Generative AI capabilities for green supply chain management improvement: extended dynamic capabilities view

Abstract

This study aims to develop and evaluate generative artificial intelligence (AI) capabilities to enhance green supply chain management (GSCM) in the automotive industry, Indonesia. Prior studies have concentrated on constructing generative AI metrics; however, there is a lack of emphasis on developing the capabilities to address dynamic environmental challenges in GSCM. This study integrates dynamic capabilities view with organisational learning theory and employs the integrated fuzzy Delphi method and fuzzy synthetic evaluation-decision-making trial and evaluation laboratory approach to ascertain the valid attributes to facilitate GSCM improvement. The findings indicate that dynamic knowledge and innovative learning capabilities and reflexive control and measurement capabilities from the perspective of sensing capabilities, as well as co-evolution capabilities from the perspective of seising capabilities, are key capabilities that need to be prioritised to enhance GSCM. In practices, data gathering and analysis for predictive maintenance, and sales and operations strategy identification must be prioritised.