Journal of Marketing Research

How should firms best communicate their corporate social responsibility efforts? Across seven preregistered studies (two large field studies and five online lab experiments), the authors find that making a series of periodic contributions (e.g., donating $20,000 per month for 12 months), rather than donating an equivalent aggregate amount (e.g., $240,000 in a year), improves outcomes for donor companies, such as reputation, customer engagement, and purchase likelihood. The benefits of periodic donations arise primarily because of heightened consumer perception of the donor company's authentic prosocial motivation, which affects outcomes in two ways: First, the consistency of periodic donations increases perception that the donor gave because of authentic prosocial motives, which then increases favorable donor evaluations. Second, heightened perception of the donor's authentic prosocial motivation also increases the perceived impact of the donation, further boosting favorable donor evaluations. Additional studies demonstrate when and why periodic donations may benefit (or, in some cases, even harm) evaluations of the donor. This research highlights consumers’ sensitivity to cues of consistency, and the importance of perceived authentic prosocial motivation, when consumers grant charitable credit for corporate social responsibility.

Despite the ubiquity of ingredient quantity information in the marketplace, prior literature has yet to examine whether ingredient quantity shapes consumer choice. This research presents and tests a novel framework that charts when, why, and how this pervasive ingredient quantity information influences consumers’ food decisions. The findings from two preregistered pilot studies, seven preregistered experiments, and ten supplementary experiments in the Web Appendix indicate that consumers are often more interested in food products framed as containing few (vs. many) ingredients, even when the same ingredient list is displayed across products. This preference stems from the perception that fewer ingredients indicate less processing, especially when a product’s processing history is unavailable. As a result, a product with fewer ingredients is perceived as more natural and is thus preferred. Further, the studies also show that although consumers commonly pursue the goal to consume natural products, when other consumption goals (e.g., the goal to seek indulgent or unique products) rise in importance, a product framed as containing more ingredients can become more preferred. This work uncovers how ingredient quantity information biases consumers’ perceptions and daily food product decisions, and it provides easily implementable guidance for marketers seeking to increase consumers’ purchase likelihood.

Communication is a key aspect of the joint decision-making process, yet the field lacks an understanding of how people talk to each other while making joint decisions. In this article, the authors analyzed nearly 200 joint decision conversations from shop-along observations. They found that joint decision conversations are composed of four distinct communication patterns, which characterize how partners talk to each other: (1) coordination (including inquiry and disclosure), (2) contrast (including persuasion and devil's advocate), (3) build, and (4) one-sided. The authors then used these communication patterns as the building blocks of joint decision conversations to quantitatively model how they dynamically flow as partners shop together, finding that decision partners navigate the decision life cycle nonlinearly and communication pattern usage affects immediate satisfaction outcomes. The findings enable connections to be drawn across the splintered literatures on dyadic communication. The authors develop a taxonomy that reflects an integrated, cross-disciplinary phenomenological understanding of each communication pattern to facilitate interdisciplinary research. Theoretical advancements and practical implications are discussed, as are areas for future research.

Consumers often resist marketing information about death-related products and services (DRPS), let alone purchase them. Yet, there is a massive market and universal necessity for DRPS offerings like life insurance and funeral services. Proactively considering DRPS in advance allows consumers to better prepare for death and its aftermath. The current research builds on terror management theory and the literature on language use and psychological distance to propose a language-based sales communication strategy for DRPS. The findings from eight studies, including two field experiments and an eye-tracking study, indicate that DRPS sales messages that appear in consumers’ second (vs. native) language (e.g., using muerte, Spanish for death, when talking to a native English speaker whose second language is Spanish) decrease consumers’ fear of death by creating greater psychological distance to death, which in turn induces more consumption (e.g., actual purchases). However, this effect becomes attenuated when consumers perceive high control over death or when the DRPS feature transcendence after death. In contrast, the effect is amplified for DRPS that require an intermediate level of customer participation. These findings offer novel insights into how marketers and policymakers can motivate consumers to consider DRPS earlier and engage in more proactive decision-making.

Figure–ground reversal (FGR) transcends visual conventions by reversing the roles of figure and ground in brand logo designs. In this research, the authors study how FGR logos affect consumers’ brand attitudes. Using traditional self-reported measures as well as biometric technology, they illuminate the unique nature of FGR's underlying mechanism and identify moderators to shed additional light on that process. Specifically, they find that the positive effect of FGR logos on brand attitude is mediated by engagement and aesthetic appeal, and moderated by the visual identification and semantic interpretability of FGR objects. Across a multimethod investigation that includes live-bidding, incentive-compatible willingness-to-pay, eye-tracking, and multiple boundary condition experiments, the authors provide empirical support for these effects and reveal the underlying mechanism. They conclude by discussing the contributions of the research to the literature on visual marketing phenomena and the implications of the findings for better visual branding in the marketplace.

A large body of research shows that even when information is accessible, consumers often fail to attend to it. To what extent and under what conditions can firms profit from such consumer inattention? The authors study this question theoretically and empirically in the used car market, focusing on the widely documented left-digit bias. Theoretically, firms can profit from targeting the most inattentive consumers even when there is an active decentralized market for used goods trading. Leveraging a detailed dataset of millions of automobile transactions from a seven-year period, the authors find that consumers exhibit inattention in the form of left-digit bias to the odometer, and such inattention is estimated to be significantly more for consumers who buy from firms. Compared with private sellers, car dealerships transact with ex post significantly more left-digit-biased consumers. Dealerships sell more vehicles with odometer readings below round numbers, sell them faster, and extract higher margins from these vehicles. The results imply that intermediaries can “skim” consumers with specific behavioral biases and extract meaningful surplus from selling to them.

Mobile applications in the personal development sector increasingly integrate goal-enabling technology features (GETFs), which allow users to define a service-related end goal, set implementation strategies through subgoals, and monitor progress. Little is known, however, about how the difficulty of goals chosen during GETF adoption affects subsequent app behaviors. This study examines whether customers who set more versus less difficult end goals and subgoals show greater engagement and retention, and whether firms can nudge customers toward goal-difficulty levels conducive to sustained engagement. Using behavioral data from an investment app that introduced GETFs, the authors employ hierarchical modeling with staggered synthetic control and instrumental variable regression to address self-selection and endogeneity. Results reveal substantial heterogeneity: Many adopters show no or negative engagement changes, whereas those selecting moderately challenging goals and subgoals significantly increase in-app investment actions, though not sign-ins. Higher engagement postadoption predicts improved retention after one year. A field experiment confirms that subgoal difficulty causally drives in-app actions. These findings suggest that personalized guidance during GETF adoption can enhance sustained engagement. Marketing managers are advised to tailor goal-setting features to individual needs, providing expert-like support. This research provides novel empirical evidence on goal-difficulty levels that most effectively promote app engagement.

This research investigates how platform-suggested prices influence sellers’ pricing decisions and selling outcomes. In collaboration with Mercari, a peer-to-peer e-commerce platform, the authors conduct a field experiment that varies whether a seller receives a suggested price—and, if so, the suggested price itself. They find that a 30% change in suggested prices leads to a 5% change in listing prices in the same direction. Suggested prices are more influential when pricing is more challenging, such as for new sellers and used items. Lower suggested prices improve both the likelihood of sale and the resulting seller revenue. A subsequent experiment shows that these results are likely to generalize to the full equilibrium. The findings imply that platform-suggested pricing is an effective compromise that guides seller pricing while allowing sellers to incorporate their private information.

People routinely make decisions based on predictions made by others (e.g., political pundits, market analysts), so it is in their best interest to identify high-quality forecasts. Experts characterize good forecasting as minimization of continuous error (i.e., predictions close to the eventual outcome). By contrast, the present work reveals that laypeople typically see good forecasts as those that correctly predict an event's categorical outcome (e.g., the winning team). Using within-subjects, between-subjects, and incentive-compatible designs, 15 studies demonstrate this “pick-the-winner-picker heuristic” as well as its psychological mechanism: People evaluate forecasts by assigning separate weights to (1) categorical correctness and (2) continuous error minimization, depending on the overall importance of the categorical and continuous dimensions for that situation. Thus, in the common case when the categorical dimension matters most (e.g., sports contests), people prize forecasts that accurately predicted the categorical outcome (e.g., the winner, not the margin of victory). However, when the categorical dimension's stakes are experimentally reduced, an attenuation is observed. Although this describes how people typically evaluate forecasts, crucially, a dimension's importance is not necessarily related to its diagnosticity of forecaster skill or reliability. Accordingly, the pick-the-winner-picker heuristic may constitute a normative mistake, while framing manipulations help debias judgments.