Analyzing rental vehicle threshold policies that consider expected waiting times for two customer classes

Abstract

Vehicle rental providers, which operate in an uncertain environment, offer differentiated services to priority and non-priority customers. In this research, we study one such service differentiation strategy, a vehicle threshold policy, which is to hold vehicles for priority class customers in anticipation of their future arrivals. To consider the impact that vehicle threshold policies have on priority and non-priority customer waiting times, we model a rental depot as a multi-class non-work-conserving semi-open queue with stochastic inputs. To analyze the effect of vehicle rental period distributions, we identify and analyze the optimal threshold quantity for stationary customer arrivals with exponential and deterministic service time distributions. For non-stationary customer arrivals, we develop different threshold policies and analyze their performance using a detailed simulation model to conduct numerical experiments. We find that a maximum threshold policy is recommended when the average arrival rate of the priority customers is larger than the average arrival rate of the non-priority customers, and a stationary independent period by period policy is recommended when the average arrival rates of the customer classes are equal and the average best case utilization is less than 0.60. Finally, we analyze the impact that allowing priority customers to upgrade to a higher class of vehicles has on threshold policies.