Random utility (RU) models are well-established methods for describing disc
rete 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 thre
e major families of models. The paper summarizes and classifies the differe
nt approaches. The advantages and limitations of the various alternatives a
re outlined. Practical issues in implementing the models are also discussed
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