Anindya Ghose’s research while affiliated with New York University and other places

Firms have two distinct options when delivering content to consumers’ mobile devices: mobile push and mobile pull. Mobile push delivers firm-initiated (ad) content directly to consumers, while mobile pull requires consumers to initiate requests for (ad) content. This study tests the impact of mobile push and mobile pull on consumers’ coupon redemption behavior in a large-scale randomized field experiment in a geo-conquesting setting, targeting customers located around competitor retail stores with mobile coupons to drive them to stores of the focal retailer. The results show that mobile push increases coupon redemption rates by 6.0%, with substantial heterogeneity based on app-specific use experience and store density: App-specific use experience negatively moderates the effect of mobile push delivery on redemptions, likely because both usage experience and push notifications reduce app-specific search costs, thereby acting as substitutes for one another. In areas with higher store density, the positive effect of mobile push delivery on the redemption likelihood is greater, suggesting that push notifications can highlight the focal coupon among alternative store choices, thereby reducing consumer switching costs. These findings have important implications for retailers and brands in creating competitive mobile targeting campaigns that effectively leverage both mobile push and pull delivery mechanisms.

Digital tracing alerts (DTAs) have emerged as effective means to share information with agility in responding to disaster outbreaks. Governments are able to instantaneously coordinate the available information to provide information related to the disaster and promote preventive actions. However, despite the opportunities granted by these innovative technologies in managing disasters, privacy concerns can arise in regard to how much of individuals’ private information should be collected and disclosed. With these considerations, we examine the extent to which instant digital tracing alerts and the information included in the alerts affect people’s actions toward disaster management in the context of South Korea. Our results show that collecting and disclosing detailed private information is unnecessary and may instead diminish the effects of DTAs. The effect of digital alerts being more pronounced among young and male individuals and in business-centric areas. Furthermore, because the effectiveness of DTAs decreases with the cumulative number of DTAs received, governments should send alerts that include more urgent information that is directly related to the risk posed by a disaster. Our results provide policymakers and law enforcement with novel insights into whether and how the usage of information technology can facilitate disaster management and to what extent they should collect and expose private information to effectively safeguards public health and safety during a crisis. The fast and comprehensive implementation of DTAs in South Korea in response to the global outbreak offers other countries learning opportunities with respect to successful collaboration among parties involved in the development and design of DTA-related infrastructure and education. We emphasize that collaboration among central policymakers, local/municipal districts, telecommunications companies, and healthcare centers is essential to establishing an innovative IT-driven disaster management infrastructure and mechanisms that help inform citizens in taking desired actions in an emergency or disastrous events.

Through a randomized field experiment, this study compared the economic effects of two categories of nudges—self-assurance- and pressure-based interventions—on consumers’ purchase and return behaviors. In contrast to pressure-oriented nudges, such as quantity scarcity, time scarcity, and social persuasion, self-assurance nudges are intended to facilitate the “light” validation of product choice and characteristics of style or size and the self-assurance-grounded justification of purchase during shopping. The findings revealed that self-assurance nudges designed to help consumers make better choices have both short-term (high sales) and long-term (few product returns) benefits. Although pressure-driven nudges offer slightly higher short-term benefits (high sales), they eventually engender unfavorable long-term outcomes (high product returns) for consumers and online retailers. Finally, under return-adjusted net sales as performance measures, self-assurance-based nudges are as effective in stimulating purchase as those that capitalize on scarcity and social pressure.

In this paper, we examine the effectiveness of various recommendation strategies in the mobile channel and their impact on consumers' utility and demand levels for individual products. We find significant differences in effectiveness among various recommendation strategies. Interestingly, recommendation strategies that directly embed social proofs for the recommended alternatives outperform other recommendations. Besides, recommendation strategies combining social proofs with higher levels of induced awareness due to the prescribed temporal diversity have an even stronger effect on the mobile channel. In addition, we examine the heterogeneity of the demand effect across items, users, and contextual settings, further verifying empirically the aforementioned information and persuasion mechanisms and generating rich insights. We also facilitate the estimation of causal effects in the presence of endogeneity using machine-learning methods. Specifically, we develop novel econometric instruments that capture product differentiation (isolation) based on deep-learning models of user-generated reviews. Our empirical findings extend the current knowledge regarding the heterogeneous impact of recommender systems, reconcile contradictory prior results in the related literature, and have significant business implications.

The internet of things (IoT) is rapidly becoming one of the most popular emerging technologies in business and society. One of the major verticals that has recently begun to effectively use IoT technologies is the retail industry. Given the unprecedented opportunities IoT generates for brands and retailers, it is important to glean timely insights regarding the business value of IoT and understand whether the introduction of an IoT technology as an alternative purchase channel for consumers affects the sales of physical products. Using empirical data from a multinational online retailer who adopted an IoT technology that largely automates the consumers’ purchases and employing a quasi-experimental framework, we study the effect of the introduction of IoT as an alternative sales channel on product sales. Our analyses reveal a statistically and economically significant increase in sales and demonstrate the business value of the IoT channel for retailers and brands. In addition, we conduct other analyses of IoT to delve into the effect of heterogeneity and empirically validate the underlying mechanisms by examining the impact of IoT for products in different price ranges, levels of substitutability, and product categories. For instance, our analyses reveal that less expensive and more differentiated products, as well as experience and utilitarian goods, can accrue higher benefits leveraging more effectively novel IoT technologies. This is the first paper to study the impact of an IoT technology on product sales, drawing important implications for devices and technologies largely automating the purchase process.

Offline retailers increasingly use location-based coupons to target consumers in their vicinity in real-time. The rationale for the use of location-based coupons is that geographic proximity increases the relevance for consumers and, thus, the effectiveness of these campaigns. Two key interface-specific aspects of location-based coupon applications that influence their effectiveness are 1) the provision of distance information and 2) the distance-based ranking of coupons. The aim of this paper is to study and quantify the impact of these two key aspects of interface design on the effectiveness of location-based coupons. We conduct a randomized field experiment with 399,913 observations, including 3,499 different coupon promotions offered by 3,930 different stores located in 2,392 ZIP code areas in a large Western European country. Our results show that the most effective interface design for location-based coupons is based on a distance-based ranking. Furthermore, we find significant differences in the impact of distance and display rank based on the interface design and the actual geographic location of users. Our results thus contribute to the understanding of consumers’ behavioral responses to location-based advertising and provide important implications for the interface-design of location-based advertising applications.

In this study, we capture the trade-off between effective and annoying display advertising. We investigate both the enduring impact of display advertising on consumers' purchase decisions and the potential of persistent display advertising to stimulate annoyance in consumers. Additionally, we study the structural dynamics of these advertising effects by allowing them to be contingent on the latent state of the purchase funnel in which each consumer resides. The findings, based on the hidden Markov model that we propose, demonstrate that a tension exists between generating interest and triggering annoyance in consumers; whereas display advertising has an enduring impact on transitioning consumers farther down the purchase funnel, persistent display advertising exposures beyond a frequency threshold can have an adverse effect by increasing the chances that consumers will be annoyed. Investigating the dynamics of these annoyance effects, we reveal that consumers who reside in different stages of the purchase funnel exhibit considerably different tolerance for annoyance stimulation. Our findings also reveal that the format of display advertisements and the level of diversification of ad creatives as well as consumer demographics moderate consumers' thresholds for annoyance elicitation. For instance, advertisers can reduce annoyance elicitation as a result of frequent display advertising exposures when they diversify the display ad creatives shown to consumers as well as when they use static rather than animated display ads.