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Assessing supply chain resilience to the outbreak of COVID-19 in Indian manufacturing firms
Operations Management Research ; 15(3-4):1161-1180, 2022.
Article in English | ProQuest Central | ID: covidwho-2129166
ABSTRACT
As the world has seen the impact of COVID-19, development of resilient supply chain strategies has emerged as top priority. The inconsistent demands, product consumption and the shorter lifecycle of products during the pandemic needs appropriate planning and designing to make the supply chain more resilient. In this study, an analytical model is proposed to assess the resilience of supply chain to overcome the effect of the disruption impacts. The supply chain risks will depend on the nature of the business and therefore, besides literature review on supply chain resilience the inputs from experts were required. The interdependency among the indicators was analysed by employing Interpretive Structural Modelling (ISM) and demonstrated with the help of a framework. The strength of the interdependence is assessed using Bayesian Network approach. BN transformed the qualitative expert inputs to quantitative assessment by utilising the principles of conditional probability. Three cases from Indian manufacturing industries were used to demonstrate and assess the critical supply chain resilience indicators using integrated ISM-BN approach. The cases showed that the proposed approach can assist decision makers in identifying the critical indicators to be focused towards improving the supply chain resilience to overcome the outbreak of Covid-19 pandemic. A comparative analysis of the supply chain risk indicators has also been performed, thereby extending the practical implication of supply chain resilience.
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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: Operations Management Research Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: Operations Management Research Year: 2022 Document Type: Article