# Heterogeneity in demand and optimal price conditioning for local rail transport

## TL;DR

This study develops a regression tree-based method to estimate demand functions for local rail tickets, revealing significant heterogeneity in price elasticity across different trip types and travel goals, which informs optimal pricing strategies.

## Contribution

It introduces a novel regression tree approach to model demand heterogeneity in local rail transport, accounting for trip-specific factors and demand elasticity variations.

## Key findings

- Demand is generally elastic, but about 25% of trips show weak elasticity.
- Lower demand elasticity correlates with less competition and inflexible travel schedules.
- Demand elasticity varies significantly by trip direction and purpose.

## Abstract

This paper describes the results of research project on optimal pricing for LLC "Perm Local Rail Company". In this study we propose a regression tree based approach for estimation of demand function for local rail tickets considering high degree of demand heterogeneity by various trip directions and the goals of travel. Employing detailed data on ticket sales for 5 years we estimate the parameters of demand function and reveal the significant variation in price elasticity of demand. While in average the demand is elastic by price, near a quarter of trips is characterized by weakly elastic demand. Lower elasticity of demand is correlated with lower degree of competition with other transport and inflexible frequency of travel.