A multidimensional scaling methodology (STUNMIX) for the analysis of subjects preference/choice of stimuli is presented, which integrates previous models into a single framework. Locations of the stimuli and the ideal-points of derived segments of subjects on latent dimensions are estimated...

Unobserved heterogeneity in random utility choice models can be dealt with by specifying either a multinomial or a normal distribution of the coefficients, leading to finite mixture logit and mixed logit models. Focusing on the former, we show that individual-level estimates and predictions of...