Navigating COVID-19: unraveling supply chain disruptions through best-worst method and fuzzy TOPSIS
Benchmarking: An International Journal
ISSN: 1463-5771
Article publication date: 19 July 2023
Issue publication date: 21 May 2024
Abstract
Purpose
The COVID-19 pandemic has caused significant disruptions to global supply chains (SCs), affecting the production, distribution, and transportation of goods and services. To mitigate these disruptions, it is essential to identify the barriers that have impeded the seamless operation of SCs. This study identifies these barriers and assesses their impact on supply chain network (SCN).
Design/methodology/approach
To determine the relative importance of different barriers and rank the affected industries, a hybrid approach was employed, combining the best-worst method (BWM) and the technique for order preference by similarity to an ideal solution (TOPSIS). To accommodate the inherent uncertainties associated with the pandemic, a triangular fuzzy TOPSIS was used to represent the linguistic variable ratings provided by decision-makers.
Findings
The study found that the airlines and hospitality industry was the most affected by the barriers, accounting for 46% of the total, followed by the healthcare industry (23%), the manufacturing industry (19%), and finally the consumer and retail industry (17%).
Research limitations/implications
This study is limited to the four critical industries and nine identified barriers. Other industries and barriers may have different weights and rankings. Nevertheless, the findings offer valuable insights for decision-makers in SC management, aiding them in mitigating the impact of COVID-19 on their operations and enhancing their resilience against future disruptions.
Originality/value
This study enhances understanding of COVID-19’s impact on SCN and provides a framework for assessing disruptions using multi-criteria decision-making processes. The hybrid approach of BWM and TOPSIS in a fuzzy environment is unique and offers potential applicability in various evaluation contexts.
Keywords
Acknowledgements
The authors would like to thank the Editor-in-Chief, the Associate Editor, and the anonymous reviewers for their valuable feedback on the previous version of this manuscript.
Citation
Ali, I., Charles, V., Modibbo, U.M., Gherman, T. and Gupta, S. (2024), "Navigating COVID-19: unraveling supply chain disruptions through best-worst method and fuzzy TOPSIS", Benchmarking: An International Journal, Vol. 31 No. 5, pp. 1548-1589. https://doi.org/10.1108/BIJ-11-2022-0708
Publisher
:Emerald Publishing Limited
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