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Decision Modeling with Risk Cascading Propagation Effects

In: Modeling and Resilience Recovery for Disrupted Supply Chain

Author

Listed:
  • Chen Peng

    (Shanghai University, School of Mechatronic Engineering and Automation)

  • Hongfeng Wang

    (Northeastern University)

  • Yi Yang

    (Shanghai University)

  • Yong Zhang

    (China University of Mining and Technology, School of Information and Control Engineering)

Abstract

To address the uncertainty of risk propagation in product and SC change systems under COVID-19, this chapter proposes an assessment-to-control decision support scheme. The bullwhip effect (BE), integrating operational and behavioral causes, is quantified as cascading amplified inventory fluctuations, while the ripple effect (RE) from large-scale supplier disruptions is measured by increased entropy rates (ERs). A closed-loop control system is constructed, and criteria for the existence of controller gains are derived to stabilize the system and mitigate BE under RE. A mask SC case study verifies the scheme’s effectiveness: the controller significantly suppresses BE even with RE, and control theory confirms that RE drives BE amplification. This chapter provides reliable support for SC risk decision-making.

Suggested Citation

  • Chen Peng & Hongfeng Wang & Yi Yang & Yong Zhang, 2026. "Decision Modeling with Risk Cascading Propagation Effects," Springer Books, in: Modeling and Resilience Recovery for Disrupted Supply Chain, chapter 0, pages 91-117, Springer.
    • Handle: RePEc:spr:sprchp:978-981-95-4901-6_5
    DOI: 10.1007/978-981-95-4901-6_5
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