Supply Chain Resilience: A Common Weights Efficiency Analysis with Non-discretionary and Non-controllable Inputs

Abstract

Supply chain resilience (SCRes) as the supply chain network's (SCN) capacity is essential to recover from disruptions. The economic, environmental, and geopolitical regional characteristics of the Pacific region present many challenges and opportunities for building supply chain resilience. This study aims to measure the resilience of supply chains (SCs) considering the characteristics of the network under which they operate. In this study, we proposed a new common set of weights (CSW) model in data envelopment analysis to evaluate the resilience of SCNs. Many external variables beyond decision-makers’ direct control impact SC operations and their resilience. Therefore, the proposed CSW model formulates the non-discretionary and non-controllable inputs in measuring the resilience of SCNs and provides a complete ranking with a higher discrimination power. To improve SCRes, SC managers are recommended to enhance the clustering coefficient and node degree of their SCN by establishing more connections with other SCNs in order to pinpoint the essential capabilities that companies should prioritise in order to develop a stronger and more adaptable SC in the post-COVID-19 pandemic.