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

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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.

论文关键词:Bayesian networks,Virtual tourism community,Causal inference,Grouped average Bayesian network model,Users’ participation mechanism

论文评审过程:Received 2 November 2020, Revised 19 March 2021, Accepted 17 May 2021, Available online 19 May 2021, Version of Record 21 May 2021.

论文官网地址:https://doi.org/10.1016/j.knosys.2021.107161