A fuzzy group decision-making model to measure resiliency in a food supply chain: A case study in Spain

The concept of supply chain management (SCM) has transformed and evolved beyond the simple rationality of benefit and economic viewpoints. With changing societal requirements in terms of the global risk-based economy, SCMs should be resilient and flexible to handle risk and quickly respond to disruptions. A food supply chain (FSC) is a critical global supply chain network due to its crucial role in meeting the growing consumer demand for edible products. Any disruptions and risks in FSC management (FSCM) may lead to irrecoverable and costly consequences; therefore, the resiliency of key players in the food SCM is very important. In this regard, this paper develops a decision-making model using the best worst method (BWM) and fuzzy measurement of alternatives and ranking according to compromise solution (fuzzy MARCOS) to measure the resiliency of key players in the FSCM with respect to different resiliency and risk factors. Sensitivity analysis tests to examine the reliability of the model are conducted. A case study of the agricultural FSCM of Andalusia Province of Spain is used to investigate the practicability of the proposed model. The results indicate that natural disasters and water system failures are two important risk factors with the highest weight coefficients, and excessive inventory was determined to be the least important risk factor. Moreover, supermarkets and wholesalers are determined to be the most resilient players in the FSCM of Andalusia Province of Spain. •Integrated fuzzy group decision making model for measuring resiliency performance in food supply chain.•Case study of agriculture and food supply chain sector of Andalusia province of Spain.•Consideration of judgmental conflicts, information inaccuracy and uncertainty.•Sensitivity analysis for testing stability of proposed model.