Journal of Marketing Research

Mediation analysis empirically investigates the process underlying the effect of an experimental manipulation on a dependent variable of interest. In the simplest mediation setting, the experimental treatment can affect the dependent variable through the mediator (indirect effect) and/or directly (direct effect). However, what appears to be an indirect effect in standard mediation analysis may reflect a data-generating process without mediation, including the possibility of a reversed causal ordering of measured variables, regardless of the statistical properties of the estimate. To overcome this indeterminacy where possible, the authors develop the insight that a statistically reliable total effect, combined with strong evidence for conditional independence of the treatment and the outcome given the mediator, is unequivocal evidence for mediation as the underlying causal model into an operational procedure. This is particularly helpful when theory is insufficient to definitely causally order measured variables, or when the dependent variable is measured before what is believed to be the mediator. The procedure combines Bayes factors as principled measures of the degree of support for conditional independence, with latent variable modeling to account for measurement error and discretization in a fully Bayesian framework. The authors reanalyze a set of published mediation studies to illustrate how their approach facilitates stronger conclusions.

Sentiment analysis has fundamentally changed marketers’ ability to assess consumer opinion. Indeed, the measurement of attitudes via natural language has influenced how marketing is practiced on a day-to-day basis. Yet recent findings suggest that sentiment analysis's current emphasis on measuring valence (i.e., positivity or negativity) can produce incomplete, inaccurate, and even misleading insights. Conceptually, the current work challenges sentiment analysis to move beyond valence. The authors identify the certainty or confidence of consumers’ sentiment as a particularly potent facet to assess. Empirically, they develop a new computational measure of certainty in language—the Certainty Lexicon—and validate its use with sentiment analysis. To construct and validate this measure, the authors use text from 11.6 million people who generated billions of words, millions of online reviews, and hundreds of thousands of entries in an online prediction market. Across social media data sets, in-lab experiments, and online reviews, the authors find that the Certainty Lexicon is more comprehensive, generalizable, and accurate in its measurement compared with other tools. The authors also demonstrate the value of measuring sentiment certainty for marketers: certainty predicted the real-world success of commercials where traditional sentiment analysis did not. The Certainty Lexicon is available at www.CertaintyLexicon.com.

Advertising to a consumer provides potentially useful information to the consumer and moves them along the purchase journey, and tracking the consumer's online activities enables an advertiser to infer the consumer's purchase journey state and target repeat ads accordingly. However, many consumers dislike being tracked, and, furthermore, repeat advertising may lead to ad wearout. The authors develop a model with consumers, an advertiser, and an ad network to investigate, under the preceding considerations, the impact of regulations that endow consumers with the choice to opt in to or out of online tracking. The authors find that, if ad effectiveness is intermediate, opting in to tracking decreases ad repetition; otherwise, opting in increases ad repetition. To make an opt-in decision, a consumer weighs the cost of ad wearout from repeat ads against the benefit of obtaining potentially relevant product information from them, and the consumer opts in to tracking if either ad effectiveness is intermediate or sensitivity to ad wearout is low. This opt-in pattern creates counterintuitive implications; for instance, higher ad effectiveness, even though it implies higher ad valuation for the advertiser, may reduce repeat ads and the ad network's profit. Under regulation that requires consumer consent for tracking, the results shed light on when and why consumers give such consent, and provide useful insights for practitioners and policy makers.

Marketers frequently create social media content (i.e., firm-generated content; FGC) to ignite interest in new movies. Thus, there is a clear need to understand the magnitude and heterogeneity of the effect of FGC on movie demand and associated user-generated content (UGC). The authors empirically examine the complex interactions among FGC, UGC, and sales using social media (tweet) data that are normally available to firms. They investigate two potential mechanisms by which FGC may drive box office revenues: (1) a direct mechanism, such that users who see FGC directly drive revenue, and (2) an indirect “ripple effect,” by which FGC increases movie-related UGC, which then drives consumption. By analyzing 145,502 firm-generated and 5.9 million user-generated Twitter posts associated with 159 movies, the authors find a positive and significant effect of FGC on movie sales, which UGC fully mediates, which supports the indirect ripple effect reasoning. Impressions of FGC by followers of firm accounts, as opposed to nonfollowers of firm accounts, mainly drive the effect of FGC on UGC. In addition, FGC by movie accounts is more effective than that by actors and studios. Firms’ regular posts with a movie-specific hashtag are more effective than replies, retweets, and posts without the hashtag. The finding of the ripple effect suggests that movie executives should focus on creating FGC that sparks conversations among followers when new movies are released.

This research aims to advance the understanding of audio branding by investigating the effect of an understudied auditory attribute, timbre, in the context of brand audio logos. Specifically, the authors propose, and provide evidence in ten studies, that timbral sound quality in audio logos (i.e., roughness/smoothness) informs abstract judgments of brand personality (i.e., ruggedness/sophistication). Study 1 shows that the industry practice of altering instrumentation, and thus timbre, in audio logos can change personality perceptions of even well-known brands. This effect persists when the sound source is kept constant with various instruments (Studies 2a–2d), with a combination of instruments (Study 3), and in the absence of an identifiable sound source (Study 4). The authors test specific acoustic underpinnings of timbral sound quality perceptions (Study 4) and show that the effect on brand personality judgments is counteracted by incongruent sensory information from another modality (Study 5). The results of Study 6 suggest that the influence of timbral sound quality on brand personality perceptions is nonconscious, as consumers are unaware of the extent to which the stimulus affects their judgments. Study 7 shows downstream consequences for purchase intentions. Practical implications, theoretical contributions, and directions for future research are discussed.

Nonprofit organizations often position their charitable efforts as fulfilling the immediate needs of those who are disadvantaged (termed “immediate aid appeals”). This study explores an alternative positioning strategy focused on the use of autonomous aid appeals, which promote the use of donated funds to facilitate the eventual self-sufficiency of those in need. Seven studies show that people are more likely to donate to a charity that uses autonomous aid appeals than immediate aid appeals. The authors generalize this effect to various contexts and examine it with actual donation behavior. They find that managerially relevant boundary conditions support a serial mediation model first through perceptions of impact and then by feelings of hope for the recipient's future. To support the proposed framework, they conduct mediation analyses and two process-by-moderation studies. The findings have practical implications for charities and their promotional messaging.

Standard choice-based conjoint models often ignore or insufficiently approximate consumers’ budget constraints, despite the prominent role of budget constraints in economic theory. The authors offer a theoretically motivated improvement to the choice-based conjoint model that is especially appropriate for high-ticket durable goods and develop a Bayesian method for the inference of unobserved budget constraints. The proposed method leverages respondents’ stated budget constraints that suffer from measurement error and respondents’ financial demographic variables as additional information to reduce the dependency on functional form assumptions in the estimation. The authors show that accounting for budget constraints substantially increases model fit and the accuracy of competitive pricing in an industry-grade discrete-choice experiment on consumer preferences for high-end laptops. The proposed model performs better than the canonical linear price benchmark model, which is not flexible enough to approximate budget constraints. In theory, more flexible utility specifications, such as the nonlinear dummy price model, can approximate consumers’ budget constraints. However, they perform poorly when only finite data are available. The authors conclude that applied researchers in industry and academia will benefit from having a better tool for estimating budgets in high-ticket categories.

This research investigates how shopping on a weekday or a weekend moderates the impact of music on supermarket sales. Contrary to the intuitive beliefs of interviewed store managers, a meta-analysis, two field studies, and a controlled experimental study indicate that playing pleasant music (vs. no music) in supermarkets on weekdays enhances sales, an effect not found on weekends. Theorizing and interviews with shoppers suggest a potential reason for this week-part difference: Shoppers are more mentally depleted on weekdays (vs. weekends). A final study demonstrates and tests mental depletion as the driving factor for how shoppers are affected by music during different week parts. When consumers are depleted (e.g., on weekdays) music increases affect, which mediates the impact of music on sales. The results of the studies further indicate that week part plays a significant role in determining the impact of in-store music on sales. This article concludes with a discussion of the substantive and theoretical importance of incorporating the impact of week parts to predict in-store marketing effectiveness.

Consumers regularly attempt to improve themselves. This research examines how consumers think about flexibility during goal pursuit, for themselves and others. Flexibility involves leaving details of a plan, such as when to go to the gym or what to eat, open or easy to change, whereas rigid plans determine those details in advance. Here, several studies across a variety of goals show that people usually choose rigid plans for others. However, people are more likely to opt for some flexibility in their own plans. This occurs because many people believe flexible plans are less effective, but also more appealing (or less unpleasant), than rigid ones. Choosing for oneself, versus for someone else, increases the degree to which one follows one's heart (i.e., relies on feelings and desires), which makes people more likely to choose the more appealing option, flexibility. Asking people to “follow their heads” instead (i.e., rely on logic and reason) causes people to choose similar (rigid) plans for themselves and others. Finally, the authors use this framework to increase preferences for rigid fitness plans in a field experiment. This research provides insight into the psychology of flexibility and how to nudge consumers to set themselves up for success.