Journal
INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE
Volume 22, Issue 1, Pages 36-65Publisher
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/10864415.2018.1396118
Keywords
Bootstrap; difference-in-differences; Foursquare; location-based advertisement; location-based social networks; modeling; social media
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Location has been identified as a critical factor for the success of a business. For example, businesses in dense urban areas are exposed to more customers than businesses in sparsely populated neighborhoods, while proximity to a popular landmark can increase a business's reach. This creates significant challenges for new businesses to expand their reach and customer base. However, the advancement of mobile, social, and spatial computing has led to the transformation of traditional web-based yellow pages to a mobile format (e.g., location-based social networks; LBSNs). This has allowed businesses that are not in prime locations to become visible to nearby customers. Furthermore, these platforms offer mechanisms that can serve as an affordable advertisement channel to local businesses. Specifically, a business can use LBSNs to promote special offers to customers who connect through the platform. Despite the promising anecdotal evidence, a systematic study of the effectiveness of this LBSN advertising paradigm has not yet been conducted. Using a large time-series data set of approximately 14 million venues in Foursquare, the largest LBSN to date, our work is the first to formally examine the effects of promotions through the platform. Our contribution is twofold. First, we identify no significant and robust evidence that can support the hypothesis of effective promotions for the specific platform. In particular, our main finding is that the probability of observing an increase in daily check-ins or new daily customers to a venue is rarely altered by the presence of a Foursquare promotion. Second, this finding motivates us to design a model that can predict the success of a promotion according to various relevant features. Our model can be used to inform the process of designing and launching successful promotions by evaluating the potential of candidate promotions before their actual release. The practical value of such prelaunch evaluations is elevated by the apparent scarcity of successful promotions, as revealed by our analysis.
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