In the wake of the Black Lives Matter protests, numerous companies took action to advance racial equality. Several online platforms added a feature that identified “minority-owned” businesses to help users locate and, thus, support them. In this study, we investigate how reviews and ratings of restaurants in New York City change after being identified as Black-owned on an online platform. We find that the number of reviews increases, but the average rating decreases after restaurants are identified as Black-owned. We investigate how various contextual factors, such as the number of hate crimes where the restaurant is located and restaurant popularity, as well as reviewer characteristics, such as reviewer race and gender, impact this relationship. We also examine mechanisms that could be contributing to our findings. Collectively, and in contrast to the positive findings in other studies, our results reveal a possible unintended consequence of identity disclosure for minority-owned businesses. Findings from our study offer important implications for society, business owners, and online platforms.

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.

Online crowdfunding platforms have created new avenues for investors to finance existing businesses or new business ventures of project creators. Project creators who launch crowdfunding campaigns can provide progress updates to potential investors throughout the fundraising process, helping to alleviate potential investors’ uncertainty about the project’s success. However, limited attention has been given to the strategic decisions of project creators on when to provide campaign updates. In this study, we focus on the timing strategy of information disclosure and investigate the effectiveness of campaign updates at different timing and performance level. Using a dataset from a leading online crowdfunding platform, we find that updates are more effective at the earlier stage of a crowdfunding campaign in attracting investors, and they play a different role depending on the project’s fundraising performance. For underperforming campaigns, the effectiveness of updates is more salient at the early stage of the campaign, whereas we find no differential impact at the later stage. By employing text analyses on the project descriptions and updates, we also derive insights about how the content of updates impacts their effectiveness at different stages of the campaign. Finally, our results also show that the timing of updates is more important for less experienced project creators, whereas the content of updates is more important for experienced project creators. These results provide important insights for project creators to strategically manage their campaigns in online crowdfunding platforms.

Research at the interface of operations management (OM) and gender bias has mostly focused on operational outcomes such as hiring decisions on behalf of the employer (or firm). Largely overlooked is how the design of operational processes exacerbates (or diminishes) the amount of gender bias exhibited on behalf of the customer in a people‐centric operations environment. In this study, we conduct a randomized field experiment with a partner firm to assess gender mismatch and bias in client‐consultant exchanges. The experimental design enables us to examine gender bias within dyadic exchanges when there are gender matches (female client‐female consultant or male client‐male consultant) or gender mismatches (female client‐male consultant or male client‐female consultant). We find that reporting the consultant's gender significantly increases the client's likelihood of leaving more and higher reviews, increases the clickthrough rate on recommended products, and that the effect is stronger for females than for male consultants. We also provide support for the heterogenous effects of client experience depending on the gender (mis)match in client‐consultant exchanges, including whether the prior effects hold when there is gender masking or manipulation (e.g., reported female consultant when actually male). Our findings offer important theoretical contributions and practical implications for OM scholars and managers.

The majority of recent empirical papers in operations management (OM) employ observational data to investigate the causal effects of a treatment, such as program or policy adoption. However, as observational data lacks the benefit of random treatment assignment, estimating causal effects poses challenges. In the specific scenario where one can reasonably assume that all confounding factors are observed-referred to as selection on observables-matching methods and synthetic controls can assist researchers to replicate a randomized experiment, the most desirable setting for drawing causal inferences. In this paper, we first present an overview of matching methods and their utilization in the OM literature. Subsequently, we establish the framework and provide pragmatic guidance for propensity score matching and coarsened exact matching, which have garnered considerable attention in recent OM studies. Following this, we conduct a comprehensive simulation study that compares diverse matching algorithms across various scenarios, providing practical insights derived from our findings. Finally, we discuss synthetic controls, a method that offers unique advantages over matching techniques in specific scenarios and is expected to become even more popular in the OM field in the near future. We hope that this paper will serve as a catalyst for promoting a more rigorous application of matching and synthetic control methodologies.

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Despite the extensive research on healthcare operations, a need remains for a deeper understanding of how to design and deploy new technologies to achieve efficiency, particularly concerning health-promoting behavior. Health-promoting behavior, driven by intrinsic motivations, often exhibits reduced efficacy as motivational impetus wanes over time. Despite the prevalence of various health interventions, there has been limited exploration of their efficacy within real-time motivation schemes. This study posits that real-time interventions grounded in social influence significantly impact users’ physical performance. In collaboration with a running app service platform, we examine how real-time voice-based interventions based on social facilitation influence users’ physical performance. Our key findings indicate that the recognition of communal exercise and the receipt of vocal encouragement in real time enhance users’ running performance. Notably, we observe a synergistic effect of these factors, particularly when a female supporter is involved. Additionally, we find heterogeneous effects based on the recipient’s gender, user performance, intervention timing, and running state. We also highlight that our intervention elicited a spillover effect on social interactions within the app. These findings have significant implications for the development of real-time interventions, accentuating the importance of social influence in enhancing health-promoting behavior.

Although digitalization is a prevalent strategy in reward programs, a minimal amount is known regarding the relationship between reward app usage and reward redemption behaviors. The enhanced availability and accessibility of information via mobile app can alter customers' reward-redemption patterns and engagement level, highlighting the need for firms to adjust their reward-based service strategies. Using unique datasets that reflect individual consumers' transactional and reward redemption behaviors, we conducted a series of analyses to capture the dynamics in the latent engagement state transitions of customers according to the type of reward program used. Results show that although reward app usage, on average, induces a more active engagement state, it polarizes the volatility of engagement state transitions. Furthermore, we find that greater volatility of engagement state transitions is significantly associated with a higher likelihood of churn. Finally, a follow-up survey and panel vector autoregression analyses are conducted to uncover the mechanisms that underlie the relationship. The results provide insights into how retailers can strategically design their reward programs in the emerging mobile-based omnichannel environment.

Influencer Commerce (I-Commerce) is an emerging business model in which influencer-generated content is embedded directly into e-commerce settings, allowing consumers to move seamlessly from endorsement exposure to purchase within a single platform. Despite its rapid growth, firms continue to struggle with how to utilize influencers effectively, particularly given the widespread reliance on follower count as a proxy for their influence. This study examines how an influencer’s follower count shapes consumer behavior across the purchase funnel in an I-Commerce context. Drawing on social influence theory, social norms theory, and social support theory, we develop a framework underscoring how the same popularity cue can activate different psychological mechanisms at distinct stages of the funnel. Using proprietary data from a leading I-Commerce platform that track consumer impressions, clicks, and purchases, we estimate a two-stage bivariate probit model with an instrumental variable approach to address endogeneity in follower count. We further validate our findings through a randomized field experiment. Our results reveal a systematic asymmetry. Influencers with larger follower bases are more effective at capturing consumer attention, significantly increasing click-through likelihood. However, conditional on clicking, these same influencers are less effective at converting attention into purchases. Additional analyses show that this conversion disadvantage is mitigated by the presence of strong consumer reviews, underscoring a complementary relationship between influencer popularity and crowd-generated information. Content-level analyses further indicate that influencers with smaller follower bases benefit more from informative and product-focused messaging, whereas emotionally resonant content amplifies the attention advantage of high-followership influencers. This study contributes to the digital commerce literatures by demonstrating that influencer popularity has stage-specific and asymmetric economic effects. Our findings offer actionable insights for firms seeking to optimize influencer strategies and allocation across the purchase funnel in I-Commerce settings.

The COVID-19 pandemic forced organizations, including higher education institutions, to rapidly adjust their operations. In the face of the pandemic, most higher education institutions shut down their campuses and transitioned to emergency remote teaching mode. This study examines digital resilience in higher education institutions through the conceptual lens of disaster response management, by assessing the role played by the centralized governance of information technology (IT) investments. We posit that centralized IT helps organizations maintain customer satisfaction with services during a crisis (e.g., student satisfaction with classes during COVID-19) by facilitating the organization-wide transition to an emergency operational mode and supporting its service operations. Consolidating data on IT investment, governance, and course evaluations from 463 U.S. higher education institutions from 2017-2020, we show that centralized IT helped organizations adapt better to the pandemic in terms of maintaining student satisfaction. Moreover, we found that centralized IT investments geared toward facilitating organizational coordination and providing instructional and technical support played a pivotal role in enabling ERT and improving student ratings during the crisis. These results are corroborated by interviews with CIOs of U.S. higher education institutions. Additional analyses also suggest that the effectiveness of centralized IT governance is contingent upon organizational size, dissimilarity of local units, and the strategic role of the CIO. We also discuss theoretical extensions toward digital resilience as well as practical implications.

The present study investigates the effects of smart speaker usage on consumers’ digital content search, purchase, and consumption behaviors. Using a unique panel data set comprising information on household patterns of digital content (e.g., video on demand [VOD]) transactions and consumption and smart speaker usage, we found that the adoption of smart speakers is positively associated with the increased purchase of digital content but negatively related to the average rate of content completion. More specifically, we found that VOD content-related expenditures increased by 21.5% following smart speaker adoption but the average consumption of VOD content purchased decreased by 3.0%. We also examined millions of data points on TV remote-control use and conducted a survey via MTurk to support the validity of the findings. Smart speaker usage can reduce search costs, which subsequently increases search incidence and conversion rates, behavioral changes that can lead to a rise in purchases. We further show that the use of smart speakers for purposes other than information seeking is positively associated with purchases. We develop insights on how to elicit economic value from voice recognition technologies and provide implications for the design and implementation of effective voice commerce strategies.

Leveraging omnichannel has become a new norm of strategic marketing in the retail industry, with many vendors foregrounding the value of customers who wish to maximize their shopping experiences across all channels. Notwithstanding such heightened attention, little is known about the effectiveness of omnichannel targeting and promotional strategies. Whereas previous studies assessed the economic worth of channel promotions independently of each other, our study delved into the effects of integrated omnichannel campaigns. Using a randomized field experiment design, we provide empirical evidence of an offline direct experience effect and revealed short-term channel substitution (spillover) effects among customers who only use the online-channel (offline-channel). We further examined omnichannel conversion behaviors after exposure to online promotion and developed different coupon schemes based on responses to the previously offered offline initiative. Finally, we detected significant patterns of post-treatment omnichannel migration and confirmed the effectiveness of integrated omnichannel promotions in fostering a shift to omnichannel shopping.

This research investigates how a shift from traditional loyalty cards to mobile-driven loyalty apps affects consumers’ reward redemption patterns, purchase behaviors, and store-level competition. The findings indicate that loyalty app adoption is associated with increased expenditure and purchase frequency as well as more active point redemption. In a multivendor loyalty program (MVLP) context, the use of loyalty apps is associated with spillover effects in which case customers visit more stores that they had not previously considered and exhibit diminished allegiance to their focal shop after they adopt a loyalty app. Finally, the adoption of loyalty apps is related to deal-prone behaviors because informed consumers tend to selectively purchase highly discounted products. Our findings provide several valuable implications for managers and platform owners who are considering launching mobile loyalty programs (LPs) and participating in an MVLP market. Although the merits of loyalty app adoption are apparent, we caution against potential downsides at individual store levels. Many customers are likely to succumb to deals, selectively purchasing highly discounted products with low margins through loyalty apps. The thrust of LPs should be directed toward fostering a strong connection with a brand, going beyond the promise of deals and promotions.

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.

Customer reward systems have rapidly shifted from plastic cards schemes to mobile application-based initiatives, yet our understanding of the economic value of mobile reward systems has not kept pace with this development. Using an individual-level transaction and reward redemption dataset from a large multi-brand, offline food-andbeverage merchandiser, we examine the effects of reward app adoption on customers’ offline purchase patterns and reward redemption behaviors by using a difference-indifference method with propensity score matching. An intriguing empirical issue is whether consumers redeem their reward points more aggressively and spend more out of pocket after adopting reward apps. Our results lend support to this argument. App engagement, which is measured by the frequency at which reward apps are activated, is positively associated with increasing cash expenditure and number of points redeemed. Furthermore, our findings imply that past reward point redemption increases the level of goodwill stock, which affects future cash expenditure.