The effects of surge pricing on driver behavior in the ride‐sharing market: Evidence from a quasi‐experiment
利用中国某网约车平台在两个城市分时引入动态定价的准实验，结合双重差分和因果森林方法，发现动态定价提高了司机周收入，但日收入下降，原因是竞争效应占优，司机通过增加工作天数来补偿，且兼职司机受益更多。
Abstract Surge pricing has been used to coordinate supply and demand in the ride‐sharing industry, but its causal effects on driver behavior remain unclear. This motivates us to examine how surge pricing causally affects driver earnings and labor supply by leveraging a unique quasi‐experiment, in which a leading ride‐sharing company in China introduced surge pricing in two cities at different times. Using a difference‐in‐differences design with the causal forest method, we find that surge pricing led to increases in drivers' weekly revenue. Decomposing the weekly revenue into “intensive margin” and “extensive margin” factors, we discover two countervailing effects at play: a cherry‐picking effect and a competition effect, and the daily revenue decreased because the latter dominated. Consequently, the increased weekly revenue can be explained by the extensive margin: drivers worked on more days to compensate for the decreased daily revenue, a result consistent with the income targeting behavior. Finally, we examine heterogeneous treatment effects across drivers, and find that surge pricing enticed more part‐time drivers to flood the market and crowd out full‐time drivers, and that the increase in the drivers' weekly revenue was primarily driven by part‐time drivers. Therefore, the benefit of surge pricing was unevenly distributed across drivers.