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Knowledge management implementation: modelling the variables

Author

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  • R. Kant
  • M.D. Singh

Abstract

The purpose of this paper is to present an approach to Knowledge Management (KM) implementation in organisations by understanding the dynamics between the various Knowledge Management Variables (KMVs). Using Interpretive Structural Modelling (ISM), the research presents a hierarchy-based model and the mutual relationships among the KMVs. The research shows that there is a group of KMVs that have a high driving power and low dependence power that require maximum attention and are of strategic importance, while another group consists of those KMVs which have a high dependence power and low driving power. A key finding of this research is that leadership is the main driver for KM implementation.

Suggested Citation

  • R. Kant & M.D. Singh, 2009. "Knowledge management implementation: modelling the variables," International Journal of Innovation and Learning, Inderscience Enterprises Ltd, vol. 6(3), pages 342-361.
    • Handle: RePEc:ids:ijilea:v:6:y:2009:i:3:p:342-361
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    Cited by:

    1. Hiteshkumar G. Shah & Ravi Kant, 2018. "Knowledge Management Enablers: Metadata Analysis for KM Implementation," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1-29, December.

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