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Balancing codification and personalization for knowledge reuse: a Markov decision process approach
DOI:10.1108/JKM-04-2013-0127.png)
摘要
En 中文
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.
Keyword:
Knowledge sharing
Knowledge management
Decision making
Modelling
Cost/benefit analysis
Knowledge reuse
Markov decision process
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