Alan D. J. Cooke

Avoiding Future Regret in Purchase-Timing Decisions

When deciding when to make a purchase, people often compare their outcomes to those that would have occurred had they purchased earlier or later. In this article, we examine how pre- and postpurchase comparisons affect regret and satisfaction, and whether consumers learn to avoid decisions that result in regret. In the first two experiments, we show that information learned after the purchase has a greater impact on satisfaction than information learned before the purchase. In addition, negative price comparisons have a greater impact on satisfaction than positive comparisons. These results imply that if consumers who receive postpurchase information wish to avoid future feelings of regret, they should defer their purchases longer. Our second two experiments demonstrate this phenomenon: Subjects who were exposed to postchoice information set higher decision thresholds, consistent with the minimization of future regret. Paradoxically, providing subjects with additional postchoice information resulted in decreased average earnings, suggesting that consumers may try to avoid future regret even when doing so conflicts with expected value maximization.

Marketing the Unfamiliar: The Role of Context and Item-Specific Information in Electronic Agent Recommendations

Electronic agents have the capacity to help consumers discover new products and generate demand for unfamiliar products. This article explores how consumers respond to recommendations of unfamiliar products made by electronic agents. Two studies using simulated music shopping agents show that (1) additional recommendations of familiar products serve as a context in which unfamiliar recommendations are evaluated; (2) when the presentation of the recommendations makes unfamiliar and familiar products appear similar, evaluative assimilation results; and (3) when additional information about unfamiliar products is given, consumers discriminate them from the familiar products, which produces evaluative contrast. These results establish that information that leads to higher evaluations when context is absent can lead to contrast and lower evaluations in the presence of attractive contextual recommendations.

Trade-offs depend on attribute range.

Contextual effects due to attribute range were examined in single-attribute and multiattribute judgments. The effect of a given attribute difference was greater when presented in a narrow range than a wide range. Stretching and shrinking the range of attributes altered the rank orders of judgments assigned to the same stimuli in different ranges. Trade-offs between time and money, one measure of ability and another, and achievement and motivation depended on attribute range. Although changes in trade-offs can result from changes in weights, data were consistent with the hypothesis that attribute range influences scale values. Scale values for common levels of an attribute spanned a wider interval when the attribute range was narrow than when the attribute range was wide.

Different Scales for Different Frames: The Role of Subjective Scales and Experience in Explaining Attribute-Framing Effects

Consumers respond more favorably to positively framed attribute information than to negatively framed attribute information, a finding that has been attributed to the affective associations evoked by each frame. We contend that framing effects also depend on the range and level of reference values used to evaluate attribute information. When the range of reference values is narrower for a positive frame than a negative frame, attribute values above expected performance levels favor the positively framed information and attribute values below expected performance levels favor the negatively framed information. When the range of reference values is wider for a positive frame than a negative frame, the opposite pattern emerges. Experience with a frame is one factor that reduces the range of reference values recruited to judge attribute information.

Stimulus Context and the Formation of Consumer Ideals

When a choice set consists of a distribution of alternatives with correlated benefits and costs, consumers often exhibit single-peaked preferences—they prefer an alternative having moderate costs and benefits. Theories disagree about how adding additional lower benefit/lower cost or higher benefit/higher cost alternatives to this choice set will affect relative preferences for the initial set of alternatives. Prototype theory predicts that adding alternatives should produce assimilation, whereas multiattribute range-frequency theory predicts that it creates contrast. We reconcile these two theories by assuming that single-peaked preferences reflect a composition of underlying benefit and cost valuations. Moreover, we claim that the correlational structure of the benefit and cost dimensions in the contextual stimuli determines whether these stimuli will exert an assimilation or contrast effect. We show that when benefits and costs are correlated (uncorrelated), adding alternatives that extend the range of offerings produces assimilation (contrast) for preference judgments. We propose a cost-benefit trade-off model that incorporates elements of single-peaked preference theory and range-frequency theory to explain the complex fashion in which contextual stimuli affect consumer ideals.

An Experimental Test of a General Class of Utility Models: Evidence for Context Dependency

Generic utility theory, a general axiomatization of utility principles developed by Miyamoto (1988, 1992), is discussed as a formulation that captures a large class of utility theories. Several general mathematical functions were used to specify further the scaling of utility within this class of models. The scaling parameters in the generic utility representation should remain invariant across gambling contexts, and this predicted invariance provided a means for testing the theory. Evidence is presented that the prediction of scaling-parameter invariance is violated. This failure is interpreted as a consequence of employing an absolute reference system for a problem that is context-sensitive.

Attentional Contrast During Sequential Judgments: a Source of the Number-Of-Levels Effect

Conjoint analysis is used to measure the importance of attribute-level trade-offs. A methodological anomaly is the number-of-levels effect; that is, as the number of intervening attribute levels increases, the derived importance weight of an attribute increases. The authors use three studies to show that attentional processes contribute to the number-of-levels effect. When there is an inequality in the number of levels across attributes, a given profile may include levels of one attribute that are relatively more novel than levels of the accompanying attributes. A process of attentional contrast directs attention toward the relatively novel attribute levels within each profile. Increased attention toward these attribute levels results in a larger derived importance weight for the attributes defined on those levels.

When absence begets inference in conjoint analysis

We appreciate the opportunity to comment on the provocative model developed by Bradlow, Hu, and Ho (BHH; 2004). Although conjoint analysis necessarily encompasses behavioral theory and statistical technique, recent developments within conjoint research have attended more to the latter. Bradlow, Hu, and Ho should be applauded for trying to bridge this divide and raise awareness of conjoint’s behavioral foundations. Specifically, BHH tackle the pragmatic design problem that arises when a full-factorial design results in an exceedingly large number of complex profiles. A common solution is to devise a set of partial profiles, each described on a subset of the attributes, and assume that respondents will restrict their evaluative assessments to the explicitly presented attributes within each profile. Bradlow, Hu, and Ho argue that this assumption is a convenient fiction and that respondents are likely to impute missing profile values. Although the notion that respondents might supplement profile information with inferred levels of missing attributes is not entirely new (e.g., Meyer 1981), the specific model that BHH propose is unique in the imputation process it proposes. Our objectives in this comment are to evaluate the proposed process in the context of the existing behavioral literature and suggest possible directions for the codevelopment of behavioral knowledge and conjoint application.

Learning from Mixed Feedback: Anticipation of the Future Reduces Appreciation of the Present

Consumers can evaluate their past choices by comparing their obtained outcome to other possible outcomes. We demonstrate that how people process this comparative feedback depends on whether they use it to prepare for future decisions. In particular, the anticipation of similar future choices increases consumers’ sensitivity to comparisons with better alternatives and reduces their liking of the chosen option. Our findings indicate that forward-looking consumers selectively test the hypothesis that their current choice can be improved on and, as a result, disproportionately attend to the unfavorable comparisons and fail to appreciate the value of their current choice.

Utility Invariance Despite Labile Preferences

Publisher Summary This chapter discusses the robustness of preference reversals as well as the research in the domain of risky decision making that goes beyond simple demonstrations of preference reversals based on a few pairs of gambles. It explains how the entire preference order over a large set of gambles changes with the response mode. It examines preference reversals in a riskless domain in which subjects state their preferences for apartments using choices and ratings of attractiveness. The chapter proposes a two-pronged theory of preference reversals. The attribute judged more important has a greater effect in choices than in ratings. There is also an explanation as to how two pronged theory, which assume that subjects change either strategies or weights across tasks, give a coherent account of many important properties of the data while allowing the elicitation of utilities or psychological values to remain constant across tasks. The chapter illustrates that, with the appropriate models, utilities are stable and have meaning over and beyond the task from which they are derived.