On the similarities between random regret minimization and mother logit: The case of recursive route choice models

We adapt and extend the RRM model proposed by Chorus (2014) to the case of recursive logit (RL) route choice models (Fosgerau et al., 2013). We argue that these RRM models can be cast as mother logit models and we define such models that are equivalent to the RRM ones considered in this paper. The results show that one of the RRM models and its mother logit equivalent has the best out-of-sample fit indicating that utility functions based on attribute differences best explains the choices in our application.