The reduction of food loss and waste (FLW) serves as a vital indicator for achieving the targets set within sustainable development goals (SDGs). Reduced FLW and SDGs are interrelated concepts that share a common focus on sustainability and global development. In this study, FLW barriers in the perishable food supply chain (PFSC) are identified through an extensive literature study and expert opinions gathered through brainstorming sessions. Subsequently, assessed using fuzzy decision-making trial and evaluation laboratory (DEMATEL) analysis, which enables a comprehensive understanding of the complex interrelationships among these barriers. The result reveals that the factors like ‘Inefficient Transport,’ ‘Bulk Purchase,’ and ‘Distribution Lead Time’ exhibit the highest level of interaction among all factors. These findings underscore the significance of addressing challenges related to transportation processes and bulk purchasing practices to enhance overall supply chain efficiency and reduce FLW. Moreover, ‘Inadequate connectivity between farmers and processing units’ and ‘Inefficient Transport’ are identified as the most influential factors in the entire FLW within the PFSC system. Their pivotal role in shaping the supply chain’s performance underscores the need for targeted interventions to improve connectivity between stakeholders and enhance transportation efficiency. The deployment of the fuzzy DEMATEL model provides robust ranks for the factors based on their (R + C) values, affirming the reliability of the methodology. These ranks remain consistent across sensitivity analyses, reinforcing the study’s findings and the reliability of the identified influential factors. Eventually, the study includes valuable insights for policymakers, industry practitioners, and stakeholders which may lead them to better resource utilization, waste reduction, and enhanced sustainability in the PFSC, contributing to the achievement of SDGs. However, the study’s limitations include the reliance on expert opinions and data availability, which may impact the comprehensiveness of the identified factors.