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On the quantification of operational supply chain resilience

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  • Albert Munoz
  • Michelle Dunbar

Abstract

Operational disruptions impact a supply chain’s ability to match supply and demand. To remain competitive, supply chains need to be resilient and thus capable of rapidly and effectively recovering from operational disruptions. Supply chain resilience is inherently multidimensional, as it spans across multiple tiers, and thus is difficult to quantify. Extant research has measured the transient response through a single-dimension or single-organisation as a proxy for operational resilience. Whilst this greatly simplifies the analysis, it is also potentially misleading, as an erroneous selection of metric(s) may lead to an inaccurate evaluation of the transient response. This research extends the understanding of operational resilience via quantitative evaluation of multiple transient response measures across multiple tiers; the objective being to construct a multidimensional, multi-echelon operational supply chain resilience metric. The study utilises disruptions as experimental inputs for a serial supply chain simulation model; results are obtained for individual measurements of the transient response across multiple supply chain tiers. Analysis indicates that individual dimensions of resilience can adequately explain the transient response at the single-firm level, whilst aggregation of multiple resilience dimensions across multiple tiers has greater capacity to holistically capture the performance response to supply chain disruptions.

Suggested Citation

  • Albert Munoz & Michelle Dunbar, 2015. "On the quantification of operational supply chain resilience," International Journal of Production Research, Taylor & Francis Journals, vol. 53(22), pages 6736-6751, November.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:22:p:6736-6751
    DOI: 10.1080/00207543.2015.1057296
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    Citations

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    Cited by:

    1. Gružauskas Valentas & Vilkas Mantas, 2017. "Managing Capabilities for Supply Chain Resilience Through it Integration," Economics and Business, Sciendo, vol. 31(1), pages 30-43, August.
    2. João Pires Ribeiro & Ana Paula F. D. Barbosa-Póvoa, 2023. "A responsiveness metric for the design and planning of resilient supply chains," Annals of Operations Research, Springer, vol. 324(1), pages 1129-1181, May.
    3. Wang, Yingcong & Xiao, Renbin, 2016. "An ant colony based resilience approach to cascading failures in cluster supply network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 150-166.
    4. Balezentis, Tomas & Zickiene, Agne & Volkov, Artiom & Streimikiene, Dalia & Morkunas, Mangirdas & Dabkiene, Vida & Ribasauskiene, Erika, 2023. "Measures for the viable agri-food supply chains: A multi-criteria approach," Journal of Business Research, Elsevier, vol. 155(PA).
    5. Kamalahmadi, Masoud & Parast, Mahour Mellat, 2016. "A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research," International Journal of Production Economics, Elsevier, vol. 171(P1), pages 116-133.
    6. Knoester, Max J. & Bešinović, Nikola & Afghari, Amir Pooyan & Goverde, Rob M.P. & van Egmond, Jochen, 2024. "A data-driven approach for quantifying the resilience of railway networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    7. Lohmer, Jacob & Bugert, Niels & Lasch, Rainer, 2020. "Analysis of resilience strategies and ripple effect in blockchain-coordinated supply chains: An agent-based simulation study," International Journal of Production Economics, Elsevier, vol. 228(C).
    8. A. V. Thomas & Biswajit Mahanty, 2021. "Dynamic assessment of control system designs of information shared supply chain network experiencing supplier disruption," Operational Research, Springer, vol. 21(1), pages 425-451, March.
    9. Raquel Sanchis & Alfonso Duran-Heras & Raul Poler, 2020. "Optimising the Preparedness Capacity of Enterprise Resilience Using Mathematical Programming," Mathematics, MDPI, vol. 8(9), pages 1-29, September.
    10. Chen, Sai & Ding, Yueting & Zhang, Yanfang & Zhang, Ming & Nie, Rui, 2022. "Study on the robustness of China's oil import network," Energy, Elsevier, vol. 239(PB).
    11. Robertson, Lindsay J. & Michael, Katina & Munoz, Albert, 2017. "Assessing technology system contributions to urban dweller vulnerabilities," Technology in Society, Elsevier, vol. 50(C), pages 83-92.
    12. Michael Huber & Nikola Komatina & Vladan Paunović & Snežana Nestić, 2023. "Analysis of the Relationship between the Organizational Resilience Factors and Key Performance Indicators’ Recovery Time in Uncertain Environments in Industrial Enterprises," Mathematics, MDPI, vol. 11(14), pages 1-19, July.
    13. Shashi & Piera Centobelli & Roberto Cerchione & Myriam Ertz, 2020. "Managing supply chain resilience to pursue business and environmental strategies," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1215-1246, March.
    14. Mahmoud Ashraf & Amr Eltawil & Islam Ali, 2024. "Disruption detection for a cognitive digital supply chain twin using hybrid deep learning," Operational Research, Springer, vol. 24(2), pages 1-31, June.
    15. Mahmoud Z. Mistarihi & Ghazi M. Magableh, 2023. "Prioritization of Supply Chain Capabilities Using the FAHP Technique," Sustainability, MDPI, vol. 15(7), pages 1-19, April.
    16. Raquel Sanchis & Luca Canetta & Raúl Poler, 2020. "A Conceptual Reference Framework for Enterprise Resilience Enhancement," Sustainability, MDPI, vol. 12(4), pages 1-27, February.

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