Knowledge that Transforms

One of the most ubiquitous practices on social media is sharing content with others to show affection or affirm an interpersonal connection. Extant consumer research has examined the circulation of objects fueled by desire or as repositories and carriers of emotion and value. The article extends this work to understand how consumer relationships are shaped through the creation, consumption, and circulation of digital objects imbued with affect. Drawing upon interviews with both managers and followers of animal accounts and netnographic data of animal content on Instagram, this work theorizes how digital affective encounters on social media transpire through the circulation of animal content. The findings highlight the processes through which content is continuously imbued with affective cues to manage parasocial and interpersonal relationships. While affect-laden content can serve as a relational token when shared between friends and family, it can also be captured and modified by large accounts. As a result, the affective force of this content can reach mass audiences and become memetic. Our article shows the significant role of affect as a mobilizing force of digital affective networks. Beyond animal content, the framework is transferable to the circulation of other social media content and consumer–influencer relationships.

Despite recognizing several ways consumers respond to perceived systemic risk scenarios, prior research emphasizes a general trend toward the privatization of risk, in which individual consumers are responsibilized for managing systemic risk scenarios through their consumption. However, prior work in this area blurs the distinction between responsibilized consumption aimed at self-protection versus preventing or reducing the likelihood of risk scenarios. Moreover, it does not explain how many consumers come to prioritize the former over the latter. To explore how this occurs, this netnography investigates doomsday preppers, consumers preparing for perceived catastrophic and systemic risk scenarios by stockpiling consumer goods, acquiring prosumptive knowledge, and cultivating survival skills. Drawing from the marketplace myths literature, this article introduces the concept of mythologized counter-futures to illustrate how preppers mobilize marketplace myths to socially construct future risk scenarios. Through mythic prefiguration, many preppers’ mythologized counter-futures ameliorate anxiety associated with vulnerability-inducing systemic risk scenarios and pattern anticipatory consumption toward self-protective consumption rather than risk-scenario preventive consumption. The analysis makes novel contributions to the literature on the social construction of risk, consumer responsibilization, consumer vulnerability, consumer timework, and marketplace myths.

We examine how people (as observers) anticipate levels of happiness from psychological consumption experiences (e.g., learning a new language or visiting a park). All else being equal, we propose and demonstrate that people expect differences in happiness based on income. Specifically, we show that relative to observers themselves, individuals simultaneously expect low-income consumers to enjoy psychological consumption experiences less and high-income consumers to enjoy them more. This is because consumers hold a lay theory that human needs must be fulfilled in a sequential, linear manner, which leads to income-based inferences of need prioritization. Thus, observers simultaneously believe that low-income consumers do (and should) prioritize their low-level physical needs first, but high-income consumers (who have presumably already fulfilled their physical needs) can prioritize their high-level psychological needs. Critically, we demonstrate that these lay theory-driven inferences are faulty, showing that the priority level assigned to these needs and the actual happiness resulting from psychological consumption experiences do not follow the predicted pattern. Namely, income either has no relationship with actual happiness (visitors to theme parks, sporting events, and concerts) or the reverse relationship, such that lower-income consumers report greater happiness than higher-income consumers (secondary data from a major league professional sports team).

Generative Artificial Intelligence (GenAI) has introduced new possibilities for both the creation and analysis of language, which is one key input for consumer culture researchers who analyze qualitative and textual data. How can consumer culture researchers use GenAI to produce insights and work with qualitative data? What are the possibilities and challenges of using these tools? And what are some valuable practices and principles for integrating GenAI into the research process? Building from interviews with researchers who use these tools, the authors identify relevant theoretical, embodied, empirical, and historical contextual dimensions that produce opportunities and challenges for human–AI collaboration. The authors then propose a set of collaborative practices and offer practical guidelines for using GenAI to generate novel and meaningful insights into consumer culture and society.

Platforms present various certifications to signal the quality of their offerings to prospective consumers. For example, Airbnb.com designates some hosts as “Superhosts” to distinguish properties that provide superior experiences. Platforms also present user-generated ratings—typically elicited and presented as “star ratings”—from their customers for the same purpose. This research investigates the interaction of these signals of quality and suggests a potential downside to platform-provided certifications: They decrease subsequent ratings. In an analysis of over 1,500,000 ratings from Airbnb.com and three follow-up studies, we find that properties with the superhost designation receive lower ratings. We assess the robustness of this result in several ways, including comparing ratings on Airbnb with those for the same property on Vrbo. In three follow-up experiments, we find that the net effect of certifications can lead to reduced choice share: The positive effect of signaling quality is more than offset by the negative effect of reduced ratings. This suggests that consumers are not sufficiently aware of this effect of quality certifications on ratings when choosing.

Care is increasingly marketized. Previous marketing and consumer research has focused on specific tensions underlying marketized care provision and the ways in which consumers navigate them. In contrast, this conceptual article draws on interdisciplinary research on care to develop a cumulative understanding of marketized care, that is, based on those effects that build up over time when a critical mass of consumers routinely addresses care needs via markets. Defining marketized care as attending to the welfare needs of human and nonhuman others through the market, we identify four negative cumulative effects: individuating effects on consumer subjectivities, alienating effects on care relationships, responsibilizing effects on consumers as opposed to other institutional actors of care provision, and exploitative effects generated in global care and supply chains. We also outline four principles that can mitigate these effects: interdependent consumer autonomy, affective reconnections, proportionate responsibilization, and market reconfiguration. Our conceptualization moves the literature on marketized care forward by outlining its cumulative nature as well as offering potential solutions that are neither demonizing nor celebratory of markets. In doing so, we offer a series of generative insights for research on marketized care that contribute to addressing collective human and nonhuman flourishing.

The use of generative AI (genAI) in consumer research is rapidly evolving, with applications including synthetic data generation, data analysis, and more. However, their role in creative ideation—a cornerstone of consumer research—remains underexplored. Drawing on the human creativity literature, we propose that ideation with genAI is facilitated by its productivity and semantic breadth, which are psychologically analogous to the dual pathways of persistence and flexibility in human ideation. Further, we distinguish between the utility of genAI as a key ideator versus humans as key ideator, conceptualized through the genAI ideation roles of Designer and Writer and of Interviewer and Actor. While genAI excels in generating incremental improvements, its potential for groundbreaking innovation could be unlocked by leveraging its ability to prompt human creativity. This article advances the theoretical and practical understanding of genAI in ideation for consumer research, offering numerous practical guidelines for integrating generative AI into research while emphasizing human–AI collaboration to achieve radical insights.

We develop a novel generative AI (GenAI) trajectory, “democratization-average trap-model collapse,” to identify data and model challenges posed by GenAI, from which we project the GenAI future of consumer research. This trajectory consists of three key phenomena: democratization broadens consumer participation, the average trap produces generic responses, and model collapse occurs when GenAI outputs lose human sensibilities. Data and model challenges arise as democratization enhances data representation while also embedding real-world biases. The average trap, caused by next-token prediction models, leads to generic outputs that lack individuality. Additionally, model collapse occurs when GenAI increasingly learns from its own outputs, amplifying machine bias and diverging from human behavior. To address these challenges, researchers can leverage democratization to study marginalized consumers and prioritize human-centered research over purely data-driven methods. The average trap can be mitigated by fine-tuning models with task-specific and marginalized consumption data while engineering responses for uniqueness. Preventing model collapse requires integrating human–machine hybrid data and applying theories of mind to realign AI with human-centric consumption. Finally, we outline three future research directions: preserving data distribution tails to support consumption democratization, countering the average trap in next-token prediction, and reversing the trajectory from democratization to model collapse.

Brands are expanding their market to new consumers by displaying cultural diversity in marketing campaigns—but the risks are unclear. This article explores the role of the brand’s characteristics in multicultural diversity. Our findings suggest that when brands launch a new multicultural diversity campaign, it may be well-received if the brand’s original focus was on the needs of nonmarginalized consumers. However, for brands with a focus on the needs of marginalized consumers (i.e., marginalized-focused brands), such a campaign may be perceived as selling out, thereby negatively impacting consumers’ reactions. Six studies with Black and White U.S. consumers explore this novel “sellout effect” across various product categories and for consequential behaviors. Inclusion is identified as a key mechanism, mitigation strategies are explored, and implications for theory and practice are discussed. Findings highlight the importance of diversity marketing, understanding marginalization for consumers and brands, and the need for research that considers race and ethnicity.

Consumption has always been part of the workplace, yet it has traditionally been seen as nonwork—an activity that depletes rather than creates value. In the knowledge and digital economy, however, consumption and work are becoming increasingly intertwined, calling for a relational perspective on consumption’s productive role. We develop this perspective through a four-year ethnography of coworking spaces across Paris and London, supplemented by post-pandemic archival data. We introduce consumptive work as the instrumentalization of consumption activities in the workplace to generate productive value. Consumptive work emerges within a postindustrial societal context where workplace culture is shaped by consumer ideology, leading to (1) customer entitlement in the workplace, (2) consumer desire toward the workplace, and (3) consumer lifestyle aspirations toward work. Consumptive work is characterized by inconspicuousness, boundarilessness, and communal and market exchange. While it can be empowering, it also fosters neo-normative alienation, particularly through performative play and leisure, and the pursuit of productive wellness. Ultimately, consumptive work reinforces evolving consumer desires and aspirations about office work and workplaces. This study advances interdisciplinary research on consumption and consumption ideology in the workplace, workplace alienation, new ways of working, and consumer research connecting work, home, and leisure.