Mobilising AI Capability for Sustainable Supply‐Chain Transformation: The Mediating Role of Green Lean Six Sigma
Year: 2026
Type: article
Study design: Observational Study
Abstract: ABSTRACT This study examines how artificial intelligence (AI) capability can be mobilised as a strategic organisational capability for sustainable supply‐chain transformation. Integrating the Natural Resource‐Based View, Dynamic Capabilities Theory and Sociotechnical Systems Theory, the study argues that AI‐enabled sensing and decision support do not automatically translate into sustainability outcomes; strategic value emerges when technological resources, managerial competencies, human expertise and process routines are aligned. Green Lean Six Sigma (GLSS) is therefore conceptualised as an organisational architecture that converts AI‐generated insight into disciplined problem definition, waste and variation reduction, process redesign, standardisation and continuous improvement. Survey data from 361 managers and executives in supply‐chain‐intensive organisations across multiple Southeast Asian countries and sectors were analysed using partial least squares structural equation modelling. AI capability is positively associated with GLSS implementation, whereas GLSS is positively associated with environmental, economic and social supply‐chain performance. Significant indirect effects further show that GLSS acts as the transmission mechanism linking AI capability to all three triple‐bottom‐line outcomes. Because the estimated structural model did not include direct AI capability‐to‐performance paths, the evidence is interpreted as support for indirect effects rather than as proof of partial mediation. The study contributes to business strategy and sustainability research by explaining how an AI capability becomes strategically valuable when embedded in a sociotechnical improvement architecture. It also offers a staged managerial road map for harmonising AI investment, GLSS techniques and sustainable business transformation.
DOI: 10.1002/bse.71697
Language: English
Subfield: Strategy and Management
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $4,480
OpenAlex ID: W7221677323
