A Structured Fuzzy Framework for Risk Prioritization in Sustainable Food Supply Chains: Supporting the Sustainable Development Goals (SDGs) through a Case Study in Indonesia

Effective risk assessment is vital for achieving the Sustainable Development Goals (SDGs), particularly in food supply chains where uncertainty and complexity are prevalent. This study proposes a structured fuzzy framework that combines the Fuzzy Delphi Method and Fuzzy Best Worst Method (Fuzzy BWM) to identify, evaluate, and prioritize sustainability-related risks. A case study conducted in Indonesia involved expert insights from various sectors within the food supply chain. The Fuzzy Delphi Method was used to screen and validate relevant risks, while Fuzzy BWM enabled the prioritization of these risks across economic, social, and environmental dimensions. The results reveal that economic-related risks are of primary concern, followed by critical risks in the social and environmental domains. This framework improves decision-making accuracy by managing uncertainty and providing a clear basis for prioritizing actions. The findings offer practical guidance for companies seeking to strengthen their sustainability strategies and contribute meaningfully to SDGs through more resilient and responsible supply chain managemen.