Developing AI-enabled sustainable supply chain quality capability: Scale development, validation, and its role in enhancing supply chain resilience and performance
Abstract
Despite growing investments in artificial intelligence (AI), limited understanding exists regarding the organizational capabilities required to integrate AI into sustainable supply chain quality management. This study develops and validates a novel construct, AI-enabled Sustainable Supply Chain Quality Capability (AISSQC), and examines its role in enhancing supply chain resilience (SCR) and sustainable performance (SP). A sequential mixed-method research design was employed. The construct was developed through an integrative literature review, semi-structured interviews with industry experts, a modified Delphi study, and cognitive pretesting. Quantitative validation was subsequently conducted using two independent samples from Canadian manufacturing firms. Exploratory factor analysis established the dimensional structure of the scale, while Partial Least Squares Structural Equation Modeling (PLS-SEM) using a separate sample validated the reflective–formative higher-order construct and tested the proposed structural relationships. The results confirm that AISSQC is a multidimensional organizational capability comprising five complementary dimensions: AI-enabled Quality Intelligence, Sustainable Quality Integration, Collaborative Quality Orchestration, Adaptive Quality Improvement, and Responsible Quality Governance. AI Capability is positively associated with AISSQC, which in turn is associated with higher SCR and SP. SCR further mediates the relationship between AISSQC and SP, demonstrating that AI creates organizational value primarily through the development of complementary organizational capabilities rather than through technology adoption alone. This study introduces and empirically validates AISSQC as a novel higher-order organizational capability that integrates AI, quality management, sustainability, and supply chain management within a unified capability framework. By extending the Resource-Based View and Dynamic Capabilities Theory, the study explains how organizations transform AI resources into resilient and sustainable operational capabilities. The validated measurement scale provides researchers with a robust instrument for future empirical studies while offering managers a practical framework for guiding AI-enabled quality transformation in sustainable supply chains. Keywords: Artificial Intelligence, AI-Enabled Sustainable Supply Chain Quality Capability, Scale Development, Dynamic Capabilities, Supply Chain Resilience, Sustainable Performance.