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Exiting the COVID-19 pandemic: after-shock risks and avoidance of disruption tails in supply chains

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  • Dmitry Ivanov

    (Professor of Supply Chain and Operations Management)

Abstract

Entering the COVID-19 pandemic wreaked havoc on supply chains. Reacting to the pandemic and adaptation in the “new normal” have been challenging tasks. Exiting the pandemic can lead to some after-shock effects such as “disruption tails.” While the research community has undertaken considerable efforts to predict the pandemic’s impacts and examine supply chain adaptive behaviors during the pandemic, little is known about supply chain management in the course of pandemic elimination and post-disruption recovery. If capacity and inventory management are unaware of the after-shock risks, this can result in highly destabilized production–inventory dynamics and decreased performance in the post-disruption period causing product deficits in the markets and high inventory costs in the supply chains. In this paper, we use a discrete-event simulation model to investigate some exit strategies for a supply chain in the context of the COVID-19 pandemic. Our model can inform managers about the existence and risk of disruption tails in their supply chains and guide the selection of post-pandemic recovery strategies. Our results show that supply chains with postponed demand and shutdown capacity during the COVID-19 pandemic are particularly prone to disruption tails. We then developed and examined two strategies to avoid these disruption tails. First, we observed a conjunction of recovery and supply chain coordination which mitigates the impact of disruption tails by demand smoothing over time in the post-disruption period. Second, we found a gradual capacity ramp-up prior to expected peaks of postponed demand to be an effective strategy for disruption tail control.

Suggested Citation

  • Dmitry Ivanov, 2024. "Exiting the COVID-19 pandemic: after-shock risks and avoidance of disruption tails in supply chains," Annals of Operations Research, Springer, vol. 335(3), pages 1627-1644, April.
  • Handle: RePEc:spr:annopr:v:335:y:2024:i:3:d:10.1007_s10479-021-04047-7
    DOI: 10.1007/s10479-021-04047-7
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    References listed on IDEAS

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    1. Wen Jun Tan & Wentong Cai & Allan N. Zhang, 2020. "Structural-aware simulation analysis of supply chain resilience," International Journal of Production Research, Taylor & Francis Journals, vol. 58(17), pages 5175-5195, September.
    2. Ivanov, Dmitry & Dolgui, Alexandre, 2021. "OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications," International Journal of Production Economics, Elsevier, vol. 232(C).
    3. Salomée Ruel & Jamal El Baz & Dmitry Ivanov & Ajay Das, 2024. "Supply chain viability: conceptualization, measurement, and nomological validation," Annals of Operations Research, Springer, vol. 335(3), pages 1107-1136, April.
    4. Tadeusz Sawik, 2020. "Supply Chain Disruption Management," International Series in Operations Research and Management Science, Springer, edition 2, number 978-3-030-44814-1, July-Dece.
    5. Dmitry Ivanov, 2018. "Revealing interfaces of supply chain resilience and sustainability: a simulation study," International Journal of Production Research, Taylor & Francis Journals, vol. 56(10), pages 3507-3523, May.
    6. He, Jian & Alavifard, Farzad & Ivanov, Dmitry & Jahani, Hamed, 2019. "A real-option approach to mitigate disruption risk in the supply chain," Omega, Elsevier, vol. 88(C), pages 133-149.
    7. El Baz, Jamal & Ruel, Salomée, 2021. "Can supply chain risk management practices mitigate the disruption impacts on supply chains’ resilience and robustness? Evidence from an empirical survey in a COVID-19 outbreak era," International Journal of Production Economics, Elsevier, vol. 233(C).
    8. Alexandre Dolgui & Dmitry Ivanov & Maxim Rozhkov, 2020. "Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 58(5), pages 1285-1301, March.
    9. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov, 2019. "The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics," International Journal of Production Research, Taylor & Francis Journals, vol. 57(3), pages 829-846, February.
    10. 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).
    11. Sanjay Mehrotra & Hamed Rahimian & Masoud Barah & Fengqiao Luo & Karolina Schantz, 2020. "A model of supply‐chain decisions for resource sharing with an application to ventilator allocation to combat COVID‐19," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(5), pages 303-320, August.
    12. Jie Yang & Hongming Xie & Guangsheng Yu & Mingyu Liu, 2021. "Antecedents and consequences of supply chain risk management capabilities: an investigation in the post-coronavirus crisis," International Journal of Production Research, Taylor & Francis Journals, vol. 59(5), pages 1573-1585, March.
    13. Li, Yuhong & Zobel, Christopher W. & Seref, Onur & Chatfield, Dean, 2020. "Network characteristics and supply chain resilience under conditions of risk propagation," International Journal of Production Economics, Elsevier, vol. 223(C).
    14. Schmitt, Thomas G. & Kumar, Sanjay & Stecke, Kathryn E. & Glover, Fred W. & Ehlen, Mark A., 2017. "Mitigating disruptions in a multi-echelon supply chain using adaptive ordering," Omega, Elsevier, vol. 68(C), pages 185-198.
    15. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2020. "Reconfigurable supply chain: the X-network," International Journal of Production Research, Taylor & Francis Journals, vol. 58(13), pages 4138-4163, July.
    16. Alikhani, Reza & Torabi, S.Ali & Altay, Nezih, 2021. "Retail supply chain network design with concurrent resilience capabilities," International Journal of Production Economics, Elsevier, vol. 234(C).
    17. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2018. "Ripple effect in the supply chain: an analysis and recent literature," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 414-430, January.
    18. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    19. Alexandra Brintrup & Johnson Pak & David Ratiney & Tim Pearce & Pascal Wichmann & Philip Woodall & Duncan McFarlane, 2020. "Supply chain data analytics for predicting supplier disruptions: a case study in complex asset manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3330-3341, June.
    20. Reza Alikhani & S.Ali Torabi & Nezih Altay, 2021. "Retail supply chain network design with concurrent resilience capabilities," Post-Print hal-03539192, HAL.
    21. Nagurney, Anna, 2021. "Supply chain game theory network modeling under labor constraints: Applications to the Covid-19 pandemic," European Journal of Operational Research, Elsevier, vol. 293(3), pages 880-891.
    22. Dmitry Ivanov & Maxim Rozhkov, 2020. "Coordination of production and ordering policies under capacity disruption and product write-off risk: an analytical study with real-data based simulations of a fast moving consumer goods company," Annals of Operations Research, Springer, vol. 291(1), pages 387-407, August.
    23. 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.
    24. Rameshwar Dubey & Angappa Gunasekaran & Stephen J. Childe & Samuel Fosso Wamba & David Roubaud & Cyril Foropon, 2021. "Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience," International Journal of Production Research, Taylor & Francis Journals, vol. 59(1), pages 110-128, January.
    25. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    26. Sube Singh & Ramesh Kumar & Rohit Panchal & Manoj Kumar Tiwari, 2021. "Impact of COVID-19 on logistics systems and disruptions in food supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 59(7), pages 1993-2008, April.
    27. John R. Macdonald & Christopher W. Zobel & Steven A. Melnyk & Stanley E. Griffis, 2018. "Supply chain risk and resilience: theory building through structured experiments and simulation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(12), pages 4337-4355, June.
    28. Andreas Wieland, 2021. "Dancing the Supply Chain: Toward Transformative Supply Chain Management," Journal of Supply Chain Management, Institute for Supply Management, vol. 57(1), pages 58-73, January.
    29. Li, Yuhong & Chen, Kedong & Collignon, Stephane & Ivanov, Dmitry, 2021. "Ripple effect in the supply chain network: Forward and backward disruption propagation, network health and firm vulnerability," European Journal of Operational Research, Elsevier, vol. 291(3), pages 1117-1131.
    30. Gupta, Varun & Ivanov, Dmitry & Choi, Tsan-Ming, 2021. "Competitive pricing of substitute products under supply disruption," Omega, Elsevier, vol. 101(C).
    31. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    32. Song Xu & Xiaotong Zhang & Lipan Feng & Wenting Yang, 2020. "Disruption risks in supply chain management: a literature review based on bibliometric analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3508-3526, June.
    33. Dmitry Ivanov & Boris Sokolov & Weiwei Chen & Alexandre Dolgui & Frank Werner & Semyon Potryasaev, 2021. "A control approach to scheduling flexibly configurable jobs with dynamic structural-logical constraints," IISE Transactions, Taylor & Francis Journals, vol. 53(1), pages 21-38, January.
    34. Dmitry Ivanov & Alexandre Dolgui, 2020. "Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak," International Journal of Production Research, Taylor & Francis Journals, vol. 58(10), pages 2904-2915, May.
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