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An integrated System Dynamics model for Closed Loop Supply Chains under disaster effects: The case of COVID-19

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  • Katsoras, Efthymios
  • Georgiadis, Patroklos

Abstract

For a Closed Loop Supply Chain (CLSC), disaster is a risk source of unknown-unknowns, which may result in production disruptions with significant consequences on -but not limited to-profitability. For this reason, we provide a System Dynamics (SD)-based analysis for disaster events on the operation of CLSCs in order to study the system response (production/collection/disassembly/remanufacturing/recycling rates, inventories, cost, profit). This response is examined through the dynamics at a manufacturer, parts producer, collector, and disassembly center level, by providing control mechanisms for resilient CLSCs under disaster effects. In this dynamic analysis, COVID-19 is treated as a disaster event. Five different business scenario settings are presented for the manufacturer, which are considered as alternative mitigation policies in responding to product demand. The extensive simulation results provide insights for policy-makers, which depend on the reduction in manufacturer's production, reduction in product demand and duration of recovery period which are considered as causal effects due to the COVID-19 outbreak. For all combinations, holding base stocks during the pre-disaster period is proposed as the best mitigation policy in terms of manufacturer's inventory. In terms of economic impact, holding base stocks or coordination with third party are revealed as the best choice depending on the combination, while remote inventory policy adoption as the worst choice.

Suggested Citation

  • Katsoras, Efthymios & Georgiadis, Patroklos, 2022. "An integrated System Dynamics model for Closed Loop Supply Chains under disaster effects: The case of COVID-19," International Journal of Production Economics, Elsevier, vol. 253(C).
    • Handle: RePEc:eee:proeco:v:253:y:2022:i:c:s0925527322001785
    DOI: 10.1016/j.ijpe.2022.108593
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    1. 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.
    2. Georgiadis, Patroklos & Michaloudis, Charalampos, 2012. "Real-time production planning and control system for job-shop manufacturing: A system dynamics analysis," European Journal of Operational Research, Elsevier, vol. 216(1), pages 94-104.
    3. Martin Peterson, 2002. "The Limits of Catastrophe Aversion," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 527-538, June.
    4. Georgiadis, Patroklos & Athanasiou, Efstratios, 2013. "Flexible long-term capacity planning in closed-loop supply chains with remanufacturing," European Journal of Operational Research, Elsevier, vol. 225(1), pages 44-58.
    5. Raj, Alok & Mukherjee, Abheek Anjan & de Sousa Jabbour, Ana Beatriz Lopes & Srivastava, Samir K., 2022. "Supply chain management during and post-COVID-19 pandemic: Mitigation strategies and practical lessons learned," Journal of Business Research, Elsevier, vol. 142(C), pages 1125-1139.
    6. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    7. John D. Sterman, 1989. "Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment," Management Science, INFORMS, vol. 35(3), pages 321-339, March.
    8. 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.
    9. 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.
    10. Besiou, Maria & Georgiadis, Patroklos & Van Wassenhove, Luk N., 2012. "Official recycling and scavengers: Symbiotic or conflicting?," European Journal of Operational Research, Elsevier, vol. 218(2), pages 563-576.
    11. Ju Myung Song & Weiwei Chen & Lei Lei, 2018. "Supply chain flexibility and operations optimisation under demand uncertainty: a case in disaster relief," International Journal of Production Research, Taylor & Francis Journals, vol. 56(10), pages 3699-3713, May.
    12. Hwarng, H. Brian & Yuan, Xuchuan, 2014. "Interpreting supply chain dynamics: A quasi-chaos perspective," European Journal of Operational Research, Elsevier, vol. 233(3), pages 566-579.
    13. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
    14. Simchi-Levi, David, 2010. "Operation Rules: Delivering Customer Value through Flexible Operations," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262525151, December.
    15. 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.
    16. Chang, Mei-Shiang & Tseng, Ya-Ling & Chen, Jing-Wen, 2007. "A scenario planning approach for the flood emergency logistics preparation problem under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 737-754, November.
    17. Tang, Ou & Nurmaya Musa, S., 2011. "Identifying risk issues and research advancements in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 133(1), pages 25-34, September.
    18. Udenio, Maximiliano & Fransoo, Jan C. & Peels, Robert, 2015. "Destocking, the bullwhip effect, and the credit crisis: Empirical modeling of supply chain dynamics," International Journal of Production Economics, Elsevier, vol. 160(C), pages 34-46.
    19. Wu, Y. & Zhang, D.Z., 2007. "Demand fluctuation and chaotic behaviour by interaction between customers and suppliers," International Journal of Production Economics, Elsevier, vol. 107(1), pages 250-259, May.
    20. Hwarng, H. Brian & Xie, Na, 2008. "Understanding supply chain dynamics: A chaos perspective," European Journal of Operational Research, Elsevier, vol. 184(3), pages 1163-1178, February.
    21. De, Manoranjan & Giri, B.C., 2020. "Modelling a closed-loop supply chain with a heterogeneous fleet under carbon emission reduction policy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    22. Qing Zhang & Weiguo Fan & Jianchang Lu & Siqian Wu & Xuechao Wang, 2021. "Research on Dynamic Analysis and Mitigation Strategies of Supply Chains under Different Disruption Risks," Sustainability, MDPI, vol. 13(5), pages 1-29, February.
    23. Li, Gang & Yang, Hongjiao & Sun, Linyan & Ji, Ping & Feng, Lei, 2010. "The evolutionary complexity of complex adaptive supply networks: A simulation and case study," International Journal of Production Economics, Elsevier, vol. 124(2), pages 310-330, April.
    24. Galindo, Gina & Batta, Rajan, 2013. "Review of recent developments in OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 230(2), pages 201-211.
    25. 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.
    26. Mahdi Bashiri & Benny Tjahjono & Jordon Lazell & Jennifer Ferreira & Tomy Perdana, 2021. "The Dynamics of Sustainability Risks in the Global Coffee Supply Chain: A Case of Indonesia–UK," Sustainability, MDPI, vol. 13(2), pages 1-20, January.
    27. Sterman, John D., 1989. "Misperceptions of feedback in dynamic decision making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 43(3), pages 301-335, June.
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