The application of complex network theory for resilience improvement of knowledge-intensive supply chains

Abstract

With frequent political conflicts and public health emergencies, global supply chains are constantly under risk interference, significantly reducing supply chain resilience (SCR), especially for the knowledge-intensive supply chains (KISCs). To assess and improve the resilience of KISC, this paper uses complex network theory to construct a directed weighted network model suitable for KISC and expresses the SCR as a comprehensive capability that can resist risk and recover from it. Using quantitative indicators plus qualitative assessment to quantify the resilience index and identify the network key nodes. Two resilience improvement paths are proposed for KISCs, improving firms’ development capacity and industrial backup. In the case study, the resilience of the integrated circuit (IC) supply chain is assessed and improved according to real data from the global IC industry. The findings show that (i) The resilience assessment based on the directed weighted network aligns with industrial reality. (ii) Improving firms’ development capability and industrial backup can improve SCR. (iii) Effective improvement of resilience requires targeting key nodes in the supply chain network (SCN). Moreover, the degree of firms’ development capability improvement and industrial backup intensity should be within a specific range.