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

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

Abstract

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.

Suggested Citation

  • Qazi, Abroon & Quigley, John & Dickson, Alex & Ekici, Şule Önsel, 2017. "Exploring dependency based probabilistic supply chain risk measures for prioritising interdependent risks and strategies," European Journal of Operational Research, Elsevier, vol. 259(1), pages 189-204.
  • Handle: RePEc:eee:ejores:v:259:y:2017:i:1:p:189-204
    DOI: 10.1016/j.ejor.2016.10.023
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    1. Botond Kőszegi & Matthew Rabin, 2006. "A Model of Reference-Dependent Preferences," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(4), pages 1133-1165.
    2. Tang, Christopher S. & Davarzani, Hoda & Sarkis, Joseph, 2015. "Quantitative models for managing supply chain risks: A reviewAuthor-Name: Fahimnia, Behnam," European Journal of Operational Research, Elsevier, vol. 247(1), pages 1-15.
    3. Norrington, Lisa & Quigley, John & Russell, Ashley & Van der Meer, Robert, 2008. "Modelling the reliability of search and rescue operations with Bayesian Belief Networks," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 940-949.
    4. Trkman, Peter & McCormack, Kevin, 2009. "Supply chain risk in turbulent environments--A conceptual model for managing supply chain network risk," International Journal of Production Economics, Elsevier, vol. 119(2), pages 247-258, June.
    5. Pfohl, Hans-Christian & Gallus, Philipp & Thomas, David, 2011. "Interpretive structural modeling of supply chain risks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 55230, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Garvey, Myles D. & Carnovale, Steven & Yeniyurt, Sengun, 2015. "An analytical framework for supply network risk propagation: A Bayesian network approach," European Journal of Operational Research, Elsevier, vol. 243(2), pages 618-627.
    7. Ashrafi, Maryam & Davoudpour, Hamid & Khodakarami, Vahid, 2015. "Risk assessment of wind turbines: Transition from pure mechanistic paradigm to modern complexity paradigm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 347-355.
    8. Tang, Christopher & Tomlin, Brian, 2008. "The power of flexibility for mitigating supply chain risks," International Journal of Production Economics, Elsevier, vol. 116(1), pages 12-27, November.
    9. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    10. Bogataj, David & Bogataj, Marija, 2007. "Measuring the supply chain risk and vulnerability in frequency space," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 291-301, July.
    11. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    12. Ackermann, Fran & Howick, Susan & Quigley, John & Walls, Lesley & Houghton, Tom, 2014. "Systemic risk elicitation: Using causal maps to engage stakeholders and build a comprehensive view of risks," European Journal of Operational Research, Elsevier, vol. 238(1), pages 290-299.
    13. Faisal Aqlan & Sarah S. Lam, 2015. "Supply chain risk modelling and mitigation," International Journal of Production Research, Taylor & Francis Journals, vol. 53(18), pages 5640-5656, September.
    14. Wu, Wei-Shing & Yang, Chen-Feng & Chang, Jung-Chuan & Château, Pierre-Alexandre & Chang, Yang-Chi, 2015. "Risk assessment by integrating interpretive structural modeling and Bayesian network, case of offshore pipeline project," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 515-524.
    15. Oke, Adegoke & Gopalakrishnan, Mohan, 2009. "Managing disruptions in supply chains: A case study of a retail supply chain," International Journal of Production Economics, Elsevier, vol. 118(1), pages 168-174, March.
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