Who will attract you? Similarity effect among users on online purchase intention of movie tickets in the social shopping context

• Published in: International journal of information management 2018-06, Vol.40, p.88-102
• Main Authors: Fu, Senhui, Yan, Qing, Feng, Guangchao Charles
• Format: Article
• Language: English
• Subjects: Consumer behavior; Digital media; Electronic commerce; Information technology; Perceived enjoyment; Perceived usefulness; Perceptions; Purchase intention; Shopping; Similarity; Similarity effect; Social networks; Technology transfer; Technology utilization; Tickets; Trust transfer
• ISSN: 0268-4012; 1873-4707
• DOI: 10.1016/j.ijinfomgt.2018.01.013

With the popularity and growth of social networking sites, users often rely on the advice and recommendations from online friends when deciding to purchase movie tickets. The relationship between users' reviews and movie ticket purchase intention in the context of social media has been demonstrated in several studies, but few studies have explored users' perceptions of the similarity effect on online purchase intention or the psychological mechanisms of the similarity effect. From an interpersonal relationship perspective, we propose that similarity (including external and internal similarity) is an important cue for users who are deciding to purchase movie tickets online. Built on SOR (Stimuli-Organism-Response) Model and drawn upon trust transfer and information technology acceptance theories, we examined whether similarity could enhance users' online purchase intention of movie tickets. The results of a PLS analysis demonstrated that both external and internal similarity significantly affected users’ perceived usefulness, enjoyment and trust transfer, which in turn exerted profound impacts on users’ social shopping behaviors. •We conduct this study from a new theoretical framework that incorporated similarities between user.•We re-conceptualize similarity by dividing similarity into two categories based on external and internal factors.•We provided a new theoretical explanation for how similarity affects user's decision-making processes.