A fuzzy approach to decision‐making in sea‐cage aquaculture production. (25th August 2020)

• Record Type: Journal Article
• Authors: Luna, Manuel; Llorente, Ignacio; Cobo, Angel
• Other Names: Albornoz Víctor M. guestEditor.; Cancela Héctor guestEditor.; Cawley Alejandro Mac guestEditor.; Maturana Sergio guestEditor.; Weintraub Andrés guestEditor.
• Is Part Of: International transactions in operational research. Volume 30:Number 4(2023)
• Page Start: 2000
• Page End: 2024
• Publication Date: 2020-08-25
• Subjects: aquaculture -- multicriteria decision‐making -- fuzzy TOPSIS -- fuzzy pay‐off; Operations research -- Periodicals; 003
• DOI: 10.1111/itor.12866
• Languages: English
• ISSNs: 0969-6016

Abstract

Abstract: Despite the rapid growth in productivity and scale of business production of aquaculture companies in the last few years, their economic results have still experienced very high volatility. This can be partly explained by the increasing complexity of management issues and the strong changes in seafood consumption patterns. But, above all else, companies' results are affected by the conditions of high uncertainty in the decision‐making processes, due to the large number of biological, technical, economic, and environmental influencing factors, many of them beyond the control of managers. In this context, the number of variables, scenarios, and the volume of data to be considered in decision‐making is increasing and, therefore, technological advances are becoming much more accepted and requested. This work presents a fuzzy model that allows aquaculture producers to easily manage the uncertainty regarding climate change and market price scenarios when they are facing production decisions, such as the choice between traditional or ecological production. To that end, this novel approach uses the fuzzy pay‐off method to estimate the companies' economic performance and a discrete multicriteria decision‐making technique (fuzzy TOPSIS) to integrate economic, environmental, and product quality criteria in the selection of the most appropriate production alternative.