Knowledge that Transforms

Consumers routinely make decisions about short time periods, such as waiting for a table or deciding whether to pay for faster delivery. Such periods are often expressed by either a duration or a clock time (e.g., if it is 6:00 PM now, “Your table will be ready in 30 minutes” vs. “Your table will be ready at 6:30 PM”). Eight experiments (N = 16,604) show that these logically equivalent frames change how long a period feels, with downstream consequences for consumer decisions. Relatively short time periods feel longer when framed by duration rather than by start and end time (i.e., clock times or calendar dates), but this pattern reverses as periods get longer. We refer to this phenomenon as time-duration asymmetry: framing an interval by its start and end time versus its duration changes how long it feels, with the direction of the effect depending on the interval’s length. We propose that this occurs because duration frames evoke compressive scalar representations shaped by diminishing sensitivity, whereas start-end frames situate time within structured categorical systems that attenuate compression. This research offers a unified framework for understanding how subtle differences in temporal framing shape perceptions of time and subsequent decisions.

Consumers can experience two types of uncertainty when purchasing a product. Preference uncertainty refers to the uncertainty associated with the horizontal product benefits one desires (e.g., “How strong do I want my coffee to be?”). Outcome uncertainty refers to the uncertainty associated with the actual benefits the product will deliver (e.g., “How strong will the coffee be?”). Ideally, retailers should strive for outcome certainty (i.e., standardize the strength profile of their coffee [coffees in their line]), and help consumers achieve preference certainty (i.e., help consumers learn their ideal coffee strength), so that consumers can purchase the appropriate product with confidence (i.e., achieve a preference-outcome match). Yet there are situations where high outcome uncertainty is a characteristic of the product class, after controlling for quality (e.g., flavor profile of wine). When outcome uncertainty is high, we paradoxically find that high preference uncertainty leads to more purchase intent than low preference uncertainty. We show this occurs because people are more optimistic that they will maximize their utility when preference uncertainty is high (i.e., multiple outcomes could potentially be the best match for their preference) than low (i.e., only one outcome could be the best match for their preference).

Why do consumers sometimes remain trapped in the very practices and communities that once helped them? Consumer practice research has largely emphasized the enabling outcomes of sustained practice participation, with less attention given to how those same practices can become entrapping. This article explores how consumer entrapment emerges within interconnected collective practices. Drawing on an ethnographic study of Chama, a community-based savings and support group in Kenya, it integrates practice theory with Hodder’s theory of entanglement. The study identifies three mechanisms (prefiguration, socialization, and entrenchment) through which participation generates commitments, dependencies, and obligations that produce recurring practice misalignments. Consumers continually work to realign these misalignments, yet under specific conditions, these efforts reproduce the contingencies that sustain participation while progressively deepening entrapment. The findings reveal a central tension: efforts to restore practice alignment can sustain what consumers value while simultaneously reproducing the interdependencies through which consumer entrapment emerges.

Many organizations are adopting algorithms for evaluating various consumer applications (e.g., loans, insurance). This research explores how consumers react to this practice, with the goal of understanding what leads some consumers to react more positively or negatively to being evaluated by an algorithm than others. In the context of consumers applying for access to valued services, opportunities, or benefits, applicant strength (i.e., how strong an applicant believes their case is based on the information they have about their standing) influences their reactions toward algorithmic versus human evaluation. Algorithmic evaluation will have a greater deterrent effect on weaker than on stronger applicants. This asymmetry is explained by weaker applicants’ stronger preference for characteristics of human evaluators, such as flexibility and leniency, that they believe may improve their chances of receiving a favorable outcome. Consumers’ preferences ultimately impact willingness to apply, such that using algorithmic evaluations disproportionally discourages weaker applicants from applying. This research contributes to the literature on consumer responses to algorithms by identifying applicant strength as a novel determinant and by extending the focus from algorithms as advisors to algorithms as evaluators of consumers.

Some consumers evaluate products against demanding, ever-rising ideals of perfection. We introduce the desire for perfect products (DPP), a novel consumer trait capturing the extent to which consumers desire flawless products. Drawing on four qualitative studies, we identify three characteristics that distinguish high (vs. low) DPP consumers: (1) richer and more demanding ideal points, (2) greater susceptibility to upwardly revising those ideals when exposed to superior products, and (3) heightened sensitivity to even minor negative deviations from the ideal. Across scale-development studies reported in the web appendix, we develop an eight-item measure of DPP, establish its discriminant validity, and validate these characteristics. Across eight experiments, we show that DPP systematically shapes consumer behavior across acquisition and disposal. High-DPP consumers employ more numerous and stringent search filters, exhibit stronger preferences for newer products even when objective quality is unchanged, and are less willing to retain, repair, or donate flawed but usable products. Finally, we identify a managerially relevant intervention: reframing flaws as a source of uniqueness attenuates high-DPP consumers’ negative reactions to imperfect products.

Initial choices often lead to downstream choices. Initial choices among restaurants lead to downstream choices among entrées, and initial choices among resorts lead to downstream choices among activities. How do the options available for downstream choices (e.g., entrées, activities) affect initial choices among multi-option alternatives (e.g., restaurants, resorts)? Forward-looking consumers should be able to identify their most-preferred downstream choice options (e.g., favorite entrée, favorite activity) and select an initial alternative accordingly. Less-preferred downstream choice options may therefore be disregarded. Yet fifteen studies across four domains (three consumer goods and risky gambles) indicate this is not how consumers choose. Instead, adding a less-preferred option to an otherwise-attractive set of downstream choice options decreases the choice share of the corresponding multi-option alternative. The effect size increases as the difference in value between the more-preferred and less-preferred options increases. Mouse-tracking reveals that participants who attend more to a less-preferred downstream choice option (e.g., entrée, activity) are less likely to choose the corresponding multi-option alternative (e.g., restaurant, resort). A manipulation of attention to the downstream choice options provides causal evidence for this mechanism. This work enhances our understanding of multi-option decision-making and how decision-makers assess the overall value of choice sets.

Rising costs have led to the emergence of skimpflation—reducing the quality of a product or service without changing its price. Although this practice is becoming increasingly common, little is known about how consumers perceive it relative to other cost-management strategies. Across multiple preregistered experiments, I find that consumers judge decreases in product quality as significantly more unfair than decreases in product size or increases in price. This “skimpflation penalty” is associated with perceptions that quality reductions are less transparent and affect more central aspects of the product and consumption experience. Consistent with this account, differences in consumer reactions are substantially reduced when firms communicate changes transparently, and the additional penalty for quality reductions disappears—or even reverses relative to size reductions—when quality reductions affect peripheral rather than central attributes. Additional studies examine behavioral consequences, showing that consumers are especially averse to purchasing products with reduced quality compared with downsized products or those with higher prices. Further, consumers react less negatively to quality reductions when the original consumption experience can be recovered. These findings offer important implications for firms managing rising costs and for policymakers concerned with transparency and market fairness.

Scientists, NGOs, companies, and the press typically communicate temporal predictions about environmental threats in terms of the calendar date by which the threat is expected to occur (e.g., “Water shortage in the UK by 2040”). However, across eight online studies and a field experiment, we find that referring instead to the amount of time left until the threat (e.g., “Water shortage in the UK within 20 years”) makes the threat feel temporally closer. Consequently, using time-left frames increases consumer engagement with environmental issues and support for pro-environmental causes. This effect arises because time-left framing makes individuals feel as though time is counting down toward the threat.

Hedonic experiences often involve multiple components that are experienced simultaneously. When watching a video clip, for instance, consumers simultaneously experience acoustic and visual elements. The authors study how framing the same experience as either a single whole (single-experience framing) or as a combination of multiple simultaneous experiences (multi-experience framing) shapes hedonic enjoyment. Across 12 studies that span a variety of consumption contexts (e.g., food, videos, music, paintings, games), this work shows that multi-experience framing increases consumers’ enjoyment of the experience and also affects consequential choices such as the willingness to continue the experience. This enjoyment boost occurs because multi-experience framing leads consumers to invest more attention into the experience. The authors also establish two boundary conditions for this effect: multi-experience framing does not boost enjoyment if consumers already pay high attention to the experience for other reasons (e.g., extrinsic rewards) or when the experience is negatively valenced. By investigating how the framing of experiences as multiple simultaneous components shapes hedonic enjoyment, these findings extend existing research on gestalt psychology, partitioning, and bundling further into the hedonic domain. This simple, yet effective, framing manipulation can help marketers, policymakers, and everyday people to maximize the hedonic enjoyment for various commonplace experiences.

Social media shapes how people connect, communicate, and consume information. As generative artificial intelligence (AI) becomes an increasingly common tool for content creation, many platforms have introduced disclosure requirements to inform consumers when content has been created or significantly edited by AI. Yet, little is known about how such AI-generated content (AIGC) disclosures influence consumer engagement, a key metric for creators, platforms, and brands. This research examines whether and why AIGC disclosures affect engagement on social media. Analysis of engagement behavior on TikTok following the introduction of their AIGC disclosure policy and eight preregistered experiments (including two in the web appendix) finds that disclosures reduce consumer engagement. This reduction does not stem from concerns about content quality, wariness of artificial content, or general AI aversion. Instead, the findings identify a novel process: AIGC disclosures reduce parasocial connection—one-sided emotional bonds between consumers and creators. Reduced parasocial connection is driven in part by the perceived effort of the content creator. As such, disclosures that signal greater effort can mitigate reductions in engagement. The implications of these findings for platform policy, content creator strategy, and the future design of AI disclosure practices are discussed.