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

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.

Keywords

• fish supply chain
• post harvest losses
• post-harvest fish losses
• fuzzy topsis
• mcdm