Foundations of Stated Preferences Elicitation provides the reader with stated preference data collection methods, discrete choice models, and statistical analysis tools that can be used to forecast demand and assess welfare impacts for new or modified products or services in real markets, and summarize the conditions under which the reliability of these methods has been demonstrated or can be tested. One focus is the collection of preference and related data from consumer responses in hypothetical choice experiments, particularly conjoint analysis methods that have proven useful in market research. Another is the economic theory and statistical analysis of choice behavior, revealed or stated, and an economic framework for forecasting market demand and measuring consumer welfare. The treatment is informed by and benefits from experiments on perceptions and decision-making behavior in cognitive science and behavioral economics, and includes methods that can accommodate features of consumer choice that impact forecast reliability such as anchoring, adaptation to the status quo, and sensitivity to context. However, the authors' emphasis is on forecasting tools developed from traditional economic consumer theory and does not touch on the implications of behavioral consumer theory for demand forecasting.

Discrete Choice Analysis presents these results in such a way that they are fully accessible to the range of students and professionals who are involved in modelling demand and consumer behavior in general or specifically in transportation - whether from the point of view of the design of transit systems, urban and transport economics, public policy, operations research, or systems management and planning. The methods of discrete choice analysis and their applications in the modelling of transportation systems constitute a comparatively new field that has largely evolved over the past 15 years. Since its inception, however, the field has developed rapidly, and this is the first text and reference work to cover the material systematically, bringing together the scattered and often inaccessible results for graduate students and professionals. Discrete Choice Analysis presents these results in such a way that they are fully accessible to the range of students and professionals who are involved in modelling demand and consumer behavior in general or specifically in transportation - whether from the point of view of the design of transit systems, urban and transport economics, public policy, operations research, or systems management and planning. The introductory chapter presents the background of discrete choice analysis and context of transportation demand forecasting. Subsequent chapters cover, among other topics, the theories of individual choice behavior, binary and multinomial choice models, aggregate forecasting techniques, estimation methods, tests used in the process of model development, sampling theory, the nested-logit model, and systems of models. Discrete Choice Analysis is ninth in the MIT Press Series in Transportation Studies, edited by Marvin Manheim.