Disturbances in the supply chains (SCs) of organizations often disrupt their operational networks. Thus, industrial SCs must be resilient and sustainable to swiftly respond to disturbances, decrease vulnerability to potential weaknesses, and mitigate the effects of adverse disruptions such as COVID-19. The aim of this research is to understand the interdependencies among the factors facilitating the development of a resilient and sustainable supply chain within the context of the Indian automotive industry in the consequences of the COVID-19 pandemic. This study proposes an integrated framework to recognize and analyze the enablers of supply chain resilience (SCR) in a typical automobile sector while maintaining sustainability. To this end, a detailed literature search was conducted to identify a complete set of enablers while ensuring the sustainability of SCs. Total interpretive structural modeling (TISM) and fuzzy cross-impact matrix multiplication applied to classification (fuzzy MICMAC) methodologies are integrated to analyze the identified enablers. The fuzzy MICMAC model is used to evaluate the interrelationships between enablers of a resilient and sustainable SC based on their driving powers and dependencies. Trust and commitment among players and information sharing are the most influential drivers in establishing a more robust and sustainable SC in post-COVID-19 situations. The proposed paradigm highlights the major techniques that SC leaders should use to improve SCR performance and sustain SC operations during unexpected disruptions.
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Khot et al. (2024) studied this question.
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