Knowledge that Transforms

This paper investigates how demand for an artist’s creative work changes when social media mobilizes to “cancel” the artist in response to misconduct. Human brands are particularly vulnerable to reputational shocks, yet how misconduct translates into changes in demand remains poorly understood. Using R. Kelly’s case, we examine how consumption of his music changed following calls for boycott and platform sanctions, including the removal of his songs from major playlists on the largest streaming platform. A cursory examination of music consumption after these scandals would lead to the erroneous conclusion that consumers are intentionally boycotting the artist. We propose an identification strategy that leverages variation in song-removal status and geographic demand to assess the relative roles of platform visibility and intentional consumer responses. Our findings show that the decrease in music consumption is primarily driven by supply-side factors due to reduced platform visibility rather than demand-side factors. Media coverage and calls for boycott have promotional effects, suggesting that social media boycotts can inadvertently increase music demand. The analysis of other cancellation cases involving Morgan Wallen, Rammstein, and Diddy shows no adverse effects on music demand, reinforcing the potential promotional effects of scandals in the absence of supply-side sanctions.

Sellers frequently make positive but vague claims about product quality—a practice known as “puffery” that typically enjoys legal protection. This research examines whether puffery influences consumer behavior in the context of Airbnb listings. The study exploits within-listing changes to claims made in hosts’ brief property descriptions and estimates their effects using a hazard model of booking timing. Adding a single puffed claim increases bookings by about .7 days per year (.2% above baseline); an exclamation point adds roughly 1.0 days per year. Puffery’s impact is statistically similar to objective claims (.5 days per year), though objective claims often duplicate information available through search filters, reducing their marginal impact; less redundant, weakly subjective claims add roughly 1.0 days per year. The study also evaluates whether puffery backfires by disappointing consumers. Results indicate limited backlash: adding a puffed claim reduces numerical ratings and review sentiment by no more than .03 standard deviations. Together, these findings question the legal assumption that consumers sufficiently discount puffed claims, but remain consistent with puffery’s continued legal protection by showing it does not reduce average consumer-reported satisfaction.

Consumers are more easily persuaded by people who are similar to them in looks, behavior, and beliefs. Does similarity’s effect on persuasion extend to similarity in how people sound? We explore how similarity in vocal timbre influences consumer choice. Using machine learning, we generate an objective measure of vocal similarity between an individual consumer and a spokesperson using mel-frequency cepstral coefficients (MFCCs) to capture vocal timbre. First, using data from 7,002 entrepreneur-investor combinations in Shark Tank, we demonstrate the effect of vocal similarity on persuasion in investment pitches. Then, in 2,091 Kickstarter campaigns, we show that a spokesperson’s voice closer to a large audience’s average voice results in higher persuasion, measured by fundraised amount and campaign success – a result driven by vocal similarity. Moreover, these effects are attenuated when external signals of campaign credibility are present. Finally, in four laboratory studies, we show that vocal similarity with a spokesperson or recommender leads to greater trust in their competence and positively influences persuasion. We also show that objective and subjective voice similarity have similar results, with objective similarity mapping on to subjective similarity. We provide a deeper understanding of consumer-spokesperson interactions, including new tools for vocal analytics.

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.

We estimate the heterogeneity of TV advertising effectiveness across store characteristics and advertising levels using a large-scale panel of 135 US retail and restaurant brands, and then use these estimates to assess strategies for improving TV advertising performance. We find significant heterogeneity in TV advertising elasticity across characteristics for over 93% of brands, but show that firms’ observed allocations generally fail to fully exploit this estimated heterogeneity and instead covary much more closely with simple heuristics. For example, we find that firms tend to advertise in areas where they already have high revenue, rather than in the areas estimated to have the highest incremental revenue from advertising. In particular, brands tend to overinvest in dense, high-income markets and underinvest in markets with high concentrations of college-educated residents. We project that brands could improve ad lift by a median 2.35 percentage points (relative to <0.5% median baseline ad lift) and earn tens of millions in additional revenue under identical-budget reallocations that better leverage this heterogeneity, and that 14-16 percentage points of brands with negative return-on-investment (ROI) from TV advertising could achieve positive ROI through such reallocations.

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.

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.

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.

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.

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.