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Some cultural products (e.g., books and movies) catch on and become popular, while others fail. Why? While some have argued that success is unpredictable, we suggest that period-to-period shifts in sentiment—what we term sentiment volatility—enhance engagement. Automated sentiment analysis of over 4,000 movies demonstrates that more volatile movies are evaluated more positively. Consistent with the notion that sentiment volatility makes experiences more stimulating, the effect is stronger in genres where evaluations are more likely to be driven stimulation (i.e., thrillers rather than romance). Further, analysis of over 30,000 online articles demonstrate that people are more likely to continue reading more volatile articles. By manipulating sentiment volatility in follow-up experiments, we underscore its causal impact on evaluations, and provide evidence for the role of stimulation in these effects. Taken together, the results shed light on what drives engagement, the time dynamics of sentiment, and cultural analytics or why some cultural items are more successful.

This article examines how unexpected changes in the marketing mix of one product in a retail setting can influence demand for other, unrelated, items. Results from two laboratory studies show that spillover effects can occur in response to both positive and negative changes in either the price or quality of a product, such that positive changes increase total spending on other items and negative changes reduce it. The results also demonstrate that an attributional process underlies these effects, indicating that consumers experience specific affective responses directed at the retailer that lead them either to reward or punish the retailer accordingly.

The process by which individuals make recurrent decisions about when to replace durable goods is examined. Two experiments are reported in which subjects play the role of purchasing agents who must repeatedly decide whether to keep a currently owned manufacturing device or replace it with a superior new one, given uncertainty about the future performance of new and currently owned machines. Replacement patterns are compared with those that would be predicted if subjects made decisions as rational economic agents, following the principles of optimal replacement theory. This comparison reveals a number of systematic departures from optimality that do not vanish with experience. Among these are a tendency to replace at a slower rate than would be predicted by normative theory and a tendency to weigh opportunity costs arising from obsolescence greater than those arising from product deterioration. In addition, subjects display a bias against making replacement purchases given short lapses of time since the previous replacement. The findings are interpreted in terms of known biases in decision making under uncertainty in dynamic and static settings.

This article examines how multiattribute impressions are formed in riskless choice and judgment when there is uncertainty or ambiguity associated with attribute-importance weights. Building on previous results in the modeling of ambiguity in probabilities, a mathematical theory of multiattribute judgments under weight uncertainty is developed. The theory incorporates framing effects for ambiguous weights in multiattribute judgments, similar to the gain-loss framing effects found in studies of preferences for lotteries. Specifically, it is shown that the importance of an attribute depends on whether it is seen as enhancing or preserving an expected level of utility in a category. The results of three experiments provide support for the predicted dependency of the effects of weight uncertainty on an attribute's framing. The data also suggest that, within frames, the effects of increasing uncertainty may not be additive across attributes. In particular, given pairs of uncertain attributes with different frames, subjects acted as if they were applying a single frame to both attributes, resulting in a common direction for the weight-uncertainty effect.

The sensitivity of the parameters and fit of compensatory choice models to contextual variations in information processing strategies is examined. A set of predictions is derived concerning specification errors which may arise when a compensatory model misrepresents a “true,” noncompensatory choice process. These predictions are then tested in an experimental analysis of apartment choice behavior. Logit analysis and protocol analysis are employed to assess how the parameters and fit of a compensatory model vary in light of changes in the underlying pattern of information processing across choice sets of differing sizes. Although attribute usage and parameter variation across set sizes conformed to theoretical expectations, a hypothesized decrease in predictive accuracy was not supported.

In a recent article, Keller and Staelin (1987) reexamined one of the more controversial questions in consumer research literature: Is it possible to provide consumers with too much information when making choices? Their work contained the valuable and insightful conjecture that increasing quantity of information available to consumers increases the overall quality of information as well, when quality is defined as the cumulative importance of each bit of information. Because prior research had not explicitly controlled these two effects, degrading effects of increasing information quantity may have been muted by unintended, but commensurate, increases in information quality. Their research objective was to decompose these two sources of variance experimentally. Keller and Staelin found that when information quality was held constant, increases in information had a strong negative effect on decision accuracy. When information quantity was held constant, increasing information quality had a positive effect, at least to a point. Keller and Staelin (1987, p. 212) interpreted their results as evidence that consumers can be overloaded with information. The results of this study imply that consumers are not able to shield themselves from being overloaded when "too much" information is made readily available to the decision maker; too much being related to the quantity and average quality of the available information.