Decoding supply chain resilience: a multi-method empirical framework to classify and validate critical drivers

Purpose This research study aims to develop a robust and ranking-based empirical framework for assessing supply chain resilience (SC-RS) through the identification, classification and validation of key driving factors. The study addresses critical gaps in existing SC-RS literature through the integration of multiple analytical techniques to evaluate the hierarchical relationships among resilience enablers. Design/methodology/approach Twelve critical drivers of SC-RS were identified through a systematic literature review (SLR) supported by theoretical synthesis and a structured survey of 283 respondents from industry and academia. The identified drivers are analyzed using interpretive structural modelling (ISM) to examine their associations and classified into four strategic clusters using MICMAC (Matrix of Cross Impact Multiplications Applied to Classification) technique relied in their driving and dependence power. The proposed conceptual model is subsequently validated by partial least squares structural equations modelling (PLS-SEM), which accesses the model’ reliability, convergent and divergent validity, and overall goodness-of-fits. Findings The findings of the study reveal that, with the use of a validated model, the firms can enhance their resilience by redesigning and optimizing their critical resources. The validated framework also provides firms with a data-driven basis for prioritization of resource allocation, optimize operational strategies and enhancing adaptive capabilities. Further, an integration of total quality management (TQM) principles into the resilience framework underscores the importance of process orientation and continuous improvement in achieving SC-RS. Research limitations/implications While this research work offers a theoretically sound and empirically tested framework, its generalizability is limited to the Indian Industrial setup. The future scholars could adopt a longitudinal or cross-national perspective, and can incorporate variables such as organization’ culture, digital maturity and agile partnership networking for more comprehensive understanding of SC-RS dynamics. Originality/value This research work contributes a novel and integrative methodological approach that connects the conceptual model and empirical validation of SC-RS. Further, by synthesizing ISM, MICMAC and PLS-SEM within a unified framework, the research provides unique strategic insights and operational tools for firms seeking to strengthen resilience across their supply chains (SCs). The framework’ relevance is further enhanced by the inclusion of TQM perspective, which encourages a balanced emphasis on process quality, resilience, and responsiveness in dynamic and changing business settings.