ABSTRACT
Worldwide Supply Chains (SC) have witnessed a vast expansion in the geographical network, investment, and goods and services offered. These have increased the complexities of SCs around the globe, thereby making them vulnerable to disruptions. The present study aims to develop a theoretical model for drivers of Supply Chain Resilience using the Interpretive Structural Modelling technique followed by model validation using Confirmatory Factor Analysis (CFA). The relationships between the drivers were defined through rigorous discussions with experts from industry and academia in India. For validation, scaled responses were obtained from experts across 56 industries, academicians, and finance managers. Preliminary statistical tests on data, CFA, and convergent and discriminant validities were performed. Model fit indices revealed a good model fit. Twelve hypotheses were developed based on the important drivers and were tested using regression. The roles of these drivers to improve resilience across different functional areas have been discussed for implementation.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The authors confirm that the data supporting the findings of this study are available within the article.