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Evolution of the Socio-cognitive Structure of Knowledge Management (1986–2015): An Author Co-citation Analysis


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Purpose

The evolution of the socio-cognitive structure of the field of knowledge management (KM) during the period 1986–2015 is described.

Design/methodology/approach

Records retrieved from Web of Science were submitted to author co-citation analysis (ACA) following a longitudinal perspective as of the following time slices: 1986–1996, 1997–2006, and 2007–2015. The top 10% of most cited first authors by sub-periods were mapped in bibliometric networks in order to interpret the communities formed and their relationships.

Findings

KM is a homogeneous field as indicated by networks results. Nine classical authors are identified since they are highly co-cited in each sub-period, highlighting Ikujiro Nonaka as the most influential authors in the field. The most significant communities in KM are devoted to strategic management, KM foundations, organisational learning and behaviour, and organisational theories. Major trends in the evolution of the intellectual structure of KM evidence a technological influence in 1986–1996, a strategic influence in 1997–2006, and finally a sociological influence in 2007–2015.

Research limitations

Describing a field from a single database can offer biases in terms of output coverage. Likewise, the conference proceedings and books were not used and the analysis was only based on first authors. However, the results obtained can be very useful to understand the evolution of KM research.

Practical implications

These results might be useful for managers and academicians to understand the evolution of KM field and to (re)define research activities and organisational projects.

Originality/value

The novelty of this paper lies in considering ACA as a bibliometric technique to study KM research. In addition, our investigation has a wider time coverage than earlier articles.

eISSN:
2543-683X
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Information Technology, Project Management, Databases and Data Mining