Table of Contents

Handbook of Research on Knowledge Management

Handbook of Research on Knowledge Management

Adaptation and Context

Research Handbooks in Business and Management series

Edited by Anders Örtenblad

This innovative Handbook aims to examine whether there is a need to adapt and widen our understanding of knowledge management. A common definition of knowledge management is taken as the starting point for discussions on its relevance in various contexts, such as Buddhist organizations, law firms, the army and indigenous organizations. Moreover, the universality of Ikujiro Nonaka’s ideas on knowledge management is explored, and some alternative definitions are suggested. This book will appeal to academics and students of business and management, business administration, sociology and organizational behavior. Practitioners, managers and business-owners will also find this an invaluable resource.

Chapter 3: A normative model of knowledge management effectiveness

Paul S. Myers

Subjects: business and management, knowledge management, innovation and technology, knowledge management


No shortage of frameworks exists to describe the organizational features, management practices and strategic intents of knowledge management (KM). These models have been developed based on data from organizations in a variety of industries, economic sectors and geographic locations. Since the field of KM emerged in the mid 1990s, a continuous stream of research on success factors and inhibitors has produced general guidance for practitioners working to improve how their organizations manage their intellectual assets. Indeed one comprehensive review identified 160 approaches to the subject developed between 1995 and 2003, after which publication of new descriptive and proscriptive models dropped off substantially (Heisig 2009). A more recent literature review by Matayong and Mahmood (2013) suggests that no convergence in analytical approaches to KM has yet occurred. Proposed KM models commonly offer comprehensive descriptions of the variables and their interactions that can influence different outcomes, and these have been the basis of empirical research to demonstrate causal links (for example, Kulkarni et al. 2006; Nejatian et al. 2013). But it is a long way from identifying correlations and covariances that meet a minimal threshold of statistical significance to devising action plans for those working to manage knowledge effectively. Practitioners can benefit from understanding the complexity they face and having a big picture awareness of the conditions that may enable or hinder their efforts (Antonacopoulou and Chiva 2007).

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