Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41152

An Empirical Analysis of On-demand Ride-sharing and Traffic Congestion

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Title: An Empirical Analysis of On-demand Ride-sharing and Traffic Congestion
Authors: Li, Ziru
Hong, Yili
Zhang, Zhongju
Keywords: digital platforms
ride-sharing services
sharing economy
traffic congestion
Issue Date: 04 Jan 2017
Abstract: On-demand ride-sharing, as one of the most representative sectors of sharing economy has received a lot of attention and significant debate. Limited conclusive empirical research has been done to investigate the social welfare of such service. In this research, we conduct difference-in-difference analysis to examine the impact of Uber, an on-demand app-based ride sharing service, on urban traffic congestion. We find that after Uber entry, congestion of this area has been reduced significantly. In order to check the robustness of the results, we conduct instrumental variable analysis, additional analysis using alternative measures. Findings of this research will contribute to IS community by enriching the literature of digital infrastructure platforms. Practical insights derived from this research will help inform policy makers and regulators.
Pages/Duration: 10 pages
URI/DOI: http://hdl.handle.net/10125/41152
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.002
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Access (or Sharing) Economy Minitrack



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