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  • 标题:Future Developments in German Fish Market – Integration of Market Expert Knowledge into a Modelling System
  • 本地全文:下载
  • 作者:Laura Angulo ; Petra Salamon ; Martin Banse
  • 期刊名称:Proceedings in Food System Dynamics
  • 印刷版ISSN:2194-511X
  • 出版年度:2017
  • 页码:94-100
  • DOI:10.18461/pfsd.2017.1710
  • 语种:English
  • 出版社:Proceedings in Food System Dynamics
  • 摘要:Globally fish has become more important in the human nutrition, thus global consumption is expected to highly increase in the future years. Business-as-usual projections for fish market are limited by availability of reliable data that hinders the differentiation on fish category level on the supply and demand side and across EU member states. The Fishmodul in AGEMEMOD provides long term predictions for the fish market by fish categories at EU member state level. For this, a status-quo simulation to the year 2030 is developed in AGMEMOD. Additionally, opinions of market experts from private sector and research institutions through interviews and an elaborated questionnaire is integrated into the model to deal with the insufficient information. Thus, expertise knowledge provides better and accurate information of the sector for market projections. As results, baseline projections were adjusted, showing a slowly increase over the years, but higher production level by 2030.
  • 其他摘要:Globally fish has become more important in the human nutrition, thus global consumption is expected to highly increase in the future years. Business-as-usual projections for fish market are limited by availability of reliable data that hinders the differentiation on fish category level on the supply and demand side and across EU member states. The Fishmodul in AGEMEMOD provides long term predictions for the fish market by fish categories at EU member state level. For this, a status-quo simulation to the year 2030 is developed in AGMEMOD. Additionally, opinions of market experts from private sector and research institutions through interviews and an elaborated questionnaire is integrated into the model to deal with the insufficient information. Thus, expertise knowledge provides better and accurate information of the sector for market projections. As results, baseline projections were adjusted, showing a slowly increase over the years, but higher production level by 2030.
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