An Empirical Analysis of On-Demand Ride Sharing and Traffic Congestion
Proc. International Conference on Information Systems 2016 (ICIS'16)
24 Pages Posted: 26 Sep 2016
Date Written: September 25, 2016
Sharing economy, which leverages information technology to re-distribute unused or underutilized assets to people who are willing to pay for the services, has received tremendous attention in the last few years. Its creative business model has disrupted many traditional industries (e.g., transportation, hotel) by fundamentally changing the mechanism to facilitate the matching of demand with supply in real time. In this research, we investigate how Uber, a peer-to-peer mobile ride-sharing platform, affects traffic congestion in the urban areas of the United States. Combining data from Uber and the Urban Mobility Report, we empirically examine whether and how the entry of Uber car services affect traffic congestion using a difference-in-difference framework. Findings from this research provide evidence on the potential effect of ride sharing services in the transportation industry, contributing to the understanding of the sharing economy and government policy decisions.
Keywords: Uber, sharing economy, ride sharing, platforms, traffic congestion, induced demand, difference in difference
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