Fuzzy-FMEA Theory Approach for Prioritizing Supply Chain Nervousness Factors

Abstract

Global supply chain shocks and interruptions underscore the importance of supply chain nervousness (SCN). A clear understanding of nervousness in the event of a crisis allows an organization to make a good plan to deal with interruptions and future shocks. This study aims to develop a model for assessing nervousness parameters in the supply chains (SCs) by incorporating the fuzzy-FMEA theory and gray correlation approach to rank the SCN factors. The integrated model used in this study can improve the accuracy of outcomes when uncertainty exists in the SCN data. The results show that the most important nervousness factors are SC planning, visibility, stability, decision support systems, and SC flexibility. The developed SCN approach allows understanding and prioritizing SCN factors with more realistic and effective assessment. Findings offer beneficial insights for SCN prevention, and suggestions are made to identify nervousness mitigations. The outcomes of this research can be used by researchers and SC specialists to develop decision support systems.