Knowledge that Transforms

Are those who are familiar with scientific research on consumer behavior better able to make predictions about phenomena in this field? Predictions were made for 105 hypotheses from 20 empirical studies selected from Journal of Consumer Research. A total of 1,736 predictions were obtained from 16 academics, 12 practitioners, and 43 high school students: The practitioners were correct on 58.2 percent of the hypotheses, the students on 56.6 percent, and the academics on 51.3 percent. No group performed better than chance. This article presents a study on the predictive value of scientific knowledge of consumer behavior. It does this by obtaining predictions from people who should be well acquainted with such knowledge, and comparing their predictions with those by people who are unlikely to have this knowledge. 2 The first section of the article presents the hypotheses. A description of the prediction study is then presented, followed by results and limitations. Finally, suggestions are provided for improving the predictive value of research on consumer behavior. Hypotheses Consumer behavior was expected to be a field in which one could demonstrate gains in predictive validity as. a

This article develops a model for the measurement of human values that, rather than obtain aggregate measurements, identifies distinct value systems within a population and classifies individuals according to them. These value systems are inferred from the stated priority rankings, obtained from each individual via the Rokeach value survey.

In an earlier Journal of Consumer Research article, Kahn, Moore, and Glazer examined the phenomenon of constrained choice in experimental settings and found empirical results that ran counter to generally accepted models of hierarchical choice (e.g., preference trees). In this article, we reexamine those findings. Specifically, our main purposes are (1) to provide an explanation for the deviations from accepted theoretical models, (2) to suggest operational measures for the new constructs identified by Kahn, Moore, and Glazer, and (3) to propose a modification of hierarchical models that improves choice prediction by adjusting for bias against lone alternatives.

This article develops a model for describing the preferences of a group in terms of its individual members. The model incorporates the empirically observed group-polarization phenomenon. It is interesting that the resulting group preference evaluation is essentially a weighted linear model of individual preferences with the addition of an intercept term. The polarization model is empirically tested in two experimental contexts, faculty-candidate and restaurant selection. For both experimental situations, the polarization model performed better for the majority of groups tested in predicting a holdout sample than did either the more common weighted linear model without an intercept (with weights summing to one) or the multilinear model.

The purpose of this research was to explore economic dimensions of a consumer gift-giving model. Two dimensions of extrahousehold gift expenditures were modeled: the probability of giving and the expected value of the corresponding expenditures. Data were from 4,139 households in the Quarterly Interview component of the 1984–1985 U.S. Continuing Consumer Expenditure Survey. The results demonstrated that both the probability of giving and the value of annual expenditures for gifts given outside the consumer unit are related to total expenditures (a proxy for income), family size, life-cycle stage, and education. In addition, the probability of gift giving is related to the number of female adults, ethnicity, and urbanization, and the value of gift expenditures is related to region. Extrahousehold gift expenditures appear to be a luxury—as income increases, gift expenditures increase more rapidly.

Consumers frequently simplify complex choices by setting attribute cutoffs, which are minimum acceptable levels that an alternative must possess to be considered further. We explore the extent to which consumers adapt these cutoffs to the choice environment. We show that, as the reliability of information about the attribute increases, consumers make more severe cutoffs (i.e., fewer attribute levels are acceptable). Further, positive correlations between attributes elicit more severe cutoffs than negative correlations do, and consumers' expectations about the choice outcome partially mediate this relationship. The format of correlational information also affects adaptation: consumers adapt their cutoffs when they are given direct information about the correlation, but not when they are allowed to infer the correlation from a set of alternatives. Overall, consumers appear to adapt to information about reliability and correlations, but they have difficulty assessing correlation from the choice environment.

Although the perception of contextualized objects pervades our everyday experiences, the literature provides little insight into how consumers ascribe meaning to contextualized products, or indeed into what meaning is. We address this gap in the literature by providing a conceptualization of consumption-object meaning and an a priori model for measuring it. An experiment tested several hypotheses concerning how the kind and amount of context affects the meanings people ascribe to ordinary consumption objects (and the labels that they use to identify those meanings). Overall, the findings support the proposed conceptualization.

We demonstrate that a superior, high-share product (beef) could lose its relative position and sales as a result of a change in consumer preference for an attribute (convenience) on which the competition (poultry) was actually weaker. We use multiple data sources to show this has happened for beef and poultry, rather than the alternative explanation of increased health awareness. These sources include United States Department of Agriculture (USDA) consumption data, a time series of new product introductions, and a sample of convenience beef and poultry products. The data support the hypothesis that increased demand for convenience contributed to poultry's success rather than the explanation that increased health awareness is solely responsible.

This article examines the distinction between and the effects of two different types of elaboration on various indicators of ad effectiveness. One type of elaboration, known as item-specific processing, emphasizes the distinctive features of each ad claim. A second type, called relational processing, highlights similarities (e.g., common themes) that link various ad claims. This study shows that recall of ad claims is enhanced when manipulations foster both types of elaboration simultaneously. However, recognition and clustered recall are enhanced only when manipulations invite item-specific and relational processing, respectively. Finally, data on product judgments, consumption intentions, and the correspondence between these types of responses suggest that item-specific processing may have more impact on these measures. C ognitive elaboration, the process of associating new information with knowledge already stored in memory (Greenwald and Leavitt 1984), plays an im-portant role in understanding how consumers respond

Especially since the publication of Sawyer's instructive article on the topic, consumer researchers have been concerned that demand artifacts significantly compromise the validity and generalizability of experimental findings. In this article we provide an overview of the issues surrounding the demand-artifacts controversy, evaluate the preconditions for demand artifacts, and offer a critique of suppositions about the consequences and appropriate control of demand artifacts. Kellaris and Cox's critique of Gorn's well-known classical conditioning experiments provides the backdrop for much of the discussion.