fish processing specific inputs. Capacity utilisation is particularly low in Newfoundland and Vietnam, but also poor in Norway and Spain. Iceland has very strong supply and cost of fresh water, with Spain and Norway following and Newfoundland and Vietnam having relatively worse scores, impacting negatively on the country’s competitiveness (Table 15). The Icelandic fish processing sectors financially outperforms the industry in the other four countries with data on this topic. ''Table 15 Fish processing specific inputs and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.5.1 Capacity utilization
| 2.9
| 4.0
| 5,5
| 2,5
| 3,8
|  
|-
| ''Distribution of the catch within the year''
| 3.3
| 2.2
| na
| na
| na
| Data
|-
| ''Timing of wetfish availability''
| 2.5
| 5.9
| 5.5
| 2.5
| 3.8
| Survey
|-
| 2.5.2 Cost items
| 5,3
| 6,8
| 5,7
| 4,3
| 3,7
|  
|-
| ''Cost of electricity''
| na
| na
| na
| na
| na
| Data
|-
| ''Supply and cost of fresh water - fish processing''
| 5.3
| 6.8
| 5.7
| 4.3
| 3.7
| Survey
|-
| 2.5.3 Profitability
| 3.7
| 5.9
| 3.9
| na
| 3.3
|  
|-
| ''Profit margin''
| 3.5
| 5.8
| 3.8
| na
| 3.5
| Data
|-
| ''Capital turnover''
| 3.0
| 6.5
| 3.0
| na
| 1.2
| Data
|-
| ''Financial strength''
| 5.0
| 5.5
| 5.5
| na
| 5.7
| Data
|-
| ''Ability to use economies of scale''
| 4.1
| 5.7
| 5.3
| 1.5
| 5.0
| Survey
|-
| ''Ability to use economies of scope''
| 4.3
| 5.9
| 5.5
| 2.3
| 5.0
| Survey
|}

 

===== '''Aquaculture specific inputs''' =====

As expected, Norway has a clear competitive advantage in aquaculture. The country scores highly in terms of transferability of licenses between firms, costs and profitability, but the impact of regulations on capacity utilisation has a better impact on competitiveness in Spain (Table 16). ''Table 16 Aquaculture specific inputs and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.6.1 Property rights
| 6.0
| 4.9
| 4.9
| na
| 1.3
|  
|-
| ''Transfers of licenses between firms''
| 6.0
| 4.9
| 4.9
| na
| 1.3
| Survey
|-
| 2.6.2 Capacity utilization
| 5.3
| 5.0
| 5.7
| na
| 4.8
|  
|-
| ''Impact of regulations on capacity utilization''
| 5.3
| 5.0
| 5.7
| na
| 4.8
| Survey
|-
| 2.6.2 Cost items
| 4,6
| 5,1
| 4,6
| 5,7
| 5,1
|  
|-
| Cost of electricity
| na
| na
| na
| na
| na
| Data
|-
| ''Supply and cost of seedstocks''
| 4.7
| 5.0
| 4.4
| 6.0
| 3.8
| Survey
|-
| ''Supply and cost of feed''
| 4.6
| 5.1
| 4.6
| 5.5
| 5.8
| Survey
|-
| 2.6.3 Profitability
| 5.5
| 1.8
| 2.8
| na
| 4.6
|  
|-
| ''Profit margin''
| 6.2
| 1.2
| 1.7
| na
| 3.7
| Data
|-
| ''Capital turnover''
| 3.8
| 2.9
| 1.9
| na
| 6.7
| Data
|-
| Financial strength
| 6.2
| na
| 6.5
| na
| 4.0
| Data
|-
| ''Ability to use economies of scale''
| 5.3
| 4.5
| 3.3
| 5.0
| 5.3
| Survey
|-
| ''Ability to use economies of scope''
| 4.8
| 4.9
| 3.5
| 5.0
| 5.3
| Survey
|}

 

===== '''Technological readiness''' =====

The level of technology in the harvesting and fish processing sectors is considerably higher in Iceland than in the other four countries, but Norway, Newfoundland and Vietnam all receive high scores for the technology employed in the aquaculture sector (Table 17).

''Table 17 Technological readiness and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.8.2 Fisheries technology
| 5.4
| 6.3
| 5.5
| 4.1
| 3.3
|  
|-
| ''Technical level of vessels and mechnical equipment''
| 6.0
| 6.4
| 5.6
| 5.3
| 3.5
| Survey
|-
| Fishing technology
| 5.4
| 5.9
| 5.7
| 4.1
| 3.5
| Survey
|-
| Processing technology on board
| 4.8
| 6.6
| 5.3
| 3.0
| 3.0
| Survey
|-
| 2.8.3 Fish processing technology
| 4.1
| 6.6
| 5.9
| 4.5
| 5.0
|  
|-
| ''General technology - fish processing''
| 4.1
| 6.6
| 5.9
| 4.5
| 5.0
| Survey
|-
| 2.8.4 Aquaculture technology
| 6.3
| 4.6
| 5.4
| 6.0
| 5.8
|  
|-
| ''General technology - aquaculture''
| 6.3
| 4.6
| 5.4
| 6.0
| 5.8
| Survey
|}

 

==== '''Pillar III Innovation and sophistication''' ====

This pillar consists of two subsections on business sophistication and R&D innovations. Vietnam received the lowest scores fin both categories (Table 18).

''Table 18 Business sophistication and two following aggregation levels of competitiveness''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
|-
| style="width: 65%" | 3 Innovation and sophistication
| 4.8
| 4.9
| 4.8
| 4.5
| 3.8
|-
| 3.1 Business sophistication
| 4.6
| 4.6
| 4.6
| 4.4
| 3.8
|-
| 3.2 R&D Innovation
| 4.9
| 5.2
| 5.1
| 4.7
| 3.7
|}

 

===== '''Business sophistication''' =====

The level of business sophistication is similar in all the countries except Vietnam (Table 19). Norway is the only country where the industry receives official marketing support.

''Table 19 Business sophistication and individual indicators, average score''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 3.1 Business sophistication
| 4.6
| 4.6
| 4.6
| 4.4
| 3.8
|  
|-
| ''Official marketing support - marketing''
| 5.0
| 1.0
| 1.0
| 1.0
| 1.0
| Survey
|-
| ''Marketing operations - wild fisheries''
| 4.9
| 4.3
| 5.9
| 5.3
| 4.0
| Survey
|-
| ''Marketing operations - aquaculture products''
| 5.2
| 4.4
| 4.7
| 6.5
| 3.8
| Survey
|-
| ''Competition among major suppliers - fisheries''
| 4.9
| 4.3
| 4.1
| 4.2
| 5.3
| Survey
|-
| ''Cooperation in the value chain - fisheries''
| 3.1
| 5.4
| 4.2
| 3.5
| 3.3
| Survey
|-
| ''Cooperation in the value chain - fish processing''
| 3.1
| 5.3
| 4.9
| 2.7
| 3.2
| Survey
|-
| ''Competition among major suppliers - fish processing''
| 4.6
| 4.3
| 4.1
| 3.5
| 4.3
| Survey
|-
| ''Cooperation along the value chain - aquaculture''
| 5.6
| 4.6
| 4.8
| 4.5
| 3.4
| Survey
|}

 

===== '''R&D Innovation''' =====

Iceland and Spain have a slight edge in R&D innovation, with Norway and Newfoundland receiving slightly lower scores and Vietnam some distance behind (Table 20).

''Table 20 R&D innovation and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 3.2 R&D Innovation
| 4.9
| 5.2
| 5.1
| 4.7
| 3.7
|  
|-
| ''R&D Fishing technology fisheries''
| 4.6
| 5.6
| 6.1
| 4.4
| 3.5
| Survey
|-
| ''R&D Processing technology fisheries''
| 3.9
| 6.2
| 6.2
| 4.0
| 4.3
| Survey
|-
| ''R&D Processing technology fish processing''
| 4.5
| 6.0
| 5.8
| 4.0
| 4.0
| Survey
|-
| ''R&D - aquaculture equipment''
| 5.9
| 3.8
| 5.3
| 6.0
| 4.4
| Survey
|}

 

== References & Readings ==

----

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DeCourcy J. 2007. Research Joint Ventures and International Competitiveness: Evidence from the National Cooperative Research Act. Economics of Innovation and New Technology 16(1), 51–65.

Dollar D., Wolff N.E. 1993. Competitiveness, Convergence and International Specialization. The MIT Press, Cambridge.

Durand M., Giorno C., 1987. Indicators of International Competitiveness: Conceptual Aspects and Evaluation. OECD Economic Studies 9, 147–182.

Esty D.C., Porter M.E. 2002. Ranking National Environmental Regulation and Performance: A Leading Indicator of Future Competitiveness? In: M.E. Porter, J.D. Sachs, P.K. Cornelius, J.W. McArthur, K. Schwab (Eds). The Global Competitiveness Report 2001–2002. Oxford University Press, Oxford, 78–101. Available at [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.476.4940&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.476.4940&rep=rep1&type=pdf].

Fagerberg J. 1988. International Competitiveness. The Economic Journal 98(391), 355–374.

Heckscher, E. 1919 ‘‘The Effect of Foreign Trade on the Distribution of Income.’’ Ekonomisk Tidskrift, 21: 497–512. T

IMD. 1994. The World Competitiveness Yearbook.

Jaffe A.B., Palmer K. 1997. Environmental Regulation and Innovation: A Panel Data Study. The Review of Economics and Statistics 79(4), 610–619.

Jorgenson D.W., Kuroda M. 1992. Productivity and International Competitiveness in Japan and the United States, 1960-1985. In: B.G. Hickman (Ed.). International Productivity and Competitiveness. Oxford University Press, New York.

Kaldor N. 1978. The Effect of Devaluations on Trade in Manufactures. In: Further Essays on Applied Economics. Duckworth, London, 99–118.

Krugman P. 1990. The Age of Diminished Expectations. The MIT Press, Cambridge, Mass. Krugman P. 1994. Competitiveness: A Dangerous Obsession. Foreign Affairs 73(2), 28–44.

Lanoie P., Laurent-Lucchetti J., Johnstone N., Ambec S. 2011. Environmental Policy, Innovation and Performance: New Insights on the Porter Hypothesis. Journal of Economics and Management Strategy 20(3), 803–842.

Leiter A.M., Parolini A., Winner H. 2009. Environmental Regulation and Investment: Evidence from European Industries. Working Papers 4, Faculty of Economics and Statistics, University of Innsbruck. Available at [https://www.econstor.eu/bitstream/10419/73552/1/742566919.pdf https://www.econstor.eu/bitstream/10419/73552/1/742566919.pdf].

Lipschitz L., McDonald D. 1991. Real Exchange Rates and Competitiveness: A Clarifi cation of Concepts and Some Measurements for Europe. IMF Working Paper, March.

List, F. 1841 [1909]. The National System of Political Economy. Longmans, Green, and Co., London. Markusen J.R. 1992. Productivity, Competitiveness, Trade Performance and Real Income: The Nexus Among Four Concepts. Economic Council of Canada, Ottawa, Canada.

von Mises, L. 1940 [1998]. Human Action: A Treatise on Economics. The Scholar’s Edition. Ludwig von Mises Institute, Auburn, Alabama.

Mulatu A., Florax R., Withagen C., 2004. Environmental Regulation and International Trade. Tinbergen Institute Discussion Paper 20/3. Available at [https://www.econstor.eu/bitstream/10419/86286/1/04-020.pdf https://www.econstor.eu/bitstream/10419/86286/1/04-020.pdf].

Mun, T. 1664 [1885]. England´s Treasure by Forreign Trade. Macmillan and Co., New York.

Neef A. 1992. An International Comparison of Manufacturing Productivity and Unit Labor Cost Trends. In: B.G. Hickman (Ed.). International Productivity and Competitiveness. Oxford University Press, New York, 137–157.

Ohlin, B. 1933. Interregional and International Trade. Harvard Economic Studies. Vol. XXXIX. Harvard University Press, Cambridge, Mass.

Peterson S. 2003. The EU Emission Trading Scheme and its Competitiveness Effects for European Business: Results from the CGE Model DART. Kiel Institute for World Economics. Available at [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.544.6341&rep=rep1&type=pdf http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.544.6341&rep=rep1&type=pdf].

Porter, M.E. 1990. The Competitive Advantage of Nations. The Free Press, New York.

Porter, M.E. 1998. On Competition. Harvard Business School Press, Boston.

Porter, M.E. 2008. How Competitive Forces Shape Strategy. Harvard Business Review, 86(1), 25-40.

Ricardo, T. 1817 [1972]. The Principles of Political Economy and Taxation. J.M. Dent & Sons Ltd., London.

Schwab K., Sala-i-Martin X. 2013. The Global Competitiveness Report 2013–2014. World Economic Forum, Geneva. Available at [http://www3.weforum.org/docs/WEF_GlobalCompetitivenessReport_2013-14.pdf http://www3.weforum.org/docs/WEF_GlobalCompetitivenessReport_2013-14.pdf].

Schumpeter, J. A. 1911 [2008]. The Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest and the Business Cycle. Transaction Publishers, New Brunswick, New Jersey.

Sharpe A., Banerjee M. 2008. Assessing Canada’s Ability to Compete for Foreign Direct Investment. Centre for the Study of Living Standards, Ottawa, Ontario. Available at [http://www.csls.ca/reports/csls2008-4.pdf http://www.csls.ca/reports/csls2008-4.pdf].

Siggel E., Cockburn J. 1995. International Competitiveness and its Sources: A Method of Development Policy Analysis. Discussion Paper 9517, Concordia University Department of Economics.

Smith A. 1776 [1904]. An Inquiry into the Nature and Causes of the Wealth of Nations. Methuen & Co., Ltd., London.

Swan T.W. 1956. Economic Growth and Capital Accumulation. Economic Record 32(2), 334–361.

Turner A., Golub S.S. 1997. Towards a System of Unit Labor Cost-Based Competitiveness Indicators for Advanced, Developing and Transition Countries. Staff Studies for the World Economic Outlook, IMF. Available at [https://www.imf.org/external/pubs/ft/wp/wp97151.pdf https://www.imf.org/external/pubs/ft/wp/wp97151.pdf].

Weber, M. 1947. The Theory of Social and Economic Organisation. Translated by A.M. Henderson and Talcott Parsons. The Free Press, Glencoe, Ill.

World Economic Forum. 2016. The Global Competitiveness Report 2016-2017. Available at [https://www.weforum.org/reports/the-global-competitiveness-report-2016-2017-1 https://www.weforum.org/reports/the-global-competitiveness-report-2016-2017-1].

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WP5

2018-10-24T11:43:24Z

Jacandrade:

= Work Package 5: Prediction models =

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== General information ==

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=== DEVELOPMENT OF SIMULATION AND PREDICTION TOOLS ===

In WP5 simulation models are developed to analyse how changes in supply and demand affect production planning, economic performance, supply chain relationships, value added, potential product success, market trends and developments and thus competitiveness as measured by the updated FACI developed in WP1. Simulations of “boom and bust” cycles will be carried out and common traits highlighted that facilitate the development of prediction models. Building on work undertaken in WP4, a set of product success indicators will be established designed to indicate probability of successful launches on a targeted seafood market. The outcome of this WP will be simulation/forecasting models for analysing changes in competitiveness, prediction of instability of demand and supply including that of warning signs for “boom and bust” cycles and for indication of potential for product innovation success (SO5).

== Deliverables ==

=== [[Deliverable_5.1|D5.1 -Developing Innovative Market Orientated Prediction Toolbox to Strengthen the Economic Sustainability and Competitiveness of European Seafood on Local and Global markets]] ===

The concept of competitiveness can be traced back to early writing on economics in the 17th and 18th centuries, but has become ever more urgent in the last decades with rapid improvements in transport and communication and a higher level of globalisation. Although competitiveness may be measured by single indicators, such as productivity of labour, a deeper understanding of the competitive standing of firms and countries can be gained by employing multi-dimensional measurements. Currently, the Global Competitiveness Index (GCI), developed and compiled by the World Economic Forum, is probably the most comprehensive index of its kind. The choice of methods depends on a variety of factors, including the perceived need for complexity, data availability and how the results are to be used. (Click title to read more)

 

== Links & Resources ==

----

*[http://www.primefish.eu/work-package-5-prediction-models More] information on Work Package 1.
*Main project [http://www.primefish.eu website]
*[http://primefish.eu/project#WP5 WP5 Consortium]

WP5

2018-10-24T11:42:38Z

Jacandrade: Created page with "= Work Package 5: Prediction models= ---- ---- == General information == ---- === DEVELOPMENT OF SIMULATION AND PREDICTION TOOLS === In WP5 simulation models are devel..."

= Work Package 5: Prediction models=

----

----

== General information ==

----

=== DEVELOPMENT OF SIMULATION AND PREDICTION TOOLS ===

In WP5 simulation models are developed to analyse how changes in supply and demand affect production planning, economic performance, supply chain relationships, value added, potential product success, market trends and developments and thus competitiveness as measured by the updated FACI developed in WP1. Simulations of “boom and bust” cycles will be carried out and common traits highlighted that facilitate the development of prediction models. Building on work undertaken in WP4, a set of product success indicators will be established designed to indicate probability of successful launches on a targeted seafood market. The outcome of this WP will be simulation/forecasting models for analysing changes in competitiveness, prediction of instability of demand and supply including that of warning signs for “boom and bust” cycles and for indication of potential for product innovation success (SO5).

== Deliverables ==

=== [[Deliverable_5.1|D5.1 -Developing Innovative Market Orientated Prediction Toolbox to Strengthen the Economic Sustainability and Competitiveness of European Seafood on Local and Global markets ]] ===

The concept of competitiveness can be traced back to early writing on economics in the 17th and 18th centuries, but has become ever more urgent in the last decades with rapid improvements in transport and communication and a higher level of globalisation. Although competitiveness may be measured by single indicators, such as productivity of labour, a deeper understanding of the competitive standing of firms and countries can be gained by employing multi-dimensional measurements. Currently, the Global Competitiveness Index (GCI), developed and compiled by the World Economic Forum, is probably the most comprehensive index of its kind. The choice of methods depends on a variety of factors, including the perceived need for complexity, data availability and how the results are to be used. (Click title to read more)

== Links & Resources ==

----

*[http://www.primefish.eu/work-package-5-prediction-models More] information on Work Package 1.
*Main project [http://www.primefish.eu website]
*[http://primefish.eu/project#WP1 WP1 Consortium]

File:Cpa tool 4.png

2018-10-19T09:58:31Z

Jacandrade: Jacandrade uploaded a new version of File:Cpa tool 4.png

CPA results page - National-level

File:Cpa tool 3.png

2018-10-19T09:58:00Z

Jacandrade: Jacandrade uploaded a new version of File:Cpa tool 3.png

CPA results page - Firm-level

File:Cpa tool 1.png

2018-10-19T09:57:22Z

Jacandrade: Jacandrade uploaded a new version of File:Cpa tool 1.png

CPA landing page

File:Cpa tool 2.png

2018-10-19T09:56:27Z

Jacandrade: Jacandrade uploaded a new version of File:Cpa tool 2.png

CPA survey page

CPA

2018-10-19T09:45:50Z

Jacandrade:

= Competitive Position Analyser =

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== Introduction ==

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The Competitive Position Analyser tool is the computerised version of the FACI survey and it is the implementation of the models described in this page. The concept of competitiveness can be traced back to early writing on economics in the 17th and 18th centuries, but has become ever more urgent in the last decades with rapid improvements in transport and communication and a higher level of globalisation. Although competitiveness may be measured by single indicators, such as productivity of labour, a deeper understanding of the competitive standing of firms and countries can be gained by employing multi-dimensional measurements.

The choice of methods depends on a variety of factors, including the perceived need for complexity, data availability and how the results are to be used. The Fisheries and Aquaculture Competitiveness Index (FACI) developed in this deliverable is modelled on the Fisheries Competitive Index (FCI) developed by the Directorate of Fresh Fish Prices in Iceland and the Norwegian College of Fishery Science at the University of Tromsø in 2004-2005. The FACI though expands on the FCI in two directions. First, by developing a national-level FACI that also includes aquaculture. Second, by designing a firm-level FACI that is intended to capture the views of operators of individual firms and is therefore less complex. The national-level FACI consists of 144 items, whereof 44 are taken from the WEF Global Competitiveness Index, 19 are based on data obtained from national, public sources and 81 are based on answers from a survey conducted among specialists in each country. . Whereas the information taken from the GCI analyses the overall competitiveness of the nation, the other sources will throw light on the competitiveness of the fisheries and aquaculture sectors. The firm-level FACI is based on a survey which in the case of firms engaged in the harvesting, processing or marketing of wild capture fish consists of 40 questions, and in the case of aquaculture firms consists of 45 questions.

The FACI was employed to analyse the competitiveness of three fisheries firms in Norway, one in Iceland and one in Newfoundland, and assess the competitive standing of Spain, Iceland, Norway and Vietnam. Newfoundland was also included in the national study, but the comparison is incomplete due to some gaps in the information collected. The firms in Newfoundland and Iceland were found to have a competitive edge over their Norwegian competitors, mostly due to their ability to fend of new entrants, flexible value-chains and high level of R&D development and innovation. At the national level, Iceland, Norway and Spain all ranked close .

 

== Methods ==

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Currently, the Global Competitiveness Index (GCI) is probably the most comprehensive index of its kind. The index defines competitiveness as the set of institutions, policies and factors that determine the level of productivity of a country. The most recent analysis covers 138 countries, with a combined output representing 98% of the world GDP. The index, which is compiled annually by the World Economic Forum, combines 114 indicators that capture concepts that matter for productivity and long-term prosperity. As shown in the [[#cpi_structure|figure ]] below, these indicators are grouped into 12 pillars: institutions, infrastructure, macroeconomic environment, health and primary education, higher education and training, goods market efficiency, labour market efficiency, financial market development, technological readiness, market size, business sophistication, and innovation. These pillars are in turn organised into three sub-indexes: basic requirements, efficiency enhancers, and innovation and sophistication factors. The three sub-indexes are given different weights in the calculation of the overall Index, depending on each economy’s stage of development, as proxied by its GDP per capita and the share of exports represented by raw materials.

[[File:Cpi structure.jpg|The structure of the Global Competitiveness Index. Source: WEF 2016.]]

=== Fisheries and Aquaculture Competitiveness Index (FACI) - Firm Level ===

As outlined above, competitiveness can be measured in a number of ways, using both simple and more complex analytical tools. The choice of methods depends on a variety of factors, including the perceived need for complexity, data availability and how the results are to be used.

he FACI must be flexible enough to meet the needs of the two different end-users; industry and policymakers. With this in mind it was decided to develop two different kinds of competitiveness indexes; a firm-level FACI and a national-level FACI. The firm-level FACI is only intended to capture the views of operators of individual firms and therefore less complex. It is based on a survey which in the case of firms engaged in the harvesting, processing or marketing of wild capture fish consists of 40 questions, and in the case of aquaculture firms consists of 45 questions. The firms are able to access the [http://dss.primefish.eu/index.php/cpa firm-level FACI], complete the survey and then compare their answers to those provided by other operators. The degree of comparison will, of course, depend on the number of firms using the PrimeDSS, but provided the number of users is large enough, it would be possible to undertake comparison between firms in the same sectors both in the same country as well as between countries, as well as between different sectors. By thus benchmarking themselves against others, firms could gain a better understanding of their competitive standing.

The national-level FACI is modelled on the Fisheries Competitive Index (FCI) developed by the Directorate of Fresh Fish Prices in Iceland and the Norwegian College of Fishery Science at the University of Tromsø in 2004-2005 (Verðlagsstofa skiptaverðs, 2005). The FCI consists of 139 questions and observations which are split between six sub-indexes that make it possible to calculate scores both for the FCI as a whole as well as for individual sub-indexes. This further expands the use of the FCI. The index was applied to the Icelandic and Norwegian fish industries. The national-level FACI consists of 144 items, whereof 44 are taken from the WEF Global Competitiveness Index, 19 are based on data obtained from national, public sources and 81 are based on answers from a survey conducted among specialists in each country. Whereas the information taken from the GCI analyses the overall competitiveness of the nation, the other sources will throw light on the competitiveness of the fisheries and aquaculture sectors. The national-level FACI will therefore yield a comprehensive measure of competitiveness which takes both into account general conditions in the country as well as those that deal specifically with the sectors of interest.

According to Porter (1998, 2008), the nature of competition is embodied in five competitive forces; (1) the threat of new entrants, (2) the threat of substitute products or services, (3) the bargaining power of suppliers, (4) the bargaining power of buyers, and (5) the rivalry among the existing competitors. As shown in the [[#firmlevel-faci|figure]] below, these forces do interact with each other. Their strength may also vary but together they determine long-term industry profitability.

[[File:FirmLevelFaci.jpg|The five competitive forces that determine industry competition. Source: Porter (1998).]]

The threat of entry puts a cap on the profit potential of an industry. When the threat is high, incumbents must keep prices low or increase production capacity to deter new competitors. Within each industry there are usually some entry barriers that deter new firms from entering the market, and give the incumbents some advantages. These may include economies of scale, network effects, customer switching costs, capital requirements, unequal access to distribution channels, restrictive government policy, expected retaliation of incumbents, and some other advantages not related to size, such as favourable geographic locations, and established brand identities.

The power of suppliers varies between industries, but in general a supplier is more powerful if is more concentrated than the industry it sells to, the supplier group does not depend heavily on the industry it is selling to, the firms face switching costs for changing suppliers and the products offered by suppliers are somewhat differentiated.

Buyers can capture more value by forcing down prices, demanding better quality or improved service, and play industry partners against each other. Analogous to suppliers, buyers have more leverage if they are few and large, the industry’s products are similar so that there are ample substitution possibilities, and there are low switching costs.

A high threat of substitutes will reduce profitability by placing a ceiling on prices. A firm can, however, distance itself from others through product performance, marking or other means. High rivalry among existing competitors will reduce the profitability of the firms in an industry. The rivalry can take many forms, including price discounting, new product innovations, advertising campaigns and service and quality improvements. Rivalry will be especially high in cases where there are many competitors and no clear industry leader, industry growth is slow and exit barriers are high. Although some market/firm/industry characteristics may be regarded as only belonging to one specific force category, other characteristics could plausible be classified in two or more different ways. Thus, the value of an output brand could impact on the bargaining power of buyers, threats of substitutes and rivalry among existing competitors. The firm-level FACI builds heavily on the theories of Porter (1998), taking into considerations all five aspects of competition outlined above. As stated earlier, this index is mostly intended for operators of fisheries and aquaculture firms who wish to analyse the competitive standing of their firm. The index consists of 40 questions – 45 in the case of aquaculture – that together yield a solid measure of competitiveness. This deliverable yields the results of a survey that was put to firm operators, but once the PrimeDSS becomes operational it will be possible to access a computerised version of the firm-level FACI, complete the survey online and then obtain a measure of the competitiveness of the firm, both by analysing the data and comparing the competitive standing of the firm to that of other firms. Each questions uses a seven-level Likert scale. Nine of the survey questions refer to the category threat of new entrants. They are as follows

*Institutional barriers (f. ex. licenses, quotas, regulations, location restrictions, water treatment)
*Investment barriers in capital (vessels, equipment, buildings)
*Other form of barriers (marketing, R&D, knowledge)
*Economies-of-scale in production
*Utilisation of economies-of-scale
*Geographical location
*Level of uncertainty in business environment
*Local availability of highly skilled labour
*Availability of qualified experts

The first three items all refer to concrete barrier to entry, such as licenses, quotas, investment, and R&D. The next two refer to the existence and utilisation of economies-of-scale, but companies that produce at a large scale enjoy a cost advantages that new entrants may have difficulties in matching. Geographical location refers to the fact that some firms are well located in terms of cost and ability to meet customer demand. An uncertain business environment may make entry less attractive, and the availability of skilled employees will certainly impact on the threat of entry. The bargaining power of suppliers is analysed on the basis of the following eight questions for fisheries firms (10 for aquaculture firms):

*Bargaining power of suppliers
*Competition among the major suppliers (fisheries)
*Current quality of raw material (fisheries)
*Ability of prices for raw material to reflect changes in (fisheries)
*Quantity
*Quality
*Timing
*Ability of prices for seed to reflect changes in (aquaculture)
*Quantity
*Quality
*Timing
*Ability of prices for feed to reflect changes in (aquaculture)
*Quantity
*Quality
*Timing
*Comparative access to raw material (fisheries)
*Comparative access to seed (aquaculture)
*Comparative access to feed (aquaculture)
*Access to supplier networks

The term “raw material” refers to landings of catch sourced by processors. Catches are by far the most important input for firms engaged in processing and marketing of wild capture fish, while for aquaculture firms the most important inputs are seed and feed. The interest here is in how well prices for these inputs reflect changes in quantity, quality and timing. The term “comparative access” refers to how firms regards their access to inputs (raw material, feed, seed) compared to their competitors. The bargaining power of suppliers is also assessed using a direct question on that issue. The bargaining power of buyers is analysed in terms of eight characteristics:

*Customers´ sensitivity to changes in product price
*Value of brand
*Loyal buyers
*Bargaining power of buyers
*Ability of output prices to reflect changes in
*Quantity
*Quality
*Timing
*Diversification of marketing options

Good brand value and loyal buyers will combine to make customers rather insensitive to changes in product prices. The survey also has questions on how firms view the price sensitivity of product prices, i.e. whether the firms regard their product price inelastic or elastic, as well as whether the bargaining power of buyers is weak or strong. Diversification of marketing options refers to whether the firm depends on a single buyer for its product or many buyers. The bargaining power of buyers may also be affected by how well output prices reflect changes in quantity, quality and timing of sale

The bargaining power of buyers is very closely linked to the threat of substitute products or services. Some of the items listed under the bargaining power of buyers, such as customers’ sensitivity to price changes, brand value and consumer loyalty, could just as easily have been listed under substitutes. Here, only two items are classified in this category, namely:

*Production to a niche market
*Availability of substitutes

Customers in niche markets are often willing to pay a premium price for a product that well satisfies their needs. These markets are often characterised by a strong brand and consumer loyalty. The two survey questions here refer to whether the firm is producing to a niche market, and whether substitutes to the product are available in the market. Most of the survey questions in the firm-level FACI are here grouped under the heading “rivalry among existing competitors”. However, many of these items could equally well have been categorised differently. These questions are on the following topics:

*R&D collaboration with technology firms
*Importance of R&D for operation and possibility to increase value added
*Importance of innovation for competitive advantage
*Ability of firm’s part of the value chain to respond to changes in market conditions
*Ability of the whole value chain to respond to changes in market conditions
*Importance of third-party audited labels
*Strength of competitive strategy
*Market share of firm
*Level of cost leadership
*Sophistication of production technology compared to best practice
*Quality of sites for production facilities
*Flexibility to adapt to unpredictable events
*Ability of risk management and insurance to protect against unpredictable negative shocks
*Comparative seed costs (aquaculture)
*Comparative feed costs (aquaculture)
*Comparative production losses due to diseases or other causes (aquaculture)

The first three questions refer to R&D and innovation activities within the firm, to which degree they are done in close collaboration with high-tech firms, and how important they are for increased value added and competitive advantage. Flexibility of the value chain – both as regards the firm itself and the whole value chain – is also important for firms facing competition. Third-party labelling has become very important in the food industry, not least for fisheries and aquaculture. Labelling may open access to markets and also indicate sustainable and environmental friendly production. The market share of firms is important, as is the level of cost leadership. Firms are also asked to indicate how sophisticated their production facilities are compared to their competitors, and assess the quality of the sites used for their production facilities. Two questions refer to the ability of the firms to adjust to unpredictable events, and three questions focus on the costs of feed and seed relative to the firm’s competitors, and comparative production losses due to fish diseases and other causes.

The firm-level FAC yields both an overall score as well as a score for each of the five competitive forces where the former is calculated as the simple average of the other five scores.

=== National-level FACI ===

The national-level FACI is a comprehensive measure that includes both factors influencing each country’s overall competitiveness as well as factors that specifically relate to the fisheries and aquaculture sectors. Most of the indicators related to overall competitiveness are taken from the Global Competitiveness Index, published by the World Economic Forum (2016), but information on the other, more specific indicators was obtained through surveys and from public data collection agencies.

The national-level FACI consists of three pillars; (I) basic requirements, (II) efficiency enhancers, and (III) innovation and sophistication. In contrast to the firm-level FACI, the national-level FACI yields a weighted overall score for each country, as well as a weighted score for each pillar and the sub-indexes contain therein. Basic requirements weigh 30% of the total score, efficiency enhancers 50% and innovation and sophistication 20%.

[[File:NationalLevelFaci.jpg|center|Overall structure of the national-level FACI.]]

The first pillar – basic requirements – comprises elements that are essential if firms are to thrive in a competitive, international world. As noted by Acemoglu and Robinson (2012), economic prosperity depends above all on the inclusiveness of economic and political institutions, where inclusiveness is defined as the situation where a large number of people have a say in political decision-making. By contrast, extractive institutions allow a certain elite to rule over and exploit others, thus preventing firms from enjoying competition on a level playing field. As shown in Table 1, there are two subsections within the first pillar, institutions and infrastructure. Institutions are then further subdivided into public institutions and management of fisheries and aquaculture. Public institutions are then finally divided into property rights and public sector performance. There is just one indicator for property rights, namely property rights, but within public sector performance there are three indicators. Well defined and secure property rights are essential for any market-based activity, as are well functioning courts and legal system that make it easy for firms to challenge government actions and/or regulations. Transparent government policy making is also important. The burden of government regulation must however not become too great. For firms operating within the fisheries and aquaculture sectors, it is also important how well these activities are managed by policy makers.

''Table 1 Structure of the first pillar, Basic requirements.''

{|
|-
! Level
! Weight
! Source
|-
! scope="row" style="width: 70%;" | 1st pillar: Basic requirements
| style="width: 15%;" | 30%
| style="width: 15%;" |  
|-
! scope="row" | . A. Institutions
| 75%
|  
|-
| .. I. Public institutions
| 33%
|  
|-
| ... 1. Property rights
| 50%
|  
|-
| .... 1.01 Property rights
| 100%
| WEF
|-
| ... 2. Public sector performance
| 50%
|  
|-
| .... 2.01 Burden of government regulation
| 33%
| WEF
|-
| .... 2.02 Efficiency of legal framework in challenging regulations
| 33%
| WEF
|-
| .... 2.03 Transparency of government policy making
| 33%
| WEF
|-
| .. II. Fisheries management
| 33%
|  
|-
| ... 3. Stability
| 33%
|  
|-
| .... 3.01 Transparency of fisheries management
| 33%
| Survey
|-
| .... 3.02 Objectives of fisheries management
| 33%
| Survey
|-
| .... 3.03 Stability of the allocation of fishing rights
| 33%
| Survey
|-
| ... 4. Research and advice
| 33%
|  
|-
| .... 4.01 Actual vs recommended fishing mortality
| 20%
| Data
|-
| .... 4.02 Extent of information gathering by marine research
| 20%
| Survey
|-
| .... 4.03 Information gathering by marine research
| 20%
| Survey
|-
| .... 4.04 Accuracy of forecasts of marine research
| 20%
| Survey
|-
| .... 4.05 Impact of marine research on investments and operation
| 20%
| Survey
|-
| ... 5. Monitoring and inspection
| 33%
|  
|-
| .... 5.01 Efficiency of the management system
| 50%
| Survey
|-
| .... 5.02 Illegal/excess catches
| 50%
| Survey
|-
| .. III. Aquaculture management
| 33%
|  
|-
| ... 6. Stability
| 50%
|  
|-
| .... 6.01 Transparency of aquaculture management
| 25%
| Survey
|-
| .... 6.02 Objectives of aquaculture management
| 25%
| Survey
|-
| .... 6.03 Stability of the allocation of the aquaculture licenses
| 25%
| Survey
|-
| .... 6.04 Efficiency of management - aquaculture
| 25%
| Survey
|-
| ... 7. Research and advice
| 50%
|  
|-
| .... 7.01 Extent of information gathering by research for aquaculture
| 100%
| Survey
|-
! scope="row" | . B. Infrastructure
| 25%
|  
|-
| .. I. Transport infrastructure
| 100%
|  
|-
| .... 8.01 Quality of overall infrastructure
| 20%
| WEF
|-
| .... 8.02 Communication network needs
| 20%
| Survey
|-
| .... 8.03 Communication network restrictions
| 20%
| Survey
|-
| .... 8.04 Cost of domestic transportation
| 20%
| Survey
|-
| .... 8.05
| Cost of cross-border transportation
| 20%
| Survey
|}

 

Table 1 also shows the weighing structure of the FACI. As noted above, the first pillar, Basic requirements, carries a weight of 30%, with institutions thereof weighing 75% and infrastructure weighing 25%. Within institutions, public institutions weigh 33%, fisheries management 33% and aquaculture management 33%. Within public institutions, property rights weigh and public sector performance each weigh 50%. Finally, each of the three indicators of public sector performance weighs 33%. The weight of each section and indicators is shown in the second-last column of Table 1, while the sources are shown in the last column of the table. WEF refers to the 2016-2017 Global Competitiveness Index carried out by the World Economic Forum, data refers to data collected from official sources, and survey refers to the survey carried out among experts in each country.

''Table 2 Structure of the second pillar, Efficiency enhancers. Subsections A-C.''

{|
|-
! Level
! Weight
! Source
|-
! scope="row" style="width: 70%;" | 2nd pillar: Efficiency enhancers
| style="width: 15%;" | 50%
| style="width: 15%;" |  
|-
! scope="row" | . A. Higher education and training
| 5
|  
|-
| .. I. Quality of education
| 25%
|  
|-
| .... 1.01 Quality of the education system
| 33%
| WEF
|-
| .... 1.02 Quality of math and science education
| 33%
| WEF
|-
| .... 1.03 Quality of management schools
| 33%
| WEF
|-
| .. II. On-the-job training
| 75
|  
|-
| .... 2.01 Local availability of specialized training services
| 10%
| WEF
|-
| .... 2.02 Extent of staff training
| 10%
| WEF
|-
| .... 2.03 Training and education fisheries
| 30%
| Survey
|-
| .... 2.04 Training and education fish processing
| 30%
| Survey
|-
| .... 2.05 Training and education aquaculture
| 30%
| Survey
|-
! scope="row" | . B. Goods market efficiency
| 10%
|  
|-
| .. I. Competition
| 67%
|  
|-
| ... 3. Domestic competition
| 50%
|  
|-
| .... 3.01 Intensity of local competition
| 5%
| WEF
|-
| .... 3.02 Extent of market dominance
| 5%
| WEF
|-
| .... 3.03 Effect of taxation on incentives to invest
| 8%
| WEF
|-
| .... 3.04 Total tax rate
| 8%
| WEF
|-
| .... 3.05 Competition for fishing rights (quota)
| 15%
| Survey
|-
| .... 3.06 Market for fresh fish - fisheries
| 15%
| Survey
|-
| .... 3.07 Market for fresh fish - fish processing
| 15%
| Survey
|-
| .... 3.08 Competition between marketing/distributors - marketing
| 15%
| Survey
|-
| .... 3.09 Competition between companies that market and distribute seafood products
| 15%
| Survey
|-
| ... 4. Foreign competition
| 50%
|  
|-
| .... 4.01 Prevalence of non-tariff barriers
| 15%
| WEF
|-
| .... 4.02 Trade-weighted average tariff rate
| 15%
| WEF
|-
| .... 4.03 Current markets - free trade agreements
| 45%
| Survey
|-
| .... 4.04 Potential markets - free trade agreements
| 25%
| Survey
|-
| .. II. Quality of demand conditions
| 33%
|  
|-
| .... 5.01 Degree of customer orientation
| 10%
| WEF
|-
| .... 5.02 Buyer sophistication
| 10%
| WEF
|-
| .... 5.03 Product development - fish processing
| 40%
| Survey
|-
| .... 5.04 Product development - aquaculture processing
| 40%
| Survey
|-
! scope="row" | . C. Labour market efficiency
| 10%
|  
|-
| .. I. Flexibillity
| 25%
|  
|-
| .... 6.01 Flexibility of wage determination
| 33%
| WEF
|-
| .... 6.02 Hiring and firing practices
| 33%
| WEF
|-
| .... 6.03 Effect of taxation on incentives to work
| 33%
| WEF
|-
| .. II. Efficient use of talent
| 25%
|  
|-
| .... 7.01 Pay and productivity
| 10%
| WEF
|-
| .... 7.02 Reliance on professional management
| 10%
| WEF
|-
| .... 7.03 Productivity of fishermen
| 30%
| Data
|-
| .... 7.04 Wage system fisheries
| 30%
| Survey
|-
| .... 7.05 Productivity of employees fish processing
| 30%
| Data
|-
| .... 7.06 Wage system fish processing
| 30%
| Survey
|-
| .... 7.07 Productivity of labor aquaculture
| 30%
| Data
|-
| .... 7.08 Labour skills and productivity - aquaculture
| 30%
| Survey
|-
| .. III. Supply of labour
| 25%
|  
|-
| .... 8.01 Supply of qualified officers
| 20%
| Survey
|-
| .... 8.02 Supply of skilled fishermen
| 20%
| Survey
|-
| .... 8.03 Supply middle management fish processing
| 20%
| Survey
|-
| .... 8.04 Supply of skilled labour fish processing
| 20%
| Survey
|-
| .... 8.05 Supply middle management aquaculture
| 20%
| Survey
|-
| .... 8.06 Supply of skilled labour aquaculture
| 20%
| Survey
|-
| .. IV. Cost of labour
| 25%
|  
|-
| .... 9.01 Labour cost fisheries
| 50%
| Data
|-
| .... 9.02 Labour cost fish processing
| 50%
| Data
|-
! scope="row" | . D. Fisheries specific inputs
| 15%
|  
|-
| .. I. Property rights
| 20%
|  
|-
| .... 10.01 Permanency of fisheries rights.
| 50%
| Survey
|-
| .... 10.02 Transfers of fishing rights between firms
| 50%
| Survey
|-
| .. II. Capacity utilization
| 20%
|  
|-
| .... 11.01 Transfers of fishing rights between vessels
| 25%
| Survey
|-
| .... 11.02 Impact of quota system on capacity utilisation
| 25%
| Survey
|-
| .... 11.03 Stability of catch for the 5 most important species.
| 25%
| Data
|-
| .... 11.04 Impact of authorities on investment decisions
| 25%
| Survey
|-
| .. III. Cost items
| 30%
|  
|-
| .... 12.01 Special taxation fishing
| 50%
| Data
|-
| .... 12.02 Oil price
| 50%
| Data
|-
| .. IV. Profitability
| 30%
|  
|-
| .... 13.01 Profit margin
| 35%
| Data
|-
| .... 13.02 Capital turnover
| 20%
| Data
|-
| .... 13.03 Financial strength
| 15%
| Data
|-
| .... 13.04 Ability to use economies of scale
| 20%
| Survey
|-
| .... 13.05 Ability to use economies of scope
| 10%
| Survey
|-
! scope="row" | . E. Fish processing specific inputs
| 15%
|  
|-
| .. I. Capacity utilization
| 20%
|  
|-
| .... 14.01 Distribution of the catch within the year
| 50%
| Data
|-
| .... 14.02 Timing of wetfish availability
| 50%
| Survey
|-
| .. II. Cost items
| 30%
|  
|-
| .... 15.01 Cost of electricity
| 50%
| Data
|-
| .... 15.02 Supply and cost of fresh water - fish processing
| 50%
| Survey
|-
| .. III. Profitability
| 30%
|  
|-
| .... 16.01 Profit margin
| 35%
| Data
|-
| .... 16.02 Capital turnover
| 20%
| Data
|-
| .... 16.03 Financial strength
| 15%
| Data
|-
| .... 16.04 Ability to use economies of scale
| 20%
| Survey
|-
| .... 16.05 Ability to use economies of scope
| 10%
| Survey
|-
! scope="row" | . F. Aquaculture specific inputs
| 15%
|  
|-
| .. I. Property rights
| 20%
|  
|-
| .... 17.01 Transfers of licenses between firms - aquaculture
| 100%
| Survey
|-
| .. II. Capacity utilization
| 20%
|  
|-
| .... 18.01 Impact of regulations on capacity utilisation - aquaculture
| 100%
| Survey
|-
| .. III. Cost items
| 30%
|  
|-
| .... 19.01 Cost of electricity - aquaculture
| 15%
| Data
|-
| .... 19.02 Supply and cost of seedstocks
| 30%
| Survey
|-
| .... 19.03 Supply and cost of feed
| 55%
| Survey
|-
| .. IV. Profitability
| 30%
|  
|-
| .... 20.01 Profit margin
| 35%
| Data
|-
| .... 20.02 Capital turnover
| 20%
| Data
|-
| .... 20.03 Financial strength
| 15%
| Data
|-
| .... 20.04 Ability to use economies of scale
| 20%
| Survey
|-
| .... 20.05 Ability to use economies of scope
| 10%
| Survey
|-
! scope="row" | . G. Financial market development
| 5%
|  
|-
| .. I. Efficiency
| 100%
|  
|-
| .... 21.01 Financial services meeting business needs
| 33%
| WEF
|-
| .... 21.02 Financing through local equity market
| 33%
| WEF
|-
| .... 21.03 Ease of access to loans
| 33%
| WEF
|-
! scope="row" | . H. Technological readiness
| 15%
|  
|-
! scope="row" | .. I. Technological adoption
| 10%
|  
|-
| .... 22.01 Availability of latest technologies
| 50%
| WEF
|-
| .... 22.02 Firm-level technology absorption
| 50%
| WEF
|-
| .. II. Fisheries technology
| 30%
|  
|-
| .... 23.01 Technical level of vessels and mechnical equipment
| 33%
| Survey
|-
| .... 23.02 Fishing technology
| 33%
| Survey
|-
| .... 23.03 Processing technology on board
| 33%
| Survey
|-
| .. III. Fish processing technology
| 30%
|  
|-
| .... 24.01 General technology - fish processing
| 100%
| Survey
|-
| .. IV. Aquaculture technology
| 30%
|  
|-
| .... 25.01 General technology - aquaculture
| 100%
| Survey
|-
| . I. Market size
| 10%
|  
|-
| .. I. Domestic market size
| 50%
|  
|-
| .... 26.01 Domestic market size index
| 100%
| WEF
|-
| .. II. Foreign market size
| 50%
|  
|-
| .... 27.01 Foreign market size index
| 100%
| WEF
|}

 

The structure of the second pillar, efficiency enhancers, is similarly shown in Tables 2. This is a much more complex pillar than the first one, with nine subsections and 88 indicators. While some of the subsections here refer to areas mostly within the reach of government, such as higher education and training, other subsections deal with areas over which the firm themselves have more control, such as the access to and utilisation of inputs. Table 2 shows higher education and training, goods market efficiency and labour market efficiency, specific inputs used in fisheries, fish processing and aquaculture, financial market development, technological readiness and market size.

The structure of pillar III – innovation and business sophistication – is far simpler than that of the other two pillars. Here there are only two subsections, business sophistication and R&D innovation. There are 16 indicators within the former subsection and 10 within the latter. Most of these indicators refers to areas over which the firms have good control, but some are also related to areas there the government is more involved.

 

{|
|-
! Level
! Weight
! Source
|-
! scope="row" style="width: 70%;" | 3rd pillar: Innovation and sophistication
| style="width: 15%;" | 20%
| style="width: 15%;" |  
|-
! scope="row" | . A. Business sophistication
| 50%
|  
|-
| .... 1.01 Local supplier quantity
| 3%
| WEF
|-
| .... 1.02 Local supplier quality
| 3%
| WEF
|-
| .... 1.03 State of cluster development
| 3%
| WEF
|-
| .... 1.04 Nature of competitive advantage
| 3%
| WEF
|-
| .... 1.05 Value chain breadth
| 3%
| WEF
|-
| .... 1.06 Control of international distribution
| 3%
| WEF
|-
| .... 1.07 Production process sophistication
| 3%
| WEF
|-
| .... 1.08 Extent of marketing
| 3%
| WEF
|-
| .... 1.09 Official marketing support - marketing
| 3%
| Survey
|-
| .... 1.10 Marketing operations - wild fisheries
| 11%
| Survey
|-
| .... 1.11 Marketing operations - aquaculture products
| 11%
| Survey
|-
| .... 1.12 Competition among major suppliers - fisheries
| 11%
| Survey
|-
| .... 1.13 Cooperation in the value chain - fisheries
| 11%
| Survey
|-
| .... 1.14 Cooperation in the value chain - fish processing
| 11%
| Survey
|-
| .... 1.15 Competition among major suppliers - fish processing
| 11%
| Survey
|-
| .... 1.16 Cooperation along the value chain - aquaculture
| 11%
| Survey
|-
! scope="row" | . B. R&D Innovation
| 50%
|  
|-
| .... 2.01 Capacity for innovation
| 8%
| WEF
|-
| .... 2.02 Quality of scientific research institutions
| 8%
| WEF
|-
| .... 2.03 Company spending on R&D
| 5%
| WEF
|-
| .... 2.04 University-industry collaboration in R&D
| 8%
| WEF
|-
| .... 2.05 Availability of scientists and engineers
| 8%
| WEF
|-
| .... 2.06 PCT patent applications
| 5%
| WEF
|-
| .... 2.07 R&D Fishing technology fisheries
| 15%
| Survey
|-
| .... 2.08 R&D Processing technology fisheries
| 15%
| Survey
|-
| .... 2.09 R&D Processing technology fish processing
| 15%
| Survey
|-
| .... 2.10 R&D - aquaculture equipment
| 15%
| Survey
|}

 
== Reports & Data ==

----

 

=== Firm-level FACI - Fisheries ===

As mentioned above, the firm-level FACI can both be applied to firms engaged in fisheries and aquaculture. This section only deals with the former, and compares results from one firm Iceland, one from Newfoundland and three Norwegian firms engaged in harvesting and processing of wild capture fish. Each firm’s scoring of individual indicators is presented in the table below:

''Questions and responses – firm level FACI – Threat of new entrants''
{| class="wikitable"
|-
! Theme
! Question
! Ice.1
! New1
! Nor1
! Nor2
! Nor3
|-
| style="width: 10%;" | Institutional barriers
| style="width: 65%;" | There are significant institutional barriers (f. ex. licenses, quotas, regulations) to entry in my industry (1=not at all; 7=make entry impossible)
| style="width: 5%;" | 7
| style="width: 5%;" | 7
| style="width: 5%;" | 3
| style="width: 5%;" | 5
| style="width: 5%;" | 7
|-
| Real capital barriers
| Entry into my industry requires investment in capital (vessels, equipment, buildings) that (1=does not deter entry at all; 7=deters entry completely)
| 5
| 7
| 4
| 4
| 5
|-
| Other investment barriers
| Entry into my industry requires other forms of investment (marketing, R&D, knowledge) that (1=does not deter entry at all; 7=deters entry completely)
| 5
| 6
| 4
| 3
| 6
|-
| Scale economics
| Does this type of production enjoy economies of scale (1=not at all; 7=to a huge degree)
| 7
| 6
| 5
| 6
| 2
|-
| Firm scale economics
| The firm takes advantage of its economies of scale (1=not at all; 7=completely)
| 7
| 6
| 5
| 5
| 1
|-
| Location
| The firm is well geographically located in terms of costs and ability to meet customer demand (1=not at all; 7=very well located)
| 4
| 5
| 5
| 3
| 7
|-
| Uncertainty
| How large uncertainty is there in your business environment? (1=none at all; 7=very great)
| 4
| 4
| 4
| 4
| 5
|-
| Labour availability
| High skilled labour in your company’s locations is (1=not readily available; 7=readily available)
| 6
| 2
| 6
| 6
| 6
|-
| Expert availability
| Qualified experts are (1=not readily available; 7=readily available)
| 6
| 6
| 2
| 3
| 5
|}

''Questions and responses – firm level FACI – Bargaining power of suppliers''
{| class="wikitable"
|-
! Theme
! Question
! Ice.1
! New1
! Nor1
! Nor2
! Nor3
|-
| style="width: 10%" | Supplier power
| style="width: 65%" | The bargaining power of suppliers is (1=weak; 7=strong)|
| style="width: 5%" | 5
| style="width: 5%" | 6
| style="width: 5%" | 5
| style="width: 5%" | 6
| style="width: 5%" | 4
|-
| Supplier competition
| Competition among the firm‘s major suppliers is (1=nonexistent; 7=fierce)
| 5
| 6
| 6
| 5
| 7
|-
| Quality raw material
| Quality of raw material is currently (1=poor; 7=excellent)
| 1
| 4
| 4
| 6
| 5
|-
| Quality and price
| How well do prices for raw materials reflect changes in Quality (1=not at all; 7=completely)
| 5
| 6
| 4
| 7
| 3
|-
| Quantity and price
| How well do prices for raw materials reflect changes in Quantity (1=not at all; 7=completely)
| 5
| 6
| 4
| 5
| 2
|-
| Timing and price
| How well do prices for raw materials reflect changes in Timing (1=not at all; 7=completely)
| 6
| 4
| 4
| 5
| 6
|-
| Access raw materials
| Compared to your most important competitors, your access to raw material is currently (1=very difficult; 7=very easy)
| 5
| 4
| 3
| 5
| 4
|-
| Supplier networks
| The firm has access to supplier networks (1=not at all; 7= very good access)
| 6
| 5
| 5
| 4
| 6
|}

''Questions and responses – firm level FACI – Bargaining power of buyers''
{| class="wikitable"
|-
! Theme
! Question
! Ice.1
! New1
! Nor1
! Nor2
! Nor3
|-
| style="width: 10%" | Product price sensitivity
| style="width: 65%" | My customers are sensitive to changes in product price (1=not at all; very much so)
| style="width: 5%" | 5
| style="width: 5%" | 7
| style="width: 5%" | 6
| style="width: 5%" | 6
| style="width: 5%" | 7
|-
| Brand value
| The brand of my product is valuable ?(1=not valuable at all; 7=immensely valuable)
| 4
| 6
| 4
| 5
| 5
|-
| Loyalty buyers
| The buyers of my product are loyal (1=not at all; 7=very much so)
| 7
| 7
| 3
| 4
| 5
|-
| Buyer power
| The bargaining power of buyers is (1=weak; 7=strong)
| 5
| 4
| 4
| 5
| 3
|-
| Quality and price
| How well do prices for your output reflect changes in Quality (1=not at all; 7=completely)
| 5
| 6
| 2
| 6
| 3
|-
| Quantity and price
| How well do prices for your output reflect changes in Quantity (1=not at all; 7=completely)
| 5
| 6
| 5
| 6
| 4
|-
| Timing and price
| How well do prices for your output reflect changes in Timing (1=not at all; 7=completely)
| 5
| 4
| 3
| 5
| 4
|-
| Diversification
| How diversified are the marketing options (does the firm depend on one buyer or many) (1=not at all; 7=very diversified)
| 6
| 5
| 5
| 4
| 6
|}

''Questions and responses – firm level FACI – Threat of substitute products or services''
{| class="wikitable"
|-
! Theme
! Question
! Ice.1
! New1
! Nor1
! Nor2
! Nor3
|-
| style="width: 10%" | Niche market
| style="width: 65%" | The firm is producing to a niche market (1=not all; 7=completely)
| style="width: 5%" | 4
| style="width: 5%" | 5
| style="width: 5%" | 2
| style="width: 5%" | 5
| style="width: 5%" | 4
|-
| Substitute availability
| There are substitutes to my products available in the market (1=not at all; 7=many substitutes exist)
| 5
| 5
| 5
| 4
| 3
|}

''Questions and responses – firm level FACI – Rivalry of existing competitors''
{| class="wikitable"
|-
! Theme
! Question
! Ice.1
! New1
! Nor1
! Nor2
! Nor3
|-
| style="width: 10%" | R&D collaboration
| style="width: 65%" | Research and development within the firm is done in close collaboration with technology firms (1=not at all; 7=completely)
| style="width: 5%" | 6
| style="width: 5%" | 4
| style="width: 5%" | 5
| style="width: 5%" | 1
| style="width: 5%" | 3
|-
| R&D importance
| How important is R&D for your operation and possibility to increase value added? (1=not important; 7=very important)
| 6
| 4
| 6
| 1
| 3
|-
| Innovation impact
| Innovation makes it possible for my firm to retain a competitive advantage (1=not at all; 7=highly)
| 6
| 6
| 5
| 3
| 3
|-
| Response market condition
| How capable is your part of the value chain of responding to changes in market conditions? (1=not capable; 7=very capable)
| 6
| 6
| 4
| 3
| 4
|-
| Value chain response
| How capable is your whole value chain of responding to changes in market conditions? (1=not capable; 7=very capable)
| 6
| 6
| 4
| 4
| 5
|-
| Importance audited labels
| How important are third-party audited labels to your operation (1=not important; 7=very important)
| 5
| 7
| 6
| 6
| 3
|-
| Competitive strategy
| The competitive strategy of my firm is (1=weak; 7=powerful)
| 6
| 5
| 5
| 4
| 3
|-
| Market share
| The market share of the firm is (1=less than 1%; 7=larger than 10%)
| 4
| 3
| 4
| 4
| 1
|-
| Cost leadership
| The firm is a cost leader (1=not at all; 7=very much so)
| 4
| 3
| 4
| 1
| 1
|-
| Technology sophistication
| How sophisticated is your production technology compared to best practice (1=not at all; 7=very sophisticated)
| 6
| 3
| 1
| 4
| 2
|-
| Production sites
| The firm has access to good sites for its production facilities (1=agree completely; 7=disagree completely)
| 6
| 5
| 5
| 4
| 6
|-
| Flexibility
| How much flexibility does your firm have in adapting to unpredictable events? (1=none at all; 7=complete flexibility)
| 4
| 3
| 5
| 3
| 4
|-
| Risk management
| To what extent does risk management and insurance protect against unpredictable negative shocks? (1=not at all; 7=completely)
| 5
| 5
| 2
| 4
| 3
|}

 

==== Total competitiveness ====

The scores for aggregated competitiveness for each of the sampled firms are presented in Figure 4. The Newfoundland and Icelandic firms receives scores of 5.2 and 5.1, while the Norwegian firms received considerably lower scores, or in the range 4.1-4.6.

[[File:Cpa figure4.png|Figure 4 Total competitiveness between sampled firms in the wildfish sector.]]
<div style="text-align: center;">''Figure 4 Total competitiveness between sampled firms in the wildfish sector''</div>

==== Competitive forces ====

By going one step beyond the total competitiveness score and looking at how the firms rank in terms of each competitive force, it is possible to gain a better insight into the firms’ competitive position. As shown in Figure 5, the Icelandic firm and the Newfoundland firm each score highest in two categories, with the difference between these two firms and the three Norwegian firms especially pronounced as regards the threat of new entrants and rivalry among competitors. The figure also reveals considerable differences between individual Norwegian firms.

[[File:Cpa figure5.png|Figure 5 First level of aggregation – firm level competitiveness.]]
<div style="text-align: center;">''Figure 5 First level of aggregation – firm level competitiveness''</div>

==== Individual indicators ====

Looking at the individual indicators for each competitive force can further illustrate differences and similarities among firms. In what follows the results are briefly discussed.

===== '''Threat of new entrants''' =====

Threat of new entrants is measured by nine individual indicators. Here the Icelandic and Newfoundland firms received the highest score. The survey reveals the existence of substantial barriers to entry, with the Icelandic firms in addition enjoying greater economies of scale and be able to take advantage of that position. The Newfoundland and Norwegian firms have a more advantageous location, but Newfoundland does not have as good access to qualified labour as the other four firms. Qualified experts are more readily available in Newfoundland and Iceland than in Norway.

[[File:Cpa figure6.png|center|Figure 6 Individual firm indicators – threat of new entrants.]]
<div style="text-align: center;">''Figure 6 Individual firm indicators – threat of new entrants.''</div>

===== '''Bargaining power of suppliers''' =====

Bargaining power of suppliers is measured through eight individual indicators. Here, one of the Norwegian firms performs much better than the firms in the survey (Figure 7). At the time of the survey, the quality of the raw material available to the Icelandic firm appears to have been very poor. Contrary to what could have been expected for a firm operating under an ITQ management system in fisheries, the relationship between price on the one hand and quality, quantity and timing is not as strong for the Icelandic firm as some of the Norwegian firms and the Newfoundland firm.

[[File:Cpa figure7.jpg|center|Figure 7 Individual firm indicators – bargaining power of suppliers.]]
<div style="text-align: center;">''Figure 7 Individual firm indicators – bargaining power of suppliers.''</div>

===== '''Bargaining power of buyers''' =====

The category bargaining power of buyers is measured through eight individual indicators. All the firms believe their buyers are quite sensitive to price changes, but do not regard their brand as particularly valuable (Figure 8). The customers of the Icelandic and Newfoundland firms are far more loyal but all firms rank the power of buyers as relatively similar. The firms have very different views on the relationship between output price and quality.

[[File:Cpa figure8.jpg|center|Figure 8 Individual firm indicators – bargaining power of buyers.]]
<div style="text-align: center;">''Figure 8 Individual firm indicators – bargaining power of buyers.''</div>

===== '''Threat of substitute products or services''' =====

The threat from substitutes is measured by two indicators. Both indicate the firms do have access to niche markets and that substitutes are available (Figure 9).

[[File:Cpa figure9.jpg|center|Figure 9 Individual firm indicators – threat of substitutes.]]
<div style="text-align: center;">''Figure 9 Individual firm indicators – threat of substitutes.''</div>

===== '''Rivalry among existing competitors''' =====

Rivalry among the existing firms is measured by 13 individual indicators (figure 10). Here the Icelandic firm performs better according to 10 of the indicators. According to the Icelandic firm, R&D collaboration is to a much higher degree conducted in close collaboration with technology firms, and R&D and innovation is regarded vital to maintain a competitive edge. The firm has also more sophisticated technology than its competitors. The Icelandic and Newfoundland value chains are also more flexible and better able to adjust to market condition.

[[File:Cpa figure10.jpg|center|Figure 10 Individual firm indicators – rivalry.]]
<div style="text-align: center;">''Figure 10 Individual firm indicators – rivalry.''</div>

[[File:Cpa figure11.jpg|center|Figure 11 Individual firm indicators – rivalry – last six indicators.]]
<div style="text-align: center;">''Figure 11 Individual firm indicators – rivalry – last six indicators.''</div>
 

=== National-level FACI ===

In the following sections the results from the competitiveness estimation are presented, first the aggregate scores, then the scores for each of the three main pillars (aggregation level 1) and then the score for the subsections within each pillar (aggregation level 2). All scoring is done using a seven step Likert scale. In some instances, data have not been available for certain countries. In particular, this applies to some of the hard data and most frequently for Newfoundland and Vietnam. When one indicator is missing, we have disregarded this from the calculation of the lowest aggregation level for the country in question. For Newfoundland, some themes had several indicators with missing data. Here we have not calculated aggregate level scoring, hence some tables have missing numbers for Newfoundland.

==== '''Aggregation level 1 and 2''' ====

The national-level FACI was applied to five countries; Norway, Iceland, Spain, Newfoundland and Vietnam. As Newfoundland-Labrador is not an independent country but one of the provinces that make up Canada, the WEF scores for Canada are used for Newfoundland. The hard data and survey is though only based on information from sources in Newfoundland. The data for Newfoundland has some gaps, but the data for the other four countries is almost complete. Because of this, no overall score is calculated for Newfoundland, but where possible scores are presented for individual pillars and subsections, as well as each indicator. Norway, Iceland and Spain all have a similar overall score of 4.8-4.9, while Vietnam gets a score of 3.9 (Table 5). The difference between the European countries and Vietnam is especially large in relation to pillar I, basic requirements, both as regards institutions and infrastructure. Norway and Iceland have a similar score for this first pillar, 4.9 and 5.0, with Spain receiving a score of 4.5. This is mostly due to the Nordic scores getting higher scores for their institutions, but Spain has better infrastructure. The European countries all receive similar scores for pillar II, Efficiency enhancers, and pillar III, Innovation and sophistication, with Vietnam lagging behind in both categories. Newfoundland ranks in between for innovation and sophistication, but due to the lack of data no overall score is calculated for Newfoundland for pillars I and II.

''Table 5 Total and first two category levels of competitiveness''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
|-
| style="width: 70%" | Total
| 4.8
| 4.9
| 4.8
|  
| 3.9
|-
| 1 Basic requirements
| 4.9
| 5.0
| 4.5
|  
| 3.5
|-
| 1.1 Institutions
| 5.2
| 5.1
| 4.3
|  
| 3.5
|-
| 1.2 Infrastructure
| 4.2
| 4.7
| 5.3
| 3.6
| 3.5
|-
| 2 Efficiency enhancers
| 4.8
| 4.8
| 4.9
|  
| 4,2
|-
| 2.1 Higher education and training
| 5.1
| 5.4
| 4.6
| 4.6
| 3.8
|-
| 2.2 Goods market efficiency
| 4.1
| 4.8
| 4.6
| 4.3
| 3.9
|-
| 2.3 Labour market efficiency
| 4.7
| 4.6
| 4.3
| 3,1
| 3,3
|-
| 2.4 Fisheries specific inputs
| 5.1
| 5.1
| 5.4
|  
| 4.9
|-
| 2.5 Fish processing specific inputs
| 4.1
| 5,8
| 5,0
| 2,3
| 3,6
|-
| 2.6 Aquaculture specific inputs
| 5.3
| 4,0
| 4.3
|  
| 4,1
|-
| 2.7 Financial market development
| 5.4
| 4.5
| 3.8
| 4.9
| 3.8
|-
| 2.8 Technological readiness
| 5.4
| 5.9
| 5.6
| 5.0
| 4.7
|-
| 2.9 Market size
| 4.6
| 2.7
| 5.6
| 5.6
| 5.2
|-
| 3 Innovation and sophistication
| 4.8
| 4.9
| 4.8
| 4.5
| 3.8
|-
| 3.1 Business sophistication
| 4.6
| 4.6
| 4.6
| 4.4
| 3.8
|-
| 3.2 R&D Innovation
| 4.9
| 5.2
| 5.1
| 4.7
| 3.7
|}

 

==== '''Pillar I Basic requirements''' ====

This section goes into detail on the two components of the first pillar – institutions and infrastructure. We first discuss the he institutions subsection consisting of sections on public institutions, fisheries management and aquaculture management. Subsequent sections discuss these areas again in more detail.Public institutions are much higher ranked in Norway and Iceland and Newfoundland than in Spain and Vietnam (Table 6). This is both due to stronger property rights in these countries and better public sector performance. Fisheries management scores highest in Iceland and Norway, but aquaculture management is considered better in Norway and Spain. Spain has the best infrastructure, followed by Iceland, Norway and Newfoundland and Vietnam having the lowest scores.

''Table 6 Basic requirements and two following aggregation levels of competitiveness''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
|-
| style="width: 70%" | 1 Basic requirements
| 4.9
| 5.0
| 4.5
|  
| 3.5
|-
| 1.1 Institutions
| 5.2
| 5.1
| 4.3
|  
| 3.5
|-
| 1.1.1 Public institutions
| 5.7
| 5.4
| 4.1
| 5.0
| 3.8
|-
| ........Property rights
| 6.2
| 5.8
| 4.7
| 5.4
| 4.0
|-
| ........Public sector performance
| 5.2
| 5.0
| 3.6
| 4.7
| 3.5
|-
| 1.1.2 Fisheries management
| 5.1
| 5.5
| 4.2
| 4.3
| 2.8
|-
| ........Stability
| 5.4
| 6.1
| 4.5
| 3.9
| 2.9
|-
| ........Research and advice
| 5.2
| 4.9
| 4.9
| 4.4
| 2.7
|-
| ........Monitoring and inspection
| 4.6
| 5.7
| 3.1
| 4.6
| 2.9
|-
| 1.1.3 Aquaculture management
| 4.7
| 4.3
| 4.6
|  
| 3.8
|-
| ........Stability
| 4.8
| 4.0
| 4.3
|  
| 4.2
|-
| ........Research and advice
| 4.6
| 4.6
| 4.8
|  
| 3.4
|-
| 1.2 Infrastructure
| 4.2
| 4.7
| 5.3
| 3.6
| 3.5
|-
| 1.2.1 Transport infrastructure
| 4.2
| 4.7
| 5.3
| 3.6
| 3.5
|}

 

===== '''Fisheries management''' =====

There is relatively large variation between the countries in the stability of fisheries management. It is considered very high in Iceland with Norway following with a score about 0,7 lower.Spain is almost a full point behind again and Newfoundland and Vietnam registering a significant lower stability (Table 7). Research and advice sees less variation between the European countries, with score slightly higher in Norway than in Iceland and Spain. Newfoundland and Vietnam again scores worst. Monitoring and inspection is best in Iceland, with Norway and Newfoundland receiving the same score. Spain and Vietnam have the lowest monitoring and inspection scores.

''Table 7 Fisheries management and individual indicators, average scores''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | '''1.1.2 Fisheries management'''
| 5.1
| 5.5
| 4.2
| 4.3
| 2.8
|  
|-
| ....Stability
| 5.4
| 6.1
| 4.5
| 3.9
| 2.9
|  
|-
| ''Transparency of fisheries management''
| 5.3
| 6.7
| 4.8
| 3.8
| 3.4
| Surv
|-
| ''Objectives of fisheries management''
| 5.2
| 5.8
| 3.9
| 3.6
| 3.3
| Surv
|-
| ''Stability of allocation of fishing rights''
| 5.7
| 5.8
| 4.8
| 4.2
| 2.0
| Surv
|-
| ....Research and advice
| 5.2
| 4.9
| 4.9
| 4.4
| 2.7
|  
|-
| ''Actual vs recommended fishing mortality''
| 6.2
| 2.2
| na
| na
| na
| Data
|-
| ''Extent of information gathered by research''
| 5.3
| 4.8
| 4.4
| 4.2
| 3.7
| Surv
|-
| ''Information gathering by marine research''
| 5.3
| 6.2
| 5.9
| 5.2
| 3.7
| Surv
|-
| ''Accuracy of forecasts by marine research''
| 4.9
| 5.4
| 4.8
| 4.8
| 2.8
| Surv
|-
| ''Impact of research on investments and operations''
| 4.3
| 5.8
| 4.6
| 3.4
| 3.4
| Surv
|-
| ....Monitoring and inspection
| 4.6
| 5.7
| 3.1
| 4.6
| 2.9
|  
|-
| ''Efficiency of management system''
| 5.9
| 6.1
| 4.3
| 3.6
| 2.6
| Surv
|-
| ''Illegal/excess catches''
| 3.4
| 5.2
| 2.0
| 5.5
| 3.1
| Surv
|}

 

===== '''Aquaculture management''' =====

Aquaculture is a major industry in Norway, Spain and Vietnam with Iceland being a relative newcomer. No data on aquaculture was available from Newfoundland. Stability is highest in Norway, with relatively small differences between the others. Norway’s leading position is due to generally higher scores on all the indicators. Apart from Vietnam, scoring the worst, there are relatively small differences between countries on in research and advice, but Spain in a slight lead (Table 8).

''Table 8 Aquaculture management and individual indicators''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 1.1.3 Aquaculture management
| 4.7
| 4.3
| 4.6
|  
| 3.8
|  
|-
| ....Stability
| 4.8
| 4.0
| 4.3
|  
| 4.2
|  
|-
| ''Transparency of aquaculture management''
| 4.9
| 4.6
| 4.3
|  
| 4.2
| Surv
|-
| ''Objectives of aquaculture management''
| 4.4
| 3.4
| 3.7
|  
| 4.2
| Surv
|-
| ''Stability of allocation of aquaculture licenses''
| 5.5
| 4.6
| 5.0
|  
| 4.8
| Surv
|-
| ''Efficiency of management - aquaculture''
| 4.5
| 3.5
| 4.3
|  
| 3.5
| Surv
|-
| ....Research and advice
| 4.6
| 4.6
| 4.8
|  
| 3.4
|  
|-
| ''Extent of information gathered by research''
| 4.6
| 4.6
| 4.8
|  
| 3.4
| Surv
|}

 

===== '''Infrastructure''' =====

Infrastructure in Spain appears to be far better than in any of the other four countries, not least because of relatively low transport costs (Table 9). Iceland and Spain receive similarly high scores for their communication systems. Norway in general scores wore than Spain for all indicators, but sees less costly transportation than Iceland. Both Newfoundland and Vietnam have poorer scores, with transportation costs and communication network needs scoring particularly badly for the former.

''Table 9 Fisheries management and individual indicators, average scores''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 1.2 Infrastructure
| 4.2
| 4.7
| 5.3
| 3.6
| 3.5
|  
|-
| ....Transport infrastructure
| 4.2
| 4.7
| 5.3
| 3.6
| 3.5
|  
|-
| ''Quality of overall infrastructure''
| 4.8
| 5.8
| 5.5
| 5.2
| 3.6
| WEF
|-
| ''Communication network needs''
| 3.8
| 5.6
| 5.3
| 3.0
| 3.5
| Surv
|-
| ''Communication network restrictions''
| 3.9
| 5.6
| 5.6
| 5.3
| 3.1
| Surv
|-
| ''Cost of domestic transportation''
| 4.0
| 3.2
| 5.3
| 2.3
| 3.5
| Surv
|-
| ''Cost of cross-border transportation''
| 4.4
| 3.6
| 4.6
| 2.3
| 3.8
| Surv
|}

 

==== '''Pillar II Efficiency enhancers''' ====

This pillar consists of a number of quite diverse subsections that measure the competitiveness of the country in terms of quality and efficiency of education, markets, inputs and technology. Norway, Iceland and Spain all receive a score of 4,8-4,9 for the pillar as a whole, but there are some important discrepancies (Table 10). Iceland receives the highest score for education and training, goods market efficiency, for inputs into harvesting and processing of wild capture fish, and technological readiness, but has an inefficient financial system and small markets. Norway has the best aquaculture sector while Spain, Newfoundland and Vietnam enjoy the largest markets.

''Table 10 Efficiency enhancers and two following aggregation levels of competitiveness''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
|-
| style="width: 65%" | 2 Efficiency enhancers
| 4.8
| 4.8
| 4.9
|  
| 4,2
|-
| 2.1 Higher education and training
| 5.1
| 5.4
| 4.6
| 4.6
| 3.8
|-
| 2.1.1 Quality of education
| 5.3
| 5.7
| 4.4
| 5.4
| 3.7
|-
| 2.1.2 On the job training
| 5.0
| 5.3
| 4.7
| 4.3
| 3.8
|-
| 2.2 Goods market efficiency
| 4.1
| 4.8
| 4.6
| 4.3
| 3.9
|-
| 2.2.1 Competition
| 4.1
| 5.0
| 4.6
| 4.3
| 4.2
|-
| ......''Domestic competition''
| 4.2
| 5.1
| 4.5
| 4.0
| 4.5
|-
| ......''Foreign competition''
| 4.1
| 4.9
| 4.6
| 4.6
| 3.9
|-
| 2.2.2 Quality of demand conditions
| 4.1
| 4.4
| 4.7
| 4.2
| 3.2
|-
| 2.3 Labour market efficiency
| 4.7
| 4.6
| 4.3
|  
| 3,3
|-
| 2.3.1 Flexibility
| 3.9
| 4.4
| 3.9
| 4.9
| 4.2
|-
| 2.3.2 Efficient use of talent
| 5,1
| 5,5
| 3.9
| 3,3
| 4,7
|-
| 2.3.3 Supply of labour
| 5.1
| 5.5
| 5.1
| 4.2
| 4.1
|-
| 2.3.4 Cost of labour
| 4.8
| 3.1
| 4.5
|  
|  
|-
| 2.4 Fisheries specific inputs
| 5.1
| 5.7
| 5.4
|  
| 4.9
|-
| 2.4.1 Property rights
| 5.4
| 6.2
| 5.4
| 2.8
| 6.1
|-
| 2.4.2 Capacity utilization
| 3.9
| 5.9
| 5,0
| 2.8
| 3,2
|-
| 2.4.3 Cost items
| 7.0
| 3.6
| 7.0
|  
| 7.0
|-
| 2.4.4 Profitability
| 3.8
| 5.2
| 4.2
| 2,2
| 3.1
|-
| 2.5 Fish processing specific inputs
| 4.1
| 5,8
| 5,0
|  
| 3,6
|-
| 2.5.1 Capacity utilization
| 2.9
| 4.0
| 5,5
| 2,5
| 3,8
|-
| 2.5.2 Cost items
| 5,3
| 6,8
| 5,7
| 4,3
| 3,7
|-
| 2.5.3 Profitability
| 3.7
| 5.9
| 3.9
|  
| 3.3
|-
| 2.6 Aquaculture specific inputs
| 5.3
| 4,0
| 4.3
|  
| 4,1
|-
| 2.6.1 Property rights
| 6.0
| 4.9
| 4.9
|  
| 1.3
|-
| 2.6.2 Capacity utilization
| 5.3
| 5.0
| 5.7
|  
| 4.8
|-
| 2.6.3 Cost items
| 4,6
| 5,1
| 4,6
|  
| 5,1
|-
| 2.6.4 Profitability
| 5.5
| 1.8
| 2.8
|  
| 4.6
|-
| 2.7 Financial market development
| 5.4
| 4.5
| 3.8
| 4.9
| 3.8
|-
| 2.7.1 Efficiency
| 5.4
| 4.5
| 3.8
| 4.9
| 3.8
|-
| 2.8 Technological readiness
| 5.4
| 5.9
| 5.6
| 5.0
| 4.7
|-
| 2.8.1 Technological adoption
| 6.3
| 6.2
| 5.1
| 5.7
| 4.3
|-
| 2.8.2 Fisheries technology
| 5.4
| 6.3
| 5.5
| 4.1
| 3.3
|-
| 2.8.3 Fish processing technology
| 4.1
| 6.6
| 5.9
| 4.5
| 5.0
|-
| 2.8.4 Aquaculture technology
| 6.3
| 4.6
| 5.4
| 6.0
| 5.8
|-
| 2.9 Market size
| 4.6
| 2.7
| 5.6
| 5.6
| 5.2
|-
| 2.9.1 Domestic market size
| 4.2
| 1.9
| 5.3
| 5.3
| 4.5
|-
| 2.9.2 Foreign market size
| 5.0
| 3.5
| 5.8
| 5.8
| 5.8
|}

 

===== '''Higher education and training''' =====

The category higher education and training consists of education and on-the-job training. Only the latter has indicators specific for the survey and is hence detailed in Table 11 below. Iceland scores slightly higher than Norway in this subsection, mainly because training and education in fish processing seems to be better in Iceland. Spain and Newfoundland have the same overall score. Vietnam appears to lag behind the other countries on all accounts.
''Table 11 On-the-job training and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.1 Higher education and training
| 5.1
| 5.4
| 4.6
| 4.6
| 3.8
|  
|-
| ....On the job training
| 5.0
| 5.3
| 4.7
| 4.3
| 3.8
|  
|-
| ''Local availability of specialized training services''
| 5.8
| 5.4
| 4.3
| 5.8
| 3.7
| WEF
|-
| ''Extent of staff training''
| 5.5
| 5.1
| 3.7
| 4.6
| 3.9
| WEF
|-
| ''Training and education fisheries''
| 4.6
| 5.4
| 5.1
| 3.8
| 3.8
| Surv
|-
| ''Training and education fish processing''
| 3.7
| 4.7
| 3.7
| 3.5
| 3.3
| Surv
|-
| ''Training and education aquaculture''
| 5.1
| 4.5
| 5.6
| 6.0
| 4.4
| Surv
|}

 

===== '''Goods market efficiency''' =====

Efficiency in the goods market appears to be quite similar in all five countries, although Iceland and Spain score higher than the other three countries (Table 12). Iceland enjoys a competitive advantage both as regards domestic and foreign competition. Taxes have a detrimental effect on competitiveness in Spain, while Vietnam suffers from lack of access to international markets due to tariffs and on-tariff barriers. The quality of demand conditions is best in Spain, but quite similar in Norway, Iceland and Newfoundland.

''Table 12 Goods market efficiency and individual indicators, average scores''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.2.1 Competition
| 4.1
| 5.0
| 4.6
| 4.3
| 4.2
|  
|-
| ....Domestic competition
| 4.2
| 5.1
| 4.5
| 4.0
| 4.5
|  
|-
| ''Intensity of local competition''
| 5.1
| 4.8
| 5.6
| 5.1
| 5.0
| WEF
|-
| ''Extent of market dominance''
| 4.7
| 3.8
| 4.1
| 5.4
| 3.6
| WEF
|-
| ''Effect of taxation on incentives to invest''
| 3.8
| 4.1
| 3.4
| 3.9
| 3.6
| WEF
|-
| ''Total tax rate''
| 3.5
| 4.1
| 2.2
| 5.7
| 3.5
| WEF
|-
| ''Competition for fishing rights (quota)''
| 3.8
| 5.3
| 4.3
| 1.8
| 2.0
| Survey
|-
| ''Market for fresh fish - fisheries''
| 5.1
| 6.3
| 4.5
| 3.0
| 5.4
| Survey
|-
| ''Market for fresh fish - fish processing''
| 2.4
| 5.0
| 4.8
| 3.8
| 5.2
| Survey
|-
| ''Competition between marketing/distributors - marketing''
| 5.2
| 4.7
| 5.5
| 5.7
| 5.4
| Survey
|-
| ''Competition between companies that market and distribute seafood products''
| 5.2
| 5.5
| 4.8
| 4.0
| 5.4
| Survey
|-
| ....Foreign competition
| 4.1
| 4.9
| 4.6
| 4.6
| 3.9
|  
|-
| ''Prevalence of non-tariff barriers''
| 4.6
| 4.3
| 4.5
| 4.5
| 3.9
| WEF
|-
| ''Trade-weighted average tariff rate''
| 5.2
| 5.3
| 4.0
| 5.3
| 2.3
| WEF
|-
| ''Current markets - free trade agreements''
| 4.3
| 5.4
| 4.8
| 4.5
| 4.6
| Surv
|-
| ''Potential markets - free trade agreements''
| 3.9
| 4.4
| 4.8
| 4.5
| 3.8
| Surv
|-
| 2.2.2 Quality of demand conditions
| 4.1
| 4.4
| 4.7
| 4.2
| 3.2
|  
|-
| ''Degree of customer orientation''
| 5.6
| 5.6
| 4.9
| 5.5
| 4.1
| WEF
|-
| ''Buyer sophistication''
| 4.6
| 4.1
| 3.3
| 4.4
| 3.5
| WEF
|-
| ''Product development - fish processing''
| 3.3
| 4.6
| 5.1
| 3.0
| 3.2
| Surv
|-
| ''Product development - aquaculture processing''
| 4.3
| 4.0
| 4.6
| 5.0
| 3.0
| Surv
|}

 

===== '''Labour market efficiency''' =====

Labour market efficiency is highest in Iceland and Norway, not least because of far higher productivity in harvesting and fish processing (Table 13). Supply of labour scores similarly in Iceland, Norway and Spain, but Newfoundland and Vietnam appear to be affected by the availability of good labour.

''Table 13 Labour market efficiency and individual indicators, average scores''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.3.2 Efficient use of talent
| 5,1
| 5,5
| 3.9
| 3,3
| 4,2
|  
|-
| ''Pay and productivity''
| 4.9
| 4.9
| 3.6
| 4.9
| 4.0
| WEF
|-
| ''Reliance on professional management''
| 6.2
| 5.5
| 4.7
| 5.8
| 3.6
| WEF
|-
| Productivity of fishermen
| 5.8
| 6.5
| 3.6
| na
| na
| Data
|-
| ''Wage system fisheries''
| 5.4
| 5.9
| 3.7
| 1.5
| 2.8
| Survey
|-
| Productivity of employees fish processing
| 3.9
| 5.8
| 2.7
| na
| na
| Data
|-
| ''Wage system fish processing''
| 4.1
| 4.9
| 3.3
| 1.7
| 6.0
| Survey
|-
| Productivity of labor aquaculture
| na
| na
| na
| na
| na
| Data
|-
| ''Labour skills and productivity - aquaculture''
| 5.8
| 4.7
| 5.8
| 5.5
| 6.0
| Survey
|-
| 2.3.3 Supply of labour
| 5.1
| 5.5
| 5.1
| 4.2
| 4.1
|  
|-
| Supply of qualified officers
| 5.0
| 6.0
| 4.1
| 4.0
| 3.2
| Survey
|-
| Supply of skilled fishermen
| 5.5
| 5.9
| 3.5
| 4.0
| 4.2
| Survey
|-
| Supply middle management fish processing
| 5.0
| 5.7
| 5.6
| 4.0
| 3.8
| Survey
|-
| Supply of skilled labour fish processing
| 4.1
| 5.2
| 5.5
| 3.0
| 4.0
| Survey
|-
| Supply middle management aquaculture
| 5.8
| 5.3
| 5.9
| 5.5
| 4.8
| Survey
|-
| Supply of skilled labour aquaculture
| 5.4
| 4.8
| 5.9
| 4.5
| 4.8
| Survey
|-
| 2.3.4 Cost of labour
| 4.8
| 3.1
| 4.5
| na
| na
|  
|-
| Labour cost fisheries
| 4.8
| 3.1
| 4.5
| na
| na
| Data
|-
| Labour cost fish processing
| na
| na
| na
| na
| na
| Data
|}

 

===== '''Fisheries specific inputs''' =====

The fisheries specific inputs score countries in terms of quality of the property rights in management, capacity utilisation, taxation and oil costs, and profitability. Iceland scores highly here, mainly because of the good quality of the property rights system employed in the harvesting sectors, high degree of capacity utilisation and profitability. However, taxation in the Icelandic fisheries erodes some of the competitive advantage. Newfoundland performs poorly in this subsection.
''Table 14 Fisheries specific inputs and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.4.1 Property rights
| 5.4
| 6.2
| 5.4
| 2.8
| 6.1
|  
|-
| ''Permanency of fisheries rights.''
| 5.8
| 5.9
| 3.8
| 1.8
| 6.2
| Survey
|-
| ''Transfers of fishing rights between firms''
| 5.0
| 6.4
| 7.0
| 3.8
| 6.0
| Survey
|-
| 2.4.2 Capacity utilization
| 3.9
| 5.9
| 3.8
| 2.8
| 3,2
|  
|-
| ''Transfers of fishing rights between vessels''
| 4.0
| 6.5
| 7.0
| 3.0
| 5.5
| Survey
|-
| ''Impact of quota system on capacity utilisation''
| 4.5
| 6.3
| 4.0
| 2.0
| 1.7
| Survey
|-
| ''Stability of catch for the 5 most important species.''
| 3.2
| 4.6
| na
| na
| 3.2
| Data
|-
| ''Impact of authorities on investment decisions''
| 4.1
| 6.1
| 4.0
| 3.3
| 2.4
| Survey
|-
| 2.4.2 Cost items
| 7.0
| 3.6
| 7.0
| na
| 7.0
|  
|-
| ''Special taxation fishing''
| 7.0
| 3.6
| 7.0
| na
| 7.0
| Data
|-
| ''Oil price''
| na
| na
| na
| na
| na
| Data
|-
| 2.4.3 Profitability
| 3.8
| 5.2
| 4.2
| 2,2
| 3.1
|  
|-
| ''Profit margin''
| 4.7
| 5.2
| 4.1
| na
| 2.0
| Data
|-
| Capital turnover
| 2.2
| 5.5
| 3.7
| na;
| 1.3
| Data
|-
| ''Financial strength''
| 2.9
| 4.3
| 6.3
| na
| 4.6
| Data
|-
| ''Ability to use economies of scale''
| 4.1
| 5.2
| 3.7
| 2.0
| 5.0
| Survey
|-
| ''Ability to use economies of scope''
| 4.3
| 6.1
| 3.8
| 2.7
| 5.0
| Survey
|}

 

===== '''Fish processing specific inputs''' =====

All the countries have rather low scores for fish processing specific inputs. Capacity utilisation is particularly low in Newfoundland and Vietnam, but also poor in Norway and Spain. Iceland has very strong supply and cost of fresh water, with Spain and Norway following and Newfoundland and Vietnam having relatively worse scores, impacting negatively on the country’s competitiveness (Table 15). The Icelandic fish processing sectors financially outperforms the industry in the other four countries with data on this topic.
''Table 15 Fish processing specific inputs and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.5.1 Capacity utilization
| 2.9
| 4.0
| 5,5
| 2,5
| 3,8
|  
|-
| ''Distribution of the catch within the year''
| 3.3
| 2.2
| na
| na
| na
| Data
|-
| ''Timing of wetfish availability''
| 2.5
| 5.9
| 5.5
| 2.5
| 3.8
| Survey
|-
| 2.5.2 Cost items
| 5,3
| 6,8
| 5,7
| 4,3
| 3,7
|  
|-
| ''Cost of electricity''
| na
| na
| na
| na
| na
| Data
|-
| ''Supply and cost of fresh water - fish processing''
| 5.3
| 6.8
| 5.7
| 4.3
| 3.7
| Survey
|-
| 2.5.3 Profitability
| 3.7
| 5.9
| 3.9
| na
| 3.3
|  
|-
| ''Profit margin''
| 3.5
| 5.8
| 3.8
| na
| 3.5
| Data
|-
| ''Capital turnover''
| 3.0
| 6.5
| 3.0
| na
| 1.2
| Data
|-
| ''Financial strength''
| 5.0
| 5.5
| 5.5
| na
| 5.7
| Data
|-
| ''Ability to use economies of scale''
| 4.1
| 5.7
| 5.3
| 1.5
| 5.0
| Survey
|-
| ''Ability to use economies of scope''
| 4.3
| 5.9
| 5.5
| 2.3
| 5.0
| Survey
|}

 

===== '''Aquaculture specific inputs''' =====

As expected, Norway has a clear competitive advantage in aquaculture. The country scores highly in terms of transferability of licenses between firms, costs and profitability, but the impact of regulations on capacity utilisation has a better impact on competitiveness in Spain (Table 16).
''Table 16 Aquaculture specific inputs and individual indicators, average scores''

{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.6.1 Property rights
| 6.0
| 4.9
| 4.9
| na
| 1.3
|  
|-
| ''Transfers of licenses between firms''
| 6.0
| 4.9
| 4.9
| na
| 1.3
| Survey
|-
| 2.6.2 Capacity utilization
| 5.3
| 5.0
| 5.7
| na
| 4.8
|  
|-
| ''Impact of regulations on capacity utilization''
| 5.3
| 5.0
| 5.7
| na
| 4.8
| Survey
|-
| 2.6.2 Cost items
| 4,6
| 5,1
| 4,6
| 5,7
| 5,1
|  
|-
| Cost of electricity
| na
| na
| na
| na
| na
| Data
|-
| ''Supply and cost of seedstocks''
| 4.7
| 5.0
| 4.4
| 6.0
| 3.8
| Survey
|-
| ''Supply and cost of feed''
| 4.6
| 5.1
| 4.6
| 5.5
| 5.8
| Survey
|-
| 2.6.3 Profitability
| 5.5
| 1.8
| 2.8
| na
| 4.6
|  
|-
| ''Profit margin''
| 6.2
| 1.2
| 1.7
| na
| 3.7
| Data
|-
| ''Capital turnover''
| 3.8
| 2.9
| 1.9
| na
| 6.7
| Data
|-
| Financial strength
| 6.2
| na
| 6.5
| na
| 4.0
| Data
|-
| ''Ability to use economies of scale''
| 5.3
| 4.5
| 3.3
| 5.0
| 5.3
| Survey
|-
| ''Ability to use economies of scope''
| 4.8
| 4.9
| 3.5
| 5.0
| 5.3
| Survey
|}

 

===== '''Technological readiness''' =====

The level of technology in the harvesting and fish processing sectors is considerably higher in Iceland than in the other four countries, but Norway, Newfoundland and Vietnam all receive high scores for the technology employed in the aquaculture sector (Table 17).

''Table 17 Technological readiness and individual indicators, average scores''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 2.8.2 Fisheries technology
| 5.4
| 6.3
| 5.5
| 4.1
| 3.3
|  
|-
| ''Technical level of vessels and mechnical equipment''
| 6.0
| 6.4
| 5.6
| 5.3
| 3.5
| Survey
|-
| Fishing technology
| 5.4
| 5.9
| 5.7
| 4.1
| 3.5
| Survey
|-
| Processing technology on board
| 4.8
| 6.6
| 5.3
| 3.0
| 3.0
| Survey
|-
| 2.8.3 Fish processing technology
| 4.1
| 6.6
| 5.9
| 4.5
| 5.0
|  
|-
| ''General technology - fish processing''
| 4.1
| 6.6
| 5.9
| 4.5
| 5.0
| Survey
|-
| 2.8.4 Aquaculture technology
| 6.3
| 4.6
| 5.4
| 6.0
| 5.8
|  
|-
| ''General technology - aquaculture''
| 6.3
| 4.6
| 5.4
| 6.0
| 5.8
| Survey
|}

 

==== '''Pillar III Innovation and sophistication''' ====

This pillar consists of two subsections on business sophistication and R&D innovations. Vietnam received the lowest scores fin both categories (Table 18).

''Table 18 Business sophistication and two following aggregation levels of competitiveness''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
|-
| style="width: 65%" | 3 Innovation and sophistication
| 4.8
| 4.9
| 4.8
| 4.5
| 3.8
|-
| 3.1 Business sophistication
| 4.6
| 4.6
| 4.6
| 4.4
| 3.8
|-
| 3.2 R&D Innovation
| 4.9
| 5.2
| 5.1
| 4.7
| 3.7
|}

 

===== '''Business sophistication''' =====

The level of business sophistication is similar in all the countries except Vietnam (Table 19). Norway is the only country where the industry receives official marketing support.

''Table 19 Business sophistication and individual indicators, average score''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 3.1 Business sophistication
| 4.6
| 4.6
| 4.6
| 4.4
| 3.8
|  
|-
| ''Official marketing support - marketing''
| 5.0
| 1.0
| 1.0
| 1.0
| 1.0
| Survey
|-
| ''Marketing operations - wild fisheries''
| 4.9
| 4.3
| 5.9
| 5.3
| 4.0
| Survey
|-
| ''Marketing operations - aquaculture products''
| 5.2
| 4.4
| 4.7
| 6.5
| 3.8
| Survey
|-
| ''Competition among major suppliers - fisheries''
| 4.9
| 4.3
| 4.1
| 4.2
| 5.3
| Survey
|-
| ''Cooperation in the value chain - fisheries''
| 3.1
| 5.4
| 4.2
| 3.5
| 3.3
| Survey
|-
| ''Cooperation in the value chain - fish processing''
| 3.1
| 5.3
| 4.9
| 2.7
| 3.2
| Survey
|-
| ''Competition among major suppliers - fish processing''
| 4.6
| 4.3
| 4.1
| 3.5
| 4.3
| Survey
|-
| ''Cooperation along the value chain - aquaculture''
| 5.6
| 4.6
| 4.8
| 4.5
| 3.4
| Survey
|}

 

===== '''R&D Innovation''' =====

Iceland and Spain have a slight edge in R&D innovation, with Norway and Newfoundland receiving slightly lower scores and Vietnam some distance behind (Table 20).

''Table 20 R&D innovation and individual indicators, average scores''
{| class="wikitable"
|-
! Level
! Norw.
! Iceland
! Spain
! Newfld.
! Vietnam
! Type
|-
| style="width: 65%" | 3.2 R&D Innovation
| 4.9
| 5.2
| 5.1
| 4.7
| 3.7
|  
|-
| ''R&D Fishing technology fisheries''
| 4.6
| 5.6
| 6.1
| 4.4
| 3.5
| Survey
|-
| ''R&D Processing technology fisheries''
| 3.9
| 6.2
| 6.2
| 4.0
| 4.3
| Survey
|-
| ''R&D Processing technology fish processing''
| 4.5
| 6.0
| 5.8
| 4.0
| 4.0
| Survey
|-
| ''R&D - aquaculture equipment''
| 5.9
| 3.8
| 5.3
| 6.0
| 4.4
| Survey
|}

 

== The tool ==

----

The [http://dss.primefish.eu/index.php/cpa | CPA tool] is the implementation of the FACI survey both at firm-level and national-level. It can be accessed by clicking the quick access icon for the CPA in the [http://dss.primefish.eu/index.php/home-registered | PrimeFish DSS] home page or by clicking the appropriate menu link in the top navigation bar.

 

=== CPA home page ===

[[File:Cpa tool 1.png|The CPA tool landing page.]]

In the home page the users can define their company's profile information, including the country, which is used as a parameter to select which values to display as a benchmark when running the CPA tool. If the user selects France as their company's country, the results will be compared against the data collected for France. The user can change the value of any of the input fields in the '''Company Profile''' section located in the left side of the home page and click the ''update'' button to save the changes.

Right below this section the users can select additional search parameters before running the CPA tool. These parameters will set which industry, species and market data will be shown in the results page. Once the user click the '''Run CPA tool''' button, the user will be redirected to the results page where a graphical analysis will be shown. Completion of any survey is not required to run the tool, however any references to user value will be set to zero in the graphical comparison in the results page.

The firm-level survey can be accessed by clicking its respective '''Update survey''' button on the right section of the CPA home page, which will redirect the user to the survey page for the chose survey. The surveys are divided in two sections by industry (Aquaculture/Wild fish) and each one is further subdivided into three subsections:

#Threat Assessment Survey
#Bargaining Power Survey
#Rivalry Assessment Survey

 

=== CPA survey pages ===

[[File:Cpa tool 2.png|The CPA tool survey page.]]

After clicking the appropriate button and being redirected to the survey page, the user can then analyse and answer the survey by choosing the answers from the array of possibilities and then choosing to move to the next/previous survey or by returning to the home page. The survey answers are automatically saved as long as the user clicks one of the blue buttons on the bottom page of the current survey page to go to the next/previous survey or to go to the home page. If the users clicks the red '''Discard changes''' button, the current changes will not be saved and the user will be redirected to the CPA home page. The answers can be updated at any time and as many times as needed. Once the user is satisfied with his answers he can run the CPA tool by clicking the '''Run CPA tool''' button in the home page to get the results relative to their answers. The user can answer as many or as few questions from any survey as he/she wants, and return at any point in time to change their answers. A yellow progress bar for each subsection of the surveys is shown in the CPA home page to let the user know of the progress they made. If no answers have been given for a particular survey subgroup, no progress bar is shown and once the user answers all questions in a survey subgroup, the progress bar will turn green. The more answers the user gives, the more accurate the calculation for the CPA will be.

 

=== CPA results page ===

[[File:Cpa tool 3.png|The CPA tool results page - firm-level.]]

When the user clicks the '''Run CPA tool''' button, the results page will first display the user's FACI score, with details about their average score in each section and also detailed comparative scores for each answered question.

[[File:Cpa tool 4.png|The CPA tool results page - national-level.]]

The tool will also display the comparison between the user's chosen country National-level FACI score against all other countries participating in the study, with graphics also detailing the average score for each pillar and its sections. The user can choose to print the results by clicking the button on the sidebar in the results page, in addition to having the ability to download the bulk data collected in the research phase. The user can also return to the CPA home page and start another analysis or choose to use any other feature of the DSS.

 

== References & Readings ==

----

CPA

2018-10-18T12:37:44Z

Jacandrade:

PSC

2018-10-04T15:19:29Z

Jacandrade:

= Product Success Check =

----

----

== Introduction ==

----

 

Consumers are too numerous, dispersed, and varied in their buying requirements to make it possible to serve all efficiently and in the same manner. At the same time, in today’s competitive landscape, companies follow more and more customised approaches to serve and satisfy the consumers which again drives their ever more differentiated wants. As a consequence, markets become “demassified”, dissolving more and more into “micro-markets”, characterised by different consumers purchasing different products in different distribution channels and attending to different communication channels. Segmentation aims at identifying such micro markets, i.e. groups of consumers that share the same expectations and behavioural patterns. The identification of the most attractive micro-markets, i.e. segment(s), for the company and its products therefore is imperative not only for successful commercialisation but also for new product development.

Following a strategic approach to markets, the company distinguishes the major market segments based on the profiling of different consumer groups along their wants, consumption and purchasing behaviour; socio-demographic characteristics etc.; targets one or more of these segments; and develops products (and marketing programs) tailored to the profile and expectations of each selected segment.Tailoring starts with an understanding of the customers and providing them with the product and service they expect but, importantly, embraces also price, distribution and communication efforts to reach the target segment efficiently. The firm focus is on the buyers whom they have the greatest chance of satisfying. Having satisfied customers is at the basis for company success and the first step to repeat purchase and customer loyalty.

Evidence for new product development or new product commercialisation success factors shows that the analyses of market segments, targeting, positioning and the alignment with the firms’ offer and resources are crucial to both new product development and new product commercialisation. It follows that segmentation helps companies to navigate an increasingly competitive market, to understand their customers better, to develop offerings that satisfy specific wants, and to address diversity in an efficient manner.

The approach to developing a robust model to analyse the likelihood that new seafood product launches will be successful follows this perspective. We develop both country specific consumer segmentations in Italy, Germany, France, Spain and the UK, as well as an overarching European segmentation useful for companies that are innovating and developing new fish products or have fish products on offer and would like to improve their commercialisation. The segmentations are based on latent class analyses of representative samples of consumers (800 in each of the five countries) who replied to an online survey in June-July 2017.

Although the segment profiles by themselves are informative, the methodology used contains an additional step in order to help the company select the most appropriate target(s). In this second stage, multinomial regression matches product (and firm) attributes with the most attractive consumer segment(s). A comparison of the segment, i.e. consumer profile, with the product attributes will further inform the company on how to improve the product and/or its marketing effort in order to tailor more closely to segment wants and characteristics and ultimately launch and commercialise successfully. Figure 1 gives an overview of the success analysis model.

'''Figure 1: The success analysis model at a glance''' [[File:Psc fig 1.JPG|center|Figure 1: The success analysis model at a glance]]

 

== The tool ==

----

The PSC tool is being developed as a proxy for the multinomial regression algorithm created as a result of the research phase of the project. It presents the user with an interface to select the variables to be used in the algorithm which will calculate the profile and consumption probability of the product being analysed, and display to the user the results in a graphical, user friendly form.

=== PSC home page ===

The suer can access the PSC tool home page by clicking the quick access link in the DSS homepage or by clicking the appropriate link in the top navigation bar.

''PSC home page'' [[File:Psc home 1.png|center|PSC home page]] [[File:Psc home 2.png|center|PSC home page]]

Once in the PSC home page, the user must initially select 5 different attributes for the product being analysed in the ''Product attributes'' section. These are required attributes and must be selected before being able to see the results. Once these attributes are set, the user can additionally select more detailed attributes in the ''Other marketing attributes'' sections to increase the relevancy of the resulting analysed profile. Optionally, the user can also select preferred presentation formats in the selection box above the ''Perform product success check'' button, which will then be highlighted in the results page preferences graph.

Behind the scenes, when the user clicks the button to perform the PSC, the tool wraps the attributes chosen by the user and hands over to the R language script developed in the research part of the project, which in turn calculates the multinomial regression for the given attributes and returns the results to the DSS tool.

=== The results ===

''PSC results page'' [[File:Psc results 1.png|center|PSC results page]] [[File:Psc results 2.png|center|PSC results page]]

After a user click the button to perform the product success check, the results page will be displayed containing the description of the best matching consumer profile for the analysed product, as well as a graphical comparison of consumption probabilities for different product formats. The presentation formats selected in the previous page will be highlighted in the graph, and the selected attributes used for the regression will be displayed in the sidebar on the left.

 

=== Segments description ===

The table here below presents a summary of the segments identified in the single countries (and in the “total” EU countries) under study. Some segments are cross-national or pan-European (light blue, light red), while others are specific to a few (grey cells)/only one country (dark green). [[File:Psc table 1.png|center|Segment tables]]

==== Italy ====

'''The health & environmentally conscious''' consumer represents 13 % of the Italian consumers (trend: stable). Members of this segment are willing to pay (second highest expenditure for fish in Italy) for beneficial effects for both personal and environmental health. Predominantly women aged 50 + value items such as environmentally friendly, sustainability and natural ingredients, nutrients, easy-to digest characteristics highly. Appearance and traceability are also important to this segment, pointing to critical evaluation and check of quality/safety issues related to fish. They prefer wild fish, boneless and traditional recipes. Their favourite place of purchase is the supermarket/fishmonger which are also their sources of information. The segment’s usage rate is medium-high. Of note, consumers here like all fish species (although they consume sea bream and sea bass most) and buy a broad range of formats. The women and their small families (3 persons) reside in bigger urban centres, with children who are grown up but still live at home.

'''The brand-convenience-taste''' consumers reflect only a small but growing portion of the Italian market (7 %). This group of young consumers with small families declares to have a preferred brand and to favor taste over nutritional aspects. Highly important to them are availability of the fish, new formats, labels and omega 3. The consumers here also value fish products that take little time to prepare while nutrients or sustainability claims are of no importance to them. Consistent with a brand buyer is also the fact that these consumers are not self-efficacious– they rely instead on the familiarity and security that comes with a preferred brand and label (another aspect of “convenience”). In line with this profile is the supermarket as the only place of purchase, which is also, together with advertisements, the segment’s main source of information. People in this group live predominantly in rural areas of the country. The favourite species are salmon (ready-to-eat/to cook, fresh fillet), sea bream (fresh fillet) and cod (frozen fillet) with overall medium consumption and average expenditure.

'''The self-efficacious cooking artist''' represents 14 % of Italian consumers (trend: growing). Here we find the self-efficacious (all items that point to knowledge and evaluation of fish score high) relatively young male who likes to cook, is creative in meal preparation and looks for versatility. Consistent with the passion for cooking, saving time in meal preparation is unimportant to him. He looks for healthy products (with traceability) but also for a reasonable price-quality ratio. He and his partner (or small family) live in coastal/rural areas as well as in urban centres. The favourite place of purchase is the supermarket or the fishmonger, the source of information is the label or the advice from the fishmonger. Chooses predominantly sea bream, sea bass and cod in a wide range of formats (except ready to eat). Fish expenditure is average, in line with the fact that those who have more knowledge of fish can find more alternatives among available products.

'''The local connoisseur''' represents the biggest segment in Italy (24%/growing). This is the group of consumers who know everything about fish (high values across self-efficacy items), use its versatility and experiment with new formats or recipes. Relatively young women here (with small family) strongly emphasise the health-nutritional aspect and underline easy digestion. This group of consumers also favours local origin. They pay attention to environment and sustainability issues and indicate the preference for a (local) brand or seller. Emphasising value for money, they do not trade off quality for price (but would instead go for a cheaper species or stock the fish in order to be flexible). They prefer wild fish, are indifferent to bones, and are inclined to traditional preparation. Their consumption is medium-high (mainly sea bream, sea bass, less cod and salmon in a wide range of formats) with an expenditure that is the highest across all Italian segments. These consumers buy in the supermarket or at the fishmonger and do not indicate any sources of information.

'''Price-wise convenience''' consumers (14%/stable) represented in segment 5 are very price conscious, reflected also in their low expenditure on fish. People here are not knowledgeable about fish. They strongly underline health, easy-to-cook characteristics and texture. In line with this profile is their fish selection – they favour cod and salmon (fresh and frozen fillets but also canned, smoked, ready-to-cook/ready-to eat). Both genders aged 54 + are represented here, mainly living with one grown up child in rural and urban areas. Preferably they buy in supermarkets which are, together with advertisements, also the source of information.

'''The self-efficacious pragmatic fish''' consumers, a large (23%) and growing segment with high fish expenditure. They value the health benefits of fish, look for conservation and versatility. Preferences here bring together the health of both, individuals and the environment, added is a strong emphasis on value for money. Although this segment is knowledgeable about fish and its preparation, the profile seems to reflect a pragmatic instance of “having to eat and cook fish” without related pleasure of doing so. In fact, this segment has only two favourite species, namely salmon and cod, which they consume frequently, predominantly as fresh/frozen fillets. Women aged 45 + with small families, medium-high education and income represent the socio-demographic profile of this segment best.

'''Indifferent''' consumers are the smallest group of consumers (6%/stable), represented by relatively young male with small family living in rural or intermediate areas of Italy. Their favourite place of purchase is the supermarket. They consult the label or ads for fish information. Species include sea bream and salmon and their expenditure is among the lowest across the segments.

 

==== Spain ====

Segment 1 represents '''brand/seller “dependent” high quality''' consumers who are not self-efficacious (23%/growing). The preferred “brand“ here is either the shop/seller or the brand itself. Consumers do not feel on the safe side regarding fish evaluation and preparation and thus rely on the trusted seller/brand of whom they learn. They give importance to inclusive health (individual and environment) and have a broad quality understanding for which they are ready to pay. This segment shows high fish consumption and the highest expenditure for fish. Consistent with the fact that they like to cook but do not indicate corresponding competence they go for a very limited range of species. They buy in supermarkets or at the fishmonger and listen to the advice of the fishmonger or seller. Women aged 46 + with small children (who eat fish) and low-medium education but relatively high income best represent this group of consumers. Favourite species are sea bream (whole/fresh fillet) and cod (fresh/frozen fillet, dried).

'''Self-efficacious selfish brand buyer''' (23%/growing): also this group of consumers has a preferred brand/seller but it is, as compared to segment 1, self-efficacious. It is “egoistic” in terms of health orientation as only items which focus on individual health are important (while environmental attention is unimportant) to this segment. Men around 55 here take care of their family which lives in cities close to the coast. They are medium sea bass and salmon consumers who spend relatively little on fish.

'''The independent “good for me” connoisseur''' (9%, growing) values taste and nutrition equally. Members of this segment love fish (sensory appeal) and they value its benefits for health. They cross-check on labels and expect a guaranteed origin. In line with this, the segments favourite species is wild fresh sea bass which is consumed in high quantities. Women aged 48, living with family in cities at the coast are willing to spend for their selected premium sea bass which they preferably buy at the fishmonger or in the supermarket.

The consumers in the 4th and biggest (29 %, stable) segment in Spain are directed towards '''nutritional-digestive and inclusive health (360 degree-health)'''. Consistent with this emphasis is the importance given to origin and traceability. Value for money is crucial to this segment, and they value conservation. Their medium-high fish consumption is reflected also in a relatively high fish expenditure mainly spent on fresh sea bream and salmon (fresh/smoked). Young women here take care of their families with young children.

'''(Salmon) Cooking artists (9%/stable)''', very young couples (24 +), like to cook and trust in their competence of fish (salmon) preparation, they are creative and experiment with new formats, and they emphasise versatility. None of the health related items is of importance. The young couples go mainly for wild salmon (medium –high consumption) in the supermarket. Salmon is the dominant species they buy in all formats. Consistent with the artist stance is also the (low) use of an exotic species such as herring. The main source of information is the seller.

'''The indifferent''' (7%/stable), with medium-low consumption of salmon and cod, spends little on fish. Typically consumers here are young male, small family size, low education level living in urban centers in the countryside.

==== France ====

'''The good for me health''' consumer represents 29 % of the French market (trend: stable) that expects mainly health benefits from fish consumption and looks for guarantees in terms of sustainability certifications and traceability. Predominantly consisting of male in their fifties, highly educated and with high income, this segment appreciates “easy-to-cook” products and emphasises value for money. It is characterised by low-medium consumption and low expenditure for sea bream (either fresh fillet or ready-to-eat). Shopping for two, predominantly in supermarkets, these men use the label or the seller for information.

'''The health oriented (selfish), (not creative) cook''' (23%/growing) is medium-high in fish consumption and the highest in expenditure. Women aged around 45 highly value the health benefits of fish, they like cooking and the variety and versatility that comes with many species and a wide range of formats (herring, cod and sea bream) in traditional preparations. They purchase in the supermarket for a small family and take information from the label and the seller.

'''The cooking artist''' represents around a quarter of fish consumers in France (trend: stable). This profile cuts across all ages, also the very young. They choose carefully, go for high quality for which they are ready to pay and they consult many information sources. Health is not on the agenda of this segment and they have no environmental concerns. They shop for sea bream at the supermarket or at the fishmonger. The couple prefers fresh, but they are flexible and willing to try different formats and recipes.

'''Self-efficacious convenience''' consumer to whom, beyond inclusive health, convenience is central (31%/stable). They give importance to each and every aspect and thus represents very demanding consumers. This consumer critically checks the expected quality: reads labels and values certificates and guarantees. Medium consumption of varied fish species and broad range of formats (reflecting convenience), and second highest expenditure on fish. Relatively young women and men are representing the class, living in the countryside/intermediate cities in small families.

'''The indifferent''' in France are the smallest group of consumers (7%/stable). The class is on a medium-low level in fish consumption and the lowest expenditure for trout, salmon and cod. Prefer mainly in fresh and frozen formats. The segment is predominantly young singles or couple, living in the countryside in smaller cities.

In all segments salmon and trout is consumed. The species mentioned above distinguish the segments from this overall baseline consumption.

==== Germany ====

'''The cooking artist''' (12%/stable) is loyal to a brand/seller and gives importance to local origin. Consumers in this segment share the characteristics that cut across-countries for the cooking artist: they like to cook/are capable of preparing fish, value versatility, are creative and ready to try new formats. Taste here clearly dominates nutritional aspects (only Omega 3 is of importance). Consumers in this segment are not price sensitive, a fact reflected also in the highest fish expenditure across German segments. They prefer fresh fish, medium usage rate, mainly salmon but also the more “exotic” sea bream (the only segment in Germany) and sea bass. The class includes both genders, they are young, live with a small family with smaller kids in cities in the countryside.

'''Healthy & environmentally-conscious''' consumers make up a third of the German market (growing). To consumers in this segment, a healthy diet and a natural product and the texture are central. Health here is inclusive of the environment, consumers value sustainability certification and put emphasis on a guaranteed origin. They are not self-efficacious and thus trust their “seller/brand”, but also consult the label and ask for guarantees. The group is ready to pay for the value they ask for, i.e. a healthy & environmentally safe diet, which is reflected in high fish expenditure. The class includes both genders aged over 54 involved in decisions and patterns of fish consumption (salmon, trout and sea bass; fresh and frozen); consistent with their health focus their consumption is medium high.

'''The convenience- brand loyal''' consumer (23%/growing), looks for value for money. Brands provide the benefits she asks for: nutrients, sustainability certification, traceability, label. Ready-to-eat is emphasised which together with fresh formats may satisfied her want for creativity. Predominantly relatively young female living in a two-person-household in cities in the countryside with lower fish expenditure and medium fish consumption represent this cluster best. The members of this segment shop in supermarkets where they get information in-store, from the seller or from the label.

The fourth segment comprises '''healthy cooking artists''' who like variety. Being a premium segment in terms of expenditure, this profile unites the cooking artist with a focus on health. Versatility is important, but experimentation is also reflected in a broad range of species and formats. The socio-demographic profile of women over 54, with medium high education, in 2 person-households, is very much in line with this segment.

'''Cheap brand and taste''' consumer (16%/stable): People in this segment have learned the claims of their preferred brand (but they are not knowledgeable about fish), omega 3 and tasty, they are price-conscious and, overall, seem to go for an easy buy without much involvement or major decision criteria. Fish here offers the best compromise between health and taste. No importance is given to origin and traceability. Male in their forties (couple) spend little for medium-low consumption.

'''The indifferent''' present around 7 % of the market, predominantly young and single. Medium consumption, relatively high expenditure and a broad range of species and formats.

Of note, herring is consumed in all segments. The species mentioned above distinguish the segments from this overall baseline consumption.

 

==== UK ====

'''Healthy convenience''' consumers (22 %, growing) have their focus on “easy” to cook, to stock, to use (versatile). Health is also central, with a strong focus on digestion and environmental concern and the request for traceability. The segment is characterised by medium consumption and highest expenditure on fish across the segments. Women, aged above 50 with medium-high education and a 2-person household describe the segment best. Members of this segment appreciate wild fish; their favourite species are sea bream, sea bass – fresh fillets, ready-to-eat, whole fish.

'''Selfish health & convenience''' consumers, the biggest segment (43 %, growing) are typically younger couples with medium – low income but relatively high expenditure on fish. They are informed and are consulting many information sources, do not trade off quality for price and are indifferent to brands, origin and traceability. The focus is on health, but also easy to cook, versatility, and conservation are important. Consume salmon and sea bass in medium quantity. This segment is similar to segment 1 in convenience but health is not inclusive and more focused on nutrients than on digestion and its information behaviour is more extensive.

'''Cooking artist''' (8 %/stable trend). Similar to her counterparts in the other countries, the British cooking artist likes to cook and to experiment with new formats. Taste is an important theme, while she is indifferent to health and environmental concerns; dietary issues are not important. British cooking artists are not really knowledgeable about fish. Women aged 44+ in small families with children eating fish do best describe the socio-demographic characteristics. Prefer wild, favourite species sea bream and cod. Given the low income she really likes and spends (over proportionally) for fish.

'''Self-efficacious & local ecologist''' (13 %/growing segment) are very young singles or 2-person households. They are knowledgeable and environmentally conscious. At the same time they give much importance to the local context. The segment members enjoy cooking and they trust in their meal preparation. Medium consumption of salmon, sea bream, sea bass, but with low expenditure.

The segment of '''indifferent''' (14 %, growing) is composed of young male, single or in a household of two, and low to medium education. Prefer salmon and cod, ready to eat, ready to cook. Medium consumers, low expenditure.

In all segments cod is consumed. The species mentioned above distinguish the segments from this overall baseline consumption.

==== Europe ====

We construct 11 European segments which are briefly discussed here below.

'''The salmon fan''' segment (9 %/growing), in line with the only species it consumes, values highest omega 3, availability, versatility and value for money. These consumers also clearly favor taste over nutritional aspects. Consumers here are women in their forties, living in households of two persons with medium – high salmon consumption of all formats and relatively high expenditure. In terms of relative composition, this segment is very prominent in the UK (29 %).

Segment two represents the '''self-efficacious inclusive health''' consumer, one of the largest EU segments (17 %, growing): knowledgeable people who appreciate the health-nutritional aspect of fish. Dietary considerations are not important (e.g. nr. of calories). Health includes the well being of the environment. People emphasise value for money, expect traceability and certification but are indifferent with regard to organic products. Male and female consumers aged around 50, with medium expenditure and fish consumption; favourite species are salmon, sea bream, cod with wide variety of formats. Germans make up 24 % of this segment.

'''Cooks with inclusive health focus''' (11%) characterise segment 3. They enjoy meal preparation (but are neither creative nor knowledgeable of fish) and emphasise omega 3 and “easy-to-digest” attributes. Their overall important theme is individual and environmental health, and, importantly, animal welfare, which is cross-checked with label and certifications. The segment is not price sensitive and is ready to pay for the expected value. Relatively young men here take care of small families who live in urban centres in the countryside. Low-medium consumption, but relatively high expenditure on fish. UK dominated with 27% of consumers in this segment (trend: stable).

'''Tasty and easy quality''' (8%). To this segment value for money is important as are “easy to cook” and quick preparation of meals. Availability and conservation is stressed, emphasising the time/convenience posture of the segment. Taste and texture are valued more than health aspects. No environmental concerns and also self-efficacy criteria are low/indifferent. Young male (early thirties) with medium-high education take care of small families. They prefer wild over farmed and spend much for taste and easy quality - high expenditure for medium-high fish consumption. Segment is mainly populated by French, Spanish and Italians (trend: increasing).

Segment 5 is the '''360 degree- health oriented''' segment (11%), which gives much importance to natural fish products. Also “easy to digest” and nutrients are of utmost importance, as is the absence of smell and a guaranteed origin. It is the only segment where people also have a concern regarding negative effects of farming. Consistent with this preference they favour wild fish. The segment is characterised by medium-high fish consumption with corresponding high expenditure. Women in their 50s in 2-people households with medium education represent best the demographic profile of the segment. Italians dominate this segment (trend: increasing ).

Segment 6, one of the smallest in EU (5 %), is characterising the '''innovative brand buyer'''. Consumers here have a favourite brand to which they are also loyal. “Claim”-related items are important but not supported by corresponding factual knowledge. People here are also the only ones to underline new dietary preparations (e.g. gluten free products), they prefer products that take little time for preparation, and they emphasise conservation and versatility. Time, overall, is an important factor for this group. The known brand is a response to this: choosing the familiar brand saves time in terms of reflection/selection and it is a guarantee for satisfied expectations. Consumption of this segment is high with corresponding highest expenditure across all segments. British, Italian and French women around 45, with small families make up this segment (trend: increasing).

'''Indifferent''': the majority of indifferent consumers is divided among UK (31 %) and France (27 %), followed by Spain and Germany (15 % and 14 %, respectively), with a stable trend. Only 12 % of the class is populated by Italian consumers. This segment is characterised by male and female aged 18-40, with low education and medium-low consumption. Expenditure, not surprisingly, is the lowest.

'''Healthy convenience''' (6 %). Segment 8 consumers look for easy to cook meals that take little time to prepare, appreciate conservation and general health/environmental benefits. Being demanding on all dimensions, they are ready to pay for the corresponding products. As confirmed by high fish expenditure, consumers do not trade off value for money. Here young dads with medium-high education take care of their bigger families’ health by balancing it with the need to have meals easily and quickly prepared (trend: stable). Only Italy is underrepresented (16 %) in this overall balanced segment.

This group –'''the local – natural brand/seller''' (5 %) - values “local” and natural highly. More than emphasising the presence of positive nutrients and elements, consumers here emphasise the absence of ingredients and substances. They are self-efficacious, trust a certain – local – brand or seller to whom they are loyal. They also stress availability. Fish consumption is medium – low, expenditure is at the lower level across segments. The socio-demographic show relatively young men and women in households of three holding a medium education level. German consumers account for 27 % of this small segment (trend: stable).

In this segment we find the '''cook with selfish health focus''' (8%) who likes taste and nutrition. Broader health, dietary or environmental concerns are not considered important. Consistent with enjoying the preparation and consumption of fish, this segment’s expenditure is medium-high with corresponding high expenditure. Relatively young Spanish women in small households without children best describe the consumers of this segment (trend: increasing).

'''Cooking artists''' (17 %, stable) are creative, like to experiment with new formats, like to cook and are self-efficacious. No environmental and health concerns. Women in their fifties in small households (2-3 members) with medium consumption and relatively low expenditure characterise this segment’s demographic profile. The majority of the class is made of Italians, while the minority comes from UK.

== References & Readings ==

PSC

2018-10-04T15:17:30Z

Jacandrade:

= Product Success Check =

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== Introduction ==

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Consumers are too numerous, dispersed, and varied in their buying requirements to make it possible to serve all efficiently and in the same manner. At the same time, in today’s competitive landscape, companies follow more and more customised approaches to serve and satisfy the consumers which again drives their ever more differentiated wants. As a consequence, markets become “demassified”, dissolving more and more into “micro-markets”, characterised by different consumers purchasing different products in different distribution channels and attending to different communication channels. Segmentation aims at identifying such micro markets, i.e. groups of consumers that share the same expectations and behavioural patterns. The identification of the most attractive micro-markets, i.e. segment(s), for the company and its products therefore is imperative not only for successful commercialisation but also for new product development.

Following a strategic approach to markets, the company distinguishes the major market segments based on the profiling of different consumer groups along their wants, consumption and purchasing behaviour; socio-demographic characteristics etc.; targets one or more of these segments; and develops products (and marketing programs) tailored to the profile and expectations of each selected segment.Tailoring starts with an understanding of the customers and providing them with the product and service they expect but, importantly, embraces also price, distribution and communication efforts to reach the target segment efficiently. The firm focus is on the buyers whom they have the greatest chance of satisfying. Having satisfied customers is at the basis for company success and the first step to repeat purchase and customer loyalty.

Evidence for new product development or new product commercialisation success factors shows that the analyses of market segments, targeting, positioning and the alignment with the firms’ offer and resources are crucial to both new product development and new product commercialisation. It follows that segmentation helps companies to navigate an increasingly competitive market, to understand their customers better, to develop offerings that satisfy specific wants, and to address diversity in an efficient manner.

The approach to developing a robust model to analyse the likelihood that new seafood product launches will be successful follows this perspective. We develop both country specific consumer segmentations in Italy, Germany, France, Spain and the UK, as well as an overarching European segmentation useful for companies that are innovating and developing new fish products or have fish products on offer and would like to improve their commercialisation. The segmentations are based on latent class analyses of representative samples of consumers (800 in each of the five countries) who replied to an online survey in June-July 2017.

Although the segment profiles by themselves are informative, the methodology used contains an additional step in order to help the company select the most appropriate target(s). In this second stage, multinomial regression matches product (and firm) attributes with the most attractive consumer segment(s). A comparison of the segment, i.e. consumer profile, with the product attributes will further inform the company on how to improve the product and/or its marketing effort in order to tailor more closely to segment wants and characteristics and ultimately launch and commercialise successfully. Figure 1 gives an overview of the success analysis model.

'''Figure 1: The success analysis model at a glance''' [[File:Psc fig 1.JPG|center|Figure 1: The success analysis model at a glance]]

 

== The tool ==

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The PSC tool is being developed as a proxy for the multinomial regression algorithm created as a result of the research phase of the project. It presents the user with an interface to select the variables to be used in the algorithm which will calculate the profile and consumption probability of the product being analysed, and display to the user the results in a graphical, user friendly form.

=== PSC home page ===

The suer can access the PSC tool home page by clicking the quick access link in the DSS homepage or by clicking the appropriate link in the top navigation bar.

''PSC home page'' [[File:Psc home 1.png|center|PSC home page]] [[File:Psc home 2.png|center|PSC home page]]

Once in the PSC home page, the user must initially select 5 different attributes for the product being analysed in the ''Product attributes'' section. These are required attributes and must be selected before being able to see the results. Once these attributes are set, the user can additionally select more detailed attributes in the ''Other marketing attributes'' sections to increase the relevancy of the resulting analysed profile. Optionally, the user can also select preferred presentation formats in the selection box above the ''Perform product success check'' button, which will then be highlighted in the results page preferences graph.

Behind the scenes, when the user clicks the button to perform the PSC, the tool wraps the attributes chosen by the user and hands over to the R language script developed in the research part of the project, which in turn calculates the multinomial regression for the given attributes and returns the results to the DSS tool.

=== The results ===

''PSC results page'' [[File:Psc results 1.png|center|PSC results page]] [[File:Psc results 2.png|center|PSC results page]]

After a user click the button to perform the product success check, the results page will be displayed containing the description of the best matching consumer profile for the analysed product, as well as a graphical comparison of consumption probabilities for different product formats. The presentation formats selected in the previous page will be highlighted in the graph, and the selected attributes used for the regression will be displayed in the sidebar on the left.

 

=== Segments description ===

The table here below presents a summary of the segments identified in the single countries (and in the “total” EU countries) under study. Some segments are cross-national or pan-European (light blue, light red), while others are specific to a few (grey cells)/only one country (dark green). [[File:Psc table 1.png|center|Segment tables]]

==== Italy ====

'''The health & environmentally conscious''' consumer represents 13 % of the Italian consumers (trend: stable). Members of this segment are willing to pay (second highest expenditure for fish in Italy) for beneficial effects for both personal and environmental health. Predominantly women aged 50 + value items such as environmentally friendly, sustainability and natural ingredients, nutrients, easy-to digest characteristics highly. Appearance and traceability are also important to this segment, pointing to critical evaluation and check of quality/safety issues related to fish. They prefer wild fish, boneless and traditional recipes. Their favourite place of purchase is the supermarket/fishmonger which are also their sources of information. The segment’s usage rate is medium-high. Of note, consumers here like all fish species (although they consume sea bream and sea bass most) and buy a broad range of formats. The women and their small families (3 persons) reside in bigger urban centres, with children who are grown up but still live at home.

''The brand-convenience-taste''' consumers reflect only a small but growing portion of the Italian market (7 %). This group of young consumers with small families declares to have a preferred brand and to favor taste over nutritional aspects. Highly important to them are availability of the fish, new formats, labels and omega 3. The consumers here also value fish products that take little time to prepare while nutrients or sustainability claims are of no importance to them. Consistent with a brand buyer is also the fact that these consumers are not self-efficacious– they rely instead on the familiarity and security that comes with a preferred brand and label (another aspect of “convenience”). In line with this profile is the supermarket as the only place of purchase, which is also, together with advertisements, the segment’s main source of information. People in this group live predominantly in rural areas of the country. The favourite species are salmon (ready-to-eat/to cook, fresh fillet), sea bream (fresh fillet) and cod (frozen fillet) with overall medium consumption and average expenditure.

'''The self-efficacious cooking artist''' represents 14 % of Italian consumers (trend: growing). Here we find the self-efficacious (all items that point to knowledge and evaluation of fish score high) relatively young male who likes to cook, is creative in meal preparation and looks for versatility. Consistent with the passion for cooking, saving time in meal preparation is unimportant to him. He looks for healthy products (with traceability) but also for a reasonable price-quality ratio. He and his partner (or small family) live in coastal/rural areas as well as in urban centres. The favourite place of purchase is the supermarket or the fishmonger, the source of information is the label or the advice from the fishmonger. Chooses predominantly sea bream, sea bass and cod in a wide range of formats (except ready to eat). Fish expenditure is average, in line with the fact that those who have more knowledge of fish can find more alternatives among available products.

'''The local connoisseur''' represents the biggest segment in Italy (24%/growing). This is the group of consumers who know everything about fish (high values across self-efficacy items), use its versatility and experiment with new formats or recipes. Relatively young women here (with small family) strongly emphasise the health-nutritional aspect and underline easy digestion. This group of consumers also favours local origin. They pay attention to environment and sustainability issues and indicate the preference for a (local) brand or seller. Emphasising value for money, they do not trade off quality for price (but would instead go for a cheaper species or stock the fish in order to be flexible). They prefer wild fish, are indifferent to bones, and are inclined to traditional preparation. Their consumption is medium-high (mainly sea bream, sea bass, less cod and salmon in a wide range of formats) with an expenditure that is the highest across all Italian segments. These consumers buy in the supermarket or at the fishmonger and do not indicate any sources of information.

'''Price-wise convenience''' consumers (14%/stable) represented in segment 5 are very price conscious, reflected also in their low expenditure on fish. People here are not knowledgeable about fish. They strongly underline health, easy-to-cook characteristics and texture. In line with this profile is their fish selection – they favour cod and salmon (fresh and frozen fillets but also canned, smoked, ready-to-cook/ready-to eat). Both genders aged 54 + are represented here, mainly living with one grown up child in rural and urban areas. Preferably they buy in supermarkets which are, together with advertisements, also the source of information.

'''The self-efficacious pragmatic fish''' consumers, a large (23%) and growing segment with high fish expenditure. They value the health benefits of fish, look for conservation and versatility. Preferences here bring together the health of both, individuals and the environment, added is a strong emphasis on value for money. Although this segment is knowledgeable about fish and its preparation, the profile seems to reflect a pragmatic instance of “having to eat and cook fish” without related pleasure of doing so. In fact, this segment has only two favourite species, namely salmon and cod, which they consume frequently, predominantly as fresh/frozen fillets. Women aged 45 + with small families, medium-high education and income represent the socio-demographic profile of this segment best.

'''Indifferent''' consumers are the smallest group of consumers (6%/stable), represented by relatively young male with small family living in rural or intermediate areas of Italy. Their favourite place of purchase is the supermarket. They consult the label or ads for fish information. Species include sea bream and salmon and their expenditure is among the lowest across the segments.

 

==== Spain ====

Segment 1 represents '''brand/seller “dependent” high quality''' consumers who are not self-efficacious (23%/growing). The preferred “brand“ here is either the shop/seller or the brand itself. Consumers do not feel on the safe side regarding fish evaluation and preparation and thus rely on the trusted seller/brand of whom they learn. They give importance to inclusive health (individual and environment) and have a broad quality understanding for which they are ready to pay. This segment shows high fish consumption and the highest expenditure for fish. Consistent with the fact that they like to cook but do not indicate corresponding competence they go for a very limited range of species. They buy in supermarkets or at the fishmonger and listen to the advice of the fishmonger or seller. Women aged 46 + with small children (who eat fish) and low-medium education but relatively high income best represent this group of consumers. Favourite species are sea bream (whole/fresh fillet) and cod (fresh/frozen fillet, dried).

'''Self-efficacious selfish brand buyer''' (23%/growing): also this group of consumers has a preferred brand/seller but it is, as compared to segment 1, self-efficacious. It is “egoistic” in terms of health orientation as only items which focus on individual health are important (while environmental attention is unimportant) to this segment. Men around 55 here take care of their family which lives in cities close to the coast. They are medium sea bass and salmon consumers who spend relatively little on fish.

'''The independent “good for me” connoisseur''' (9%, growing) values taste and nutrition equally. Members of this segment love fish (sensory appeal) and they value its benefits for health. They cross-check on labels and expect a guaranteed origin. In line with this, the segments favourite species is wild fresh sea bass which is consumed in high quantities. Women aged 48, living with family in cities at the coast are willing to spend for their selected premium sea bass which they preferably buy at the fishmonger or in the supermarket.

The consumers in the 4th and biggest (29 %, stable) segment in Spain are directed towards '''nutritional-digestive and inclusive health (360 degree-health)'''. Consistent with this emphasis is the importance given to origin and traceability. Value for money is crucial to this segment, and they value conservation. Their medium-high fish consumption is reflected also in a relatively high fish expenditure mainly spent on fresh sea bream and salmon (fresh/smoked). Young women here take care of their families with young children.

'''(Salmon) Cooking artists (9%/stable)''', very young couples (24 +), like to cook and trust in their competence of fish (salmon) preparation, they are creative and experiment with new formats, and they emphasise versatility. None of the health related items is of importance. The young couples go mainly for wild salmon (medium –high consumption) in the supermarket. Salmon is the dominant species they buy in all formats. Consistent with the artist stance is also the (low) use of an exotic species such as herring. The main source of information is the seller.

'''The indifferent''' (7%/stable), with medium-low consumption of salmon and cod, spends little on fish. Typically consumers here are young male, small family size, low education level living in urban centers in the countryside.

==== France ====

'''The good for me health''' consumer represents 29 % of the French market (trend: stable) that expects mainly health benefits from fish consumption and looks for guarantees in terms of sustainability certifications and traceability. Predominantly consisting of male in their fifties, highly educated and with high income, this segment appreciates “easy-to-cook” products and emphasises value for money. It is characterised by low-medium consumption and low expenditure for sea bream (either fresh fillet or ready-to-eat). Shopping for two, predominantly in supermarkets, these men use the label or the seller for information.

'''The health oriented (selfish), (not creative) cook''' (23%/growing) is medium-high in fish consumption and the highest in expenditure. Women aged around 45 highly value the health benefits of fish, they like cooking and the variety and versatility that comes with many species and a wide range of formats (herring, cod and sea bream) in traditional preparations. They purchase in the supermarket for a small family and take information from the label and the seller.

'''The cooking artist''' represents around a quarter of fish consumers in France (trend: stable). This profile cuts across all ages, also the very young. They choose carefully, go for high quality for which they are ready to pay and they consult many information sources. Health is not on the agenda of this segment and they have no environmental concerns. They shop for sea bream at the supermarket or at the fishmonger. The couple prefers fresh, but they are flexible and willing to try different formats and recipes.

'''Self-efficacious convenience''' consumer to whom, beyond inclusive health, convenience is central (31%/stable). They give importance to each and every aspect and thus represents very demanding consumers. This consumer critically checks the expected quality: reads labels and values certificates and guarantees. Medium consumption of varied fish species and broad range of formats (reflecting convenience), and second highest expenditure on fish. Relatively young women and men are representing the class, living in the countryside/intermediate cities in small families.

'''The indifferent''' in France are the smallest group of consumers (7%/stable). The class is on a medium-low level in fish consumption and the lowest expenditure for trout, salmon and cod. Prefer mainly in fresh and frozen formats. The segment is predominantly young singles or couple, living in the countryside in smaller cities.

In all segments salmon and trout is consumed. The species mentioned above distinguish the segments from this overall baseline consumption.

==== Germany ====

'''The cooking artist''' (12%/stable) is loyal to a brand/seller and gives importance to local origin. Consumers in this segment share the characteristics that cut across-countries for the cooking artist: they like to cook/are capable of preparing fish, value versatility, are creative and ready to try new formats. Taste here clearly dominates nutritional aspects (only Omega 3 is of importance). Consumers in this segment are not price sensitive, a fact reflected also in the highest fish expenditure across German segments. They prefer fresh fish, medium usage rate, mainly salmon but also the more “exotic” sea bream (the only segment in Germany) and sea bass. The class includes both genders, they are young, live with a small family with smaller kids in cities in the countryside.

'''Healthy & environmentally-conscious''' consumers make up a third of the German market (growing). To consumers in this segment, a healthy diet and a natural product and the texture are central. Health here is inclusive of the environment, consumers value sustainability certification and put emphasis on a guaranteed origin. They are not self-efficacious and thus trust their “seller/brand”, but also consult the label and ask for guarantees. The group is ready to pay for the value they ask for, i.e. a healthy & environmentally safe diet, which is reflected in high fish expenditure. The class includes both genders aged over 54 involved in decisions and patterns of fish consumption (salmon, trout and sea bass; fresh and frozen); consistent with their health focus their consumption is medium high.

'''The convenience- brand loyal''' consumer (23%/growing), looks for value for money. Brands provide the benefits she asks for: nutrients, sustainability certification, traceability, label. Ready-to-eat is emphasised which together with fresh formats may satisfied her want for creativity. Predominantly relatively young female living in a two-person-household in cities in the countryside with lower fish expenditure and medium fish consumption represent this cluster best. The members of this segment shop in supermarkets where they get information in-store, from the seller or from the label.

The fourth segment comprises '''healthy cooking artists''' who like variety. Being a premium segment in terms of expenditure, this profile unites the cooking artist with a focus on health. Versatility is important, but experimentation is also reflected in a broad range of species and formats. The socio-demographic profile of women over 54, with medium high education, in 2 person-households, is very much in line with this segment.

'''Cheap brand and taste''' consumer (16%/stable): People in this segment have learned the claims of their preferred brand (but they are not knowledgeable about fish), omega 3 and tasty, they are price-conscious and, overall, seem to go for an easy buy without much involvement or major decision criteria. Fish here offers the best compromise between health and taste. No importance is given to origin and traceability. Male in their forties (couple) spend little for medium-low consumption.

'''The indifferent''' present around 7 % of the market, predominantly young and single. Medium consumption, relatively high expenditure and a broad range of species and formats.

Of note, herring is consumed in all segments. The species mentioned above distinguish the segments from this overall baseline consumption.

 

==== UK ====

'''Healthy convenience''' consumers (22 %, growing) have their focus on “easy” to cook, to stock, to use (versatile). Health is also central, with a strong focus on digestion and environmental concern and the request for traceability. The segment is characterised by medium consumption and highest expenditure on fish across the segments. Women, aged above 50 with medium-high education and a 2-person household describe the segment best. Members of this segment appreciate wild fish; their favourite species are sea bream, sea bass – fresh fillets, ready-to-eat, whole fish.

'''Selfish health & convenience''' consumers, the biggest segment (43 %, growing) are typically younger couples with medium – low income but relatively high expenditure on fish. They are informed and are consulting many information sources, do not trade off quality for price and are indifferent to brands, origin and traceability. The focus is on health, but also easy to cook, versatility, and conservation are important. Consume salmon and sea bass in medium quantity. This segment is similar to segment 1 in convenience but health is not inclusive and more focused on nutrients than on digestion and its information behaviour is more extensive.

'''Cooking artist''' (8 %/stable trend). Similar to her counterparts in the other countries, the British cooking artist likes to cook and to experiment with new formats. Taste is an important theme, while she is indifferent to health and environmental concerns; dietary issues are not important. British cooking artists are not really knowledgeable about fish. Women aged 44+ in small families with children eating fish do best describe the socio-demographic characteristics. Prefer wild, favourite species sea bream and cod. Given the low income she really likes and spends (over proportionally) for fish.

'''Self-efficacious & local ecologist''' (13 %/growing segment) are very young singles or 2-person households. They are knowledgeable and environmentally conscious. At the same time they give much importance to the local context. The segment members enjoy cooking and they trust in their meal preparation. Medium consumption of salmon, sea bream, sea bass, but with low expenditure.

The segment of '''indifferent''' (14 %, growing) is composed of young male, single or in a household of two, and low to medium education. Prefer salmon and cod, ready to eat, ready to cook. Medium consumers, low expenditure.

In all segments cod is consumed. The species mentioned above distinguish the segments from this overall baseline consumption.

==== Europe ====

We construct 11 European segments which are briefly discussed here below.

'''The salmon fan''' segment (9 %/growing), in line with the only species it consumes, values highest omega 3, availability, versatility and value for money. These consumers also clearly favor taste over nutritional aspects. Consumers here are women in their forties, living in households of two persons with medium – high salmon consumption of all formats and relatively high expenditure. In terms of relative composition, this segment is very prominent in the UK (29 %).

Segment two represents the '''self-efficacious inclusive health''' consumer, one of the largest EU segments (17 %, growing): knowledgeable people who appreciate the health-nutritional aspect of fish. Dietary considerations are not important (e.g. nr. of calories). Health includes the well being of the environment. People emphasise value for money, expect traceability and certification but are indifferent with regard to organic products. Male and female consumers aged around 50, with medium expenditure and fish consumption; favourite species are salmon, sea bream, cod with wide variety of formats. Germans make up 24 % of this segment.

'''Cooks with inclusive health focus''' (11%) characterise segment 3. They enjoy meal preparation (but are neither creative nor knowledgeable of fish) and emphasise omega 3 and “easy-to-digest” attributes. Their overall important theme is individual and environmental health, and, importantly, animal welfare, which is cross-checked with label and certifications. The segment is not price sensitive and is ready to pay for the expected value. Relatively young men here take care of small families who live in urban centres in the countryside. Low-medium consumption, but relatively high expenditure on fish. UK dominated with 27% of consumers in this segment (trend: stable).

'''Tasty and easy quality''' (8%). To this segment value for money is important as are “easy to cook” and quick preparation of meals. Availability and conservation is stressed, emphasising the time/convenience posture of the segment. Taste and texture are valued more than health aspects. No environmental concerns and also self-efficacy criteria are low/indifferent. Young male (early thirties) with medium-high education take care of small families. They prefer wild over farmed and spend much for taste and easy quality - high expenditure for medium-high fish consumption. Segment is mainly populated by French, Spanish and Italians (trend: increasing).

Segment 5 is the '''360 degree- health oriented''' segment (11%), which gives much importance to natural fish products. Also “easy to digest” and nutrients are of utmost importance, as is the absence of smell and a guaranteed origin. It is the only segment where people also have a concern regarding negative effects of farming. Consistent with this preference they favour wild fish. The segment is characterised by medium-high fish consumption with corresponding high expenditure. Women in their 50s in 2-people households with medium education represent best the demographic profile of the segment. Italians dominate this segment (trend: increasing ).

Segment 6, one of the smallest in EU (5 %), is characterising the'''innovative brand buyer'''. Consumers here have a favourite brand to which they are also loyal. “Claim”-related items are important but not supported by corresponding factual knowledge. People here are also the only ones to underline new dietary preparations (e.g. gluten free products), they prefer products that take little time for preparation, and they emphasise conservation and versatility. Time, overall, is an important factor for this group. The known brand is a response to this: choosing the familiar brand saves time in terms of reflection/selection and it is a guarantee for satisfied expectations. Consumption of this segment is high with corresponding highest expenditure across all segments. British, Italian and French women around 45, with small families make up this segment (trend: increasing).

'''Indifferent''': the majority of indifferent consumers is divided among UK (31 %) and France (27 %), followed by Spain and Germany (15 % and 14 %, respectively), with a stable trend. Only 12 % of the class is populated by Italian consumers. This segment is characterised by male and female aged 18-40, with low education and medium-low consumption. Expenditure, not surprisingly, is the lowest.

'''Healthy convenience''' (6 %). Segment 8 consumers look for easy to cook meals that take little time to prepare, appreciate conservation and general health/environmental benefits. Being demanding on all dimensions, they are ready to pay for the corresponding products. As confirmed by high fish expenditure, consumers do not trade off value for money. Here young dads with medium-high education take care of their bigger families’ health by balancing it with the need to have meals easily and quickly prepared (trend: stable). Only Italy is underrepresented (16 %) in this overall balanced segment.

This group –'''the local – natural brand/seller''' (5 %) - values “local” and natural highly. More than emphasising the presence of positive nutrients and elements, consumers here emphasise the absence of ingredients and substances. They are self-efficacious, trust a certain – local – brand or seller to whom they are loyal. They also stress availability. Fish consumption is medium – low, expenditure is at the lower level across segments. The socio-demographic show relatively young men and women in households of three holding a medium education level. German consumers account for 27 % of this small segment (trend: stable).

In this segment we find the '''cook with selfish health focus''' (8%) who likes taste and nutrition. Broader health, dietary or environmental concerns are not considered important. Consistent with enjoying the preparation and consumption of fish, this segment’s expenditure is medium-high with corresponding high expenditure. Relatively young Spanish women in small households without children best describe the consumers of this segment (trend: increasing).

'''Cooking artists''' (17 %, stable) are creative, like to experiment with new formats, like to cook and are self-efficacious. No environmental and health concerns. Women in their fifties in small households (2-3 members) with medium consumption and relatively low expenditure characterise this segment’s demographic profile. The majority of the class is made of Italians, while the minority comes from UK.

== References & Readings ==

File:Psc table 1.png

2018-10-04T15:15:57Z

Jacandrade: Jacandrade uploaded a new version of File:Psc table 1.png

File:Psc table 1.png

2018-10-04T15:15:00Z

Jacandrade:

PSC

2018-10-04T15:14:38Z

Jacandrade:

= Product Success Check =

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== Introduction ==

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Consumers are too numerous, dispersed, and varied in their buying requirements to make it possible to serve all efficiently and in the same manner. At the same time, in today’s competitive landscape, companies follow more and more customized approaches to serve and satisfy the consumers which again drives their ever more differentiated wants. As a consequence, markets become “demassified”, dissolving more and more into “micromarkets”, characterized by different consumers purchasing different products in different distribution channels and attending to different communication channels. Segmentation aims at identifying such micro markets, i.e. groups of consumers that share the same expectations and behavioural patterns. The identification of the most attractive micromarkets, i.e. segment(s), for the company and its products therefore is imperative not only for successful commercialization but also for new product development.

Following a strategic approach to markets, the company distinguishes the major market segments based on the profiling of different consumer groups along their wants, consumption and purchasing behaviour; socio-demographic characteristics etc.; targets one or more of these segments; and develops products (and marketing programs) tailored to the profile and expectations of each selected segment.Tailoring starts with an understanding of the customers and providing them with the product and service they expect but, importantly, embraces also price, distribution and communication efforts to reach the target segment efficiently. The firm focus is on the buyers whom they have the greatest chance of satisfying. Having satisfied customers is at the basis for company success and the first step to repeat purchase and customer loyalty.

Evidence for new product development or new product commercialization success factors shows that the analyses of market segments, targeting, positioning and the alignment with the firms’ offer and resources are crucial to both new product development and new product commercialization. It follows that segmentation helps companies to navigate an increasingly competitive market, to understand their customers better, to develop offerings that satisfy specific wants, and to address diversity in an efficient manner.

The approach to developing a robust model to analyze the likelihood that new seafood product launches will be successful follows this perspective. We develop both country specific consumer segmentations in Italy, Germany, France, Spain and the UK, as well as an overarching European segmentation useful for companies that are innovating and developing new fish products or have fish products on offer and would like to improve their commercialization. The segmentations are based on latent class analyses of representative samples of consumers (800 in each of the five countries) who replied to an online survey in June-July 2017.

Although the segment profiles by themselves are informative, the methodology used contains an additional step in order to help the company select the most appropriate target(s). In this second stage, multinomial regression matches product (and firm) attributes with the most attractive consumer segment(s). A comparison of the segment, i.e. consumer profile, with the product attributes will further inform the company on how to improve the product and/or its marketing effort in order to tailor more closely to segment wants and characteristics and ultimately launch and commercialize successfully. Figure 1 gives an overview of the success analysis model.

'''Figure 1: The success analysis model at a glance''' [[File:Psc fig 1.JPG|center|Figure 1: The success analysis model at a glance]]

 

== The tool ==

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The PSC tool is being developed as a proxy for the multinomial regression algorithm created as a result of the research phase of the project. It presents the user with an interface to select the variables to be used in the algorithm which will calculate the profile and consumption probability of the product being analysed, and display to the user the results in a graphical, user friendly form.

=== PSC home page ===

The suer can access the PSC tool home page by clicking the quick access link in the DSS homepage or by clicking the appropriate link in the top navigation bar.

''PSC home page'' [[File:Psc home 1.png|center|PSC home page]] [[File:Psc home 2.png|center|PSC home page]]

Once in the PSC home page, the user must initially select 5 different attributes for the product being analysed in the ''Product attributes'' section. These are required attributes and must be selected before being able to see the results. Once these attributes are set, the user can additionally select more detailed attributes in the ''Other marketing attributes'' sections to increase the relevancy of the resulting analysed profile. Optionally, the user can also select preferred presentation formats in the selection box above the ''Perform product success check'' button, which will then be highlighted in the results page preferences graph.

Behind the scenes, when the user clicks the button to perform the PSC, the tool wraps the attributes chosen by the user and hands over to the R language script developed in the research part of the project, which in turn calculates the multinomial regression for the given attributes and returns the results to the DSS tool.

=== The results ===

''PSC results page'' [[File:Psc results 1.png|center|PSC results page]] [[File:Psc results 2.png|center|PSC results page]]

After a user click the button to perform the product success check, the results page will be displayed containing the description of the best matching consumer profile for the analysed product, as well as a graphical comparison of consumption probabilities for different product formats. The presentation formats selected in the previous page will be highlighted in the graph, and the selected attributes used for the regression will be displayed in the sidebar on the left.

 

=== Segments description ===

The table here below presents a summary of the segments identified in the single countries (and in the “total” EU countries) under study. Some segments are cross-national or pan-European (light blue, light red), while others are specific to a few (grey cells)/only one country (dark green).
[[File:Psc_table_1.png|center|Segment tables]]

====Italy====

'''The health & environmentally conscious''' consumer represents 13 % of the Italian consumers (trend: stable). Members of this segment are willing to pay (second highest expenditure for fish in Italy) for beneficial effects for both personal and environmental health. Predominantly women aged 50 + value items such as environmentally friendly, sustainability and natural ingredients, nutrients, easy-to digest characteristics highly. Appearance and traceability are also important to this segment, pointing to critical evaluation and check of quality/safety issues related to fish. They prefer wild fish, boneless and traditional recipes. Their favourite place of purchase is the supermarket/fishmonger which are also their sources of information. The segment’s usage rate is medium-high. Of note, consumers here like all fish species (although they consume sea bream and sea bass most) and buy a broad range of formats. The women and their small families (3 persons) reside in bigger urban centres, with children who are grown up but still live at home.

''The brand-convenience-taste''' consumers reflect only a small but growing portion of the Italian market (7 %). This group of young consumers with small families declares to have a preferred brand and to favor taste over nutritional aspects. Highly important to them are availability of the fish, new formats, labels and omega 3. The consumers here also value fish products that take little time to prepare while nutrients or sustainability claims are of no importance to them. Consistent with a brand buyer is also the fact that these consumers are not self-efficacious– they rely instead on the familiarity and security that comes with a preferred brand and label (another aspect of “convenience”). In line with this profile is the supermarket as the only place of purchase, which is also, together with advertisements, the segment’s main source of information. People in this group live predominantly in rural areas of the country. The favourite species are salmon (ready-to-eat/to cook, fresh fillet), sea bream (fresh fillet) and cod (frozen fillet) with overall medium consumption and average expenditure.

'''The self-efficacious cooking artist''' represents 14 % of Italian consumers (trend: growing). Here we find the self-efficacious (all items that point to knowledge and evaluation of fish score high) relatively young male who likes to cook, is creative in meal preparation and looks for versatility. Consistent with the passion for cooking, saving time in meal preparation is unimportant to him. He looks for healthy products (with traceability) but also for a reasonable price-quality ratio. He and his partner (or small family) live in coastal/rural areas as well as in urban centres. The favourite place of purchase is the supermarket or the fishmonger, the source of information is the label or the advice from the fishmonger. Chooses predominantly sea bream, sea bass and cod in a wide range of formats (except ready to eat). Fish expenditure is average, in line with the fact that those who have more knowledge of fish can find more alternatives among available products.

'''The local connoisseur''' represents the biggest segment in Italy (24%/growing). This is the group of consumers who know everything about fish (high values across self-efficacy items), use its versatility and experiment with new formats or recipes. Relatively young women here (with small family) strongly emphasise the health-nutritional aspect and underline easy digestion. This group of consumers also favours local origin. They pay attention to environment and sustainability issues and indicate the preference for a (local) brand or seller. Emphasising value for money, they do not trade off quality for price (but would instead go for a cheaper species or stock the fish in order to be flexible). They prefer wild fish, are indifferent to bones, and are inclined to traditional preparation. Their consumption is medium-high (mainly sea bream, sea bass, less cod and salmon in a wide range of formats) with an expenditure that is the highest across all Italian segments. These consumers buy in the supermarket or at the fishmonger and do not indicate any sources of information.

'''Price-wise convenience''' consumers (14%/stable) represented in segment 5 are very price conscious, reflected also in their low expenditure on fish. People here are not knowledgeable about fish. They strongly underline health, easy-to-cook characteristics and texture. In line with this profile is their fish selection – they favour cod and salmon (fresh and frozen fillets but also canned, smoked, ready-to-cook/ready-to eat). Both genders aged 54 + are represented here, mainly living with one grown up child in rural and urban areas. Preferably they buy in supermarkets which are, together with advertisements, also the source of information.

'''The self-efficacious pragmatic fish'' consumers, a large (23%) and growing segment with high fish expenditure. They value the health benefits of fish, look for conservation and versatility. Preferences here bring together the health of both, individuals and the environment, added is a strong emphasis on value for money. Although this segment is knowledgeable about fish and its preparation, the profile seems to reflect a pragmatic instance of “having to eat and cook fish” without related pleasure of doing so. In fact, this segment has only two favourite species, namely salmon and cod, which they consume frequently, predominantly as fresh/frozen fillets. Women aged 45 + with small families, medium-high education and income represent the socio-demographic profile of this segment best.

'''Indifferent''' consumers are the smallest group of consumers (6%/stable), represented by relatively young male with small family living in rural or intermediate areas of Italy. Their favourite place of purchase is the supermarket. They consult the label or ads for fish information. Species include sea bream and salmon and their expenditure is among the lowest across the segments.

====Spain====

Segment 1 represents '''brand/seller “dependent” high quality''' consumers who are not self-efficacious (23%/growing). The preferred “brand“ here is either the shop/seller or the brand itself. Consumers do not feel on the safe side regarding fish evaluation and preparation and thus rely on the trusted seller/brand of whom they learn. They give importance to inclusive health (individual and environment) and have a broad quality understanding for which they are ready to pay. This segment shows high fish consumption and the highest expenditure for fish. Consistent with the fact that they like to cook but do not indicate corresponding competence they go for a very limited range of species. They buy in supermarkets or at the fishmonger and listen to the advice of the fishmonger or seller. Women aged 46 + with small children (who eat fish) and low-medium education but relatively high income best represent this group of consumers. Favourite species are sea bream (whole/fresh fillet) and cod (fresh/frozen fillet, dried).

'''Self-efficacious selfish brand buyer''' (23%/growing): also this group of consumers has a preferred brand/seller but it is, as compared to segment 1, self-efficacious. It is “egoistic” in terms of health orientation as only items which focus on individual health are important (while environmental attention is unimportant) to this segment. Men around 55 here take care of their family which lives in cities close to the coast. They are medium sea bass and salmon consumers who spend relatively little on fish.

'''The independent “good for me” connoisseur''' (9%, growing) values taste and nutrition equally. Members of this segment love fish (sensory appeal) and they value its benefits for health. They cross-check on labels and expect a guaranteed origin. In line with this, the segments favourite species is wild fresh sea bass which is consumed in high quantities. Women aged 48, living with family in cities at the coast are willing to spend for their selected premium sea bass which they preferably buy at the fishmonger or in the supermarket.

The consumers in the 4th and biggest (29 %, stable) segment in Spain are directed towards '''nutritional-digestive and inclusive health (360 degree-health)'''. Consistent with this emphasis is the importance given to origin and traceability. Value for money is crucial to this segment, and they value conservation. Their medium-high fish consumption is reflected also in a relatively high fish expenditure mainly spent on fresh sea bream and salmon (fresh/smoked). Young women here take care of their families with young children.

'''(Salmon) Cooking artists (9%/stable)''', very young couples (24 +), like to cook and trust in their competence of fish (salmon) preparation, they are creative and experiment with new formats, and they emphasise versatility. None of the health related items is of importance. The young couples go mainly for wild salmon (medium –high consumption) in the supermarket. Salmon is the dominant species they buy in all formats. Consistent with the artist stance is also the (low) use of an exotic species such as herring. The main source of information is the seller.

'''The indifferent''' (7%/stable), with medium-low consumption of salmon and cod, spends little on fish. Typically consumers here are young male, small family size, low education level living in urban centers in the countryside.

====France====

'''The good for me health''' consumer represents 29 % of the French market (trend: stable) that expects mainly health benefits from fish consumption and looks for guarantees in terms of sustainability certifications and traceability. Predominantly consisting of male in their fifties, highly educated and with high income, this segment appreciates “easy-to-cook” products and emphasises value for money. It is characterised by low-medium consumption and low expenditure for sea bream (either fresh fillet or ready-to-eat). Shopping for two, predominantly in supermarkets, these men use the label or the seller for information.

'''The health oriented (selfish), (not creative) cook''' (23%/growing) is medium-high in fish consumption and the highest in expenditure. Women aged around 45 highly value the health benefits of fish, they like cooking and the variety and versatility that comes with many species and a wide range of formats (herring, cod and sea bream) in traditional preparations. They purchase in the supermarket for a small family and take information from the label and the seller.

'''The cooking artist''' represents around a quarter of fish consumers in France (trend: stable). This profile cuts across all ages, also the very young. They choose carefully, go for high quality for which they are ready to pay and they consult many information sources. Health is not on the agenda of this segment and they have no environmental concerns. They shop for sea bream at the supermarket or at the fishmonger. The couple prefers fresh, but they are flexible and willing to try different formats and recipes.

'''Self-efficacious convenience''' consumer to whom, beyond inclusive health, convenience is central (31%/stable). They give importance to each and every aspect and thus represents very demanding consumers. This consumer critically checks the expected quality: reads labels and values certificates and guarantees. Medium consumption of varied fish species and broad range of formats (reflecting convenience), and second highest expenditure on fish. Relatively young women and men are representing the class, living in the countryside/intermediate cities in small families.

'''The indifferent''' in France are the smallest group of consumers (7%/stable). The class is on a medium-low level in fish consumption and the lowest expenditure for trout, salmon and cod. Prefer mainly in fresh and frozen formats. The segment is predominantly young singles or couple, living in the countryside in smaller cities.

In all segments salmon and trout is consumed. The species mentioned above distinguish the segments from this overall baseline consumption.

====Germany====

'''The cooking artist''' (12%/stable) is loyal to a brand/seller and gives importance to local origin. Consumers in this segment share the characteristics that cut across-countries for the cooking artist: they like to cook/are capable of preparing fish, value versatility, are creative and ready to try new formats. Taste here clearly dominates nutritional aspects (only Omega 3 is of importance). Consumers in this segment are not price sensitive, a fact reflected also in the highest fish expenditure across German segments. They prefer fresh fish, medium usage rate, mainly salmon but also the more “exotic” sea bream (the only segment in Germany) and sea bass. The class includes both genders, they are young, live with a small family with smaller kids in cities in the countryside.

'''Healthy & environmentally-conscious''' consumers make up a third of the German market (growing). To consumers in this segment, a healthy diet and a natural product and the texture are central. Health here is inclusive of the environment, consumers value sustainability certification and put emphasis on a guaranteed origin. They are not self-efficacious and thus trust their “seller/brand”, but also consult the label and ask for guarantees. The group is ready to pay for the value they ask for, i.e. a healthy & environmentally safe diet, which is reflected in high fish expenditure. The class includes both genders aged over 54 involved in decisions and patterns of fish consumption (salmon, trout and sea bass; fresh and frozen); consistent with their health focus their consumption is medium high.

'''The convenience- brand loyal''' consumer (23%/growing), looks for value for money. Brands provide the benefits she asks for: nutrients, sustainability certification, traceability, label. Ready-to-eat is emphasised which together with fresh formats may satisfied her want for creativity. Predominantly relatively young female living in a two-person-household in cities in the countryside with lower fish expenditure and medium fish consumption represent this cluster best. The members of this segment shop in supermarkets where they get information in-store, from the seller or from the label.

The fourth segment comprises '''healthy cooking artists''' who like variety. Being a premium segment in terms of expenditure, this profile unites the cooking artist with a focus on health. Versatility is important, but experimentation is also reflected in a broad range of species and formats. The socio-demographic profile of women over 54, with medium high education, in 2 person-households, is very much in line with this segment.

'''Cheap brand and taste''' consumer (16%/stable): People in this segment have learned the claims of their preferred brand (but they are not knowledgeable about fish), omega 3 and tasty, they are price-conscious and, overall, seem to go for an easy buy without much involvement or major decision criteria. Fish here offers the best compromise between health and taste. No importance is given to origin and traceability. Male in their forties (couple) spend little for medium-low consumption.

'''The indifferent''' present around 7 % of the market, predominantly young and single. Medium consumption, relatively high expenditure and a broad range of species and formats.

Of note, herring is consumed in all segments. The species mentioned above distinguish the segments from this overall baseline consumption.

====UK====

'''Healthy convenience''' consumers (22 %, growing) have their focus on “easy” to cook, to stock, to use (versatile). Health is also central, with a strong focus on digestion and environmental concern and the request for traceability. The segment is characterised by medium consumption and highest expenditure on fish across the segments. Women, aged above 50 with medium-high education and a 2-person household describe the segment best. Members of this segment appreciate wild fish; their favourite species are sea bream, sea bass – fresh fillets, ready-to-eat, whole fish.

'''Selfish health & convenience''' consumers, the biggest segment (43 %, growing) are typically younger couples with medium – low income but relatively high expenditure on fish. They are informed and are consulting many information sources, do not trade off quality for price and are indifferent to brands, origin and traceability. The focus is on health, but also easy to cook, versatility, and conservation are important. Consume salmon and sea bass in medium quantity. This segment is similar to segment 1 in convenience but health is not inclusive and more focused on nutrients than on digestion and its information behaviour is more extensive.

'''Cooking artist''' (8 %/stable trend). Similar to her counterparts in the other countries, the British cooking artist likes to cook and to experiment with new formats. Taste is an important theme, while she is indifferent to health and environmental concerns; dietary issues are not important. British cooking artists are not really knowledgeable about fish. Women aged 44+ in small families with children eating fish do best describe the socio-demographic characteristics. Prefer wild, favourite species sea bream and cod. Given the low income she really likes and spends (over proportionally) for fish.

'''Self-efficacious & local ecologist''' (13 %/growing segment) are very young singles or 2-person households. They are knowledgeable and environmentally conscious. At the same time they give much importance to the local context. The segment members enjoy cooking and they trust in their meal preparation. Medium consumption of salmon, sea bream, sea bass, but with low expenditure.

The segment of '''indifferent''' (14 %, growing) is composed of young male, single or in a household of two, and low to medium education. Prefer salmon and cod, ready to eat, ready to cook. Medium consumers, low expenditure.

In all segments cod is consumed. The species mentioned above distinguish the segments from this overall baseline consumption.

====Europe====

We construct 11 European segments which are briefly discussed here below.

'''The salmon fan''' segment (9 %/growing), in line with the only species it consumes, values highest omega 3, availability, versatility and value for money. These consumers also clearly favor taste over nutritional aspects. Consumers here are women in their forties, living in households of two persons with medium – high salmon consumption of all formats and relatively high expenditure. In terms of relative composition, this segment is very prominent in the UK (29 %).

Segment two represents the '''self-efficacious inclusive health''' consumer, one of the largest EU segments (17 %, growing): knowledgeable people who appreciate the health-nutritional aspect of fish. Dietary considerations are not important (e.g. nr. of calories). Health includes the well being of the environment. People emphasise value for money, expect traceability and certification but are indifferent with regard to organic products. Male and female consumers aged around 50, with medium expenditure and fish consumption; favourite species are salmon, sea bream, cod with wide variety of formats. Germans make up 24 % of this segment.

'''Cooks with inclusive health focus''' (11%) characterise segment 3. They enjoy meal preparation (but are neither creative nor knowledgeable of fish) and emphasise omega 3 and “easy-to-digest” attributes. Their overall important theme is individual and environmental health, and, importantly, animal welfare, which is cross-checked with label and certifications. The segment is not price sensitive and is ready to pay for the expected value. Relatively young men here take care of small families who live in urban centres in the countryside. Low-medium consumption, but relatively high expenditure on fish. UK dominated with 27% of consumers in this segment (trend: stable).

'''Tasty and easy quality''' (8%). To this segment value for money is important as are “easy to cook” and quick preparation of meals. Availability and conservation is stressed, emphasising the time/convenience posture of the segment. Taste and texture are valued more than health aspects. No environmental concerns and also self-efficacy criteria are low/indifferent. Young male (early thirties) with medium-high education take care of small families. They prefer wild over farmed and spend much for taste and easy quality - high expenditure for medium-high fish consumption. Segment is mainly populated by French, Spanish and Italians (trend: increasing).

Segment 5 is the '''360 degree- health oriented''' segment (11%), which gives much importance to natural fish products. Also “easy to digest” and nutrients are of utmost importance, as is the absence of smell and a guaranteed origin. It is the only segment where people also have a concern regarding negative effects of farming. Consistent with this preference they favour wild fish. The segment is characterised by medium-high fish consumption with corresponding high expenditure. Women in their 50s in 2-people households with medium education represent best the demographic profile of the segment. Italians dominate this segment (trend: increasing ).

Segment 6, one of the smallest in EU (5 %), is characterising the''' innovative brand buyer'''. Consumers here have a favourite brand to which they are also loyal. “Claim”-related items are important but not supported by corresponding factual knowledge. People here are also the only ones to underline new dietary preparations (e.g. gluten free products), they prefer products that take little time for preparation, and they emphasise conservation and versatility. Time, overall, is an important factor for this group. The known brand is a response to this: choosing the familiar brand saves time in terms of reflection/selection and it is a guarantee for satisfied expectations. Consumption of this segment is high with corresponding highest expenditure across all segments. British, Italian and French women around 45, with small families make up this segment (trend: increasing).

'''Indifferent''': the majority of indifferent consumers is divided among UK (31 %) and France (27 %), followed by Spain and Germany (15 % and 14 %, respectively), with a stable trend. Only 12 % of the class is populated by Italian consumers. This segment is characterised by male and female aged 18-40, with low education and medium-low consumption. Expenditure, not surprisingly, is the lowest.

'''Healthy convenience''' (6 %). Segment 8 consumers look for easy to cook meals that take little time to prepare, appreciate conservation and general health/environmental benefits. Being demanding on all dimensions, they are ready to pay for the corresponding products. As confirmed by high fish expenditure, consumers do not trade off value for money. Here young dads with medium-high education take care of their bigger families’ health by balancing it with the need to have meals easily and quickly prepared (trend: stable). Only Italy is underrepresented (16 %) in this overall balanced segment.

This group –''' the local – natural brand/seller''' (5 %) - values “local” and natural highly. More than emphasising the presence of positive nutrients and elements, consumers here emphasise the absence of ingredients and substances. They are self-efficacious, trust a certain – local – brand or seller to whom they are loyal. They also stress availability. Fish consumption is medium – low, expenditure is at the lower level across segments. The socio-demographic show relatively young men and women in households of three holding a medium education level. German consumers account for 27 % of this small segment (trend: stable).

In this segment we find the '''cook with selfish health focus''' (8%) who likes taste and nutrition. Broader health, dietary or environmental concerns are not considered important. Consistent with enjoying the preparation and consumption of fish, this segment’s expenditure is medium-high with corresponding high expenditure. Relatively young Spanish women in small households without children best describe the consumers of this segment (trend: increasing).

'''Cooking artists''' (17 %, stable) are creative, like to experiment with new formats, like to cook and are self-efficacious. No environmental and health concerns. Women in their fifties in small households (2-3 members) with medium consumption and relatively low expenditure characterise this segment’s demographic profile. The majority of the class is made of Italians, while the minority comes from UK.

== References & Readings ==

File:Wtp results 2.png

2018-09-27T00:07:34Z

Jacandrade:

File:Wtp results 1.png

2018-09-27T00:06:54Z

Jacandrade:

File:Wtp home.png

2018-09-27T00:05:36Z

Jacandrade:

WTP

2018-09-27T00:01:54Z

Jacandrade:

= Willingness to Pay =

----

----

== Introduction ==

----

The average apparent fish consumption per capita in the EU is the second highest in the world (at around 22 kg/capita/year), and some individual EU Member States are among the highest fish consuming countries in the world (EEA, 2016). The EU is the largest market in the world for fish; with a value of €55 billion and a volume of 12 million tons (FAO, 2016). While EU fish and seafood consumption has risen over the past 10 years with stable or declining supply from the fisheries sector, most of this increase has come from imports rather than from EU aquaculture. In 2014, around 75% of fisheries and aquaculture products consumed in the EU came from marine capture fisheries, which remains consistent with trends over the last decade (EUMOFA, 2015). Today 25% of all EU seafood consumption comes from EU fisheries, 10% from EU aquaculture and 65% from imports from third countries, both fisheries and aquaculture products. European aquaculture growth has stagnated since the turn of the century partly because its products have not been competitive compared with imports. In a market driven by the demand a better understanding of consumer purchasing behaviour towards fish products is paramount to developing more effective marketing and policy strategies. Therefore, understanding the consumers’ preferences across the EU countries for fish species and fish product attributes is crucial to sustain the fisheries and aquaculture sectors. The objective of this study was to investigate consumer demand and choice behaviour for fresh fish at the retail market. In particular, we examined consumer preferences for different fish alternative species, as well as different attributes. The outcomes allowed us to elicit consumers’ preferences and willingness to pay (WTP) for the salient attributes of a variety of fresh fish species in the retail market. We applied a discrete choice experiment (DCE) to accomplish this objective; this method is strongly consistent with the economic demand theory and in particular with the multi-attribute demand studies based on the Lancastrian consumer theory .This theory assumes that consumer’s utility stems from product properties rather than the products themselves. Thus, multi-attribute demand models can elicit the intrinsic value of the product attributes and have been applied widely in marketing research. Moreover, this method is highly flexible with respect to data collection and model specifications. DCE is based on random utility theory about individual decision making, and seems realistic in imitating real shopping behaviour (Louviere et al., 2000). Choice modelling techniques are multi-attribute valuation techniques that elicit values for multiple attributes by asking respondents to rate, rank or choose a set of attributes (levels). In particular, choice experiments are valuation techniques where respondents have to make trade-offs and indicate their preferred option out of a set of alternatives. We developed a choice-based on-line experiment, on a number of 500 respondents per country (Italy, France, Spain, UK and Germany). The profile attributes and levels analysed are derived from previous qualitative tasks (i.e., qualitative analysis by in-person interviews), and include product innovation features such as health claims, sustainability certification, etc. To accommodate the evaluation of choice alternatives through both attribute judgment and alternative comparison, we applied a labelled choice experiment (LCE), where choice alternatives were labelled by the respective names of the seafood (e.g., salmon, cod, herring, etc.) (Nguyen et al., 2015). We set our model specification in such a way that the constant terms, which represent intrinsic value of the alternatives, and attribute parameters were varied both over fish alternatives and across countries. The WTP associated with each attribute, by species and country, was also estimated.

 

 

== Tool overview ==

The tool contains the explanation necessary to understand its working and results. Once you select the product attributes and click the Run button, a results page will be displayed containing the results and an analytical explanation of its contents.

=== Landing page ===
The WTP home page is quite straight forward and offers a general description for the tool. The home page displays the different inputs, and also provides links to this wiki page for deeper information about the research and tool.

[[File:Wtp home.png|home]]

=== Reference and pictures for Presentation format (whole fish, fillet, ready-to-cook) ===

The DSS Willingness To Pay is the result of a methodology called “choice modelling”, where consumers participating in an online experiment have indicated their preference on a set of goods. While choosing one alternative instead of another, consumers indicate their preference on a fish species (e.g., cod), and on a particular combination of the following characteristics (what we call “attributes”):

*Price
*Production method (farm-raised or wild-caught fish)
*Presentation format (whole fish, fillet, ready-to-cook)
*Sustainability label
*Nutritional and health claim

'Here is a set of pictures of the Presentation format attribute, by species in each country.''

===== France =====

[[File:Wtp table a3 france.png|center|WTP Table A3 - France.]]

===== Germany =====

[[File:Wtp table a3 germany.png|center|WTP Table A3 - Germany.]]

===== Italy =====

[[File:Wtp table a3 italy.png|center|WTP Table A3 - Italy.]]

===== Spain =====

[[File:Wtp table a3 spain.png|center|WTP Table A3 - Spain.]]

===== UK =====

[[File:Wtp table a3 uk.png|center|WTP Table A3 - UK.]]

 

=== Results ===
The results page displays firstly a Bar chart highlighting the base price and the WTP variations for the selected inputs, followed by a quick general explanation about the results.
At the bottom, a graphical comparison of the WTP variation for the different attributes of the chosen species and country, followed by a chart of the WTP variation by country and species for the same input choices for the product.

[[File:Wtp results 1.png|results]]
[[File:Wtp results 2.png|results]]

== References & readings ==

WTP

2018-09-25T23:42:26Z

Jacandrade:

= Willingness to Pay =

----

----

== Introduction ==

----

The average apparent fish consumption per capita in the EU is the second highest in the world (at around 22 kg/capita/year), and some individual EU Member States are among the highest fish consuming countries in the world (EEA, 2016). The EU is the largest market in the world for fish; with a value of €55 billion and a volume of 12 million tons (FAO, 2016). While EU fish and seafood consumption has risen over the past 10 years with stable or declining supply from the fisheries sector, most of this increase has come from imports rather than from EU aquaculture. In 2014, around 75% of fisheries and aquaculture products consumed in the EU came from marine capture fisheries, which remains consistent with trends over the last decade (EUMOFA, 2015). Today 25% of all EU seafood consumption comes from EU fisheries, 10% from EU aquaculture and 65% from imports from third countries, both fisheries and aquaculture products. European aquaculture growth has stagnated since the turn of the century partly because its products have not been competitive compared with imports. In a market driven by the demand a better understanding of consumer purchasing behaviour towards fish products is paramount to developing more effective marketing and policy strategies. Therefore, understanding the consumers’ preferences across the EU countries for fish species and fish product attributes is crucial to sustain the fisheries and aquaculture sectors. The objective of this study was to investigate consumer demand and choice behaviour for fresh fish at the retail market. In particular, we examined consumer preferences for different fish alternative species, as well as different attributes. The outcomes allowed us to elicit consumers’ preferences and willingness to pay (WTP) for the salient attributes of a variety of fresh fish species in the retail market. We applied a discrete choice experiment (DCE) to accomplish this objective; this method is strongly consistent with the economic demand theory and in particular with the multi-attribute demand studies based on the Lancastrian consumer theory .This theory assumes that consumer’s utility stems from product properties rather than the products themselves. Thus, multi-attribute demand models can elicit the intrinsic value of the product attributes and have been applied widely in marketing research. Moreover, this method is highly flexible with respect to data collection and model specifications. DCE is based on random utility theory about individual decision making, and seems realistic in imitating real shopping behaviour (Louviere et al., 2000). Choice modelling techniques are multi-attribute valuation techniques that elicit values for multiple attributes by asking respondents to rate, rank or choose a set of attributes (levels). In particular, choice experiments are valuation techniques where respondents have to make trade-offs and indicate their preferred option out of a set of alternatives. We developed a choice-based on-line experiment, on a number of 500 respondents per country (Italy, France, Spain, UK and Germany). The profile attributes and levels analysed are derived from previous qualitative tasks (i.e., qualitative analysis by in-person interviews), and include product innovation features such as health claims, sustainability certification, etc. To accommodate the evaluation of choice alternatives through both attribute judgment and alternative comparison, we applied a labelled choice experiment (LCE), where choice alternatives were labelled by the respective names of the seafood (e.g., salmon, cod, herring, etc.) (Nguyen et al., 2015). We set our model specification in such a way that the constant terms, which represent intrinsic value of the alternatives, and attribute parameters were varied both over fish alternatives and across countries. The WTP associated with each attribute, by species and country, was also estimated.

 

 

== Tool overview ==

The tool contains the explanation necessary to understand its working and results. Once you select the product attributes and click the Run button, a results page will be displayed containing the results and an analytical explanation of its contents.

=== Landing page ===

[[File:Wtp home.png|home]]

=== Reference and pictures for Presentation format (whole fish, fillet, ready-to-cook) ===

The DSS Willingness To Pay is the result of a methodology called “choice modelling”, where consumers participating in an online experiment have indicated their preference on a set of goods. While choosing one alternative instead of another, consumers indicate their preference on a fish species (e.g., cod), and on a particular combination of the following characteristics (what we call “attributes”):

* Price
* Production method (farm-raised or wild-caught fish)
* Presentation format (whole fish, fillet, ready-to-cook)
* Sustainability label
* Nutritional and health claim

'Here is a set of pictures of the Presentation format attribute, by species in each country.''

=====France=====
[[File:Wtp_table_a3_france.png|center|WTP Table A3 - France.]]

=====Germany=====
[[File:Wtp_table_a3_germany.png|center|WTP Table A3 - Germany.]]

=====Italy=====
[[File:Wtp_table_a3_italy.png|center|WTP Table A3 - Italy.]]

=====Spain=====
[[File:Wtp_table_a3_spain.png|center|WTP Table A3 - Spain.]]

=====UK=====
[[File:Wtp_table_a3_uk.png|center|WTP Table A3 - UK.]]

=== Results ===

[[File:Wtp results 1.png|results]]

== References & readings ==

WTP

2018-08-05T19:04:30Z

Jacandrade:

= Willingness to Pay =

----

----

== Introduction ==

----

The average apparent fish consumption per capita in the EU is the second highest in the world
(at around 22 kg/capita/year), and some individual EU Member States are among the highest fish consuming
countries in the world (EEA, 2016). The EU is the largest market in the world for fish; with a value of
€55 billion and a volume of 12 million tons (FAO, 2016). While EU fish and seafood consumption has risen
over the past 10 years with stable or declining supply from the fisheries sector, most of this increase
has come from imports rather than from EU aquaculture. In 2014, around 75% of fisheries and aquaculture
products consumed in the EU came from marine capture fisheries, which remains consistent with trends over
the last decade (EUMOFA, 2015). Today 25% of all EU seafood consumption comes from EU fisheries, 10% from
EU aquaculture and 65% from imports from third countries, both fisheries and aquaculture products. European
aquaculture growth has stagnated since the turn of the century partly because its products have not been
competitive compared with imports. In a market driven by the demand a better understanding of consumer purchasing
behaviour towards fish products is paramount to developing more effective marketing and policy strategies.
Therefore, understanding the consumers’ preferences across the EU countries for fish species and fish
product attributes is crucial to sustain the fisheries and aquaculture sectors. The objective of this study was
to investigate consumer demand and choice behaviour for fresh fish at the retail market. In particular, we examined consumer
preferences for different fish alternative species, as well as different attributes. The outcomes allowed us
to elicit consumers’ preferences and willingness to pay (WTP) for the salient attributes of a variety of
fresh fish species in the retail market. We applied a discrete choice experiment (DCE) to accomplish this objective;
this method is strongly consistent with the economic demand theory and in particular with the multi-attribute
demand studies based on the Lancastrian consumer theory .This theory assumes that consumer’s utility stems
from product properties rather than the products themselves. Thus, multi-attribute demand models can elicit
the intrinsic value of the product attributes and have been applied widely in marketing research.
Moreover, this method is highly flexible with respect to data collection and model specifications.
DCE is based on random utility theory about individual decision making, and seems realistic in imitating
real shopping behaviour (Louviere et al., 2000). Choice modelling techniques are multi-attribute valuation
techniques that elicit values for multiple attributes by asking respondents to rate, rank or choose a set of
attributes (levels). In particular, choice experiments are valuation techniques where respondents have to
make trade-offs and indicate their preferred option out of a set of alternatives. We developed a choice-based
on-line experiment, on a number of 500 respondents per country (Italy, France, Spain, UK and Germany).
The profile attributes and levels analysed are derived from previous qualitative tasks (i.e., qualitative
analysis by in-person interviews), and include product innovation features such as health claims, sustainability
certification, etc. To accommodate the evaluation of choice alternatives through both attribute judgment and
alternative comparison, we applied a labelled choice experiment (LCE), where choice alternatives were labelled
by the respective names of the seafood (e.g., salmon, cod, herring, etc.) (Nguyen et al., 2015). We set
our model specification in such a way that the constant terms, which represent intrinsic value of the alternatives,
and attribute parameters were varied both over fish alternatives and across countries. The WTP associated with
each attribute, by species and country, was also estimated.

 

==Tool overview ==

The tool contains the explanation necessary to understand its working and results.
Once you select the product attributes and click the Run button, a results page
will be displayed containing the results and an analytical explanation of its contents.

===Landing page===

[[File:Wtp_home.png|home]]

===Results===

[[File:Wtp_results_1.png|results]]

==References & readings==

WTP

2018-08-05T19:03:51Z

Jacandrade:

= Willingness to Pay =

----

----

== Introduction ==

----

The average apparent fish consumption per capita in the EU is the second highest in the world
(at around 22 kg/capita/year), and some individual EU Member States are among the highest fish consuming
countries in the world (EEA, 2016). The EU is the largest market in the world for fish; with a value of
€55 billion and a volume of 12 million tons (FAO, 2016). While EU fish and seafood consumption has risen
over the past 10 years with stable or declining supply from the fisheries sector, most of this increase
has come from imports rather than from EU aquaculture. In 2014, around 75% of fisheries and aquaculture
products consumed in the EU came from marine capture fisheries, which remains consistent with trends over
the last decade (EUMOFA, 2015). Today 25% of all EU seafood consumption comes from EU fisheries, 10% from
EU aquaculture and 65% from imports from third countries, both fisheries and aquaculture products. European
aquaculture growth has stagnated since the turn of the century partly because its products have not been
competitive compared with imports. In a market driven by the demand a better understanding of consumer purchasing
behaviour towards fish products is paramount to developing more effective marketing and policy strategies.
Therefore, understanding the consumers’ preferences across the EU countries for fish species and fish
product attributes is crucial to sustain the fisheries and aquaculture sectors. The objective of this study was
to investigate consumer demand and choice behaviour for fresh fish at the retail market. In particular, we examined consumer
preferences for different fish alternative species, as well as different attributes. The outcomes allowed us
to elicit consumers’ preferences and willingness to pay (WTP) for the salient attributes of a variety of
fresh fish species in the retail market. We applied a discrete choice experiment (DCE) to accomplish this objective;
this method is strongly consistent with the economic demand theory and in particular with the multi-attribute
demand studies based on the Lancastrian consumer theory .This theory assumes that consumer’s utility stems
from product properties rather than the products themselves. Thus, multi-attribute demand models can elicit
the intrinsic value of the product attributes and have been applied widely in marketing research.
Moreover, this method is highly flexible with respect to data collection and model specifications.
DCE is based on random utility theory about individual decision making, and seems realistic in imitating
real shopping behaviour (Louviere et al., 2000). Choice modelling techniques are multi-attribute valuation
techniques that elicit values for multiple attributes by asking respondents to rate, rank or choose a set of
attributes (levels). In particular, choice experiments are valuation techniques where respondents have to
make trade-offs and indicate their preferred option out of a set of alternatives. We developed a choice-based
on-line experiment, on a number of 500 respondents per country (Italy, France, Spain, UK and Germany).
The profile attributes and levels analysed are derived from previous qualitative tasks (i.e., qualitative
analysis by in-person interviews), and include product innovation features such as health claims, sustainability
certification, etc. To accommodate the evaluation of choice alternatives through both attribute judgment and
alternative comparison, we applied a labelled choice experiment (LCE), where choice alternatives were labelled
by the respective names of the seafood (e.g., salmon, cod, herring, etc.) (Nguyen et al., 2015). We set
our model specification in such a way that the constant terms, which represent intrinsic value of the alternatives,
and attribute parameters were varied both over fish alternatives and across countries. The WTP associated with
each attribute, by species and country, was also estimated.

 

==Tool overview ==

The tool contains the explanation necessary to understand its working and results.
Once you select the product attributes and click the Run button, a results page
will be displayed containing the results and an analytical explanation of its contents.

===Landing page===

[[File:Wtp_home.png|home]]

===Results===

[[File:Wtp_result_1.png|results]]

==References & readings==

VCA

2018-08-05T18:49:22Z

Jacandrade:

= Value Chain Analyser =

----

----

== Introduction ==

----

The purpose of the Value Chain Analyser is to give examples of case studies on how
competitors have survived in the market place.
The Value chain analyser tool is built to support you with crucial information about the different
value chains of the PrimeFish DSS supported species.
It is composed of four different modules to help you access different levels of information
about a particular value chain.

* Report generator
** Containing the data generated in the research phase of the project, this module allows you to generate detailed
reports about the different steps of the value chains of the studied species.

* CR4 charts
** Displays a visual representation of the CR4 value and different information about the CR4 companies
for different year/species (under development)

* GSI map
** Displays the location of members and non-members of the Global Salmon initiative and accredited certificates.

* Value Add Calculator
** The VCA Value Add Calculator is a tool designed to help cod processors find the optimum combination of
products based on their own costs, processing yields and market assessments.(under development)

== Tool Overview ==

----

===Landing page===

In the VCA tool landing page you can select any of the modules through either the quick access buttons
or by clicking the corresponding tab.

[[File:Vca_home.png|home]]

The leading module is the report generator, where you can click the 'Add section button' to start customizing
the report you wish to generate.

[[File:Vca_rg_home.png|home]]

Once you click the add button, a modal box will appear where you can select the species and sections of the
value chain you wish to include in the report. After you click the add button of the modal, the section and its
content will be displayed in the report generator page. You can edit, delete or add more sections to your liking,
and once satisfied, click the generate report button.

[[File:Vca_rg_add.png|home]]

The report generated will be displayed in a results page with the sections index on the sidebar on the left.
You can navigate each section of the report by clicking it's entry in the index.

[[File:Vca_rg_result.png|home]]

== References & Readings ==

----

VCA

2018-08-05T18:48:36Z

Jacandrade:

File:Vca rg home.png

2018-08-05T18:47:42Z

Jacandrade: Uploaded with SimpleBatchUpload

File:Vca home.png

2018-08-05T18:47:34Z

Jacandrade: Uploaded with SimpleBatchUpload

File:Vca rg result.png

2018-08-05T18:47:33Z

Jacandrade: Uploaded with SimpleBatchUpload

File:Vca rg add.png

2018-08-05T18:47:31Z

Jacandrade: Uploaded with SimpleBatchUpload

SFS

2018-08-05T17:51:48Z

Jacandrade:

= Success & Failure Stories =

----

----

== Introduction ==

----

Prime DSS has been designed to help fishing sector stakeholders to improve their competitiveness in the Fisheries and Aquaculture markets. One core component of identifying areas of competitive improvement involves the collection and dissemination of data revealed in success and failure stories. These stories include information collected on innovative product development and consumer behavior to understand which product attributes best fit customer preferences and therefore improving the possibility of a successful product launch.

All fishing sector stakeholders are invited to share their stories about success and failure experiences when launching innovative products onto the market place. Over time, sector users will have access to a wealth of information that will provide invaluable insights into consumer behaviour and reactions to specific product attributes that will assist with launching successful products. The Success & Failure stories tool is a collections of the stories shared among stakeholders.

== The tool ==

===Landing page===

[[File:Sfs_home.png|home]]

In the landing page the user will be able to see the latest approved stories on the left, and also a list
of stories uploaded by the user with their current status. The user can click the upload story button to
open a modal where the story details can be entered and submitted for upload.
Uploaded stories will then go through a review process by the DSS administrators and will either be approved or
rejected by the administrators.

The user can also use the search form to search for specific stories containing desired attributes and click the
search button to see if any stories match their query. If no parameters are selected, all stories will be displayed.

[[File:Sfs_search.png|search]]

Both at the home page or at the search results, the user can click the ''read'' link on a story to read its full content.

[[File:Sfs_read.png|read]]

== References & readings ==

File:Sfs home.png

2018-08-05T17:50:41Z

Jacandrade: Uploaded with SimpleBatchUpload

File:Sfs read.png

2018-08-05T17:50:40Z

Jacandrade: Uploaded with SimpleBatchUpload

File:Sfs search.png

2018-08-05T17:50:39Z

Jacandrade: Uploaded with SimpleBatchUpload

PSC

2018-08-05T17:26:31Z

Jacandrade:

PSC

2018-08-05T17:23:19Z

Jacandrade: