Selected Publications
Targeted Advertising as Implicit Recommendation: Strategic Mistargeting and Personal Data Opt-Out
( Z. Eddie Ning | Jiwoong Shin | Jungju Yu )MARKETING SCIENCEforthcoming
Abstract
We study an advertiser’s targeting strategy and its effects on consumer data privacy choices, both of which determine the advertiser’s targeting accuracy. Targeted ads, serving as implicit recommendations when consumer preferences are uncertain, not only influence the consumer’s beliefs and purchasing decisions but also amplify the advertiser’s temptation towards strategic mistargeting—sending ads to poorly matched consumers. Our analysis reveals that advertisers may, paradoxically, choose less precise targeting as accuracy improves. Even if prediction is perfect, the advertiser still targets the wrong consumers, leading to strategic mistargeting. Nev-ertheless, consumer surplus can remain positive due to improved identification of well-matched consumers, thereby reducing the incentive for consumers to withhold information. However, the scenario shifts with endogenous pricing; better prediction leads to more precise targeting, although mistargeting persists. To exploit the recommendation effect of advertising, the ad-vertiser raises prices instead of diluting recommendation power, lowering consumer welfare and prompting consumers to opt out of data collection. Furthermore, we investigate the impact of consumer data opt-out decisions under varying privacy policy defaults (opt-in vs. opt-out). These decisions significantly affect equilibrium outcomes, influencing both the advertiser’s tar-geting strategies and consumer welfare. Our findings highlight the complex relationship between targeting accuracy, privacy choices, and advertisers’ incentives.
Physical Friction and Digital Banking Adoption
( Choi, Hyun-Soo | Loh, Roger )MANAGEMENT SCIENCEforthcoming
Abstract
The behavioral literature suggests that minor frictions can elicit desirable behavior without obvious coercion. Using closures of ATMs in a densely populated city as an instrument for small frictions to physical banking access, we find that customers affected by ATM closures increase their usage of the bank’s digital platform. Other spillover effects of this adoption of financial technology include increases in point-of-sale transactions, electronic fund transfers, automatic bill payments, and savings, and a reduction in cash usage. Our results show that minor frictions can help overcome the status quo bias and facilitate significant behavior change
Contextual Targeting in mHealth Apps: Harnessing Weather Information and Message Framing to Increase Physical Activity
( Kyung, Nakyung | Chan, Jason | Lim, Sanghee | Lee, Byungtae )INFORMATION SYSTEMS RESEARCHforthcoming
Abstract
This paper addresses how real-time weather information acquired through mobile technology can be leveraged to enhance the efficacy of mobile interventions for spurring users' healthier behaviors. Through a field experiment that each participant experience different weather conditions in two different treatment periods under the gain or loss interventions, we found that the effects of gain or loss interventions across sunny and cloudy weather are not uniformly distributed. Loss intervention induces higher levels of fulfillment of exercise goals than gain intervention in sunny weather, whereas gain interventions are more effective than loss interventions in cloudy weather. We also provided empirical evidence to uncover the underlying mechanisms and rules out alternative explanations. The follow-up experiment reveals that weather-based intervention can be used repeatedly over time without losing its effectiveness. Moreover, our result suggests that the observed effect is more evident for people with a lower exercise level and living in areas of lower income. Our study provides theoretical guidance and practical implications for academics, healthcare businesses, and policymakers on the strategy of using weather based messaging for enhancing physical activity levels.
Inter-Unit Executive Redeployment in Multiunit Firms: Evidence from Korean Business Groups
( Chang, Sea-Jin | Kim, Young-Choon | Park, Sangchan )ORGANIZATION SCIENCEforthcoming
Abstract
Building on the literature on resource reconfiguration theory, we formulate a new theoretical framework that explains how executive redeployment within a diversified firm transfers different types of human capital embodied in executives to different units facing specific business challenges. In the empirical context of Korean business groups, we find that executives with unit-specific human capital, like turnaround experience, competitive experience, and international expansion experience, are redeployed to units with corresponding business challenges like financial difficulties, intensifying competition, and early-stage international expansion, respectively. We also show that executives with unit-generic human capital, like corporate management practices and interunit coordination experiences, are redeployed to younger units seeking to establish corporate-level policies and practices. Additional analyses also show that the value of firm-specific human capital in driving the redeployment of executives is contingent on their functional orientation and seniority.
Optimal influence design in networks
( Jeong, Daeyoung | Shin, Euncheol )Journal of Economic Theory2024-09
Abstract
We examine an influence designer's optimal intervention in the presence of social learning in a network. Before learning begins, the designer alters initial opinions of agents within the network to shift their ultimate opinions to be as close as possible to the target opinions. By decomposing the influence matrix, which summarizes the learning structure, we transform the designer's problem into one with an orthogonal basis. This transformation allows us to characterize optimal interventions under complete information. We also demonstrate that even in cases where the designer has incomplete information about the network structure, the designer can still design an asymptotically optimal intervention in a large network. Finally, we provide examples and extensions, including repeated social learning and competition.
