Abstract
AbstractStimulating is an important mechanism in Virtual Community (VC) during the Knowledge Sharing (KS) process. In this paper, we combine the power of game theory and stimulating mechanism together to optimize the KS process in Social Network (SN). We first model the basic stimulating mechanism as a static game of complete information, under which the stimulating threshold for Nash Equilibrium (NE) is derived. Next, we modify the static model by introducing the KREPS-MILGROM-ROBERTS-WILSON (KMRW) reputation model, where the dynamic case is studied and the Perfect Bayesian Equilibrium is proved. We then propose a novel rational stimulating mechanism by combining the finitely repeated game with basic stimulating mechanism together. Theoretical analyzing indicates that, by introducing incomplete information, the rational stimulating achieves a lower cost; through stimulating, the Perfect Bayesian Equilibrium’s condition is satisfied and the KS rate will approach 100% as long as the KS process is repeated enough. Finally, we extend our rational stimulating mechanism to the multi-person model.KeywordsSocial NetworkVirtual CommunityKnowledge SharingStimulatingGame Theory
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