Risk Propagation and Supply Chain Health Control Based on the SIR Epidemic Model

Di Liang, Ran Bhamra, Zhongyi Liu () and Yucheng Pan
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Di Liang: School of Mechanical and Engineering, Shenyang University, Shenyang 110044, China
Ran Bhamra: School of Business and Management Royal Holloway, University of London, Egham TW20 0EX, UK
Zhongyi Liu: School of Mechanical and Engineering, Shenyang University, Shenyang 110044, China
Yucheng Pan: Yantai Zhenghai Magnetic Material Co., Ltd., Yantai 264006, China

Mathematics, 2022, vol. 10, issue 16, 1-16

Abstract: Risk propagation is occurring as an exceptional challenge to supply chain management. Identifying which supplier has the greater possibility of interruptions is pivotal for managing the occurrence of these risks, which have a significant impact on the supply chain. Identifying and predicting how these risks propagate and understanding how these risks dynamically diffuse if control strategies are installed can help to better manage supply chain risks. Drawing on the complex systems and epidemiological literature, we research the impact of the global supply network structure on risk propagation and supply network health. The SIR model is used to dynamically identify and predict the risk status of the supply chain risk at different times. The results show that there is a significant relationship between network structure and risk propagation and supply network health. We demonstrate the importance of supply network visibility and of the extraction of the information of node firms. We build up an R package for geometric graphs and epidemics. This paper applies the R package to model the supply chain risk for an automotive manufacturing company. The R package provides a firm to construct the complicated interactions among suppliers and display how these interactions impact on risks. Theoretically, our study adapts a computational approach to contribute to the understanding of risk management and supply networks. Managerially, our study demonstrates how the supply chain network analysis approach can benefit the managers by developing a more holistic framework of system-wide risk propagation. This provides guidance for network governance policies, which will lead to healthier supply chains.

Keywords: supply chain risk management; supply chain resilience; risk propagation; supply network health; SIR epidemic model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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