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Modeling defaults of companies in multi-stage supply chain networks

Author

Listed:
  • Mizgier, Kamil J.
  • Wagner, Stephan M.
  • Holyst, Janusz A.

Abstract

The interest in supply chain networks and their analysis as complex systems is rapidly growing. The physical approach to the topic draws on the concept of heterogenous interacting agents. The interaction among agents is considered as a repeated process of orders and production. The dynamics of production in the supply chain network which we observe is nonlinear due to the random failures in processes of orders and production. We introduce an agent-based model of a supply chain network which represents in more detail the real economic environment in which firms operate. We focus on the influence of local processes on the global economic behavior of the system and study how the proposed modifications change the general properties of the model. We observe collective bankruptcies of firms, which lead to self-emerging network structures. Our results give insight into the dynamics of default processes in supply chain networks, which have important implications both for risk managers and policy makers. Based on the simulations we show that agent-based modeling is a powerful tool for optimization of supply chain networks.

Suggested Citation

  • Mizgier, Kamil J. & Wagner, Stephan M. & Holyst, Janusz A., 2012. "Modeling defaults of companies in multi-stage supply chain networks," International Journal of Production Economics, Elsevier, vol. 135(1), pages 14-23.
  • Handle: RePEc:eee:proeco:v:135:y:2012:i:1:p:14-23
    DOI: 10.1016/j.ijpe.2010.09.022
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Wuttke, David A. & Blome, Constantin & Henke, Michael, 2013. "Focusing the financial flow of supply chains: An empirical investigation of financial supply chain management," International Journal of Production Economics, Elsevier, vol. 145(2), pages 773-789.
    2. Mizgier, Kamil J. & Wagner, Stephan M. & Jüttner, Matthias P., 2015. "Disentangling diversification in supply chain networks," International Journal of Production Economics, Elsevier, vol. 162(C), pages 115-124.
    3. Chong, You Quan & Wang, Bin & Yue Tan, Gladys Li & Cheong, Siew Ann, 2014. "Diversified firms on dynamical supply chain cope with financial crisis better," International Journal of Production Economics, Elsevier, vol. 150(C), pages 239-245.
    4. Dominguez, Roberto & Cannella, Salvatore & Framinan, Jose M., 2015. "On returns and network configuration in supply chain dynamics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 73(C), pages 152-167.
    5. Lee, Byung Kwon & Zhou, Rong & de Souza, Robert & Park, Jaehun, 2016. "Data-driven risk measurement of firm-to-firm relationships in a supply chain," International Journal of Production Economics, Elsevier, vol. 180(C), pages 148-157.
    6. Chen, Tsung-Kang & Liao, Hsien-Hsing & Kuo, Hui-Ju, 2013. "Internal liquidity risk, financial bullwhip effects, and corporate bond yield spreads: Supply chain perspectives," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2434-2456.
    7. Mohammad Fathian & Javid Jouzdani & Mehdi Heydari & Ahmad Makui, 0. "Location and transportation planning in supply chains under uncertainty and congestion by using an improved electromagnetism-like algorithm," Journal of Intelligent Manufacturing, Springer, vol. 0, pages 1-18.
    8. Wagner, Stephan M. & Mizgier, Kamil J. & Papageorgiou, Stylianos, 2017. "Operational disruptions and business cycles," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 66-78.
    9. Chowdhury, Md. Maruf Hossan & Quaddus, Mohammed A., 2015. "A multiple objective optimization based QFD approach for efficient resilient strategies to mitigate supply chain vulnerabilities: The case of garment industry of Bangladesh☆,☆☆☆This manuscript was pro," Omega, Elsevier, vol. 57(PA), pages 5-21.
    10. Charles D. Brummitt & Kenan Huremovic & Paolo Pin & Matthew H. Bonds & Fernando Vega-Redondo, 2017. "Contagious disruptions and complexity traps in economic development," Papers 1707.05914, arXiv.org.
    11. Sungchul Cho & Up Lim, 2016. "The Sustainability of Global Chain Governance: Network Structures and Local Supplier Upgrading in Thailand," Sustainability, MDPI, Open Access Journal, vol. 8(9), pages 1-13, September.

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