A quantitative social network analysis approach to mitigate the ripple effect in supply chain networks

Supply chain network disruptions have become an increasingly relevant topic in literature and industry. Just recently the COVID-19 pandemic demonstrated the need for greater resilience in global supply chain networks. We present a quantitative social network analysis (SNA) approach to selectively fortify nodes in complex supply chain networks targeting ripple-effect mitigation and enhancing supply chain network resilience (SCNR). Our model can be used to analyze supply chain resilience and derive strategies to mitigate disruptions, specifically using betweenness centrality for fortification. The model can be applied by supply chain managers to existing supply chain networks regardless of the underlying network type