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Predicting Knowledge Sharing On Knowledge Management Systems

In: People, Knowledge And Technology What Have We Learnt So Far?

Author

Listed:
  • SCOTT KREBS

    (School of Psychology, University of Queensland, Brisbane, QLD 4072, , Australia)

  • PRASHANT BORDIA

    (School of Psychology, University of Queensland, Brisbane, QLD 4072, , Australia)

Abstract

Knowledge management systems (KMS) enable the codification and transfer of individual and organizational knowledge across a firm. Used effectively, KMS can promote organizational learning and thus develop a firm’s competitive advantage. However, many KMS implementations have been unsuccessful, as important contextual factors of knowledge and its management is neglected in both research and practice. The purpose of this paper is to stimulate KMS research by proposing a theoretical model, which aims to predict knowledge sharing on to electronic databases. As knowledge sharing largely relies on employees’ willingness to share, we theorize that social and organizational influences will be critical factors in employees’ intention to contribute to databases. Practical implications of the model are discussed.

Suggested Citation

  • Scott Krebs & Prashant Bordia, 2004. "Predicting Knowledge Sharing On Knowledge Management Systems," World Scientific Book Chapters, in: Bruno Trezzini & Patrick Lambe & Suliman Hawamdeh (ed.), People, Knowledge And Technology What Have We Learnt So Far?, chapter 15, pages 152-162, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812702081_0015
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