Sample-based longitudinal discrete choice experiments: preferences for electric vehicles over time

Abstract Discrete choice experiments have emerged as the state-of-the-art method for measuring preferences, but they are mostly used in cross-sectional studies. In seeking to make them applicable longitudinal studies, our study addresses two common challenges: working with different respondents and handling altering attributes. We propose a sample-based discrete experiment combination covariate-extended hierarchical Bayes logit estimator that allows one test statistical significance of changes. showcase this method’s use studies about preferences electric vehicles over six years empirically observe develop an unpredictable, non-monotonous way. also find inspecting only absolute differences between samples may result misleading inferences. Moreover, surveying new sample produced similar results asking same time. Finally, we experimentally how adding or removing attribute affects other