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Knowledge Sharing Framework: a Game-Theoretic Approach
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DOI：10.1007/s13132-020-00710-9.png)
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Abstract
En 中文
Uncertainty in business environments is promoting learning as an organizational value. Organizations need to implement knowledge management (KM) processes as well as organizational mechanisms transforming collective knowledge into a learning organizational capability. Literature identifies knowledge sharing (KS) as a fundamental KM process. Moreover, KM was found to be a prerequisite to a learning organization. Unfortunately, organizational initiatives promoting KS are challenged with the hoarding wisdom, knowledge is power. Literature has researched intrinsic and extrinsic motivations affecting KS intention. The rational action theory (RAT) explains the embedded utility function merging these motivations. Despite many studies, the dynamics of KS behavior needs further examination. This paper is an attempt to frame the KS behavior using game theory and RAT. We represent individuals' perceived utility in two functions: knowledge and trustworthiness. This limits the perceived utility to personal enjoyment and reciprocity, which could be viewed as establishing a baseline KS behavior. We use the assurance game framework to incubate the two utility functions. Finally, we argue that KS intention is actually a dynamic state within a KS strategy. We identify five KS strategies: cooperation, defection, tit-for-tat, unforgiving, and random. It is the performance of these strategies that needs to be studied. Several scenarios are simulated to observe the progression of knowledge within each strategy. Interestingly, two strategies start with positive KS intention yet end up converging with those who started with negative KS intention. On the long run, only cooperatives seem to be contributing to collective knowledge. Empirical data from a teaching hospital is collected and analyzed for comparison.
Keywords:
Game theory
Knowledge management
Learning organization
Modeling and simulation
Knowledge sharing
Rational action theory
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2.5K
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