Research on users’ participation mechanisms in virtual tourism communities by Bayesian network

In the context of the Internet age, the tourism industry has opened up new development opportunities with the help of Internet technology advancement. It has produced many tourism virtual communities such as TripAdvisor, Ctrip, Mafengwo Many studies have been conducted on user behavior’s influencing factors in virtual communities (such as co-creation and participants’ value-in-use). However, the studies on the mechanism of user participation in virtual communities are limited. This paper proposes a group average Bayesian network model, which is a data-driven method for obtaining the user participation mechanism’s causal network. An induced Bayesian network is used to discover conditional dependence between factors and perform probabilistic inferences. Eleven main factors have been selected, including participation intensity, subjective norm, social identity, group norm, functional value, emotional value, social value, share, interaction, user experience and user satisfaction. We found that user experience, and functional value have the most significant impact on user satisfaction, and social identity plays an essential intermediary role in the participation mechanism. This study enriches the research methods of user participation mechanisms and provides a reference for the virtual tourism community’s theoretical research and management practice.