Knowledge that Transforms

This research investigates when and why consumers purchase products with social costs (e.g., environmental harm). Six studies demonstrate that upper-class consumers are more likely to purchase a product with social costs when it has a higher price because they experience greater entitlement, which the authors term the “price entitlement effect,” allowing for purchase justification. In contrast, lower-class consumers do not feel entitled to purchase a product with social costs when it is higher-priced. This effect occurs because upper-class consumers tend to have a greater self-focus, with a higher price entitling them to more resources than others. Consistent with the entitlement mechanism, when egalitarian values are made salient, the price entitlement effect is mitigated, reducing upper-class consumers’ purchase of socially costly products. Notably, the price entitlement effect occurs only when products have social costs rather than for all higher-priced products. However, when the social costs of a product are severe, price entitlement does not sufficiently justify product purchase. This research provides theoretical and practical insights regarding when and why higher price entitles purchase of socially costly products, contributing to research on social class and socially responsible (vs. costly) consumption as well as choice justification.

Although companies increasingly are adopting algorithms for consumer-facing tasks (e.g., application evaluations), little research has compared consumers’ reactions to favorable decisions (e.g., acceptances) versus unfavorable decisions (e.g., rejections) about themselves that are made by an algorithm versus a human. Ten studies reveal that, in contrast to managers’ predictions, consumers react less positively when a favorable decision is made by an algorithmic (vs. a human) decision maker, whereas this difference is mitigated for an unfavorable decision. The effect is driven by distinct attribution processes: it is easier for consumers to internalize a favorable decision outcome that is rendered by a human than by an algorithm, but it is easy to externalize an unfavorable decision outcome regardless of the decision maker type. The authors conclude by advising managers on how to limit the likelihood of less positive reactions toward algorithmic (vs. human) acceptances.

Consumers often become “stuck in a rabbit hole” when consuming media. They may watch several YouTube videos in the same category or view several thematically similar artistic images on Instagram in a row, finding it difficult to stop. What causes individuals to choose to consume additional media on a topic that is similar to (vs. different from) what they just experienced? The authors examine a novel antecedent: the consecutive consumption of multiple similar media. After viewing multiple similar media consecutively, more consumers choose to (1) view additional similar media over dissimilar media or (2) complete a dissimilar activity entirely, even when the prior consumption pattern is externally induced. The rabbit hole effect occurs because of increased accessibility of the shared category: when a category is more accessible, people feel immersed in it and anticipate that future options within that category will be more enjoyable. The authors identify three characteristics of media consumption that contribute to the rabbit hole effect by increasing category accessibility: similarity, repetition, and consecutiveness of prior media consumption. This research contributes to literature on technology, choice, and variety seeking, and it offers implications for increasing (vs. slowing) similar consumption.

This article proposes a panel data generalization for a recently suggested instrumental variable‐free estimation method that builds on joint estimation. The author shows how the method can be extended to linear panel models by combining fixed-effects transformations with the common generalized least squares transformation to allow for heterogeneous intercepts. To account for between-regressor dependence, the author proposes determining the joint distribution of the error term and all explanatory variables using a Gaussian copula function, with the distinction that some variables are endogenous and the others are exogenous. The identification does not require any instrumental variables if the regressor–error relation is nonlinear. With a normally distributed error, nonnormally distributed endogenous regressors are therefore required. Monte Carlo simulations assess the finite sample performance of the proposed estimator and demonstrate its superiority to conventional instrumental variable estimation. A specific advantage of the proposed method is that the estimator is unbiased in dynamic panel models with small time dimensions and serially correlated errors; therefore, it is a useful alternative to generalized-method-of-moments-style instrumentation. The practical applicability of the proposed method is demonstrated via an empirical example.

One of the greatest challenges in education marketing is designing effective marketing messages, especially when targeting consumers with different cultural backgrounds. This research examines the impact of power distance belief (PDB) on the persuasiveness of affective appeal versus cognitive appeal in education marketing messages. The authors theorize that low-PDB consumers tend to prefer education products presented with affective appeal because of their process learning mindset, which focuses on self-discovery and self-development. By contrast, high-PDB consumers tend to prefer education products presented with cognitive appeal because of their outcome learning mindset, which focuses on acquiring skills and social/economic gains relevant to such skills. These effects were supported by converging results from four experiments, a field study, and a content analysis across 37 countries using a wide range of education products and services. This research contributes to the literature on PDB, education, and cross-cultural consumer behavior and provides guidelines for global education marketers.

Consumers display an expense prediction bias in which they underpredict their future spending. The authors propose this bias occurs in large part because (1) consumers base their predictions on typical expenses that come to mind easily during prediction, (2) taken together, typical expenses lead to a prediction near the mode of a consumer's expense distribution rather than the mean, and (3) expenses display positive skew (with mode < mean). Accordingly, the authors also propose that prompting consumers to consider reasons why their expenses might be different than usual increases predictions—and therefore prediction accuracy—by bringing atypical expenses to mind. Ten studies (N = 6,044) provide support for this account of the bias and the “atypical intervention” developed to neutralize it.

Drawing from a content analysis of publicly traded companies’ privacy notices, a survey of managers, a field study, and five online experiments, this research investigates how consumers respond to privacy notices. A privacy notice, by placing legally enforceable limits on a firm's data practices, communicating safeguards, and signaling transparency, might be expected to promote confidence that personal data will not be misused. Indeed, most managers expected a privacy notice to make customers feel more secure (Study 1). Yet, consistent with the analogy that bulletproof glass can increase feelings of vulnerability despite the protection offered, formal privacy notices undermined consumer trust and decreased purchase interest even when they emphasized objective protection (Studies 2, 3, and 5) or omitted any mention of potentially concerning data practices (Study 6). These unintended consequences did not occur, however, when consumers had an a priori reason to be distrustful (Study 4) or when benevolence cues were added to privacy notices (Studies 5 and 6). Finally, Study 7 showed that both the presence and conspicuous absence of privacy information are sufficient to trigger decreased purchase intent. Together, these results provide actionable guidance to managers on how to effectively convey privacy information (without hurting purchase interest).

The authors empirically examine how firms learn to set prices in a new market. The 2012 privatization of off-premises liquor sales in Washington State created a unique opportunity to observe retailers learning to set prices from the beginning of the learning process. Tracking this market as it evolved through time, the authors find that firms indeed learn to set more profitable prices, that these prices increasingly reflect demand fundamentals, and that prices ultimately converge to levels consistent with (static) profit maximization. The authors further demonstrate that initial pricing mistakes are largest for products whose demand conditions differ the most from those of previously privatized markets, that retailers with previous experience in the category are initially better informed, and that learning is faster for products with more precise sales information. These findings indicate that firm behavior converges to rational models of firm conduct, but such convergence takes time to unfold and plays out differently for different firms. These patterns suggest the important roles of firms’ learning and heterogeneous firm capabilities.

Fake news advertising—advertising that mimics legitimate news articles—can be harmful if it misleads consumers to take actions they otherwise would not have taken (e.g., purchase an inferior product). However, little is known about whether fake news ads bring in new customers or are merely viewed by people already in the market for the advertised products. The author exploits a Federal Trade Commission–enabled shutdown of fake news advertisements for various products such as acai cleanses and teeth whiteners (but where the product sites continued to remain operational) to identify the extent of consumer interest in the presence and absence of fake news advertising. The findings indicate that interest wanes after the shutdown of fake news advertising, with the probability of a product site not receiving any new visits increasing by 22%. The overall decline in visits caused by the absence of fake news ads occurs despite some substitution by consumers to regular advertisements.