Surge Pricing Solves the Wild Goose Chase

Abstract

Why is dynamic pricing more prevalent in ride-hailing apps than movies and restaurants? Arnott (1996) observed that an over-burdened taxi dispatch system may be forced to send cars on a wild goose chase to pick up distant customers when few taxis are free. These chases occupy taxis and reduce earnings, effectively removing cars from the road and exacerbating the problem. While Arnott dismissed this outcome as a Pareto-dominated equilibrium, we show that when prices are too low relative to demand it is the unique equilibrium of a system that uses a first-dispatch protocol (as many ride-hailing services have committed to). This effect dominates more traditional price theoretic considerations and implies that welfare and profits fall dramatically as price falls below a certain threshold and then decline only gradually move in price above this point. A platform forced to charge uniform prices over time will therefore have to set very high prices to avoid catastrophic chases. Dynamic “surge pricing” can avoid these high prices while maintaining system functioning when demand is high. We show that pooling can complicate and exacerbate these problems.