IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v136y2020ics1366554520304300.html
   My bibliography  Save this article

Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case

Author

Listed:
  • Ivanov, Dmitry

Abstract

Epidemic outbreaks are a special case of supply chain (SC) risks which is distinctively characterized by a long-term disruption existence, disruption propagations (i.e., the ripple effect), and high uncertainty. We present the results of a simulation study that opens some new research tensions on the impact of COVID-19 (SARS-CoV-2) on the global SCs. First, we articulate the specific features that frame epidemic outbreaks as a unique type of SC disruption risks. Second, we demonstrate how simulation-based methodology can be used to examine and predict the impacts of epidemic outbreaks on the SC performance using the example of coronavirus COVID-19 and anyLogistix simulation and optimization software. We offer an analysis for observing and predicting both short-term and long-term impacts of epidemic outbreaks on the SCs along with managerial insights. A set of sensitivity experiments for different scenarios allows illustrating the model’s behavior and its value for decision-makers. The major observation from the simulation experiments is that the timing of the closing and opening of the facilities at different echelons might become a major factor that determines the epidemic outbreak impact on the SC performance rather than an upstream disruption duration or the speed of epidemic propagation. Other important factors are lead-time, speed of epidemic propagation, and the upstream and downstream disruption durations in the SC. The outcomes of this research can be used by decision-makers to predict the operative and long-term impacts of epidemic outbreaks on the SCs and develop pandemic SC plans. Our approach can also help to identify the successful and wrong elements of risk mitigation/preparedness and recovery policies in case of epidemic outbreaks. The paper is concluded by summarizing the most important insights and outlining future research agenda.

Suggested Citation

  • Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
  • Handle: RePEc:eee:transe:v:136:y:2020:i:c:s1366554520304300
    DOI: 10.1016/j.tre.2020.101922
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554520304300
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tre.2020.101922?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fahimnia, Behnam & Jabbarzadeh, Armin & Sarkis, Joseph, 2018. "Greening versus resilience: A supply chain design perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 129-148.
    2. Luca Fornaro & Martin Wolf, 2020. "Covid-19 coronavirus and macroeconomic policy," Economics Working Papers 1713, Department of Economics and Business, Universitat Pompeu Fabra.
    3. 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.
    4. Florian Lücker & Ralf W. Seifert & Işık Biçer, 2019. "Roles of inventory and reserve capacity in mitigating supply chain disruption risk," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1238-1249, February.
    5. Varun Gupta & Dmitry Ivanov, 2020. "Dual sourcing under supply disruption with risk-averse suppliers in the sharing economy," International Journal of Production Research, Taylor & Francis Journals, vol. 58(1), pages 291-307, January.
    6. 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.
    7. Mengshi Lu & Lun Ran & Zuo-Jun Max Shen, 2015. "Reliable Facility Location Design Under Uncertain Correlated Disruptions," Manufacturing & Service Operations Management, INFORMS, vol. 17(4), pages 445-455, October.
    8. Linda V. Green, 2012. "OM Forum--The Vital Role of Operations Analysis in Improving Healthcare Delivery," Manufacturing & Service Operations Management, INFORMS, vol. 14(4), pages 488-494, October.
    9. Salehi Sadghiani, N. & Torabi, S.A. & Sahebjamnia, N., 2015. "Retail supply chain network design under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 95-114.
    10. Thiemo Fetzer & Lukas Hensel & Johannes Hermle & Christopher Roth, 2021. "Coronavirus Perceptions and Economic Anxiety," The Review of Economics and Statistics, MIT Press, vol. 103(5), pages 968–978-9, December.
    11. Dmitry Ivanov & Alexandre Dolgui & Ajay Das & Boris Sokolov, 2019. "Digital Supply Chain Twins: Managing the Ripple Effect, Resilience, and Disruption Risks by Data-Driven Optimization, Simulation, and Visibility," International Series in Operations Research & Management Science, in: Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov (ed.), Handbook of Ripple Effects in the Supply Chain, pages 309-332, Springer.
    12. Hou, Yunzhang & Wang, Xiaoling & Wu, Yenchun Jim & He, Peixu, 2018. "How does the trust affect the topology of supply chain network and its resilience? An agent-based approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 229-241.
    13. Nezih Altay & Raktim Pal, 2014. "Information Diffusion among Agents: Implications for Humanitarian Operations," Production and Operations Management, Production and Operations Management Society, vol. 23(6), pages 1015-1027, June.
    14. Farahani, Reza Zanjirani & Lotfi, M.M. & Baghaian, Atefe & Ruiz, Rubén & Rezapour, Shabnam, 2020. "Mass casualty management in disaster scene: A systematic review of OR&MS research in humanitarian operations," European Journal of Operational Research, Elsevier, vol. 287(3), pages 787-819.
    15. Meena, P.L. & Sarmah, S.P., 2013. "Multiple sourcing under supplier failure risk and quantity discount: A genetic algorithm approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 50(C), pages 84-97.
    16. Hamed Mamani & Stephen E. Chick & David Simchi-Levi, 2013. "A Game-Theoretic Model of International Influenza Vaccination Coordination," Management Science, INFORMS, vol. 59(7), pages 1650-1670, July.
    17. Li, Yuhong & Zobel, Christopher W., 2020. "Exploring supply chain network resilience in the presence of the ripple effect," International Journal of Production Economics, Elsevier, vol. 228(C).
    18. Ji Chou & Nai-Fong Kuo & Su-Ling Peng, 2004. "Potential Impacts of the SARS Outbreak on Taiwan's Economy," Asian Economic Papers, MIT Press, vol. 3(1), pages 84-99.
    19. Yifei Lyu & Jun Nie, 2020. "Coronavirus Dampens China’s First-Quarter GDP," Economic Bulletin, Federal Reserve Bank of Kansas City, issue April 6, , pages 1-5, April.
    20. Dmitry Ivanov & Alexandre Dolgui, 2019. "Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 5119-5136, August.
    21. 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.
    22. Dmitry Ivanov & Alexander Tsipoulanidis & Jörn Schönberger, 2019. "Global Supply Chain and Operations Management," Springer Texts in Business and Economics, Springer, edition 2, number 978-3-319-94313-8, April.
    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. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Roubaud, David & Fosso Wamba, Samuel & Giannakis, Mihalis & Foropon, Cyril, 2019. "Big data analytics and organizational culture as complements to swift trust and collaborative performance in the humanitarian supply chain," International Journal of Production Economics, Elsevier, vol. 210(C), pages 120-136.
    25. Cui, Jianxun & Zhao, Meng & Li, Xiaopeng & Parsafard, Mohsen & An, Shi, 2016. "Reliable design of an integrated supply chain with expedited shipments under disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 143-163.
    26. Tsan‐Ming Choi & Stein W. Wallace & Yulan Wang, 2018. "Big Data Analytics in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1868-1883, October.
    27. Wilson, Martha C., 2007. "The impact of transportation disruptions on supply chain performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(4), pages 295-320, July.
    28. 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.
    29. Rameshwar Dubey & Angappa Gunasekaran & Thanos Papadopoulos, 2019. "Disaster relief operations: past, present and future," Annals of Operations Research, Springer, vol. 283(1), pages 1-8, December.
    30. 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.
    31. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    32. Ivanov, Dmitry & Pavlov, Alexander & Dolgui, Alexandre & Pavlov, Dmitry & Sokolov, Boris, 2016. "Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 7-24.
    33. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    34. Tsan‐Ming Choi & James H. Lambert, 2017. "Advances in Risk Analysis with Big Data," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1435-1442, August.
    35. Brian Tomlin, 2006. "On the Value of Mitigation and Contingency Strategies for Managing Supply Chain Disruption Risks," Management Science, INFORMS, vol. 52(5), pages 639-657, May.
    36. 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.
    37. 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.
    38. Klibi, Walid & Martel, Alain, 2012. "Modeling approaches for the design of resilient supply networks under disruptions," International Journal of Production Economics, Elsevier, vol. 135(2), pages 882-898.
    39. Ming Zhao & Nickolas K. Freeman, 2019. "Robust Sourcing from Suppliers under Ambiguously Correlated Major Disruption Risks," Production and Operations Management, Production and Operations Management Society, vol. 28(2), pages 441-456, February.
    40. Sawik, Tadeusz, 2011. "Selection of supply portfolio under disruption risks," Omega, Elsevier, vol. 39(2), pages 194-208, April.
    41. ., 2020. "Impact of international economic integration on location," Chapters, in: Evolutionary Spatial Economics, chapter 32, pages 579-595, Edward Elgar Publishing.
    42. 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.
    43. Boot, Arnoud W. A. & Carletti, Elena & Haselmann, Rainer & Kotz, Hans-Helmut & Krahnen, Jan Pieter & Pelizzon, Loriana & Schaefer, Stephen M. & Subrahmanyam, Marti G., 2020. "The Coronavirus and financial stability," SAFE Policy Letters 78, Leibniz Institute for Financial Research SAFE.
    44. Hasani, Aliakbar & Khosrojerdi, Amirhossein, 2016. "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 20-52.
    45. Fattahi, Mohammad & Govindan, Kannan & Keyvanshokooh, Esmaeil, 2017. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 176-200.
    46. Dmitry Ivanov, 2017. "Simulation-based single vs. dual sourcing analysis in the supply chain with consideration of capacity disruptions, big data and demand patterns," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 11(1), pages 24-43.
    47. Dmitry Ivanov, 2018. "Structural Dynamics and Resilience in Supply Chain Risk Management," International Series in Operations Research and Management Science, Springer, number 978-3-319-69305-7, April.
    48. Zhang, Ying & Qi, Mingyao & Lin, Wei-Hua & Miao, Lixin, 2015. "A metaheuristic approach to the reliable location routing problem under disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 90-110.
    49. Azrah A. Anparasan & Miguel A. Lejeune, 2018. "Data laboratory for supply chain response models during epidemic outbreaks," Annals of Operations Research, Springer, vol. 270(1), pages 53-64, November.
    50. Torabi, S.A. & Baghersad, M. & Mansouri, S.A., 2015. "Resilient supplier selection and order allocation under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 22-48.
    51. Büyüktahtakın, İ. Esra & des-Bordes, Emmanuel & Kıbış, Eyyüb Y., 2018. "A new epidemics–logistics model: Insights into controlling the Ebola virus disease in West Africa," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1046-1063.
    52. Riccardo Aldrighetti & Ilenia Zennaro & Serena Finco & Daria Battini, 2019. "Healthcare Supply Chain Simulation with Disruption Considerations: A Case Study from Northern Italy," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(1), pages 81-102, December.
    53. Choi, Tsan-Ming & Wen, Xin & Sun, Xuting & Chung, Sai-Ho, 2019. "The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 178-191.
    54. 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.
    55. Dmitry Ivanov, 2020. "‘A blessing in disguise’ or ‘as if it wasn’t hard enough already’: reciprocal and aggravate vulnerabilities in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 58(11), pages 3252-3262, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    3. 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.
    4. 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).
    5. Aarti Singh & Ratri Parida, 2022. "Decision-Making Models for Healthcare Supply Chain Disruptions: Review and Insights for Post-pandemic Era," International Journal of Global Business and Competitiveness, Springer, vol. 17(2), pages 130-141, December.
    6. K. Katsaliaki & P. Galetsi & S. Kumar, 2022. "Supply chain disruptions and resilience: a major review and future research agenda," Annals of Operations Research, Springer, vol. 319(1), pages 965-1002, December.
    7. Maciel M. Queiroz & Dmitry Ivanov & Alexandre Dolgui & Samuel Fosso Wamba, 2022. "Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1159-1196, December.
    8. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    9. Burgos, Diana & Ivanov, Dmitry, 2021. "Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    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. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    12. Belhadi, Amine & Kamble, Sachin & Jabbour, Charbel Jose Chiappetta & Gunasekaran, Angappa & Ndubisi, Nelson Oly & Venkatesh, Mani, 2021. "Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    13. Alexander Pavlov & Dmitry Ivanov & Frank Werner & Alexandre Dolgui & Boris Sokolov, 2022. "Integrated detection of disruption scenarios, the ripple effect dispersal and recovery paths in supply chains," Annals of Operations Research, Springer, vol. 319(1), pages 609-631, December.
    14. Chen, Li-Ming & Chang, Wei-Lun, 2021. "Supply- and cyber-related disruptions in cloud supply chain firms: Determining the best recovery speeds," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    15. Cheramin, Meysam & Saha, Apurba Kumar & Cheng, Jianqiang & Paul, Sanjoy Kumar & Jin, Hongyue, 2021. "Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    16. Fattahi, Mohammad & Govindan, Kannan & Maihami, Reza, 2020. "Stochastic optimization of disruption-driven supply chain network design with a new resilience metric," International Journal of Production Economics, Elsevier, vol. 230(C).
    17. Ivanov, Dmitry, 2023. "Intelligent digital twin (iDT) for supply chain stress-testing, resilience, and viability," International Journal of Production Economics, Elsevier, vol. 263(C).
    18. Dmitry Ivanov & Boris Sokolov, 2019. "Simultaneous structural–operational control of supply chain dynamics and resilience," Annals of Operations Research, Springer, vol. 283(1), pages 1191-1210, December.
    19. Goldbeck, Nils & Angeloudis, Panagiotis & Ochieng, Washington, 2020. "Optimal supply chain resilience with consideration of failure propagation and repair logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    20. Xuanlong Qin & Danish Iqbal Godil & Muhammad Kamran Khan & Salman Sarwat & Sadaf Alam & Laeeq Janjua, 2022. "Investigating the effects of COVID-19 and public health expenditure on global supply chain operations: an empirical study," Operations Management Research, Springer, vol. 15(1), pages 195-207, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:136:y:2020:i:c:s1366554520304300. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.