ABSTRACT
This chapter is an overview of the motivation for, and structure of, advanced discrete choice models derived from random utility maximization. The discussion is intended to familiarize readers with structural alternatives to the multinomial logit. Before proceeding to review advanced discrete choice models, we first summarize the assumptions of the multinomial logit (MNL) formulation. This is useful since all other random utility maximizing discrete choice models focus on relaxing one or more of these assumptions.
