Difference between revisions of "CPA"
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Revision as of 22:50, 29 January 2018
Work Package 1: Data management
Introduction
WP1 develops and sets up the methodology that will be used to assess the competitiveness of European aquaculture and fisheries sectors. The methodology, which will use both macro-economic and micro-economic data as a basis, will build upon the methodology used in the Fishery Competitive Index which breaks down competitiveness into 3 major themes (Creating stability, Stimulating environment and Competence of the industry). The assessment methodology will be extended to cover aquaculture production and it will be revised to strengthen areas of product development, value chain management, marketing and innovation. The result will be a comprehensive index for fisheries and aquaculture competitiveness (FACI). On a disaggregated level, the index can be used to benchmark individual producers within a given sector. On an aggregated level, the index can be used to compare the competitiveness of sectors in different countries (as the original FCI work did) or different production sectors in the same country. The index will be computerised for data exploration in WP2 and WP3 and for modelling in WP5. An online resource will be created that allows for self-assessment. The outcome of the WP will be an adapted and updated methodology for the assessment of the competitiveness of aquaculture and fisheries (SO1).
Objectives
-To select, configure, extend and harmonise the use of the various methodologies involved in assessing the competitiveness of the aquaculture and fisheries sectors. This includes data collection methods and procedures, and data analysis methods. -To develop and extend the methodology to analyse competitiveness in seafood sectors to cover specific species (fished and farmed) and for peer comparison by individual companies. -To collect feedback from the respective method users; to evaluate the relevance, scope and suitability of the respective methods and to produce a comparative overview, both as part of the PrimeFish Decision Support Framework (PrimeDSF) and as a scientific publication in a peer-refereed journal.
