Journal of Interactive Marketing

The rapid growth of consumer-to-consumer luxury resale platforms has raised important questions about how price premiums influence follow-up sales. While existing research has explored the relationship between price premiums and consumer demand using analytical or theoretical approaches, empirical research on this topic has been impeded by the limited availability of transaction-level data and the absence of an appropriate modeling framework. This study addresses this important research gap through a combination of (1) transaction-level data from Korea's largest luxury resale platform, (2) a representation learning model that compresses product-related information, and (3) a machine learning–based causal inference model that enables nonlinear estimation of the causal effect. The results reveal that higher price premiums generally lead to increased consumer demand, and vice versa. However, this relationship reverses when the price premiums exceed a certain threshold. The study contributes to the luxury consumption behavior literature and provides actionable insights for platform owners and consumers.

As concerns about sexually transmitted infections rise, individuals increasingly rely on social media–based communities for peer-driven information and support due to persistent barriers to appropriate medical care. Using a qualitative, multimethod approach that combines in-depth interviews with netnographic observation of a large online sexual health community (OSHC), this study explores consumers’ motivations for engagement with OSHC. Findings contribute to the development of a new theoretical framework that reveals two main motivational patterns for consumer engagement with OSHCs: proactive motivations, such as community homophily, information diversity, language barriers, convenience, community moderation, inclusive language, and collaborative knowledge building; and reactive motivations, triggered by emotional distress, loneliness, perceived stigma and discrimination, confidentiality assurance, information gatekeeper, and need for social support. The cultural context moderates these motivations. Engagement outcomes include health empowerment, perceived value, sexual health confidence and well-being, and relief and reduction in emotional distress, moderated by the perceived severity of users’ health conditions. The study advances understanding of digital consumer engagement in stigmatized health contexts and offers a theoretical framework for how individuals cocreate knowledge, manage risk, and achieve empowerment through online peer interaction. The study offers implications for policymakers, health communities, and medical organizations.

Product recommendation posts by influencers are a new and popular form of product promotion in which message content can be objective or subjective, aiming to engage consumers and drive sales. However, current research in influencer marketing provides little knowledge about how including subjective language along with objective language in product recommendation posts shapes an influencer's impact. A multimethod investigation, combining a controlled experiment (Study 2) with natural language processing of 58,659 influencer product recommendation posts (Study 1), demonstrates that adding subjective language increases customer engagement and purchase likelihood, and these effects are driven by perceived relevance. However, the positive effect of including both subjective and objective language can be mitigated if the influencer has a large number of followers or the recommended product is an experience good. These findings extend the literature on how influencer product recommendation language impacts the effectiveness of product recommendations, deepen the understanding of the drivers of influencer content relevance, and provide crucial guidance for influencer marketing practitioners.

Data is an indispensable asset in the AI ecosystem. This article investigates consumers’ lay understanding of the different types of data that AI systems use to generate recommendations, and how this understanding influences their likelihood of accepting those recommendations. Across one pilot study and four main studies, the authors establish consumers’ mental construction of three different data types and experimentally validate two mechanisms that shape recommendation acceptance: (1) perceived individuality threat associated with these data types and (2) their processing acceptability.

Electronic word of mouth (eWOM) can inform consumers’ decisions, but do older consumers (i.e., those age 65 and older) respond to eWOM in the same way as younger ones? If not, what underlying factors contribute to this difference, and what strategies can be implemented to encourage older consumers to utilize this accessible and useful information source in their decision-making? Answering these questions is crucial given the global increase in the aging population and the growing shift toward digitalization. Three studies examine this phenomenon. Study 1 reveals a negative association between age and eWOM persuasion, so that, as consumers age, they tend to be less persuaded by eWOM. However, drawing on aging literature and self-control theory, Studies 2 and 3 demonstrate that situationally inducing older consumers to feel younger, through instructions or communication cues, increases their perceived sense of control, and ultimately results in greater eWOM persuasion. These findings expand the literature at the intersection of aging, sense of control, and eWOM by identifying perceived youthfulness and sense of control as determinants of eWOM persuasion among older consumers. They also provide marketers and policymakers with actionable insights on how to facilitate older consumers’ use of eWOM, while keeping in mind potential ethical considerations.

Increasing competition pushes firms to accelerate their product launches, leading to closely spaced launches within firms. Especially in fast-paced markets, such as digital entertainment, the postlaunch period of one product often overlaps with the prelaunch period of the next. Existing studies examined firm-initiated communications in separate pre- versus postlaunch periods. In contrast, the authors study the effects of a publisher's overlapping product launches on social media engagement and associated spillovers of social media posts across partners promoting the focal product: publishers, product creators, and product accounts. The regressions use daily data covering the pre- and postlaunch periods of video games released by major publishers. The results show that overlaps harm the engagement rates of publishers and product accounts but benefit creators. Partner spillovers are asymmetric: Publisher and creator posts drive engagement to product accounts but not vice versa, and creator posts benefit publishers but not vice versa. Overlap effects on spillovers are usually most prominent when overlap occurs in the focal game's prelaunch period, with limited available product information, rather than postlaunch. Partners should align their social media strategies around overlapping launches to boost engagement for the focal product: Creators should intensify communication prelaunch, whereas publishers should increase communication postlaunch.

Brands increasingly adopt two strategies in tandem: They use artificially intelligent agents, such as service robots, to more efficiently serve customers, and they engage in corporate social responsibility (CSR) activities to positively shape brand-related perceptions and behaviors. In this research, across four studies (including a pilot study, an online interaction with an AI-powered robot, and three preregistered studies, involving real and fictitious brands and intentional and actual behavior) the authors provide evidence for the notion that these two strategies are not necessarily compatible. The authors reveal the counterintuitive and nuanced finding that brands engaging in high-fit CSR suffer more from the introduction of service robots than brands that engage in low-fit CSR. This outcome is explained by a perceived lack of alignment in consumers’ attributions regarding brands’ motivations behind the two strategies, especially regarding the brand's profit-maximization intentions. The authors further identify two managerially actionable moderators. First, a communal service robot strategy can mitigate the negative impact of service robots in instances of high-fit CSR. Second, a more communal CSR implementation (i.e., volunteering time compared with donating money) can lead to a negative impact of service robots when a firm pursues a low-fit CSR strategy.

Voice shopping is on the rise. However, with the absence of visual stimuli, consumers face difficulties in processing brand and product information during the shopping process. Drawing on the load theory of attention and the literature on imagery and information processing, the authors conducted two studies to examine how the level of imagery in auditory product descriptions and the number of product attributes shape consumer responses. The results indicate that high-imagery descriptions increase brand stimulation, which in turn improves brand attitude, purchase intention, and actual product purchase. Additionally, the imagery level of an auditory product description positively influences brand recall directly. These results provide new insights into how auditory message design shapes consumer evaluation and decision-making in voice-based shopping contexts.

Privacy regulations, such as the General Data Protection Regulation (Article 17) and California Consumer Privacy Act, give consumers the right to request the deletion of their personal information. While researchers have begun to examine the implications of these laws, the effects of different data request options (to provide, keep, or delete information) on consumers’ personal-information-sharing behavior have not been thoroughly studied. Drawing on prior work on autonomy, the authors investigate a new construct, “enactment autonomy.” They demonstrate that data requests can alter perceptions of shared autonomy, influencing feelings of vulnerability and subsequent information-sharing behavior. Six experimental studies, including one behavioral study and a within-paper meta-analysis, provide support for the proposed data request effect as well as boundary conditions related to perceived information sensitivity and the presence of a third party.

Supplier to small business to consumer (S2b2C) has emerged as a novel e-commerce model, where S2b2C platforms source products from upstream suppliers and distribute them through individual sellers who promote and sell products within their own social networks. This model differs from traditional e-commerce in two key aspects: It segments the entire consumer market into distinct communities (i.e., consumer segmentation) and creates additional consumer value through social interactions with individual sellers (i.e., interaction utility). This article examines the impacts of consumer segmentation and interaction utility on the market outcomes. Specifically, the authors compare the S2b2C model with traditional e-commerce in terms of prices, demands, profits, consumer surplus, and social welfare and report the following findings. First, firms benefit from an asymmetric consumer-segmentation structure, where the high-end seller targets consumers with sufficiently high valuations, while the low-end seller serves the remaining market segment. Second, conventional wisdom on double marginalization may not hold under the S2b2C model. Despite the introduction of an additional layer in the S2b2C supply chain, both the wholesale price and the retail price can be lower. Finally, S2b2C can result in win-win, win-lose, lose-win, or lose-lose outcomes for firms and consumers, depending on the consumer-segmentation structure and the value consumers place on social interactions.

To establish if and how reviewers’ use of self-references is associated with the helpfulness of their reviews, the current research draws on the elaboration likelihood model and predicts a pattern of diminishing returns. The marginal effect of self-reference on helpfulness and purchase intentions should be positive at moderate levels but diminish at higher levels. Using an archival dataset from Amazon and a controlled experiment, the author establishes consistent evidence of this predicted pattern. The nonlinear effect appears to stem in part from readers’ perceptions of certainty, and it is also more substantial for hedonic products. These findings offer critical implications for effective word-of-mouth communication and provide platform managers with practical insights by clarifying the nuanced association between self-referencing review information and downstream marketing consequences, such as review helpfulness and purchase intentions.

With the emergence of blockchain technology, many firms have approached cryptocurrency by allowing their customers to use it as a form of payment. However, little research has examined firms’ acceptance of cryptocurrency, the unique strategies that have been undertaken, or the impact on firm-level outcomes. Drawing on signaling theory, the author applies the event study methodology to learn how firm value (i.e., stock price) is impacted by firms’ announcement of cryptocurrency acceptance. The author finds that, on average, firms have lost 2.73% in firm value as a result of announcing cryptocurrency acceptance. However, a moderation analysis reveals that firms that have chosen to accept Bitcoin (as opposed to focusing exclusively on alternative cryptocurrencies) and firms that have approached cryptocurrency acceptance in more recent years experience financial gains. The geographical location (i.e., domestic or international) of cryptocurrency acceptance is not found to have a moderating impact.

Online customer reviews of products and services are essential for facilitating trust and efficient e-commerce. The review system depends crucially on consumers’ voluntary provision of reviews, yet most consumers consult others’ reviews while few consumers post their own reviews. The current research (1) empirically assessed motivations to post and not to post reviews, (2) tested messages inspired from behavioral-intervention theories to encourage online reviewing, and (3) manipulated when the message was presented to online shoppers. Unlike previous findings in other domains, messages that invoked norms or moralization were not successful in motivating online reviewing. Instead, the authors discovered novel message content and interactive presentations that successfully increased review intention. The content addressed motivations assessed in the initial studies and was stated with low threat to avoid reactance. Crucially, the message was presented interactively in real time during shopping instead of after purchase.

Consumers often purchase new products based on online reviews and recommendations from both friends and strangers. Previous studies have extensively explored the effects of word of mouth (WOM) on the prepurchase stage, but little is known about whether WOM from friends or strangers can alter consumers’ postpurchase behavior. The authors propose that positive WOM from distant (vs. close) others increases consumers’ intention to share negative WOM when the product/service fails to perform to their satisfaction due to two distinctive motivations. First, consumers perceive that positive WOM from distant others might mislead more people, and, consequently, consumers expect their negative WOM to have a greater impact on helping others. Second, when receiving positive WOM from close others, they are less willing to publicly contradict the close others’ WOM even though they believe the WOM is misleading. Studies 1a and 1b demonstrate the main effect of interpersonal closeness on negative WOM intention, while Study 2 reveals the dual mediating effects of anticipated impact and relationship norm. Studies 3 and 4 validate these mechanisms by showing the moderating role of the self-construal level while ruling out the role of impression management. This research offers practical implications for WOM management across different social ties.

Consumer-to-consumer (C2C) online reviews are important sources of information that help consumers decide which products and services to buy. Although C2C reviews in video format (e.g., on YouTube) have become increasingly popular, research remains focused primarily on textual reviews. This article emphasizes the importance of C2C video reviews in influencing consumer outcomes through parasocial interaction, a special—albeit one-sided—connection with reviewers. Interactivity and self-disclosure are suggested as online communication techniques reviewers can use to foster parasocial interaction with their viewers in a single encounter. Parasocial interaction is further established as a psychological mechanism that underlines the impacts of interactivity and self-disclosure on source credibility, leading to improved consumer purchase intentions. The authors also propose that strong parasocial interaction with reviewers exerts a particularly powerful influence on the purchase decisions of consumers who experience low levels of decision confidence, while arguing for the importance of C2C video reviews in guiding the decisions of various consumer groups. Research recommendations reveal how managers can encourage consumers to create and share video reviews on different platforms and offer guidance on the ways companies can foster parasocial interaction through firm-related marketing communications.