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Article type: Research Article
Authors: Meng, Jianfenga | Zhang, Gongpengb; * | Li, Zihana | Yang, Hongjic
Affiliations: [a] School of Management, Langfang Normal University, Langfang, Hebei, China | [b] Tourism College, Beijing Union University, Beijing, China | [c] School of Computing and Mathematical Sciences Leicester University Leicester, UK
Correspondence: [*] Corresponding author: Gongpeng Zhang, Tourism College, Beijing Union University, Beijing, 100101, China. E-mail: [email protected].
Abstract: Crowdsourcing community, as an important way for enterprises to obtain external public innovative knowledge in the era of the Internet and the rise of users, has a very broad application prospect and research value. However, the influence of social preference is seldom considered in the promotion of knowledge sharing in crowdsourcing communities. Therefore, on the basis of complex network evolutionary game theory and social preference theory, an evolutionary game model of knowledge sharing among crowdsourcing community users based on the characteristics of small world network structure is constructed. Through Matlab programming, the evolution and dynamic equilibrium of knowledge sharing among crowdsourcing community users on this network structure are simulated, and the experimental results without considering social preference and social preference are compared and analysed, and it is found that social preference can significantly promote the evolution of knowledge sharing in crowdsourcing communities. This research expands the research scope of the combination and application of complex network games and other disciplines, enriches the theoretical perspective of knowledge sharing research in crowdsourcing communities, and has a strong guiding significance for promoting knowledge sharing in crowdsourcing communities.
Keywords: Crowdsourcing community, knowledge sharing, social preference complex network
DOI: 10.3233/MGS-221532
Journal: Multiagent and Grid Systems, vol. 19, no. 3, pp. 253-269, 2023
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