Start Date
11-12-2016 12:00 AM
Description
Online deal communities where members can submit deals offered by firms and where they share information on discounted products are currently enjoying great popularity. However, studies on drivers of deal popularity in these communities are still scarce. Although deal popularity may be attributed to a large extent to the discount price, an extensive investigation of why some deals are voted more favorably than others is still lacking. Addressing this question by analyzing intrinsic and extrinsic deal quality signals, we advance knowledge in three ways. First, we enhance the understanding of the antecedents of human voting behavior in online deal communities building on signaling and social influence theory. Second, we improve the value of deal platforms by providing guidance on which factors determine the deal’s value to the community. Third, we provide a model to predict a minimum level of achievable deal popularity in the absence of community members’ votes.
Recommended Citation
Bergmeier, Markus; Ivanova, Olga; Totzek, Dirk; and Scholz, Michael, "What Makes a Hot Deal? Drivers of Deal Popularity in Online Deal Communities" (2016). ICIS 2016 Proceedings. 28.
https://aisel.aisnet.org/icis2016/HumanBehavior/Presentations/28
What Makes a Hot Deal? Drivers of Deal Popularity in Online Deal Communities
Online deal communities where members can submit deals offered by firms and where they share information on discounted products are currently enjoying great popularity. However, studies on drivers of deal popularity in these communities are still scarce. Although deal popularity may be attributed to a large extent to the discount price, an extensive investigation of why some deals are voted more favorably than others is still lacking. Addressing this question by analyzing intrinsic and extrinsic deal quality signals, we advance knowledge in three ways. First, we enhance the understanding of the antecedents of human voting behavior in online deal communities building on signaling and social influence theory. Second, we improve the value of deal platforms by providing guidance on which factors determine the deal’s value to the community. Third, we provide a model to predict a minimum level of achievable deal popularity in the absence of community members’ votes.