04/03/2016
On the Class of Attitudinal Discrete Choice Models
Manish Aggarwal
Working Papers
The complex human attitudinal character plays an important role in the real world decision
making. To this end, we present a family of extended probabilistic discrete choice models. The
attitude-based variants of multinomial logit, probit, nested, and mixed multinomial models are
presented. The proposed models are further empowered through their generalization leading to a
host of exponential attitudinal discrete choice models. It is shown that the existing models are
the special cases of the proposed models that allow to generate a very wide range of choice
probabilities in accordance with the adjustable parameter(s). The usefulness of the proposed
models in modelling a decision-maker's decision model is shown in a sequel paper.