Supply Chain Management: A Bibliometric Mapping of Research Clusters and Scholarly Influence

Abstract

This study aims to map the intellectual structure and scholarly influence of Supply Chain Management research through a bibliometric approach. Data were collected from the Scopus database and analyzed using VOSviewer to examine keyword co-occurrence, co-citation networks, and thematic evolution. The results reveal that supply chain management remains a central and highly interconnected research domain, with major clusters encompassing sustainability, digital transformation, risk management, and operational performance. Overlay visualization indicates a temporal shift from traditional themes such as risk assessment and operational efficiency toward emerging topics including artificial intelligence, blockchain, machine learning, and Industry 4.0. Density analysis further highlights that while core concepts such as supply chain management and decision making are well-established, newer areas related to digital technologies and sustainability continue to gain traction. The study also identifies influential scholarly contributions and global research patterns, reflecting the increasing interdisciplinarity of the field. The findings suggest that contemporary SCM research is transitioning toward a more integrated paradigm that combines technological innovation, environmental sustainability, and strategic competitiveness. This study contributes by providing a comprehensive overview of research clusters and offering directions for future studies in advancing resilient and sustainable supply chains.