The objective of this research is to understand the demand for information technology among trucking companies. A multivariate discrete choice model is estimated on data from a large-scale survey of the trucking industry in California. This model is designed to identify the influences of each of twenty operational characteristics on the propensity to adopt each of seven different information te...

We propose a multiplicative speci cation of a discrete choice model that renders choice probabilities independent of the scale of the utility. The scale can thus be random with unspeci ed distribution. The model mostly outperforms the classical additive formulation over a range of stated choice data sets. In some cases, the improvement in likelihood is greater than that obtained from adding obs...

despite progress towards greater public engagement, questions about the optimal approach to access public preferences remain unanswered. we review two increasingly popular methods for engaging the public in healthcare priority-setting and determining their preferences; the citizens’ jury (cj) and discrete choice experiment (dce). we discuss the theoretical framework from which each method is de...

This note presents an algorithm that extends a binary choice model to choice among multiple alternatives. Both neoclassical microeconomic theory and Luce choice model are consistent with the proposed algorithm. The algorithm is compatible with several empirical findings (asymmetric dominance and attraction effects) that cannot be explained within standard models.

The attributes that consumers anticipate or expect when choosing among alternatives (i.e., prior to consumption) often differ from the attributes that they actually experience when consuming their chosen alternative. This paper describes, and illustrates with several examples, the calculation of consumer surplus in this situation and the loss in consumer surplus due to the imperfect foreknowled...

In recent years there has been a growing stream of literature in marketing and economics that models consumers as Bayesian learners. Such learning behavior is often embedded within a discrete choice framework which is then calibrated on scanner panel data. At the same time it is now accepted wisdom that disentangling preference heterogeneity and state dependence is critical in any attempt to un...