Pricing for Refund Service Fee of High-Speed Railway: An Optimization Approach with Uncertain Demand

Compared to single ticket purchase behavior, the impact of ticket cancellation behavior on revenue is full of complexity. Due to the cancelled tickets will be resold with uncertain demand, ticket cancellation behaviors and ticket purchase behaviors are intertwined and influenced, composed of a dynamic and complex system in the presale period. How to charge for ticket cancellation behavior in the name of refund service fee to reduce losses as much as possible is an urgent problem for high-speed railway enterprises. However, there has been little research on this issue. Therefore, a pricing optimization approach for refund service fee based on negative binomial distribution was proposed in this article. Firstly, we proved that the probability of passengers arriving based on the accumulated ticket sales obeyed the negative binomial distribution, which was used to fit the uncertainty demand of passengers. Then, we categorized the passengers to build an optimization model with the objective of maximizing compensation for losses caused by ticket cancellation. A case study was implemented to show that the proportion of refund service fee to ticket price is generally higher than 50%. The refund service fee remains monotonously nondecreasing as the departure date approaches. It also indicated that the current charging standard for refund service fees was too low to offset the losses. In addition, passenger preferences and passenger flow have significant impacts on the dynamic pricing strategy for refund service fees.