There is much evidence that consumers' eco-friendly consumption behaviors have changed with the development of the mobile internet economy and social networks.Social commerce, which combines social media and e-commerce, is widely used to promote eco-friendly consumption behavior. However, there has been insufficient empirical research into how technological and social factors affect consumers' ecofriendly behavior in the social commerce context. Taking the "Green Box Area" program based on Alibaba Group's two mobile apps as the research object, this study developed a model that integrated technological and social roles to predict consumers' eco-friendly behavior. Using data from 468 users participating in the "Green Box Area" program, structural equation modeling analysis suggested that technological and social factors are essential predictors of consumers' eco-friendly behavior in both short-term and medium-/long-term models. Furthermore, consumer achievement played a critical mediating role in the causal chain of social factors influencing eco-friendly behavior. Additionally, the findings showed that perceived ease of use and social influence significantly affected short-term but not medium-/long-term eco-friendly behavior. Conversely, social interaction affected eco-friendly behavior only in the medium-/long-term. The results offer implications for policymakers and social commerce practitioners to consider the effective promotion of consumers' eco-friendly behavior.

Smart media combines media and artificial intelligence (AI) and can also be a user-centered content service market. However, existing research lacks an understanding of user's perceptions concerning smart services generated by different user experience types across different payment groups. Taking AI-powered Smart TV (AI TV) as a typical research object, this study (1) develops a theoretical model by integrating the technology acceptance model with users' smart service belief factors and (2) employs the user experience type as an original moderator. Using data from 585 AI TV users, the structural equation modeling analysis suggests that perceived two-way communication, perceived personalization, and perceived co-creation as three belief factors, are important antecedent constructs in the extended technology acceptance model. The analysis also suggests that the user experience type exerts positive moderating effects on two-way communication and personalization to attitude toward behavior and purchase intention. This study thus contributes to the literature on smart service by identifying and studying smart service belief factors. The addition of smart service belief factors as antecedents, as well as user experience type as a moderator, are crucial to expand the generalizability of TAM to the smart media service context. From a customer experience management perspective, this study shows how to convert ad-supported users into new paid subscribers, while keeping existing subscribers by fulfilling their smart service requirements.

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