Exploring supply chain network resilience in the presence of the ripple effect

Yuhong Li and Christopher W. Zobel

International Journal of Production Economics, 2020, vol. 228, issue C

Abstract: This study aims to investigate overall supply chain network resilience (SCNR) in the presence of ripple effect, or risk propagation, i.e. the phenomenon that disruptions at a few firms in a supply chain network (SCN) can spread to their neighboring firms, then eventually spread to other firms in the SCN. We begin by developing a multi-dimensional quantitative framework to measure SCNR, which includes three resilience dimensions based on three different network performance indicators. Given this framework, we then systematically explore the determining factors of SCNR and present a comprehensive analysis of how network structure and node risk capacity influence different aspects of SCNR. Our results clearly indicate the following important implications for managers. First, the influence of network type on SCNR tends to be more significant in the short-term than it is in the longer-term, given the ripple effect. Second, SCNR can be improved more effectively by enhancing node risk capacity than by adjusting network structure. Third, tradeoffs exist between the robustness of the network against a disruption and its ability to recover from that disruption. Fourth, different network performance indicators can provide different perspectives on SCNR. Together these help show that the multi-dimensional framework enables a better characterization of the complexity of SCNR, and thus that it provides support for more informed managerial decision-making about investing in improving resilience. The paper concludes the discussion by addressing opportunities for further extending the research effort.

Keywords: Supply chain network resilience; Risk propagation; Network structure; Node risk capacity (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (58)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:228:y:2020:i:c:s0925527320300840

DOI: 10.1016/j.ijpe.2020.107693

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