A Hybrid Multi-Criteria Decision-Making Framework for Prioritizing Supply Chain Risks in Perishable Food Manufacturing

Abstract

Food-processing supply chains are severely threatened by interruptions in procurement, storage and transport due to the perishability of products and the strict delivery demands. Conventional risk models rank the importance of the factors, but do not differentiate the root causes from the downstream consequences. The study proposes a multi-method framework for assessing ten critical disruption factors with the use of expert judgments. RII used to Quantifies perceived factor importance for Maps structural dependencies and hierarchy ISM is used. Fuzzy DEMATEL Identifies direct or indirect causal drivers despite expert ambiguity. AHP Establishes priority weights for strategic intervention. (F6) was perceived as the most important (RII) = 0.9857, but (F10) was the key root-cause driver (D - R = 1.574). AHP validated F10 as the highest priority for intervention (weight: 0.2189), followed by storage violations (F7) and demand spikes (F8). Highly visible disruptions are often symptoms not root causes. Focusing interventions on underlying causal drivers such as traceability significantly enhances overall food supply-chain resilience.