35 Pages Posted: 14 Sep 2016 Last revised: 10 Jul 2017
Date Written: August 30, 2016
Sharing economy platforms leverage information technology (IT) to provide services that re-distribute unused or underutilized assets to individuals who are willing to pay for the services. Its creative business models have disrupted many traditional industries (e.g., transportation, hotel) by fundamentally changing the mechanism to match demand with supply in real time. In this research, we investigate the impact of Uber, a peer-to-peer mobile on-demand ride-sharing platform, on traffic congestion in the urban areas of the United States. Based on a unique data set combining data of Uber entry and the Urban Mobility Report, we empirically examine whether the entry of Uber on-demand ride-sharing services affects traffic congestion using a difference-in-differences framework. Our findings provide evidence that after entering an urban area, ride-sharing services such as Uber significantly decrease traffic congestion time, congestion costs, and excessive fuel consumption. To further assess the robustness of the main results, we perform additional analyses including the use of alternative measures, instrumental variables, placebo tests, heterogeneous effects, and a relative time model with more granular data. We discuss a few plausible mechanisms to explain our findings as well as their implications for the platform-based sharing economy.
Keywords: Sharing Economy, Ride-Sharing Services, Digital Platforms, Traffic Congestion
Suggested Citation: Suggested Citation
Li, Ziru and Hong, Yili and Zhang, Zhongju, Do On-demand Ride-sharing Services Affect Traffic Congestion? Evidence from Uber Entry (August 30, 2016). Available at SSRN: https://ssrn.com/abstract=2838043 or http://dx.doi.org/10.2139/ssrn.2838043