Modeling discrete choices with augmented perception hurdles

Abstract Through creating latent perception hurdles associated with each attribute considered in a stated conjoint experiment, this article describes a model that augments the conventional approach by utilizing the importance ratings provided by respondents prior to the discrete choice stage. The resulting perception hurdle logit (PHL) model has both advantages and disadvantages compared to the conditional logit (CL) and mixed logit models. Although the proposed model may not have the best within‐sample fit, it outperforms the other two models in predicting choices in a hold out sample. In addition, the proposed model is also used to reveal that depending on their own characteristics and the process of the survey, respondents may employ an array of different decision strategies.