Accommodating taste heterogeneity in railway passenger choice models based on internet booking data

This paper presents an application of advanced econometric techniques to railway passenger choices in the context of revenue management. Three modeling approaches; multinomial logit, latent class, and mixed logit models are applied to ticket purchase timing decisions and to three market segments. The analysis, based on internet booking data with limited individual variables, investigates heterogeneous characteristics of passenger behavior across railway markets that differ by the length of haul.