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The main objective of this paper is to compare the consequences of treating the attitudinal and perceptual indicators of hybrid discrete choice (HDC) models as continuous or ordinal outcomes. Based on tradition and computational reasons, such indicators are still predominantly treated as continuous outcomes in practice. This usually neglects their nature (as respondents are normally asked to state their preferences, or level of agreement with a set of statements, using a discrete scale) and may induce bias.

We conducted an analysis based on simulated data and real information (two case studies) and were able to find that the distribution of the indicators (especially when associated with non-uniformly spaced thresholds) may lead to a clear deterioration of the model’s overall predictive capacity, when assuming continuous indicators. This, however, does not translate to the goodness-of-fit of the discrete-choice …