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Modelling default dependence in automotive supply networks using vine-copula

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  • Farzad Alavifard

Abstract

This paper presents an intuitive model for default dependencies in supply networks and its application in firms’ capital management. Modern supply chain networks are characterised by horizontal ties between firms within a particular industry or group, which are sequentially arranged based on vertical ties between firms in different layers. The recognition and accounting of these simultaneous interdependencies is crucial for a more advanced understanding of complex inter-organisational relations. Using the state-of-the art vine-copulae, we model these multidimensional interdependencies in the automotive industry, and capture the default tail dependency between alliance partners. Further, we apply our model to determine the optimal economic capital, such that companies can absorb unexpected losses from defaults in supply chain, while avoiding over-capitalisation. Our findings should spur managers to analyse their supplier networks with respect to default dependencies and to take this phenomenon into consideration when making sourcing decisions.

Suggested Citation

  • Farzad Alavifard, 2019. "Modelling default dependence in automotive supply networks using vine-copula," International Journal of Production Research, Taylor & Francis Journals, vol. 57(2), pages 433-451, January.
  • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:2:p:433-451
    DOI: 10.1080/00207543.2018.1443522
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    Cited by:

    1. Sun Meng & Yan Chen, 2023. "Market Volatility Spillover, Network Diffusion, and Financial Systemic Risk Management: Financial Modeling and Empirical Study," Mathematics, MDPI, vol. 11(6), pages 1-16, March.

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