Bibliometric analysis of the impact of artificial intelligence on supply chain management

This thesis presents a bibliometric analysis of the impact of Artificial Intelligence (AI) on Supply Chain Management (SCM) based on data extracted from the Scopus database. The study covers research publications from 2020 to the first quarter of 2024, with a particular focus on the applications of AI in logistics and inventory management. This research aims to explain the growing landscape of AI integration in SCM by a detailed examination of publication trends, geographical distribution, key journals, conferences, emerging topics, and citation analysis of influential papers, authors, and institutions. The results demonstrate a notable increase in research activity and publications in this field, highlighting AI's growing interest and importance in enhancing SCM. Key findings point out that AI-based technologies like Machine Learning (ML), Deep Learning (DL), and generative adversarial networks create efficiency, predictive analytics, automation, and supply chain visibility. Moreover, the analysis recognizes a number of leading clusters, including sustainable smart cities, exploratory studies in food waste management, and reverse logistics. It shows AI's diverse applications and benefits in SCM. The Scopus Database's selection as a single source of information limits the number of relevant publications and excludes relevant studies listed in other databases. Similar cases display a fragmentary view of the study landscape. Still, the study offers valuable knowledge for researchers, policymakers, and practitioners. In addition, it helps them determine future research directions and underscores areas for investment in AI and SCM. The study exclusively focuses on the existing academic publications to reveal AI systems' capacities, advantages, and overall impact on the SCM domain. In addition, it underlines the interpretation of AI-based technologies and their implementation into SCM. It gives knowledge regarding AI's impact on informed decision-making, advanced technology transformation, and ideal collaboration and outcome. Moreover, the need for further analysis of related topics is highlighted. The author has faith in collaboration and teamwork by scholars and practitioners. Their joint work ensures the complete integration of AI's innovative capabilities and their usage in the SCM domain.