Modelling heterogeneity in behavioral response to peak-avoidance policy utilizing naturalistic data of Beijing subway travelers

•This paper contributes to the understanding of the taste heterogeneity of travelers to pre-peak discount pricing strategy.•Naturalistic data from smart card data users in Beijing before and after a policy intervention is used in this regard.•Four groups of travelers with heterogeneous characteristics are classified by constructing a latent class model.•Different targeted policy recommendations for each group of travelers are proposed in order to improve the policy effect.