Knowledge that Transforms

New empirical models of consumer demand that incorporate social effects seek to measure the causal effect of past adopter's behavior—the “installed-base”—on current adoption behavior. Identifying such causal effects is challenging due to several alternative confounds that generate correlation in agents' actions. In the absence of experimental variation, a preferred solution has been to control for these spurious correlations using a rich specification of fixed effects. The authors show that fixed-effects estimators of this sort are inconsistent in the presence of installed-base effects; in simulations, random-effects specifications perform even worse. The analysis reveals the tension the applied empiricist faces in this area: a rich control for unobservables increases the credibility of the reported causal effects, but the incorporation of these controls introduces biases of a new kind in this class of models. The authors present two solutions: a modified version of an instrumental variable approach and a new bias-correction approach, both of which deliver consistent estimates of causal installed-base effects. The empirical application to the adoption of the Toyota Prius Hybrid in California shows evidence for social influence in diffusion and reveals that implementing the bias correction reverses the sign of the measured installed-base effect. The authors also discuss implications of the results for identification of models in marketing involving state dependence in demand, and incorporating discrete games of strategic interaction.

Consumers' time allocation decisions among various activities are fundamental to marketing research and consumer behavior. The authors construct a dynamic panel data model to examine how consumers allocate time to a portfolio of leisure activities over time. The data comprise a longitudinal panel in which the authors tracked 287 U.S. consumers' time use, consumption motives, and expertise measures on a weekly basis from January to June 2011. This is the first empirical research to examine the underlying mechanisms that guide the dynamics of an individual's activity consumption. The authors demonstrate that expertise contributes to the perceived benefits of an activity, which in turn leads to high value associated with it. Expertise also directly influences value obtained from an activity. This expertise, in turn, is acquired over time through past consumption. This finding implies a chain from expertise to value to time use and back to expertise, which may lead consumers to form a lifestyle in which they specialize in a subset of activities they know well. Consequently, expertise can be regarded as a key variable that explains lifestyle choices.

The authors measure the revenue and cost implications to supermarkets of changing their price positioning strategy in oligopolistic downstream retail markets. Their approach formally incorporates the dynamics induced by the repositioning in a model with strategic interaction. They exploit a unique data set containing the price format decisions of all U.S. supermarkets in the 1990s. The data contain the format change decisions of supermarkets in response to a large shock to their local market positions: the entry of Wal-Mart. The authors exploit the responses of retailers to Wal-Mart entry to infer the cost of changing pricing formats using a revealed-preference argument. The interaction between retailers and Wal-Mart in each market is modeled as a dynamic game. The authors find evidence that entry by Wal-Mart had a significant impact on the costs and incidence of switching pricing strategy. Their results add to the marketing literature on the organization of retail markets and have implications for long-term market structure in the supermarket industry. Their approach, which incorporates long-term dynamic consequences, strategic interaction, and sunk investment costs, may be used to empirically model firms’ positioning decisions in marketing more generally.

Why do bidders in buyer-determined procurement auctions often bid above the lowest observed bid over the course of the auction? Are such bidding patterns meaningful? In this research, the authors propose that because bidders are differentiated in their value to the buyer and competition in these auctions is anonymous, bidders infer their potential quality advantage or disadvantage through their observation of competitive bids and incorporate this information into their responses and price bids. Using point-by-point bid data from two industrial procurement auctions, the authors show that bidders appear to be making inferences about their own implied quality differentials and adjust their bidding strategies and bidding aggression accordingly. Specifically, they find that high-quality bidders tend to be more aggressive in bidding against potentially higher-quality competition and less aggressive when bidding against potentially lower-quality competition. In contrast, low-quality bidders appear aggressive regardless of their implied quality in relation to the competition. The authors conclude with a discussion of implications for management and auction design.

Different framing of the same duration (one year, 12 months, 365 days) can influence consumers’ impressions of subjective duration, thereby affecting their judgments and decisions. The authors propose that, ironically, self-relevance amplifies this duration framing effect. Consumers for whom a particular self-improvement domain is personally relevant are less likely to adopt a one-year self-improvement plan as compared with a 12-month plan because they perceive it as longer and more difficult. This bias is more likely to manifest in consumers who report that the task is highly personally relevant to them, who are making predictions for themselves (vs. others), and who have high (vs. low) task involvement. Personal relevance amplifies this effect because it prompts process-focused simulation of the plan, consequently increasing susceptibility to spurious duration and difficulty cues embedded in frames.

Across five studies, the authors demonstrate that warm (vs. cool) temperatures deplete resources, increase System 1 processing, and influence performance on complex choice tasks. Real-world lottery data (pilot study) and a lab experiment (Study 1) demonstrate the effect of temperature on complex choices: People are less likely to make difficult gambles in warmer temperatures. Study 2 implicates resource depletion as the underlying process; warm temperatures lower cognitive performance for nondepleted people but do not affect the performance of depleted people. Study 3 illustrates the moderating role of task complexity to show that warm temperatures are depleting and decrease willingness to make a difficult product choice. Study 4 juxtaposes the effects of depletion and temperature to reveal that warm temperatures hamper performance on complex tasks because of the participants’ increased reliance on System 1 (heuristic) processing.