Measuring and modeling the (limited) consistency of free choice attitude questions

On average, respondents who give a positive answer to a binary free choice attitude question are NOT more likely, if surveyed again, to respond positively than to response negatively. However, stronger brands obtain more repeated positive answers. Our model shows why these two effects have to happen, even though all brands in a category benefit from the same reliability.survey reliability; attitude measurement; stochastic models; beta-binomial model; brand image; market research

Modeling the latent preference structure implied by discrete choice experiments

Applications of discrete choice experiments to study consumer choice behavior have grown significantly over the past decade. Typically, discrete choice experiment data are analyzed using McFadden’s Multinomial Logit (MNL) model or a more sophisticated extension that relaxes some of MNL’s restrictive assumptions. Advantages of MNL for analyzing discrete responses are well-known to marketing academics and practitioners, but arguably the latent preference structure that explains discrete responses has yet to be clearly articulated. For example, integration of latent variable systems and discrete choice experiments has several advantages. First, it is possible to model the variances associated with consumers’ discrete choices by introducing latent preference variables, which can provide useful information on the consistency of consumers’ choices. Second, one can specify fully generalized models whereby brand characteristics explain variation in consumers’ latent brand preferences to provide insight into processes that drive consumers’ preferences. Third, the resulting latent variable systems generalize to all of the characteristics of brands one chooses to study. We illustrate the integration in an application to consumer preferences for brands in the “last minute” hotel accommodation market. For convenience, we use Joreskog’s LISREL model to fit the latent structure, although other latent variable systems are considered. The study has immediate implications for researchers analyzing stated preference data, with additional implications for potential applications to revealed preference data

The influence of individuals in forming collective household preferences for water quality

Preference for water quality and its nonmarket valuation can be used to inform the development of pricing policies and long term supply strategies. Tap water quality is a household concern. The objective status quo of water provision varies between households and not between individuals within households, while charges are levied on households not individuals. Individual preferences differ from collective preferences. In households where there are two adults, we examine the preferences of each separately and then as a couple in collective decisions. We show the level of influence each has in developing the collective decision process. We use discrete choice experiments to model preference heterogeneity across three experiments on women, men and on both. We propose a random utility model which decomposes the error structure in the utility of alternatives so as to identify the individual influence in collective decisions. This approach to choice data analysis is new to environmental economic