Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case
Open accessAbstract
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.
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- Authors
- Ivanov, D.
- Affiliations
- Berlin School of Economics and Law (DE)
- Corresponding author
- Ivanov, Dmitry
- ORCID
- Ivanov, Dmitry
- Venue
- Transportation Research Part E: Logistics and Transportation Review
- Publisher
- Elsevier BV
- Published
- 2020-04
- Volume
- 136
- Pages
- 101922
- ISSN
- 1366-5545 (ISSN-L)
- PMC
- PMC7147532
- OpenAlex
- W3013474995
- Cited by
- 2,280
- References
- 3
- Citations by year
- 2026: 229 · 2025: 233 · 2024: 241 · 2023: 318 · 2022: 510 · 2021: 502 · 2020: 241 · 2019: 3 · 2018: 2 · 2015: 1
- FWCI
- 419.19
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Transportation Research Part E Logistics and Transportation Review (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Strategy and Management › Supply Chain Resilience and Risk Management
- Social Sciences › Business, Management and Accounting › Management Information Systems › Supply Chain and Inventory Management
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › COVID-19 Pandemic Impacts
- Keywords
- infectious disease outbreaks, supply chain disruption, COVID-19 pandemic, SARS-CoV-2, supply chain risk, cascading effects, lead time, supply chain performance, pandemic preparedness, risk mitigation, supply chain simulation
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