4.5 Article

A fuzzy approach to decision-making in sea-cage aquaculture production

Journal

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
Volume 30, Issue 4, Pages 2000-2024

Publisher

WILEY
DOI: 10.1111/itor.12866

Keywords

aquaculture; multicriteria decision-making; fuzzy TOPSIS; fuzzy pay-off

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Despite the rapid growth in productivity and scale of aquaculture companies, their economic results have experienced high volatility. This is due to the increasing complexity of management issues, changes in seafood consumption patterns, and the high uncertainty in decision-making processes. To address this, a fuzzy model has been proposed to help aquaculture producers manage uncertainty related to climate change and market price scenarios when making production decisions.
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.

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