Value of Information Sharing via Ride-Hailing Apps: An Empirical Analysis
Kyung Sun Rhee, Jinyang Zheng, Youwei Wang, Yong Tan
Abstract
This study examines the effects of an information sharing restriction policy that restricts taxi drivers’ access to ride requests via ride-hailing apps. We show that the policy significantly decreases the ridership of an affected taxi fleet during times of enforcement but significantly increases the demands at some times of nonenforcement after launch. Furthermore, the traffic on public transportation, including metro, bus, ferry, and park & ride, and the congestion on the surface roads and expressways significantly increase after launching the policy during both enforcement and most nonenforcement times. We also show that the profitability of taxi fleet decreases after the restriction, which supports the notion that information sharing via ride-hailing apps enables them to match not only with more orders but also with those of higher marginal profit. These findings suggest that information sharing via ride-hailing apps can improve the utilization of existing taxi capacity, which further alleviates traffic during alternative times and the burden placed on alternative transportation modes. Policymakers and platform managers should dissect the value of information sharing from that of other aspects (e.g., changes in supply) in on-demand platforms and design policies that more specifically restrict the harmful aspects rather than restricting the use of such apps.