Evolutionary Game of User Knowledge Sharing Behaviors in Enterprise Brand Virtual Community: Influence of Multiple Level Factors
Chengyi Le, Peipei Li, Ya Zeng
Abstract
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Chengyi Le, Peipei Li, Ya Zeng
Abstract
Open-access reader
The exchange and sharing of user knowledge in the brand virtual community is an important way for enterprise product innovation. Therefore, how to encourage users to share their knowledge continuously in the brand virtual community is a key issue. Based on evolutionary game theory, this paper analyzes the influence of various factors on user’s knowledge sharing behavior from the aspects of individual factors, mutual factors and community factors. Through simulation, it is found that there exist two evolutionary stability strategies, that is, (knowledge sharing, knowledge sharing) and (no knowledge sharing, no knowledge sharing). And which direction this system evolves depends on the initial probability and critical points of knowledge sharing. Results show that user’s knowledge level in individual level, the ability to transform and absorb knowledge, the degree of knowledge sharing, the innovation degree of knowledge sharing and the incentive coefficient in community level have a positive impact on the user’s knowledge sharing behavior. Meanwhile, the cost of knowledge sharing between individuals, the homogeneity of knowledge and the spillover effect in mutual level have a negative impact on the behavior of user knowledge sharing. What’s more, there is an optimal coefficient of collaborative profit distribution, which makes the system most likely to evolve in the direction of (knowledge sharing, knowledge sharing).
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The exchange and sharing of user knowledge in the brand virtual community is an important way for enterprise product innovation. Therefore, how to encourage users to share their knowledge continuously in the brand virtual community is a key issue. Based on evolutionary game theory, this paper analyzes the influence of various factors on user’s knowledge sharing behavior from the aspects of individual factors, mutual factors and community factors. Through simulation, it is found that there exist two evolutionary stability strategies, that is, (knowledge sharing, knowledge sharing) and (no knowledge sharing, no knowledge sharing). And which direction this system evolves depends on the initial probability and critical points of knowledge sharing. Results show that user’s knowledge level in individual level, the ability to transform and absorb knowledge, the degree of knowledge sharing, the innovation degree of knowledge sharing and the incentive coefficient in community level have a positive impact on the user’s knowledge sharing behavior. Meanwhile, the cost of knowledge sharing between individuals, the homogeneity of knowledge and the spillover effect in mutual level have a negative impact on the behavior of user knowledge sharing. What’s more, there is an optimal coefficient of collaborative profit distribution, which makes the system most likely to evolve in the direction of (knowledge sharing, knowledge sharing).
Key concepts: Knowledge sharing, Knowledge management, Knowledge value chain, Incentive, Computer science, Domain knowledge, Business, Organizational learning