As global supply chains grow increasingly complex, volatile, and sustainability-sensitive, effective supply chain due diligence (SCDD) has become a critical strategic imperative for organizations. Despite this importance, many firms struggle to identify and prioritize the interrelated factors necessary for successful implementation.
The research employs a mixed qualitative and structured modelling approach. Initially, a set of enablers related to sustainability, ethics, resilience, and governance in SCDD was extracted from the literature survey. These enablers were validated and refined through expert consultations across industry, academia, and regulatory bodies. Then, modified Total Interpretive Structural Modelling (m-TISM) was applied to establish a multi-level hierarchical model, that incorporates interpretive logic at each level. Subsequently, a MICMAC (Cross-Impact Matrix Multiplication Applied to Classification) analysis was performed to categorize enablers based on their driving and dependence power.
Three key findings emerge from this study: (1) regulatory alignment, organizational leadership commitment, and multi-stakeholder collaboration serve as the most foundational and high-driving enablers of SCDD; (2) traceability systems, circular economy integration, and real-time ESG risk monitoring represent outcome-level enablers that are strongly dependent on these foundational factors; and (3) institutional and strategic factors exert a cascading influence on operational and technological SCDD capabilities.
The interpretive model provides a strategic roadmap for global firms aiming to design or enhance their SCDD systems. It supports prioritization under regulatory, resource, or capability constraints and aids in benchmarking due diligence maturity. The model also informs regulators and industry bodies that develop frameworks or capacity-building programs to support due diligence implementation across various tiers and geographies. Overall, the findings provide a foundation for future empirical validations, sector-specific adaptations, and simulation-based decision models.
This study is among the first to systematically model the enablers of SCDD using m-TISM in the context of global supply chain operations. It addresses a key gap in both theory and practice by offering an interpretive framework that integrates sustainability, resilience, and governance perspectives, while accounting for structural complexity and stakeholder interdependence.
