The Global Research Landscape of Knowledge Management in Economics: A Network Visualisation and Topic Modelling Approach

This study explores the global research landscape of Knowledge Management (KM) in economics by applying the network visualisation and topic modelling techniques. The primary goal is to provide a comprehensive understanding of key research trends, collaborations and emerging themes within the field. A systematic scientometric analysis was conducted using a dataset of 19,907 publications retrieved from the Scopus database during 2014-2023. Network visualisation was employed to map collaborations among authors, countries and journals, while topic modelling identified latent themes. Tools such as Biblioshiny and LDAShiny were utilised for performance analysis and topic extraction. The findings reveal a growing trend in KM-related research in economics, particularly since 2019, with sustainable development and intellectual capital emerging as the dominant themes focussing on sustainability and organisational knowledge assets. China, the US and the UK have emerged as leaders in global collaborations within this field, with Resources, Conservation and Recycling identified as the most productive journal. However, a recent decline in citation rates raises potential concerns regarding future research engagement. The study is limited to English language publications, potentially excluding significant contributions in other languages, highlighting the need for continuous analysis to track evolving trends in KM and economics. Furthermore, the implications of this research indicate that KM is critical for policymakers and organisations in addressing sustainability challenges and fostering innovation. Integrating KM into economic policies and strategies can enhance evidence-based decision-making and organisational competitiveness. This study provides a unique combination of network visualisation and topic modelling to present a holistic view of the KM–economics research landscape, providing valuable insights for scholars, policymakers and organisations seeking to deepen their understanding of KM’s role in economics.