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Selection of Optimal Redundancy Strategies for a Supply Network

In: Innovations and Strategies for Logistics and Supply Chains: Technologies, Business Models and Risk Management. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 20

Author

Listed:
  • Qazi, Abroon
  • Quigley, John
  • Dickson, Alex
  • Gaudenzi, Barbara
  • Önsel, Şule

Abstract

Supply chains have become more vulnerable because of increased globalization and interdependency between network actors and risks. It is, therefore, extremely important to model interdependency between risks taking into account the supply network configuration. In this paper, we have followed the existing concept of modelling supply network as a Bayesian belief network capturing network configuration, probabilistic interdependency between risks and losses resulting from the realization of risks. We propose a new method for evaluating efficacy of different combinations of redundancy strategies. For each node of the network, we incorporated a strategy of adding redundant resource as a risk management approach that would disengage the particular node from its parent node(s). The model was solved against the bicriteria objective of maximizing normalized expected utility for loss exposure and normalized utility for cost of redundancy strategies keeping into account different risk attitudes and criteria weights. The model also helped in identifying optimal combination of strategies for specific allocation of budget as there could be different combinations of allocating redundant resources across the network resulting in supoptimal values of risk measures.

Suggested Citation

  • Qazi, Abroon & Quigley, John & Dickson, Alex & Gaudenzi, Barbara & Önsel, Şule, 2015. "Selection of Optimal Redundancy Strategies for a Supply Network," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Innovations and Strategies for Logistics and Supply Chains: Technologies, Business Models and Risk Management. Proceedings of the Hamburg Internationa, volume 20, pages 419-450, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    • Handle: RePEc:zbw:hiclch:209264
    DOI: 10.15480/882.1264
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    References listed on IDEAS

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    1. ManMohan S. Sodhi & Christopher S. Tang, 2012. "Supply Chain Risk Management," International Series in Operations Research & Management Science, in: Managing Supply Chain Risk, edition 127, chapter 0, pages 3-11, Springer.
    2. 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.
    3. Iwan Vanany & Suhaiza Zailani & Nyoman Pujawan, 2009. "Supply Chain Risk Management: Literature Review and Future Research," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 2(1), pages 16-33, January.
    4. ManMohan S. Sodhi & Christopher S. Tang, 2012. "Managing Supply Chain Risk," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4614-3238-8, December.
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