Beyond the mean: Quantile Regression insights into high-speed rail pricing strategies
摘要
Passenger rail transport is an important sector today due to the advantages it offers, amongst which is the fact that it is a less polluting mode. Despite its public ownership, Revenue Management has been implemented in High-Speed Rail to make the use of this resource profitable and optimised. The novelty of this research lies in several aspects: supply online data is used, business-leisure behaviour is compared, non-pandemic and pandemic-data are considered and quantities on offer are analysed in addition to price data. Quantile Regression Models allow us to analyse the dynamic pricing behaviour offered in more detail, broadening the scope of the analysis. Being based on median price values instead of the average (OLS Models), the results allow for a joint analysis of the company's pricing strategy together with the volume of data offered. Researchers can use the advances made on offer behaviour as the last frontier in income generation.