Chatbots have been widely adopted to support online customer service and supplement human agents. However, online data transmission may involve privacy issues and arouse users’ privacy concerns. In order to understand the privacy management mechanism when interacting with chatbots and human agents, we designed a cross-national comparative study and conducted online experiments in China and the United States based on Communication Privacy Management (CPM) theory. The results show that privacy concerns and boundary linkage played different mediation roles between agent identity and the intention to disclose as well as the intention to use the service. Information sensitivity had a significant moderating effect on the mechanism. Our research contributes to a better understanding of personal boundary management in the context of human-machine interaction.

Live streaming is an essential means through which spectators view and engage with esports. In this study, an extended model is proposed and tested based on the expectation confirmation theory to examine esports fans’ live streaming experience and the factors contributing to their intention to continue using particular live streaming platforms. Survey data (N = 1004) were collected from King Pro League fans in China and analyzed using structural equation modeling. The results demonstrate that effort and enjoyment expectancies are important factors driving fans’ confirmation of expectations regarding live streaming services. The findings also confirm that both spatial presence and co-presence positively relate to viewers’ satisfaction with a live streaming platform and their continued intention to use it. This study provides new insights into esports fans’ viewing practices and the experiences they find most engaging via live streaming platforms.

Members’ knowledge sharing is essential in order for online health support groups (OHSGs) to provide informational support, but factors influencing knowledge sharing intention in OHSGs have not been sufficiently explored. This study provides some insights by adopting a person-situation interactionist perspective and developing a model that synthesizes the five-factor model of personality traits and the three dimensions of social capital – structural (social interaction ties), relational (trust), and cognitive (shared vision). Structural equation modeling was used to test the model, drawing on online survey data collected from OHSGs in China (N = 546). Three main findings were revealed. First, sharing intention is promoted by social interaction, trust, and shared vision, although trust has the largest effect size. Second, trust promotes social interaction and shared vision. Third, the five personality factors can be categorized into three groups of personality: interactive (extraversion), trusting (conscientiousness, openness to experience), and cooperative (agreeableness and neuroticism). These findings suggest three mechanisms behind knowledge sharing intention in OHSGs via the three social capital dimensions, with trust being the most important factor.