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Supply chain risk modelling and mitigation

Author

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  • Faisal Aqlan
  • Sarah S. Lam

Abstract

In today’s global competitive environment, supply chains are more susceptible to vulnerability due to the increasing occurrence of internal and external risk events. In addition, the trend associated with lean management, which involves reducing inventory, leads to more dependency of supply chain partners on each other which exacerbates risk exposure of companies in the supply chain. This creates the need for more effective management of supply chain risks. In this research, a methodology based on Bow-Tie analysis and optimisation techniques is proposed to quantify and mitigate supply chain risks. The proposed methodology takes into consideration risk interconnections, and it identifies the best combination of mitigation strategies under budget constraints. A real case study from a high-end server manufacturing environment is presented. Results from the case study showed that the proposed methodology for risk modelling and mitigation can effectively be used to quantify the risks and achieve the required risk reduction at minimum cost while considering risk correlations.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:18:p:5640-5656
    DOI: 10.1080/00207543.2015.1047975
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    Citations

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    Cited by:

    1. Ivana Dvorski Lackovic & Marijana Bubanic & Vladimir Kovsca, 2018. "A Literature Survey On Risk Management In Supply Chains," Business Logistics in Modern Management, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 18, pages 551-564.
    2. Dmitry Ivanov, 2017. "Simulation-based ripple effect modelling in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 2083-2101, April.
    3. Zhao, Na, 2019. "Managing interactive collaborative mega project supply chains under infectious risks," International Journal of Production Economics, Elsevier, vol. 218(C), pages 275-286.
    4. Qazi, Abroon & Dickson, Alex & Quigley, John & Gaudenzi, Barbara, 2018. "Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks," International Journal of Production Economics, Elsevier, vol. 196(C), pages 24-42.
    5. Ali, Syed Mithun & Rahman, Md. Hafizur & Tumpa, Tasmia Jannat & Moghul Rifat, Abid Ali & Paul, Sanjoy Kumar, 2018. "Examining price and service competition among retailers in a supply chain under potential demand disruption," Journal of Retailing and Consumer Services, Elsevier, vol. 40(C), pages 40-47.
    6. Manel Elmsalmi & Wafik Hachicha & Awad M. Aljuaid, 2021. "Modeling Sustainable Risks Mitigation Strategies Using a Morphological Analysis-Based Approach: A Real Case Study," Sustainability, MDPI, vol. 13(21), pages 1-17, November.
    7. da Ponte, Aureliano & Leon, Gonzalo & Alvarez, Isabel, 2023. "Technological sovereignty of the EU in advanced 5G mobile communications: An empirical approach," Telecommunications Policy, Elsevier, vol. 47(1).
    8. Kraude, Richard & Narayanan, Sriram & Talluri, Srinivas, 2022. "Evaluating the performance of supply chain risk mitigation strategies using network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1168-1182.
    9. Dadsena, Krishna Kumar & Sarmah, S.P. & Naikan, V.N.A. & Jena, Sarat Kumar, 2019. "Optimal budget allocation for risk mitigation strategy in trucking industry: An integrated approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 37-55.
    10. Rohit Kumar Singh & Sachin Modgil & Padmanav Acharya, 2019. "Assessment of Supply Chain Flexibility Using System Dynamics Modeling," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(1), pages 39-63, December.
    11. Pythagoras N. Petratos & Alessio Faccia, 2023. "Fake news, misinformation, disinformation and supply chain risks and disruptions: risk management and resilience using blockchain," Annals of Operations Research, Springer, vol. 327(2), pages 735-762, August.
    12. Dong, Qingxing & Cooper, Orrin, 2016. "An orders-of-magnitude AHP supply chain risk assessment framework," International Journal of Production Economics, Elsevier, vol. 182(C), pages 144-156.
    13. Sherwin, Michael D. & Medal, Hugh & Lapp, Steven A., 2016. "Proactive cost-effective identification and mitigation of supply delay risks in a low volume high value supply chain using fault-tree analysis," International Journal of Production Economics, Elsevier, vol. 175(C), pages 153-163.
    14. 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.

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