This paper aims to provide a systematic framework for organizations to analyze their knowledge reuse processes, and balance codification and personalization within their knowledge strategy according to cost/benefit analysis.
This paper divides knowledge reuse process into a sequence of five stages, and accordingly analyzes costs/benefits under codification and personalization strategies. Markov decision process, a mathematical framework for multi-stage decision-making, is employed to optimize a mixed strategy for knowledge reuse processes within an organization.
Organizations need to consider factors such as the number of reusable knowledge items, reuse patterns, and intra-organizational interest alignment which are critical to determine their optimal mix between codification and personalization. Companies should determine a knowledge strategy based on their knowledge reuse contexts instead of following success cases blindly.
This paper presents an illustrative example to show how this framework might be applied by an organization. However, the validity and reliability of strategic decision-making also depends on the accuracy of the model's parameter values. Firms can adopt many methods as surveys, Delphi method, to determine the parameter values.
The proposed framework offers an opportunity for firms to gain insights by setting the model's parameters to their own reuse contexts/characteristics and conducting what-if analysis.
This paper proposes a formal framework for analyzing knowledge reuse processes and offers organizations guidelines about decision-making of knowledge strategies.
Received 3 April 2013 Revised 9 July 2013 Accepted 9 July 2013
Liu, H., Chai, K. and F. Nebus, J. (2013), "Balancing codification and personalization for knowledge reuse: a Markov decision process approach", Journal of Knowledge Management, Vol. 17 No. 5, pp. 755-772. https://doi.org/10.1108/JKM-04-2013-0127Download as .RIS
Emerald Group Publishing Limited
Copyright © 2013, Emerald Group Publishing Limited