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An improved method for managing catastrophic supply chain disruptions

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  • Bradley, James R.

Abstract

This article analyzes the differences between frequent and rare risks for supply chain disruptions, and proposes a new, improved risk measurement and prioritization method to account for the characteristics of rare risks. The varying idiosyncrasies of decision makers are integrated into this method such that risk management can be brought into alignment with an individual manager's preferences. Also woven into this tapestry is the notion of detection, which is familiar to those who have applied failure modes and effects analysis (FMEA), but novel in the arena of supply chain risk management. Rare risks in the supply chain are, by their nature, unsettling: unforeseen disruptions are always present, probability estimates are imprecise, and comprehensive data collection is impossible. These difficulties are taken into account by the presented risk management framework. While the proposed ordinal scales are perhaps unsettling to many who desire greater precision, measurement methods must fit the precision that is possible. By considering rare risks along with frequent risks, managers can be better positioned to deal with the unforeseen.

Suggested Citation

  • Bradley, James R., 2014. "An improved method for managing catastrophic supply chain disruptions," Business Horizons, Elsevier, vol. 57(4), pages 483-495.
    • Handle: RePEc:eee:bushor:v:57:y:2014:i:4:p:483-495
    DOI: 10.1016/j.bushor.2014.03.003
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    References listed on IDEAS

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    Cited by:

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    3. Sáenz, María Jesús & Revilla, Elena & Acero, Beatriz, 2018. "Aligning supply chain design for boosting resilience," Business Horizons, Elsevier, vol. 61(3), pages 443-452.
    4. Nitya Singh & Paul Hong, 2023. "CSR, Risk Management Practices, and Performance Outcomes: An Empirical Investigation of Firms in Different Industries," JRFM, MDPI, vol. 16(2), pages 1-20, January.
    5. Sanjoy Kumar Paul & Ruhul Sarker & Daryl Essam & Paul Tae-Woo Lee, 2019. "A mathematical modelling approach for managing sudden disturbances in a three-tier manufacturing supply chain," Annals of Operations Research, Springer, vol. 280(1), pages 299-335, September.
    6. Wong, Christina W.Y. & Lirn, Taih-Cherng & Yang, Ching-Chiao & Shang, Kuo-Chung, 2020. "Supply chain and external conditions under which supply chain resilience pays: An organizational information processing theorization," International Journal of Production Economics, Elsevier, vol. 226(C).
    7. M. Ali Ülkü & Melek Akgün & Uday Venkatadri & Claver Diallo & Simranjeet S. Chadha, 2020. "Managing Environmental and Operational Risks for Sustainable Cotton Production Logistics: System Dynamics Modelling for a Textile Company," Logistics, MDPI, vol. 4(4), pages 1-20, December.
    8. Kouvelis, Panos, 2022. "Paradoxes and mysteries in virus-infected supply chains: Hidden bottlenecks, changing consumer behaviors, and other non-usual suspects," Business Horizons, Elsevier, vol. 65(4), pages 469-479.
    9. Anasse Amarouche & Philippe Chapellier & Alain George, 2018. "La gestion des risques dans une chaîne d’approvisionnement [La gestion des risques dans une chaine d'approvisionnement : Le cas de la filière d'approvisionnement en fruits et légumes d'une entrepri," Post-Print hal-02101506, HAL.

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