Summary: The preference disaggregation paradigm in multi-criteria decision analysis allows inferring a multicriteria preference model for decision makers from their holistic judgments. In the well-known additive value function framework, preference disaggregation methods infer parameters that define the value functions for the multiple criteria. The present work addresses the use of choice-based multiple questions, rather than eliciting a ranking or a classification of alternatives as typically done. It proposes simple mathematical formulations to obtain the most typical value-function shapes (concave, convex, or S-shaped) and a post-optimization step to avoid extreme cases. These methods are applied in an empirical study concerning the preferences of a population towards vehicle technologies. Over a hundred potential vehicle buyers in Portugal were interviewed in person. The analysis examines to what extent respondents are consistent, what do their value functions inferred from choice-based questions look like, and how well do these functions represent their preferences for alternative vehicle technologies. Respondents were found to be frequently inconsistent in their answers to choice-based questions. However, the inferred value functions reproduced their choices with a relatively small internal error. Requiring the value function to have a typical shape did not increase error in general. The post-optimization step contributes to decrease the difference among the criteria weights and matches better the preferences displayed by the respondents when performing an additional task based on a detailed elicitation process.