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Exiting the COVID-19 pandemic: after-shock risks and avoidance of disruption tails in supply chains.
Ivanov, Dmitry.
  • Ivanov D; Berlin School of Economics and Law, Department of Business and Economics, Professor of Supply Chain and Operations Management, 10825 Berlin, Germany.
Ann Oper Res ; : 1-18, 2021 Apr 05.
Article in English | MEDLINE | ID: covidwho-1173928
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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Ann Oper Res Year: 2021 Document Type: Article Affiliation country: S10479-021-04047-7

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Ann Oper Res Year: 2021 Document Type: Article Affiliation country: S10479-021-04047-7