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A bibliometric study on authorship trends and research themes in knowledge management literature
Laboratory of Industrial and Information Management Tampere University of Technology, Tampere, Finland.
The Business School, University of Exeter, Exeter, UK.
Örebro University, Örebro University School of Business. Laboratory of Industrial and Information Management, Tampere University of Technology, Tampere, Finland.ORCID iD: 0000-0001-6324-5425
Laboratory of Industrial and Information Management, Tampere University of Technology, Tampere, Finland.
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2017 (English)In: 12th International Forum on Knowledge Asset Dynamics, St. Petersburg, Russia 7-9 June 2017: Knowledge Management in the 21th Century: Resilience, Creativity and Co-creation. Proceedings / [ed] JC Spender, Giovanni Schiuma, Tatiana Gavrilova, St. Petersburg, Russia: Proceedings IFKAD... , 2017, Vol. 12, p. 389-397Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
St. Petersburg, Russia: Proceedings IFKAD... , 2017. Vol. 12, p. 389-397
Series
IFKAD Proceedings, E-ISSN 2280-787X
Keywords [en]
Knowledge Management, bibliometrics, bibliography, network analysis, scientometrics
National Category
Computer Sciences Information Systems, Social aspects
Identifiers
URN: urn:nbn:se:oru:diva-63943ISBN: 978-88-96687-10-9 (electronic)OAI: oai:DiVA.org:oru-63943DiVA, id: diva2:1171691
Conference
12th International Forum on Knowledge Asset Dynamics (IFKAD 2017), St. Petersburg, Russia, June 7-9, 2017
Available from: 2018-01-08 Created: 2018-01-08 Last updated: 2022-08-12Bibliographically approved

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Aramo-Immonen, Heli

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Citation style
  • apa
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Language
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Output format
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  • asciidoc
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