Fuzzy TOPSIS for Post-Harvest Losses Drivers Evaluation in Fish Supply Chain: A Case Study

Muhammad Faisal Ibrahim, Taufik Kurrahman, Prita Meilanitasari
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Abstract

Being highly susceptible to damage, fish result in significant post-harvest fish losses (PHFL) due to quality deterioration from inefficient harvesting and market dynamics. This study aims to identify the leading factors driving PHFL and construct a practical decision-making framework for the fisheries industry's development. Employing the fuzzy TOPSIS method, we scrutinized the critical causes of PHFL. Our literature review revealed four aspects and 13 operational processes contributing to PHFL across the supply chain. Among these processes, four drivers were the primary culprits: excessive fish capacity in shipping baskets, inadequate ice cooling during transportation to suppliers, insufficient ice cooling during supplier sorting, and the absence of appropriate tools for small retailers. To alleviate PHFL and enhance the fishery industry, priority should be given to addressing excessive fish capacity in shipping baskets, which poses a risk of physical damage during transit. Moreover, inadequate ice-cooling techniques, particularly in transportation and supplier sorting stages, raise public health and food safety concerns. Stakeholders must prioritize these critical factors for PHFL reduction.
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渔业供应链采后损失驱动因素评价的模糊TOPSIS方法研究
鱼类极易受到损害,由于低效率的捕捞和市场动态导致质量恶化,导致收获后鱼类损失严重。本研究旨在找出推动渔业产业发展的主要因素,并建构一个实用的渔业产业发展决策框架。采用模糊TOPSIS方法,对PHFL的关键原因进行了分析。我们的文献综述揭示了整个供应链中促进PHFL的四个方面和13个操作流程。在这些过程中,四个驱动因素是主要的罪魁祸首:运输篮中鱼的容量过大,运输到供应商的过程中冰冷却不足,供应商分拣过程中冰冷却不足,以及小型零售商缺乏适当的工具。为了减轻PHFL和加强渔业,应优先解决运输篮中鱼类容量过大的问题,因为这在运输过程中有造成物理损害的危险。此外,冰冷却技术不足,特别是在运输和供应商分类阶段,引起了公众健康和食品安全方面的关切。利益相关者必须优先考虑减少PHFL的这些关键因素。
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