Social interaction-based consumer decision-making model in social commerce: The role of word of mouth and observational learning

Social commerce mediated by social media and social network platforms has led to the development of new business models in e-commerce and digitized the consumer decision journey. Social interaction is considered as a prerequisite for successful social commerce since consumers now expect an interactive and social experience while making purchase decisions. Drawing on word of mouth (WOM) and observational learning theories, we conceptualize social interactions in social commerce environments into two forms: WOM communication and observing other consumers’ purchases, and examine their impact on consumer purchase intention and actual purchase behavior. Analyzing primary data (n = 217) collected from surveyed active consumers within social commerce sites at two stages (pre-purchase and post-purchase), we found that positive and negative valence WOM, WOM content, and observing other consumers’ purchases significantly affect consumers’ intention to buy a product, thereby increasing the likelihood of actual buying and sharing product information with others on social commerce sites.     

The dynamic effect of interactivity on customer engagement behavior through tie strength: Evidence from live streaming commerce platforms

Interactivity, which is a key characteristic of the live streaming commerce environment, fosters users’ active attitudes and behaviors in communications and transactions. However, the literature on live streaming commerce, is scarce, and few studies examine how interactivity influences customers’ non-transactional behaviors from a dynamic perspective. In this setting, based on the stimulus-organism-response (S-O-R) framework, we developed a research model using real-time data to investigate the dynamic effect of interactivity on customer engagement behavior through tie strength in live streaming commerce, which is a relatively new derivative of social commerce. This study developed a text mining method to quantify constructs using a large-scale sample of 3,500,445 online review texts. Our empirical study found that interactivity has a curvilinear relationship with customer engagement behavior. Besides, tie strength plays an intermediary role between interactivity and customer engagement behavior. It was further observed that both tenure of membership and popularity have an important moderating relationship between interactivity and tie strength. The study enriches the relationship marketing theory and live streaming commerce literature. Moreover, this study is one of the first studies to use real-time online data for live streaming commerce research.