From Meter to Algorithm: An Empirical Analysis of Fare Estimation Discrepancies on Ride‑Hailing Platforms

Abstract

In recent years, the rise of ride‑hailing apps has exerted substantial disruption on the traditional taxi industry. Both app‑based ride‑hailing services and conventional taxis mainly rely on platforms to obtain orders, but they differ in fare calculation and commission structures. Drawing on theories of two‑sided platforms and information asymmetry, the study argues that when trip fares exceed a certain amount, the platform has an incentive to adjust the relationship between estimated fares and final paid fares to maximize platform commission revenue. To test this proposition, this study collected paired observations by sending two researchers simultaneously on trips between fixed origin–destination pairs. Statistical results show that the estimated fare for ride‑hailing was 2.6% lower than that for the taxi. The estimated fares exceeded actual paid fares by 5.4% for taxi. The actual fares paid for ride‑hailing trips were 4.2% higher than the actual fares for taxi trips. All of these differences are statistically significant. By contrast, there was no significant difference between the ride‑hailing platforms’ estimated fares and the actual fares paid for raid-hailing trips. These findings enrich the literature on two‑sided platforms and offer new empirical evidence on information asymmetry and platform governance in the urban passenger‑transport market.