Pitfalls and Potentials of Knowledge Management

By Sunil Choenni, Saskia Harkema and Debora Moolenaar.

Published by The Organization Collection

Format Price
Article: Print $US10.00
Article: Electronic $US5.00

Organizations are interested in actively using knowledge / past experiences to improve their business processes. In this paper, we address some of the major issues in obtaining this goal.

Keywords: (Perspectives on) Knowledge Management, Codifying Knowledge, Representing Knowledge, Knowledge Distribution, Information Retrieval, Data Mining

International Journal of Knowledge, Culture and Change Management, Volume 5, Issue 7, pp.33-40. Article: Print (Spiral Bound). Article: Electronic (PDF File; 1.943MB).

Dr. Sunil Choenni

Sunil Choenni is heading the department of Statistical Information Management and Policy Analysis at the Research & Documentation Centre (WODC), which is an institute of the Dutch Ministry of Justice. Prior to joining WODC he held several teaching and research positions at different universities and research centres. He published many papers in the field of Information Management and Business Administration and serves as PC member in a number of international conferences.

Dr. Saskia Harkema

Saskia Harkema received her PhD from Universiteit Nyenrode for her dissertation “Complexity and emergent learning in innovation projects”. She is currently Assistant Professor at the Universiteit Utrecht and Associate Professor at The Hague University of Higher Education. Her research interests include innovation management, complexity theory and the learning organization.

Debora Moolenaar

Debora Moolenaar received her PhD from the University of Amsterdam for her dissertation "The Dutch market for agency work". She is currently working as a researcher at the department of Statistical Information Management and Policy Analysis at the Research & Documentation Centre (WODC), which is an institute of the Ministry of Justice in the Netherlands. Her research interests include econometrics, forecasting models, law & economics, labor market economics, benchmarking and efficiency analysis.

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