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Behavior evolution of supply chain networks under disruption risk — From aspects of time dynamic and spatial feature

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  • Wang, Jiepeng
  • Zhou, Hong
  • Zhao, Yujie

Abstract

Supply chain disruptions are inevitable and may bring about fatal influence to the system. In this article, we examine how up and downstream firms embedded in a supply chain network engage in decision-making under disruption risk. The decision evolution of the supply chain network, treated as a complex adaptive system (CAS), is investigated from both the aspects of time dynamic and spatial feature by employing the Evolutionary Game Theory (EGT) and Cellular Automata (CA) approach, respectively. Supply chain network agents (i.e., up and downstream firms) are supposed to have two optional responses, positive strategy or negative strategy when facing the disruption risk. By observing a series of simulation experiments on the developed EGT model and CA model, we offer some testable propositions regarding the behavioral nature of the agents in the supply chain network. Some managerial insights in managing supply chain disruption risk are presented as well. We find that the spatial feature of the supply chain network plays a vital role in the evolution process which can lead the system to a more satisfactory equilibrium, compared with the evolution process only considering the time dynamic.

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  • Wang, Jiepeng & Zhou, Hong & Zhao, Yujie, 2022. "Behavior evolution of supply chain networks under disruption risk — From aspects of time dynamic and spatial feature," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    • Handle: RePEc:eee:chsofr:v:158:y:2022:i:c:s0960077922002831
    DOI: 10.1016/j.chaos.2022.112073
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    1. Wang, Jiepeng & Zhou, Hong & Sun, Xinlei & Yuan, Yufei, 2023. "A novel supply chain network evolving model under random and targeted disruptions," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).

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