Author(s): Baltas G, Doyle P
Random utility (RU) models are well-established methods for describing discrete choice behavior. Recently, there has been a strong upsurge in interest driven by advances in data gathering and estimation technology. This review paper describes the principles and issues, and develops a taxonomy of three major families of models. The paper summarizes and classifies the different approaches. The advantages and limitations of the various alternatives are outlined. Practical issues in implementing the models are also discussed.
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