WTP - Revision history

Andrew at 09:21, 28 September 2018

2018-09-28T09:21:19Z

Andrew at 09:10, 28 September 2018

2018-09-28T09:10:09Z

Andrew at 08:31, 28 September 2018

2018-09-28T08:31:36Z

Jacandrade at 00:01, 27 September 2018

2018-09-27T00:01:54Z

Jacandrade at 23:42, 25 September 2018

2018-09-25T23:42:26Z

Jacandrade at 19:04, 5 August 2018

2018-08-05T19:04:30Z

Jacandrade at 19:03, 5 August 2018

2018-08-05T19:03:51Z

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Andrew at 17:39, 15 February 2018

2018-02-15T17:39:52Z

Jacandrade at 23:17, 8 February 2018

2018-02-08T23:17:05Z

Jacandrade at 23:14, 8 February 2018

2018-02-08T23:14:16Z

@@ Line 22: / Line 22: @@
 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).&nbsp;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.
-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).
+A discrete choice experiment (DCE) was applied 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.

@@ Line 19: / Line 19: @@
 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).
@@ Line 24: / Line 26: @@
 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.
+The choice-based on-line experiment included 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 ==

@@ Line 10: / Line 10: @@
 ----
-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.
+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).
-&nbsp;
+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.
 &nbsp;
@@ Line 18: / Line 30: @@
 == 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.
+The tool contains the explanation necessary to understand its workings 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]]
@@ Line 27: / Line 40: @@
 === 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”):
+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 for 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
@@ Line 35: / Line 48: @@
 *Nutritional and health claim
-'Here is a set of pictures of the Presentation format attribute, by species in each country.''
+'Here is a set of pictures of the Presentation format attribute, by species in each country.
 ===== France =====
@@ Line 60: / Line 73: @@
 === Results ===
-[[File:Wtp results 1.png|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 2.png|results]]
 == References & readings ==

@@ Line 21: / Line 21: @@
 === Landing page ===
 [[File:Wtp home.png|home]]
@@ Line 26: / Line 27: @@
 === 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”):
+[[File:Wtp table a3 france.png|center|WTP Table A3 - France.]]
-* Price
+[[File:Wtp table a3 germany.png|center|WTP Table A3 - Germany.]]
-'Here is a set of pictures of the Presentation format attribute, by species in each country.''
+===== Italy =====
-=====France=====
+[[File:Wtp table a3 italy.png|center|WTP Table A3 - Italy.]]
-=====Germany=====
+===== Spain =====
-=====Italy=====
+[[File:Wtp table a3 spain.png|center|WTP Table A3 - Spain.]]
-=====Spain=====
+===== UK =====
-=====UK=====
+[[File:Wtp table a3 uk.png|center|WTP Table A3 - UK.]]
 === Results ===
 [[File:Wtp results 1.png|results]]
 == References & readings ==

@@ Line 10: / Line 10: @@
 ----
-The average apparent fish consumption per capita in the EU is the second highest in the world
+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.
 &nbsp;
-==Tool overview ==
+=====Italy=====
-The tool contains the explanation necessary to understand its working and results.
+=====Spain=====
-Once you select the product attributes and click the Run button, a results page
+[[File:Wtp_table_a3_spain.png|center|WTP Table A3 - Spain.]]
-===Landing page===
+=====UK=====
-===Results===
+=== Results ===
-[[File:Wtp_results_1.png|results]]
+[[File:Wtp results 1.png|results]]
-==References & readings==
+== References & readings ==

@@ Line 1,920: / Line 1,920: @@
-== The tool ==
 ----
-The WTP tool is a simple implementation of an aggregator value based on the data collected in the research phase.
+The WTP tool is a simple implementation of an aggregator value based on the data collected in the research phase. Similar to any other tool, the WTP can be accessed by clicking the quick access menu for the WTP in the [htpp://dss.primefish.eu/index.php/registered-home DSS] home page or by clicking its respective link in the top navigation bar. The user will be redirected to the WTP home page.
-Once in the home page, the user can select the different attributes of the proposed product to be analysed and
+=== WTP home page ===
-===WTP results page===
+[[File:Wtp home.JPG|center|WTP homepage.]]
-[[File:Wtp_results.JPG|center|WTP results.]]
+Once in the home page, the user can select the different attributes of the proposed product to be analysed and click the '''Run WTP tool''' button to generate the results.
-The results page displays to the user the maximum valuer that a consumer is willing to pay for a product.
+=== WTP results page ===
 == References & Readings ==

@@ Line 1: / Line 1: @@
 = Willingness to Pay =
@@ Line 1,881: / Line 1,882: @@
 ''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.]]
@@ Line 1,886: / Line 1,888: @@
 ''Table A2: Preliminary list of attributes and levels by species.''
 [[File:Wtp_table_a2.JPG|center|WTP Table A2.]]
@@ Line 1,892: / Line 1,895: @@
 =====France=====
-[[File:Wtp_table_a3_france.PNG|center|WTP Table A3 - France.]]
+[[File:Wtp_table_a3_france.png|center|WTP Table A3 - France.]]
 =====Germany=====
-[[File:Wtp_table_a3_germany.PNG|center|WTP Table A3 - Germany.]]
+[[File:Wtp_table_a3_germany.png|center|WTP Table A3 - Germany.]]
 =====Italy=====
-[[File:Wtp_table_a3_italy.PNG|center|WTP Table A3 - Italy.]]
+[[File:Wtp_table_a3_italy.png|center|WTP Table A3 - Italy.]]
 =====Spain=====
-[[File:Wtp_table_a3_spain.PNG|center|WTP Table A3 - Spain.]]
+[[File:Wtp_table_a3_spain.png|center|WTP Table A3 - Spain.]]
 =====UK=====
-[[File:Wtp_table_a3_uk.PNG|center|WTP Table A3 - UK.]]
+[[File:Wtp_table_a3_uk.png|center|WTP Table A3 - UK.]]

@@ Line 1,892: / Line 1,892: @@
 =====France=====
-[[File:Wtp_table_a3_france.JPG|center|WTP Table A3 - France.]]
+[[File:Wtp_table_a3_france.PNG|center|WTP Table A3 - France.]]
 =====Germany=====
-[[File:Wtp_table_a3_germany.JPG|center|WTP Table A3 - Germany.]]
+[[File:Wtp_table_a3_germany.PNG|center|WTP Table A3 - Germany.]]
 =====Italy=====
-[[File:Wtp_table_a3_italy.JPG|center|WTP Table A3 - Italy.]]
+[[File:Wtp_table_a3_italy.PNG|center|WTP Table A3 - Italy.]]
 =====Spain=====
-[[File:Wtp_table_a3_spain.JPG|center|WTP Table A3 - Spain.]]
+[[File:Wtp_table_a3_spain.PNG|center|WTP Table A3 - Spain.]]
 =====UK=====
-[[File:Wtp_table_a3_uk.JPG|center|WTP Table A3 - UK.]]
+[[File:Wtp_table_a3_uk.PNG|center|WTP Table A3 - UK.]]
@@ Line 1,939: / Line 1,939: @@
 It also shows the WTP ammount variation for each attribute in the chosen country, as well as
 the WTP comparison for the same attributes chosen but for different species in the country selected.
-The user can click the button on the bottom of the results page to return to the WTP home page and perform another analysis or click any other link to navigate to other sections of the DSS.
+The user can click the button on the bottom of the results page to return to the WTP home page and perform another
@@ Line 1,984: / Line 1,985: @@
 ===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