A robust finding documented in the literature is the post-return sales lift. We draw on emerging research that conceptualizes return incidence as contributing to a return stock variable, thereby enhancing consumer memory of the availability of this option. Against this backdrop, we investigate the post-return sales lift via two theoretical lenses: (i) risk- reduction, and (ii) locus of attribution. In our analysis of matched consumers at a South Korean grocery retailer, we find a substantial increase in spending following return incidence. Supporting risk-reduction, this increase is more pronounced for consumers with greater variety-seeking tendencies and smaller basket sizes, suggesting that heightened memory of the return option increases consumer willingness to explore new products and expand their purchases. Supporting attribution, this increase is attenuated when the return includes perishable food items and the holding time of the product(s) in the consumer’s home is shorter. In these cases, we conjecture that consumers attribute responsibility to the retailer, thereby weakening the post-return sales lift. Interestingly, we find carry-over effects for the stock associated with the first return. However, multiple returns suggest an implied negative accumulation. Overall, our conceptualization and empirical findings add to our understanding of the post-return sales lift.
As influencers increasingly serve as frontline salespeople, consumers’ perceptions of influencer expertise emerge as a key factor shaping influencers’ sales effectiveness; yet, few studies have explored the sales effect of perceived expertise using video data from social media retailing. To fill this gap, we develop a multistudy framework. In Study 1, we introduce a predictive AI model, the Memory Fusion Network (MFN), to measure influencers’ perceived expertise with 2728 livestreaming videos, achieving an accuracy of 91.75%. then, we introduce explainable AI, eXtreme Gradient Boosting (XGBoost) and Shapley Additive Explanations (SHAP), to open the black box of MFN. The results indicate that eye gaze (image), speech rate (audio), and expertise language (text) are the most predictive indicators of perceived expertise. In Study 2, using TikTok sales data, we explore the positive correlation of perceived expertise and actual sales; and further demonstrate the mediating role of competence-based trust. In Study 3, to provide causal evidence, we use generative AI tools to generate video stimuli, and then conduct a preregistered randomized online experiment. The results corroborate findings of Study 2. In Study 4, to explore the boundary conditions, we examine a series of theoretically and practically relevant moderators. The results indicate that the sales effect of perceived expertise is more pronounced for bottom influencers (vs. top influencers), high price-tier products (vs. low price-tier products), and non-official stores (vs. official stores). These findings offer actionable insights for retailers on how to leverage text, audio, and image signals to enhance influencers’ perceived expertise and drive actual sales.
Social media platforms and influencer culture have fundamentally transformed retail exchange, yet their implications for buyer-seller relationships remain undertheorized. Existing research primarily positions influencers as promotional intermediaries who generate awareness and affinity on behalf of retailers. We argue that this framing overlooks a broader transformation already underway in digital retailing, in which influencer culture reorganizes how retail exchange is structured, enacted, and sustained across social media environments. Drawing on parasocial and affordance theories, we conduct a netnography of 32 independent sellers operating on TikTok and Instagram within a global direct selling organization. Our findings identify three interrelated transformations in buyer-seller relationships. First, functional transformations shift market knowledge from firm-directed and prescriptive to relationally generated through continuous platform engagement. Second, interactive transformations reorganize buyer-seller interaction from episodic encounters into persistent, cross-platform relational journeys sustained through transparasocial intimacy. Third, performative transformations embed retail exchange within ongoing identity performance, where authenticity functions as a sales technology. Together, these transformations reveal a structurally distinct retail format that we conceptualize as influselling: a digital retail format in which transparasocially constituted buyer-seller relationships function as the primary mechanism of exchange.
While most customer service interactions are civil in nature, retail frontline employees (FLEs) often face customers who behave in unfriendly, insulting, or disrespectful ways, which can harm FLEs and the organization. Prior research typically treats such incivility as an inherently harmful hindrance stressor with uniformly negative consequences. Drawing on the transactional theory of stress, we reconceptualize customer incivility as a dual stressor that can be appraised as either a challenge or a hindrance. Using multisource data from 241 FLEs, 34 supervisors, and archival performance records of a large retail banking chain, we find that when FLEs view customer incivility as a challenge it enhances proactive work behavior, which then positively influences FLE performance. In contrast, when FLEs view customer incivility as a hindrance, it increases counterproductive work behavior, which negatively influences FLE performance. Thus, the same uncivil customer behavior can elicit different behavioral and performance consequences depending on how it is appraised by an FLE. Moreover, by integrating conservation of resources theory, we show that internal psychological resources (such as empathy and grit) and external organizational resources (such as employee bonuses) moderate how appraisal tendencies translate into proactive versus counterproductive work behavior.
Luxury products provide consumers not only with functional value but also with social status utility. An increasing number of consumers knowingly purchase non-deceptive copycat luxury products to obtain similar status benefits at lower prices, while observers often cannot distinguish genuine purchases from copycats due to information asymmetry. In response, luxury brands may strategically disclose quality information to differentiate themselves from copycats and shape social recognition. This paper develops a game-theoretic model of status-driven quality disclosure in which a luxury brand competes with a non-deceptive copycat. We examine how copycat competition and consumer status preferences jointly affect firms’ disclosure strategies, profits, and welfare outcomes. Our analysis yields several key findings. First, in contrast to monopoly settings, copycat competition induces luxury brands to adopt a status-driven partial disclosure strategy. Second, the luxury brand’s profit exhibits a U-shaped relationship with consumer status preference: profits initially decline as status dilution dominates under non-disclosure, but subsequently increase once disclosure becomes sufficiently valuable to restore exclusivity. This result highlights that stronger status-seeking may initially disadvantage luxury brands while benefiting copycats. Third, higher consumer status preference may reduce consumer surplus while increasing overall social welfare, reflecting a trade-off between surplus appropriation and improved market differentiation. These findings underscore the distinctive role of endogenous quality disclosure in luxury markets and offer implications for managers and policymakers seeking to balance transparency, brand exclusivity, and welfare in the presence of non-deceptive copycat competition.
Most negative incidents facing retail brands dissipate without consequence, so a critical challenge is predicting which ones escalate into crises with reputational and financial repercussions. We address this challenge by tracking how stakeholder reactions unfold across traditional media, social media, and consumer mindset metrics surrounding 510 retail incidents. Using dynamic time warping, we identify 11 distinct trajectory types, i.e. recurring temporal patterns in stakeholder responses, and show that they predict whether an incident reduces retailer firm value. Incidents escalate into crises when an immediate negative media frame for an incident coincides with deteriorating retailer reputation and social media amplification. When these adverse signals align, cumulative abnormal returns become consistently negative. In contrast, incidents following gradual or mixed media trajectories typically dissipate without financial harm, even when aggregate media volume is high. The temporal shape of stakeholder reactions, rather than their aggregate volume, determines crisis outcomes. Moreover, retailer communication timing matters more than volume: restrained, early communication can shape developing narratives, whereas heavy reactive communication is associated with stock market losses. Our trajectory-based framework equips managers with actionable early-warning signals to distinguish routine negativity from high-risk events and calibrate response strategies accordingly.
Global macro-events, such as pandemics, inflation, economic recessions, technological breakthroughs like GenAI, trade wars, and political conflicts, can disrupt the retail industry by increasing risks, altering financial outcomes, and straining supply chains. Such disruptions force retailers to reconfigure their operations. For example, the COVID-19 pandemic led to the rapid launch of e-commerce platforms, contactless payments, and curbside pickups. Likewise, the sharp rise in global inflation from 1.9% to 8.8% between the third quarters of 2020 and 2022 compelled retailers to seek lower-cost suppliers and adjust pricing and return policies to retain customer loyalty. Despite the significant impact of macro-events, existing literature often examines them in isolation, without a comprehensive framework that explains how event characteristics influence retailers' risk perceptions and induce retailer business model innovations (RBMIs). This research fills that gap by developing a conceptual framework grounded in Event System Theory (EST). It categorizes macro-events through three independent dimensions, event strength, event space, and event time, and introduces business risk perceptions as a mediating mechanism, explaining how retailers interpret these events and assess their impact on business models through demand-side and operations-side risk perceptions. Retailers' event-sensing and event-response capabilities further shape these risk perceptions, amplifying their influence on RBMI. Through a text analysis of 10-K reports, the authors provide initial plausibility evidence for how retailers express risks differently across economic, technological, and political dimensions in response to macro-events. The framework advances understanding of how macro-events shape risk perceptions and, in turn, RBMI, offering insights for retailers seeking to build resilience and adaptability in an increasingly volatile global environment.
Many retail areas are in a “vicious circle” of declining retail area visits and store closures. Cities try to mitigate this negative development through interventions that revitalize retail areas, one of which is events. This study examines whether and which events can have a positive incremental (or: net) effect on retail area visits. Specifically, it explores which event characteristics and event timing increase retail area visits most. An analysis of panel data from events in two cities against synthetic control groups shows that events have a positive effect on retail area visits during the event (+5.9% visitor increase), without a negative pre/post cannibalization of visits. The positive effect of events is contingent on event characteristics and timing: Retail events (+22.2%, vs. non-retail events) exacerbate the positive effect on visits, while longer events diminish it. However, the event-driven increase in visits to a retail area might be redistributive, coming at the cost of visits to neighboring city retail areas, which creates potential trade-offs for event organizers. These findings can help policymakers and retailers as empirical benchmarks for event effectiveness, as events come at a substantial cost.
Digital Native Vertical Brands (DNVBs) are born-online retailers that sell directly to consumers, with a value proposition focused on customer experience (CX). DNVBs have emerged as a distinct force in the retail landscape. DNVBs emphasize a system-level retail logic that incumbent retail formats struggle to replicate. Yet they remain undertheorized in marketing. Applying a variation–selection–retention (VSR) lens, we offer an integrated account of their emergence, architecture, and persistence. Drawing on prior literature and illustrative secondary sources, we propose that DNVBs arose as retail variants generated through entrepreneurial responses to unmet customer needs for seamless, personalized, and ethically grounded CX and simultaneous environmental factors, including market opportunities, economic pressures, and off-the-shelf enabling technologies. We conceptualize DNVBs as a new retail form that emerges from entrepreneurial sensemaking, featuring a distinctive retail architecture and producing widespread effects on incumbent brick-and-mortar retailing. We describe DNVBs’ retail architecture as an orchestrated portfolio of brand experience traits (empathic product design, brand coolness, brand authenticity) and service experience traits (service convenience, service control, service connectivity). We explain DNVB form persistence via diffusion, hybridization, adaptation, and convergence, following which we identify the resultant tensions for DNVBs and incumbent retailers. The research generates actionable guidance for DNVBs, platforms, and incumbents seeking distinctiveness at scale.
Retailers increasingly adopt temporary loyalty programs (TLPs). While the success of such promotional campaigns hinges on their proper execution of in-store support, industry reports suggest that commitment to execution standards is often poor. Our study sheds light on the magnitude and drivers of execution shortfalls in TLPs, and on the impact that these have on store sales. We use a unique dataset that tracks in-store execution during a TLP and create a panel dataset with sales data before, during and after the program. We show that poor execution of in-store promotional instruments (signage, displays, staff support, and reward availability) is ubiquitous, and uncover its link with demand-intensity and operational factors that drive store engagement. We also document the pattern of sales losses from execution shortfalls, across instruments and stores, and illustrate that poor execution affects reward redemption in the TLP. Our results can guide retailers and external parties in optimizing the sales effectiveness of in-store promotional execution.
Loyalty programs (LPs) are widely used to manage customer relationships, but evidence on their effectiveness remains mixed. We argue that LP effectiveness should be understood across the recurring customer journey rather than as a single aggregate effect. We meta-analyze 434 effect sizes from 78 independent samples comparing LP members and nonmembers; classify outcomes into pre-purchase, purchase, and post-purchase stages; and test LP design characteristics and product types as moderators. Results show that LP membership is positively associated with outcomes across all three stages, with the strongest integrated effect in the purchase stage. Moderator analyses further indicate that LP effectiveness is stage-specific and depends on both program design and product type. These findings extend LP research by showing that mixed evidence on LP effectiveness partly reflects differences regarding where outcomes occur in the customer journey and under which conditions LP membership effects are assessed. For retailers, the results suggest that LPs should be designed around stage-specific objectives rather than treated as uniform incentive systems.
This study investigates how retail frontline employees (FLEs) appraise their jobs (e.g., customer interactions) and explores the factors that shape these appraisals, ultimately influencing FLE outcomes. We propose that (1) FLEs perceive their job tasks in both positive and negative ways—namely, as challenge and hindrance appraisals, respectively; (2) these two types of appraisals interact with perspective-taking (a personal factor) and performance pressure (a situational factor) to differentially influence learning from customers and depersonalization. Specifically, perspective-taking negatively (positively) moderates the positive relationship between challenge (hindrance) appraisals and learning from customers (depersonalization), whereas performance pressure moderates these relationships in the opposite direction—a counterintuitive result that challenges common assumptions but aligns with theoretical predictions; and (3) these interaction effects indirectly influence FLE service performance through two parallel mediating paths: learning from customers and depersonalization. Using a mixed-methods design, we combine experimental studies (Preliminary Studies One and Two) with a multi-source, multi-wave field survey to test the proposed relationships. These findings highlight routes for managers to enhance the positive, and mitigate the negative, effects of FLEs’ job appraisals resulting in improved service performance.
The current research focuses on the overlooked spillover implications of brand collaboration on downstream consumer decisions. The authors propose that brand collaborations create a broader consumer mindset, which can inadvertently encourage choices beyond the brand franchise. The authors identify collectionist behavior (i.e., the tendency to collect items from specific product lines) and time-induced construal level as moderators of this unintended negative downside effect. A retail field study and five laboratory experiments provide evidence for the effect, the underlying mindset mediator and the moderating conditions. We recommend that retailers and brand owners assess both positive and negative outcomes of brand collaborations for their business and brands. Finally, we call for further research to examine the consequences of brand collaborations on the entire brand franchise, beyond their immediate effects on brand-collaboration products.
Literature on reference prices suggests that consumers carry a reference price for a brand in their memory, which they use to evaluate brands when making purchases. Further, research has shown that consumers respond more to losses (prices that are higher than reference prices) than to gains (lower prices). Many reference price models have been estimated using household purchase data in several product categories. A notable omission is that even though the reference price is an individual level construct, models have been estimated at the household level. In this study we examine whether an individual level reference price model for each member within a household provides different estimates and insights than the household level model. We seek to understand the magnitude of bias in the parameters of a brand choice model if one estimates the model at a household level. Further, we assess how firms will vary their targeted promotions if they use individual level estimates and how it affects their profits.We use a unique data set that identifies brand choices made by individual customers within a household to answer the above questions. We estimate two different reference price models using a random coefficients multinomial logit specification in three different product categories. Since frequent buyers are expected to have well-formed reference prices relative to infrequent buyers, we focus on the difference between these two groups. We find that customer level estimates are significantly different from those obtained at the household level and that frequent buyers are more price sensitive and respond differently to reference prices than infrequent buyers within the same household. We show that using individual customer level estimates to target households with a promotion, results in significantly higher profits and that ignoring reference price effects can lead to significantly reduced profits.
This paper explores how fluctuations in real estate values affect changes in the physical retail space and the number of retail stores. Higher property prices increase operating costs for physical stores -return on investment (ROI) effect- but simultaneously boost the collateral values of properties owned by retailers – collateral effect-, easing credit constraints and encouraging investment. Using data for 54 countries, we find that higher real estate price growth is associated with stronger expansion in both total retail space and the number of retail stores, indicating that the collateral effect dominates the return-on-investment effect. The strength of this relationship varies with the level of digital and financial development and the extent of price controls in the retail sector. Despite the rapid expansion of online channels, our findings suggest that physical stores continue to play a key role, particularly in environments where investment is financed through collateralized credit. County-level evidence from the United States supports these findings, showing that real estate prices have a stronger impact on retailers that rely primarily on physical locations than on those that have the flexibility to operate through online channels along with physical locations.
Addressing customers by name is widely promoted as a best practice in frontline service, yet its true impact on customer experiences, the psychological mechanisms underlying it, and boundary conditions remain insufficiently understood. Using a real-world field experiment capturing actual sales and upselling behavior and three online experiments, we systematically examine employee-initiated name usage as a frontline interpersonal influence tactic, its key linguistic (frequency, placement) and contextual (neutral vs. embarrassing) boundary conditions, and the psychological processes that may underlie its effects. Our findings reveal a clear duality: while employees addressing customers by name can enhance satisfaction and drive upselling effectiveness, this same practice can diminish satisfaction when overused, misused, or applied in embarrassing contexts. Further, a dual‑process mechanism emerges: rapport explains when name usage improves outcomes, whereas discomfort explains when it backfires. Taken together, this research offers new insights into the dynamics of name‑based personalization in service, conceptualizing employee‑initiated name usage as a specific personalization‑based influence tactic that carries both interpersonal benefits and potential unintended negative consequences for customers and firms.
Marketing scholarship in the retailing domain can play an important role in advancing environmentally sustainable consumption and production. We synthesize prior research across marketing and related fields and introduce a novel two-stage framework that examines sustainability interventions through the lens of retail actor interactions. The framework characterizes how different actors (e.g., consumers, retailers, manufacturers, regulators) influence one another and evaluates interventions based on their feasibility and environmental impact. Although marketing has contributed to unsustainable consumption patterns, we argue that it holds significant potential to accelerate the transition toward environmental sustainability. Retail emerges not only as a context in which sustainability challenges manifest, but as a strategic domain where coordinated action can drive transformative change. Our framework offers a structured approach to mapping interventions, assessing their effectiveness, and understanding the mechanisms that link the interventions to their effectiveness. It helps stakeholders identify the most promising strategies to foster environmentally sustainable behavior and manage interactions across the retail ecosystem. The framework informs marketing scholars by highlighting research gaps, by revealing barriers that limit the effectiveness of current interventions, and by pointing to opportunities to adapt successful approaches across actors to better support sustainability goals.
Digital innovations in retail environments can significantly influence product choices and consumer spending. This research examines the effects of mobile, location-based advertisements delivered via digital shopping cart screens in a real-world field quasi-experiment. Results reveal two key effects on purchasing (i.e., quantity, variety, and spending). First, location-based digital cart ads increase purchase quantity and spending on advertised products, consistent with enhanced awareness and consideration at the point of purchase. Second, these ads increase quantity, variety, and spending on non-advertised products within the advertised category, indicating spillover effects beyond the focal product. To investigate these effects, we tested two ad formats: centrally displayed ads and peripherally displayed ads aligned with product locations in the aisle. Both formats significantly increased purchasing relative to shopping carts without ad displays, but peripheral ads did not reliably outperform central ads. Exploratory analyses further show that the effect of cart ads remains robust across store zones and throughout the shopping journey. Together, these findings show that in-cart ads not only drive sales of promoted products but also increase overall purchasing within advertised categories, highlighting the profit potential of in-cart, location-based advertising.
This paper investigates the tensions restaurants face when partnering with third-party food delivery platforms such as Meituan and Uber Eats. While platforms often frame these partnerships as empowering, restaurants frequently perceive them as exploitive. Restaurants turn to these platforms to expand market reach and enhance convenience; however, outsourcing delivery services has downsides, including less access to customer data, reduced control over customer relationships, greater exposure to competitors, and pressure on already thin margins. These competing forces create an outsourcing paradox. To assess whether such alliances are mutually beneficial, we quantify two-way revenue interactions between restaurants and platforms. Drawing on resource dependence theory (RDT), we develop hypotheses and estimate a two-equation model of restaurant and platform revenues while addressing endogeneity and autocorrelation. The results reveal asymmetric cross-effects: platform revenues exhibit a significant and positive relationship with restaurant revenues, whereas restaurant-to-platform cross-effects are insignificant. We further find that promotions, menu novelty, and competition moderate these cross-effects. Overall, restaurant–platform partnerships appear largely win–neutral – a double-edged outcome for restaurants. While the platform-to-restaurant finding is an obvious plus, the lack of reciprocal effects highlights restaurants’ growing dependence on platforms. These findings provide important implications for both restaurants and platforms.
