The Electronic Journal of Knowledge Management publishes original articles on topics relevant to studying, implementing, measuring and managing knowledge management and intellectual capital.

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Journal Issue
Volume 14 Issue 2 / Jun 2016  pp89‑158

Editor: Ken Grant

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Editorial  pp89‑90

Ken Grant

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Linking Decision Artifacts: A Means for Integrating Business Intelligence and Knowledge Management  pp91‑102

William McHenry

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Understanding Business Intelligence Understanding: Through Goods‑ and Service‑Dominant Logic Lenses  pp103‑115

Pamela R. Clavier

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The Role of the HRM in the Construction of KM for the Innovation in Technological SMEs  pp116‑125

Thibaut Métailler

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Crowdsourcing User‑Contributed Solutions to Aerospace Product Development Issues through Micro‑Blogging  pp126‑136

Richard David Evans, James Xiaoyu Gao, Sara Mahdikhah, Mourad Messaadia, David Baudry

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Knowledge Sharing and Business Expertise Factor Relationships  pp137‑158

Neil David John Topping

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Abstract: Research into knowledge sharing has predominantly utilised qualitative research methods. The quantitative research methods that built models focused upon a narrow grouping of factors. This research sought to develop a holistic model of the predi ctors of knowledge sharing, with expertise factors added, to qualify the value of the expertise being shared. An extensive literature review and individual / series of interviews were carried out to identify the knowledge sharing factors, of which 18 were recognised. The value of knowledge shared is dependent on the expertise of the individual, and two expertise orientated factors were developed. These two factors were based upon two self‑assessment constructs, a Cochran‑Weiss‑Shanteau measure, and a peer ‑comparison measure, both of which were used to identify an individuals the level of expertise. Using these factors a model was developed that, enabled individual self‑assessment of knowledge sharing and expertise latent variables. 103 participants compl eted the survey, and the results were analysed using structured equation modelling (SEM) and confirmatory factor analysis (CFA). The model did not achieve a goodness of fit. There were 6 factors that were significantly related to the intention to shar e knowledge construct, with both expertise factors found to be significantly related to an expertise construct. The intention to share knowledge construct was significantly related to the expertise construct. This model has been used to identify 4 types o f knowledge sharers. These types offer significant practical benefit for human resource activities, specifically in recruitment and organisational design. 


Keywords: Keywords: Cochran-Weiss-Shanteau, Structured Equation Modelling, SEM, Confirmatory Factor Analysis, CFA, Knowledge sharing types, Expertise


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