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Channel: Emerald Group Publishing Limited: Journal of Knowledge Management: Table of Contents
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Balancing Codification and Personalization for Knowledge Reuse: a Markov Decision Process Approach

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Abstract

Purpose - 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.Design/methodology/approach - 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. Findings - 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.Research limitations/implications - 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.Practical implications - 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.Originality/value - This paper proposes a formal framework for analyzing knowledge reuse processes and offers organizations guidelines about decision-making of knowledge strategies.

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