A Tripartite Evolutionary Game Analysis of Online Knowledge Sharing Community. (20th September 2022) - Yang, Jian
Abstract : With the rapid development of information technology, online knowledge monetization has emerged as a potential business model for several social Q&A platforms, which brings more complex benefits and cost tradeoffs for users. However, most of the previous studies were based on free Q&A platforms, which made it difficult to explain the influencing factors of various stakeholders in the decision-making process of knowledge sharing and failed to comprehensively analyze the behavior of knowledge sharing subjects using dynamic system theory. This study establishes a tripartite evolutionary game model of knowledge consumers, knowledge providers, and knowledge payment platforms and discusses evolutionary stability strategies, evolutionary trends, and factors affecting the evolutionary path of tripartite behavior. The extensive experimental results show that knowledge payment is an important way to promote knowledge sharing. Meanwhile, the implementation of a rewards and punishment system on payment platforms will encourage knowledge providers to provide high-quality knowledge content and increase the willingness of knowledge consumers to pay, thereby facilitating the knowledge-sharing process. This paper provides the decision-making basis for the operation of the online knowledge community and proposes a new proposition to solve the conflict of interest in the process of knowledge sharing from the perspective of evolutionary theory.