Prioritisation of strategies for the adoption of organic agriculture using BWM and fuzzy CoCoSo

  • Authors:
    Luis A. Fernández-Portillo, Morteza Yazdani, Lorenzo Estepa-Mohedano y Roberta Sisto
    Soft Computing
    Year: 2023


Organic agriculture offers numerous benefits to the environment, consumers, and farmers. However, its adoption remains slow, particularly in developing countries, where smallholders face multiple obstacles. To overcome these obstacles, specific strategies need to be designed and prioritised (ideally, with participative methods), requiring a decision-making process that is usually complex, and calls for the support of sophisticated tools. To help address this issue, this study aims to assess the feasibility of using two multi-criteria decision analysis techniques, the best–worst method (BWM) and the fuzzy combined compromise solution (F-CoCoSo) with direct inputs from the farmers, to prioritise strategies for overcoming the obstacles to organic agriculture in two departments of Paraguay. The study involved interviewing local smallholders to identify the key barriers to adopting organic agriculture using the BWM. Then, a group of producers were selected based on a social network analysis to prioritise a list of 20 strategies using the F-CoCoSo technique. Results revealed significant differences in strategy rankings between both departments, reflecting variations in farm size and product specialisation. The study’s findings could benefit farmers and policy practitioners supporting organic agriculture and demonstrate the feasibility of using these sophisticated techniques to promote organic agriculture in developing countries.

This work was supported by the Agencia Española de Cooperación Internacional para el Desarrollo, AECID (Spanish Agency for International Development Cooperation), under grant number 2020/PRYC/000982.

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