The DOI matches its Crossref record; 125 of the 125 references it cites were found in a registry or an index.
COVID-19 pandemic related supply chain studies: A systematic review
Open accessAbstract
The global spread of the novel coronavirus, also known as the COVID-19 pandemic, has had a devastating impact on supply chains. Since the pandemic started, scholars have been researching and publishing their studies on the various supply-chain-related issues raised by COVID-19. However, while the number of articles on this subject has been steadily increasing, due to the absence of any systematic literature reviews, it remains unclear what aspects of this disruption have already been studied and what aspects still need to be investigated. The present study systematically reviews existing research on the COVID-19 pandemic in supply chain disciplines. Through a rigorous and systematic search, we identify 74 relevant articles published on or before 28 September 2020. The synthesis of the findings reveals that four broad themes recur in the published work: namely, impacts of the COVID-19 pandemic, resilience strategies for managing impacts and recovery, the role of technology in implementing resilience strategies, and supply chain sustainability in the light of the pandemic. Alongside the synthesis of the findings, this study describes the methodologies, context, and theories used in each piece of research. Our analysis reveals that there is a lack of empirically designed and theoretically grounded studies in this area; hence, the generalizability of the findings, thus far, is limited. Moreover, the analysis reveals that most studies have focused on supply chains for high-demand essential goods and healthcare products, while low-demand items and SMEs have been largely ignored. We also review the literature on prior epidemic outbreaks and other disruptions in supply chain disciplines. By considering the findings of these articles alongside research on the COVID-19 pandemic, this study offers research questions and directions for further investigation. These directions can guide scholars in designing and conducting impactful research in the field.
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Citations
Cites
Tranfield, D., Denyer, D., & Smart, P. (2003) · British Journal of Management · doi:10.1111/1467-8551.00375 · Cited by 15,386
Perspectives in supply chain risk management
Tang, C. S. (2006) · International Journal of Production Economics · doi:10.1016/j.ijpe.2005.12.006 · Cited by 2,577
Understanding the concept of supply chain resilience
Ponomarov, S. Y., & Holcomb, M. C. (2009) · The International Journal of Logistics Management · doi:10.1108/09574090910954873 · Cited by 2,530
Ivanov, D. (2020) · Transportation Research Part E: Logistics and Transportation Review · doi:10.1016/j.tre.2020.101922 · Cited by 2,280
Ivanov, D., & Dolgui, A. (2020) · International Journal of Production Research · doi:10.1080/00207543.2020.1750727 · Cited by 2,100
Ivanov, D., & Dolgui, A. (2021) · Production Planning & Control · doi:10.1080/09537287.2020.1768450 · Cited by 1,790
Supply chain risk management: a literature review
Ho, W., Zheng, T., Yildiz, H., & Talluri, S. (2015) · International Journal of Production Research · doi:10.1080/00207543.2015.1030467 · Cited by 1,363
Ivanov, D. (2022) · Annals of Operations Research · doi:10.1007/s10479-020-03640-6 · Cited by 1,343
Food supply chains during the COVID‐19 pandemic
Hobbs, J. E. (2020) · Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie · doi:10.1111/cjag.12237 · Cited by 1,313
Hendricks, K. B., & Singhal, V. R. (2005) · Production and Operations Management · doi:10.1111/j.1937-5956.2005.tb00008.x · Cited by 1,303
Metadata
- Authors
- Chowdhury, P., Paul, S. K., Kaisar, S., & Moktadir, M. A.
- Venue
- Transportation Research Part E: Logistics and Transportation Review
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 148
- Pages
- 102271
- ISSN
- 1366-5545 (ISSN-L)
- OpenAlex
- W3133395039
- Cited by
- 992
- References
- 125
- FWCI
- 34.64
- Type
- journal article
- Language
- en
- Open access
- green
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- Chowdhury, P., Paul, S. K., Kaisar, S., & Moktadir, M. A. (2021). COVID-19 pandemic related supply chain studies: A systematic review. Transportation Research Part E: Logistics and Transportation Review. https://doi.org/10.1016/j.tre.2021.102271
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