Green Supplier Prioritization in Food Manufacturing: A Hybrid Fuzzy Decision Model for Sustainability and Resilience Performance
Main article
Abstract
This study develops a hybrid fuzzy decision model for prioritizing green suppliers in food manufacturing where procurement teams must balance price, product safety, carbon performance, social responsibility, and disruption recovery. Unlike conventional supplier selection models that focus mainly on cost or quality, the proposed model integrates sustainability and resilience performance into one auditable prioritization process. The model combines a fuzzy linguistic evaluation scale, subjective expert weighting, objective CRITIC-based contrast weighting, and a fuzzy TOPSIS ranking procedure. A case study of six candidate suppliers for a mid-sized Chinese food manufacturer is used to demonstrate the model. Sixteen criteria are organized into four dimensions: economic reliability, environmental performance, social and food-safety responsibility, and operational resilience. The results show that recovery speed, food safety governance, buffer capacity, multi-source adaptability, and labor and welfare compliance receive the highest hybrid weights. Supplier A1 obtains the highest final fuzzy closeness score, followed by A5 and A3. Sensitivity tests indicate that the top two suppliers remain stable when the balance between subjective and objective weights changes, while the middle-ranked suppliers are more sensitive to the decision maker's strategic emphasis. The findings suggest that food manufacturers should not treat green supplier selection as a single environmental screening problem. Instead, it should be designed as a portfolio decision that links green capability, product safety, traceability, and resilience. The study contributes a practical fuzzy decision-support framework for procurement managers and extends green supply chain research by demonstrating how sustainability and resilience can be jointly operationalized in supplier prioritization.
