A bibliometric study on authorship trends and research themes in knowledge management literature

被引:0
|
作者
Jussila, Jari J. [1 ]
Mustafee, Navonil [2 ]
Aramo-Immonen, Heli [1 ]
Menon, Karan [1 ]
Hajikhani, Arash [3 ]
Helander, Nina [1 ]
机构
[1] Tampere Univ Technol, Lab Ind & Informat Management, POB 541, FI-33100 Tampere, Finland
[2] Univ Exeter, Business Sch, Rennes Dr, Exeter EX4 4ST, Devon, England
[3] Lappeenranta Univ Technol, POB 20, FI-53851 Lappeenranta, Finland
关键词
Knowledge Management; bibliometrics; bibliography; network analysis; scientometrics; PERFORMANCE; NETWORKS;
D O I
暂无
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
The aim of the study is to identify the contribution of authors in the domain of Knowledge Management (KM). The underlying data is from two leading KM journals, namely, the Journal of Knowledge Management (JKM) and the Journal of Intellectual Capital (JIC). We downloaded articles from Thomson Reuters Web of Science (WoS), with JKM and JIC-specific searches resulting in 508 and 73 citing articles respectively. The timeframe of analysis was 2009-2016. This dataset was used to create co-citation network visualisations to provide insights into the clusters of authors and research topics. Measures such as Betweenness centrality and hubs-authorities (HITS) were used to identify significant authors and their key themes of interest. More specifically, network analysis identified six dominant research themes, it revealed a total of 14,422 authors being cited (depicted as nodes in the visualisation) with a total of 1,023,123 citations (edges). Based on the findings of this study, the paper will explore the specific themes and the intellectual turning points in KM research and its evolution. Our bibliometric analysis has practical significance for researchers since it recognises the dominant research areas, and by extension, it identifies those that are still in their infancy; the latter having the potential of representing an interesting research gap. The limitation of the study is that the underlying data is only from two journals (albeit, from the top two journals in KM), which may lead to partially biased results. In future, the aim is to also leverage the analysis to more KM journals, e.g., the top ten journals within the Serenko & Bontis (2013) most updated list.
引用
收藏
页码:389 / 397
页数:9
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