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Research on Trade Credit Spreading and Credit Risk within the Supply Chain

Author

Listed:
  • Qian Qian

    (School of Economics and Management, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China)

  • Yang Yang

    (#x2020;School of Economic Mathematics, Southwestern University of Finance and Economics, Chengdu, 611130, P. R. China)

  • Zong-Fang Zhou

    (School of Economics and Management, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China)

Abstract

Capital constraints in the supply chain have linked trade credit to the banks’ credit risk exposure. This paper focuses on how trade credit, which is widespread in the supply chain, affects the banks’ risk exposure by constructing a two-echelon Stackelberg framework in a case involving supplier dominance. A numerical analysis illustrates the following: First, the contagion intensity, which measures trade credit’s impact on the banks’ risk exposure, positively relates to the uncertainty of demand. Second, the retailer’s characteristics have a significant, moderating effect on this positive relationship between the banks’ risk exposure and the uncertainty demand. Finally, suppliers can reduce the contagion intensity by screening different types of retailers, which consequently decreases the banks’ risk exposure.

Suggested Citation

  • Qian Qian & Yang Yang & Zong-Fang Zhou, 2019. "Research on Trade Credit Spreading and Credit Risk within the Supply Chain," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 389-411, January.
  • Handle: RePEc:wsi:ijitdm:v:18:y:2019:i:01:n:s0219622018410018
    DOI: 10.1142/S0219622018410018
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    Cited by:

    1. Melika Parichehreh & Nikbakhsh Javadian, 2020. "A Mixed-Integer Programming Model to Configure a Post Supply Chain Network," Annals of Data Science, Springer, vol. 7(2), pages 281-290, June.

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