The Impact of Unobserved Social Networks and Privacy Concerns on Group-buying Decisions

Leveraging the viral power of social networks, group buying has rapidly emerged as a promising e-commerce model with substantial market potential. Companies have been increasingly integrating group-buying campaigns into social media platforms to further accelerate demand growth. However, tapping into these expansive social networks can heighten users' privacy concerns especially regarding the uncontrolled exposure risks as personal information propagates across widening social circles. Despite the tension between leveraging social networks for viral marketing and addressing privacy concerns, the empirical effects of social networks and privacy concerns on group buying behaviors remain unclear. This knowledge gap persists primarily because of the inability to observe underlying peer connections in many group-buying datasets. We address this research gap by applying an econometric technique tailored for social network effects with unobserved networks to the group buying context. Leveraging a novel group-buying dataset on a Chinese social media platform, we measure the impacts of social networks and privacy concerns on users' group-buying behavior while the links of social networks are unobserved. We find that (1) An individual user is more likely to participate in group buying when close friends have signed up. (2) A privacy-sensitive user is less likely to participate in group buying themselves. However, (3) when close friends with high privacy sensitivity sign up, the individual user would be more likely to participate in group buying, indicating a positive contextual effect of privacy concern. Beyond these main effects, we also examine how the impact of privacy concerns varies across regions with different economic development levels. Further, we examine how underlying social network structural features-particularly network degree and centrality-affect group-buying participation decisions. Our findings provide important implications for platforms to design group-buying mechanisms.