Artificial intelligence applications in electric vehicle supply chain management: a systematic review and research agenda

Abstract

Abstract The supply chain of electric vehicles (EV) is a special challenge because of the complexity of battery lifecycle, reverse logistics, sustainability pressure, and distributed operations worldwide. Machine Learning and Artificial Intelligence (AI) have become essential facilitators of improving the efficiency, resilience, and decision-making within supply chain management (SCM). Nevertheless, the application of AI to EV-specific supply chains is still disjointed and under-synthesized in literature. The paper undertakes a systematic literature review to review the AI implementation in EV supply chain management through a systematic and reproducible approach. A total of 982 articles were obtained in the Scopus and Web of Science databases and systematically filtered according to PRISMA requirements. As a result of title-level and content-based search, 38 review papers that addressed AI in supply chains were found and divided into seven major domains of supply chain application: route optimization (10.5%), demand forecasting (5.3%), resilience (18.4%), battery management and reinforcement learning (13.2%), sustainability (23.7%), data governance (15.8% Moreover, using Boolean filtering and thorough analysis, 28 most relevant studies related to the intersection of AI, SCM, and EVs were chosen. The results demonstrate that the existing studies are focused on the sustainability and resilience aspects, whereas EV-specific topics, including battery lifecycle management, reverse logistics, and integrated EV supply chain optimization are not actively studied. Also, the research notes the new trends in digital transformation driven by AI, real-time analytics, and sustainable supply chain practices. An organized taxonomy is established to frame AI methods to supply chain operations in the EV setting. The study has value because it will synthesize the available data on the use of AI in EV supply chains, pinpoint key gaps in the research, and formulate a research agenda in the future. The findings provide practical lessons to researchers and practitioners who would like to come up with smart, robust, and resilient EV supply chain systems.