With the rapid development of the Internet and the widespread adoption of mobile devices, live streaming has become a new social medium in the last few years. Hence, the continuous usage of live streaming platforms has become an important issue. Based on social exchange theory, this study investigates how different kinds of interactions affect viewers’ sense of virtual community (SOVC) and in turn facilitate their continuous watching intention. Empirical results (N = 423) reveal that both viewer-broadcaster interaction and viewer-viewer interaction positively affect viewers’ SOVC, which further enhances their stickiness. Furthermore, viewer-platform interaction positively moderates the effects of interactions between viewers and broadcasters on their SOVC, whereas the moderating role of gift-giving behaviour is insignificant. Finally, the effects of viewer-broadcaster interaction and viewer-viewer interaction on stickiness are partially mediated by SOVC. This study contributes to in-depth research on the relationships between different specific interactions and viewers’ continuous watching intention, which enriches the existing study on live streaming and deepens our understanding of viewers’ stickiness. The empirical findings of this study suggest that social media developers and managers take actions to encourage interactions that increase viewers’ stickiness.

In this paper, we model a fully covered duopoly market in which two firms offer a differentiated information product that exhibits positive network effects and a complementary premium service to consumers. For each firm, there are two marketing strategies: the freemium strategy and the bundling strategy. We find that, under the market equilibrium, a firms’ decision whether to employ the freemium strategy or not depends largely on the quality of the information product compared to its rival. When the information product quality is similar and the products’ intrinsic values are sufficiently large, both firms will be better off by adopting the freemium strategy, while the bundling strategy will prevail if the products’ intrinsic values are sufficiently small. Additionally, when the magnitude of complementary effects or network effects exceeds a given threshold, both firms’ profit can be enhanced by an increase in the degree of product complementarity or in the intensity of network effects. We also demonstrate that a firm can benefit from an increasing market size only if the intrinsic value of its information product is sufficiently large. Finally, we extend our model to the uncovered market and derive the equilibrium prices and profits.

Purpose: The purpose of this paper is to treat WeChat moments as social media environments and applies the research model to explore the effect of social media environments on perceived interactivity from the perspective of environmental psychology. Design/methodology/approach: This paper proposes social media environments as effective stimuli for future participate in online social interactions. First, two cues of social media environments (user-to-system cues and user-to-user cues) can be important antecedents of users’ perception of interactivity. Second, users’ intention of future participates in online social interactions can be influenced by three dimensions of perceived interactivity (action control, connectedness and responsiveness). Using data from 334 users of WeChat moments, the authors conduct partial least squares analysis to validate the research model. Findings: The results indicate that both technological and social environments positively affect three dimensions of perceived interactivity, respectively, including action control, connectedness and responsiveness. Moreover, actual findings also suggest that higher perceived interactivity increases users’ intention of future participate in online social interactions. Originality/value: This work contributes to in-depth research on the relationships between social environments and perceived interactivity. Besides, this paper demonstrates that both technological and social cues of social media environments are significant elements in simulating users’ internal experience and behavioral intention. The main conclusions of this study can be valuable to social media developers and managers.

Understanding customer needs is of great significance to enhance service quality and competitive advantage. However, for the tourism industry, it is still unclear how to mine service improvement strategies from tourist-generated online reviews. This paper aims to develop a data-driven approach to conduct a fine-grained dimension analysis of customer satisfaction with tourism services. First, this paper uses Latent Dirichlet Allocation to explore the key dimensions of tourist satisfaction from online reviews. Next, based on the Chinese sentiment dictionary, tourists’ emotional attitudes towards each service dimension can be identified. Then, the backpropagation neural network is used to measure the complex relationship between tourists’ sentiment orientations towards different dimensions and their satisfaction. Finally, according to the improved Kano model, multi-dimensional attribute classification is realized to support the strategic analysis of tourism service quality improvement. The proposed method is empirically verified through a real tourism review dataset. The results exhibit the theoretical and practical implications of our method.