Exploring dependency based probabilistic supply chain risk measures for prioritising interdependent risks and strategies

Abroon Qazi, John Quigley, Alex Dickson, Şule Önsel Ekici

Research output: Contribution to journalArticlepeer-review

52 Citations (Scopus)
24 Downloads (Pure)


In this paper, we introduce an integrated supply chain risk management process that is grounded in the theoretical framework of Bayesian Belief Networks capturing interdependency between risks and risk mitigation strategies, and integrating all stages of the risk management process. The proposed process is unique in four different ways: instead of mapping the supply network, it makes use of Failure Modes and Effects Analysis to model the risk network which is feasible for modelling global supply chains; it is driven by new dependency based risk measures that can effectively capture the network wide impact of risks for prioritisation; it utilises the concept of Shapley value from the field of cooperative game theory to determine a fair allocation of resources to the critical risks identified; and the process helps in prioritising potential risk mitigation strategies (both preventive and reactive) subject to budget and resource constraints. We demonstrate its application through a simulation study.
Original languageEnglish
Pages (from-to)189–204
Number of pages16
JournalEuropean Journal of Operational Research
Issue number1
Early online date20 Oct 2016
Publication statusE-pub ahead of print - 20 Oct 2016


  • supply chain risk management
  • Bayesian belief networks
  • failure modes and effects analysis (FMEA)
  • risk measures
  • risk mitigation strategies

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