Matching and Pricing in Ride Hailing: Wild Goose Chases and How to Solve Them
研究发现网约车市场存在“追逐空车”的匹配失败现象，即高需求引发司机空驶、接单时间长、收入低的恶性循环，降低社会福利。平台可通过提高价格或动态加价来避免该问题，动态加价效果优于调整匹配算法。
We show that ride-hailing markets are prone to a matching failure (“wild goose chases”) in which high demand sets off a harmful feedback cycle of few idle drivers, high pickup times, and low earnings, drastically reducing welfare. After characterizing these failures theoretically and showing empirical evidence of their relevance, we analyze how platforms can avoid them. Raising prices brings demand back under control. Platforms can thus set a uniform high price, or they can use high “surge” pricing during high demand times while keeping prices low at other times. Some adjustments to the matching algorithm can also avoid the problem, but surge pricing performs better than them. This paper was accepted by Itai Ashlagi, revenue management and market analytics. Funding: This research was supported by the Kapnick Foundation Fellowship through a grant to the Stanford Institute for Economic Policy Research and by the John S. and James L. Knight Foundation through a grant to the University of Pennsylvania Center for Technology, Innovation, & Competition and to the Warren Center for Network and Data Sciences’s Economics of Digital Services initiative. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.00096 .