The Bibliometric Keywords Network Analysis of Human Resource Management Research Trends: The Case of Human Resource Management Journals in South Korea

• Main Authors: Chungil Chae, Jeong-Ha Yim, Jaeeun Lee, Sung Jun Jo, Jeong Rok Oh
• Format: Article
• Language: English
• Published: MDPI AG 2020-07-01
• Series: Sustainability
• Subjects: human resource management (HRM); research trends; keyword network; bibliometrics; South Korea
• Online Access: https://www.mdpi.com/2071-1050/12/14/5700

Although previous studies on human resource management (HRM) research trends in the global context provided very useful information about the structures of HRM research trends, they have critical limitations. Despite the growing contribution and significance of HRM practices in Korea, a dominant group of scholars has rarely focused on what is going on in the research community in the country. To overcome the limitations and fill the gaps found in studies on the global HRM trends, the purpose of this study is to conduct the keyword network analysis investigating the semantic network structure composed of Korean HRM studies. A total of 1158 research papers published by three top peer-reviewed HRM journals in Korea that were published from 2007 to 2018 were analyzed. The result shows that the whole network structure of Korean HRM has a complex semantic structure that is socially constructed. Additionally, this study identified the top 10 prominent keywords and its ego-centric networks, and nine thematic clusters. By adopting keywords network analysis in bibliometric methods, this study provides an accurate structural interpretation of Korean HRM research practice to facilitate the sustainable development of the studies on the global HRM trends.