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Assessing risk of supply chain disruption due to COVID-19 with fuzzy VIKORSort
The rapid spread of the COVID-19 pandemic has disrupted many economic activities around the world. The complete and partial lockdown policies, as well as the closure of borders by many countries has halted trade, consequently disrupting domestic and international supply chain networks. Like many oth...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9462645/ https://www.ncbi.nlm.nih.gov/pubmed/36105541 http://dx.doi.org/10.1007/s10479-022-04940-9 |
Sumario: | The rapid spread of the COVID-19 pandemic has disrupted many economic activities around the world. The complete and partial lockdown policies, as well as the closure of borders by many countries has halted trade, consequently disrupting domestic and international supply chain networks. Like many other countries, various economic sectors in Pakistan also bore high economic losses due to these disruptions. Multiple studies have analyzed on the impact of the COVID-19 pandemic on different economic sectors in Pakistan, i.e. construction, accommodation and food, manufacturing, wholesale and retail goods, energy, and the information and communication sectors. However, no study has examined sorting these economic sectors based on supply chain disruptions due to the pandemic. Therefore, this study aims to observe the resilience of these economic sectors and perform sorting using three predefined classes, i.e. severe, moderate, and low disruptions. For this purpose, we propose using the novel methodology fuzzy VIKORSort, which is the major contribution of this paper. This methodology evaluates the aforementioned economic sectors based on 10 criteria. The results of the study revealed that the accommodation and food sector, along with the construction sector, experienced the most severe disruption, followed by manufacturing, wholesale and retail goods, and energy, with moderate disruption, whereas the information and communication sector bore the least disruption. The proposed methodology will help the researchers and authorities deal with sorting and decision problems to prioritize the preventive measures of such undesirable events. |
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