Optimal Fleet Size and Fare Setting in Emerging Taxi Markets with Stochastic Demand

Abstract

AbstractThe emerging taxi services, for instance, Uber and Lyft, are challenging traditional fully regulated taxi markets. Transportation agencies are spending significant efforts to understand the optimal pricing and fleet size taxis that are efficient for a given urban area. This study develops a modeling framework for studying a decentralized equilibrium based market study where the fare is strictly regulated by a taxi commission. The nature of demand‐supply equilibria with stochastic demand are discussed to determine optimal development strategies, for instance, number of issued licenses and fare setting. Two Stackelberg games are formulated to specify leader‐follower relationships between transportation authorities and and the followers — taxi drivers and passengers. An iterative approach is designed to simulate the games and solve corresponding mathematical optimization problems. The case study is based on New York City data which shows that the taxi market may be oversupplied and underpriced, which confirms findings from other studies and price hikes in 2012. Furthermore, different development strategies are proposed based on two Stackelberg games to respond to intended taxi system changes, such as price and quantity elasticity of taxi demand, levels of demand variance, average taxi operation speed, passengers' waiting time value, and taxi service coverage. The results have important implications in determining development strategies for taxi industry with emerging taxi services, stochastic demand, and the rapidly changing environment.