Professor Nishikant Mishra Nishikant.Mishra@hull.ac.uk
Professor/ Head of Management Systems Subject Group
Professor Nishikant Mishra Nishikant.Mishra@hull.ac.uk
Professor/ Head of Management Systems Subject Group
Niladri Palit
Atanu Chaudhuri
India faced a unique situation during the ongoing COVID-19 pandemic when millions of migrant workers, in different states had to be transported to their home states as workplaces shut down. The governments in respective states faced challenges of minimizing economic impact while ensuring that the risk of infection was also kept under control. This paper develops models based on various secondary data from governmental and relevant non-governmental sources, trying to minimize the economic impact while keeping the rate of infection low and determining whether the migrant workforce should be allowed to stay in their workplace state or allowed to return to their home state. We found that the number of days of lockdown had a significant impact on the results. Fewer days of lockdown resulted in workers remaining in their work state as the preferred outcome, while a higher number of days of lockdown implied that people traveled to their home state and remain there. The proportion of workers who were willing to return to their work state played an important role on the results too. Beyond the threshold percentages of migrant workers returning to their work state, it became optimal for the government to encourage the workers to travel to their home state. However, this was mostly visible for moderate number of lockdown days as the effects on results were dominated by the impact from the number of lockdown days for too high or too low number of lockdown days. There is also an important trade-off between the budget and infection rate ‘R’ for the governments to consider. Minimizing the risk of infection requires an additional budget.
Mishra, N., Palit, N., & Chaudhuri, A. (2023). Humanitarian management strategy for interstate movement of migrant workers in India during COVID-19 pandemic: an optimization based approach. Annals of Operations Research, https://doi.org/10.1007/s10479-023-05199-4
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 18, 2023 |
Online Publication Date | Feb 14, 2023 |
Publication Date | 2023 |
Deposit Date | Jan 23, 2023 |
Publicly Available Date | Feb 15, 2024 |
Journal | Annals of Operations Research |
Print ISSN | 0254-5330 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
DOI | https://doi.org/10.1007/s10479-023-05199-4 |
Keywords | Economic impact of COVID-19; Optimization in humanitarian crisis; Migrant worker movement in India |
Public URL | https://hull-repository.worktribe.com/output/4186633 |
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Reduce inequality within and among countries
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Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0
Copyright Statement
© The Author(s) 2023.
Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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