Mapping the existing research landscape of AI-enabled green procurement in the Industry 4.0 ERA: a bibliometric analysis - Rafiuddin, Mohd Yunus; Norhana, Mohd Aripin; Muhammad Ashraf, Fauzi; Nur Sofia Nabila, Alimin; Muhammad Fakhrul, Yusuf (Learning Gate, 2026)
Utilizing technologies from Artificial Intelligence (AI) and Industry 4.0, these technologies are gaining wider recognition as enablers of data-driven and sustainability-oriented procurement practices. Nevertheless, the studies of the use of AI to enable green procurement are fragmented. The paper presents a bibliometric investigation that traces the development, topical framework, and theoretical basis of AI-enabled green procurement between 2015 and 2025. The analysis considers descriptive publication trends, bibliographic coupling, and keyword co-occurrence to identify essential research clusters using a curated collection of peer-reviewed articles on green procurement and public policy, AI-enabled procurement transformation, and Industry 4.0 technologies that can support sustainable sourcing. The results highlight that procurement has shifted to intelligent, automated, and data-driven ecosystems, rather than traditional compliance-based green purchasing. Although interest has increased, the study identifies several existing gaps, including a lack of empirical evidence, ethical issues in AI-driven decision-making, and uneven organizational digital preparedness. The reviewed article contributes to a cohesive research map and suggests future directions, focusing on AI governance, implementation capability, and interdisciplinary cooperation to enhance the sustainability of procurement outcomes in the Industry 4.0 era.