TECHNOLOGY-DRIVEN KNOWLEDGE MANAGEMENT: A BIBLIOMETRIC EXPLORATION OF EMERGING TRENDS

Abstract

This paper offers a systematic and thorough examination of the convergence of emerging technologies and Knowledge Management (KM). Using data from the Scopus database, the study examines 956 publications over 11 years, applying bibliometric methodologies to identify patterns and deficiencies in the existing academic environment. The study emphasizes a strong academic interest in incorporating technologies such as blockchain, artificial intelligence (AI), and the Internet of Things (IoT) into KM methods. To obtain comprehensive and reliable results, the researchers used various analytical tools, including exclusion criteria to refine the search, Microsoft Excel to calculate the frequency and percentage of published materials, Harzing's Publish and Perish software to calculate citation metrics, and to create bibliometric networks and visualizations. The bibliometric analysis reveals significant findings, such as a total citation count of 10,399, an average of 945.2 per year, and 10.88 per paper. These results highlight the long-lasting influence of the analyzed collection of documents. An examination of research trends provides valuable insights into the continuous development of the subject, highlighting initial patterns centered around fundamental technologies and the growing emphasis on multidisciplinary approaches. To summarise, this study, based on Scopus, not only brings together the scattered nature of existing research but also offers a proactive view of upcoming patterns. This assists academics and professionals in navigating the ever-changing field of KM, which is influenced by evolving technology.