A semi-compensatory discrete choice model with explicit attribute thresholds of perception

Applying the model to real and simulated data allowed us to conclude that if thresholds exist in the population, the use of compensatory models such as Multinomial Logit or even Mixed Logit, can lead to serious errors in model estimation and, therefore, in the computation of marginal rates of substitution such as the subjective value of time, as well as in prediction. Although the Mixed Logit model can deal with random parameters allowing to treat taste differences, we found it could not be used to accommodate non-compensatory behaviour or to represent the existence of thresholds.