Drawing on the rational addiction framework, this study explores the digital vulnerabilities driven by dependence on mobile social apps (e.g., social network sites and social games). Rational addicts anticipate the future consequences of their current behaviors and attempt to maximize utility from their intertemporal consumption choices. Conversely, myopic addicts tend toward immediate gratification and fail to fully recognize the future consequences of their current consumption. In lieu of conducting self-report surveys or aggregate-level demand estimation, this research examines addictive behaviors on the basis of consumption quantity at an individual level. To empirically validate rational addiction in the context of social app consumption, we collect and analyze 13-month, individual-level panel data on the weekly app usage of thousands of smartphone users. Results indicate that the average social app user conducts herself in a forward-looking manner and rationally adjusts consumption over time to derive optimal utility. The subgroup analysis, however, indicates that substantial variations in addictiveness and forward-looking propensities exist across demographically diverse groups. For example, addictive behaviors toward social network sites are more myopic in nature among older, less-educated, high-income groups. Additionally, the type of social app moderates the effects of demographic characteristics on the nature of addictive behaviors. We provide implications that policymakers can use to effectively manage mobile addiction problems, with the recommendations focusing on asymmetric social policies (e.g., information- and capacity-enhancing measures).

The implementation of digital channels as avenues for economic transactions (e.g., online and mobile banking/FinTech) has shifted the paradigm of customer–bank interactions, providing unprecedented opportunities for both parties. The prevailing belief is that digital banking has several advantages, such as lower costs and higher information transferability for customers. These benefits can also promote competition between banks given customers' predilection for “multi‐homing,” or engagement with multiple banks. This study investigated the impact of customers' digital banking adoption on hidden defection, in which customers purchase financial products from competing banks instead of their primary banks. To this end, we developed an analytical model to provide insights into the effects of digital banking adoption while taking customers' multi‐homing behaviors into consideration. We then conducted a series of empirical analyses using comprehensive individual‐level transaction data to provide evidence of hidden defection. Our findings indicate that customers with higher loyalty exhibit greater hidden defection after digital banking adoption. Customers who engage primarily with personal‐service channels (e.g., branches) show stronger hidden defection than do self‐service channel (e.g., ATMs) users, and this effect is more prevalent among loyal customers. Our results provide valuable implications for omni‐channel services in a market characterized by multi‐homing behavior of customers.

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Despite the average daily commuting time of commuters increasing by the day, the way marketers can benefit from our commuting behaviors has not yet been thoroughly examined.In collaboration with one of the largest global mobile service platform providers, this study investigates how contextual targeting with commuting is associated with responses to mobile coupons. The analysis is based on a field study in which 14,741 mobile coupons were sent to 9,928 public transit app users on commuting routes or routes other than commuting routes (i.e. commuters or non-commuters). The key findings indicate that commuters are about three times as likely to redeem their first mobile coupon compared to non-commuters. Further analyses allowing users to receive multiple coupons provide useful insight into an effective distribution strategy for mobile coupons. The findings suggest that enhanced receptiveness to mobile coupons is more perceivable when users obtain multiple coupons. Additionally, multiple-coupon distribution strategy increases response rates more effectively among non-commuters than commuters. Moreover, coupons with short expiration dates more successfully improve the response rates of commuters than do coupons with long expiration dates. For non-commuters, however, the reverse holds true; their response rates are higher for coupons with long expiration. Finally, commuters redeem coupons not only more frequently but also at a faster rate. Both dynamic and static matching methods are adopted to address possible selection biases. By carefully exploiting commuting, which is easily identifiable and occurs throughout the world, managers may improve their mobile marketing effectiveness.

Artificial intelligence (AI) is transforming healthcare operations. Nevertheless, particularly in the context of preventive care, little is known about how laypeople perceive and accept AI and change their behavior accordingly. Grounded in a solid theoretical framework of trust, this study bridges this gap by exploring individuals’ acceptance of AI‐based preventive health interventions and following health behavior change, which is critical for preventive care providers’ operational and business performance. Through a randomized field experiment with 15,000 users of a mobile health app complemented by a survey, we first show that the use and disclosure of AI in preventive health interventions improve their effectiveness. However, individuals are less likely to accept and achieve the health behavior change suggested by AI than when they receive similar interventions from health experts. We also observe that the effectiveness of AI‐based interventions can be improved by combining them with human expert opinions, increasing their algorithmic transparency, or emphasizing their genuine care and warmth. These results collectively suggest that, different from conventional technologies, AI's deficient affective trust, rather than comparable cognitive trust, play a decisive role in the acceptance of AI‐based preventive health interventions. This study sheds light on the literature on the role of new‐age information technologies in behavioral operations management, consumer marketing, and healthcare as well as the role of trust in technology acceptance. Valuable practical implications for more effective management of AI for preventive care operations and promotion of consumers’ health behavior are also provided.