Can location-based mobile promotion (LMP) trigger contemporaneous and delayed sales purchases? As mobile technologies can reach users anywhere and anytime, LMP becomes a promising new channel. We unravel the dynamic sales impact of LMP on the basis of a randomized field experiment with 22,000 mobile users sponsored by one of the largest mobile service providers in the world. Our identification strategy is to gauge the marginal increases in consumer purchases of the geo-fenced treatment group of users who received LMP, above and beyond the baseline control groups. There are two controls: one group who received the same LMP but not in the virtual geo-fencing locational range (nongeo-fenced control), and the other who did not receive the LMP but in the geo-fencing range (geo-fenced control). The latter control serves as an organic holdout baseline from the similar population, i.e., counterfactual test of what if without the mobile LMP intervention, to identify the actual ÒliftÓ of incremental purchases caused by the treatment with the mobile LMP intervention. Findings suggest that LMP treatment has a significantly stronger impact on contemporaneous (same-day) purchases and delayed (subsequent-days) purchases than the controls. The randomized experiment design renders these findings robust to alternative explanations such as mobile usage behavior heterogeneity, product effects heterogeneity, nonrandomized sample-selection bias, and endogeneity concerns. Follow-up surveys with the field experiment users explore the nuanced mechanisms via which LMP may induce the impulsive, same-day purchases, and create product awareness for the planned subsequent-days purchases. LMP can generate six times more purchases than nongeo-fenced control with the LMP intervention, and 12 times more than geo-fenced control without the LMP intervention. LMP has a delayed sales effect for 12 days after the mobile promotions. The total sales impact of LMP could be underestimated by 54% if excluding the delayed sales impact and only including the contemporaneous impact. These findings are new to the literature and often neglected in mobile promotion practices, proffering novel implications on the sales value of LMP in the mobile era.
Companies have increasingly advocated social media technologies to transform businesses and improve organizational performance. This study scrutinizes the predictive relationships between social media and firm equity value, the relative effects of social media metrics compared with conventional online behavioral metrics, and the dynamics of these relationships. The results derived from vector autoregressive models suggest that social media-based metrics (Web blogs and consumer ratings) are significant leading indicators of firm equity value. Interestingly, conventional online behavioral metrics (Google searches and Web traffic) are found to have a significant yet substantially weaker predictive relationship with firm equity value than social media metrics. We also find that social media has a faster predictive value, i.e., shorter "wear-in" time, than conventional online media. These findings are robust to a consistent set of volume-based measures (total blog posts, rating volume, total page views, and search intensity). Collectively, this study proffers new insights for senior executives with respect to firm equity valuations and the transformative power of social media.
Consumer buzz in the form of user-generated reviews, recommendations, and blogs signals that consumer attitude and advocacy can influence firm value. Web traffic also affects brand awareness and customer acquisition, and is a predictor of the performance of a firm's stock in the market. The information systems and accounting literature have treated buzz and traffic separately in studying their relationships with firm performance. We consider the interactions between buzz and traffic as well as competitive effects that have been overlooked heretofore. To study the relationship between user-initiated Web activities and firm performance, we collected a unique data set with metrics for consumer buzz, Web traffic, and firm value. We employed a vector autoregression with exogenous variables model that captures the evolution and interdependence between the time series of dependent variables. This model enables us to examine a series of questions that have been raised but not fully explored to date, such as dynamic effects, interaction effects, and market competition effects. Our results support the dynamic relationships of buzz and traffic with firm value as well as the related mediation effects of buzz and traffic. They also reveal significant market competition effects, including effects of both a firm's own and its rivals' buzz and traffic. The findings also provide insights for e-commerce managers regarding Web site design, customer relation management, and how to best respond to competitors' strategic moves.