Knowledge that Transforms

Firms and other entities provide category-level product attribute information via attribute filters and other tools to aid consumers in filtering, evaluating, comparing, and choosing products. This research examines how displaying this information as a range with or without the distribution of values systematically affects judgments involving attribute value comparisons. Specifically, distributions draw attention away from attribute values, reducing the importance of attribute value differences. With this reduced importance, consumers are less sensitive to attribute value differences; thus, consumers evaluate individual products more positively as they seem more similar to the best available option. Likewise, wider bands of attribute values are selected when filtering product options, as the minimum and maximum values chosen seem less different. Reduced sensitivity to differences also has implications for choices involving tradeoffs between attributes. Importantly, the presence of a distribution itself is the primary driver of this effect, more so than distribution type, as the effect is largely independent of the type of distribution displayed (e.g., normal, bimodal, skewed, uniform). Across six main and seven supplemental experiments, this research highlights a novel consideration for how consumers filter options, form preferences, and choose products. These findings have practical implications and highlight important topics for future research.

With the rise of machine learning and “big data,” many large yet spurious relationships between variables are discovered, leveraged by marketing communications, and publicized in the media. Thus, consumers are increasingly exposed to many large-magnitude relationships between variables that do not signal causal effects. This exposure may carry a substantial cost. Seven studies demonstrate that the magnitudes of relationships between variables can distort consumers’ judgments about whether those relationships reflect causal effects. Specifically, consumers often use a magnitude heuristic: consumers infer that relationships with larger perceived magnitudes are more likely to reflect causal effects, even when this is not true (and even when relationships’ correlations are held constant). In many situations, relying on the magnitude heuristic will distort causality judgments, such as when large-magnitude relationships between variables are spurious, or when normatively extraneous factors (e.g., reference points) distort perceptions of magnitudes. Moreover, magnitude-distorted (mis)perceptions of causality, in turn, distort consumers’ purchase and consumption decisions. Since consumers often encounter spurious relationships with large magnitudes in the health domain and in other consequential domains, the magnitude heuristic is likely to lead to biases in some of consumers’ most important decisions.

Contemporary developments in material duplication promise product alternatives that are physically and sensorially indistinguishable from incumbent offerings. When fully realized, such duplicate offerings should obsolete the incumbents as a consequence of wider availability and lower monetary and social costs. Disruption will be impeded, however, if consumers favor incumbent products on the basis of non-material qualities. The authors show that the influence of such qualities depends on both the product category and characteristics of the consumer. In particular, when a creator is central to the product and when the consumer is inclined toward extraordinary beliefs, the influence of origin looms especially large. By contrasting origin and substance, the present research exposes dualistic thinking in consumers’ product evaluations, enriches prior research on authenticity and extraordinary beliefs, and contributes to the stubborn problem of technology adoption.

When consumers select bundles of goods, they may construct those sequentially (e.g., building a bouquet one flower at a time) or make a single choice of a prepackaged bundle (e.g., selecting an already-complete bouquet). Previous research suggested that the sequential construction of bundles encourages variety seeking. The present research revisits this claim and offers a theoretical explanation rooted in combinatorics and norm communication. When constructing a bundle, a consumer chooses among different choice permutations, but when selecting amongst prepackaged bundles, the consumer typically considers unique choice combinations. Because variety is typically overrepresented among permutations compared to combinations, certain consumers (in particular, those with similar attitudes toward items that could compose a bundle) are induced by these different numbers of pathways to variety to display more or less variety-seeking behavior. This is in part explained by the variety norms communicated by different choice architectures, cues most likely to be inferred and used by those who are indifferent between the potential bundle components and thus looking for guidance. Across 5 studies in the main text and 11 in the web appendix, this article tests this account and offers preliminary exploration of newly identified residual effects that the pathways-to-variety account cannot explain.

Eight studies (N = 5,025) demonstrate that consumers persist more when they must complete a target number of goal-related actions before receiving continuous rewards (i.e., what we term work-to-unlock rewards) than when they receive continuous rewards for their effort right away (i.e., what we term work-to-receive rewards). The authors suggest that the motivating power of work-to-unlock rewards arises because these rewards (1) naturally encourage consumers to set an attainable goal to start earning rewards, motivating consumers initially through goal setting and (2) keep consumers engaged after reaching this goal due to low perceived progress in earning rewards. A work-to-unlock reward structure increases persistence relative to standard continuous rewards across a variety of consumer-relevant domains (e.g., exercising, flossing, evaluating products), and even when work-to-unlock rewards offer rewards of a lower magnitude. Further, a work-to-unlock reward structure outperforms other reward structures that encourage goal setting. Lastly, the authors identify a theoretically consistent boundary condition of this effect: the length of the unlocking period.

Mediation analysis is used to study the relationship between stimulus and response in the presence of intermediate, generative variables. The traditional approach to the analysis utilizes the results of an aggregate regression model, which assumes that all respondents go through the same data-generating mechanism. We introduce a new approach that is able to uncover the heterogeneity in mediating mechanisms and provides more informative insights from mediation studies. The proposed approach provides individual-specific probabilities to mediate as well as a new measure of the degree of mediation as the prevalence of mediation in the sample. Covariates in the proposed model help describe the variation in the probability to mediate among respondents. The empirical examination of published studies demonstrates the presence of heterogeneity in mediating processes and supports the need for this new approach. We present evidence that the results of our more flexible heterogeneous mediation analysis do not necessarily agree with the traditional aggregate measures. We find that the conclusions from the aggregate analysis are neither sufficient nor necessary to claim mediation in the presence of heterogeneity. A web-based application allowing researchers to analyze the data with the proposed model in a user-friendly environment is developed.

Purchase decisions typically involve tradeoffs between attributes associated with desirability (e.g., quality) and feasibility (e.g., price). In this article, we examine how the decision context impacts consumers’ preference between a high-desirability (HD) option and a high-feasibility (HF) alternative. Nineteen studies demonstrate a novel context effect, the “upscaling effect,” whereby introducing a symmetrically dominated decoy option to a set (i.e., an option that is inferior compared to all alternatives in the set) leads to an increase in the choice share of the HD option. To account for the upscaling effect, we advance a two-stage model of consumer decision-making for decisions that involve tradeoffs between desirability and feasibility. According to our model, when the decision context provides a reason for choosing either option, such as when a decoy option is added to the set, consumers prioritize reasons that support choice of HD options over HF alternatives. Our model can explain the upscaling effect, as well as other findings reported in the literature, such as asymmetric attraction effects (Heath and Chatterjee 1995) and asymmetric sales promotion effects (Blattberg and Wisniewski 1989). Furthermore, the upscaling effect holds important managerial implications because it provides an effective way to increase sales of high-end products.