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

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dc.contributor.authorLi, Ziru
dc.contributor.authorHong, Yili
dc.contributor.authorZhang, Zhongju
dc.date.accessioned2016-12-28T23:41:18Z
dc.date.available2016-12-28T23:41:18Z
dc.date.issued2017-01-04
dc.description.abstractOn-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.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2017.002
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41152
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectdigital platforms
dc.subjectride-sharing services
dc.subjectsharing economy
dc.subjecttraffic congestion
dc.titleAn Empirical Analysis of On-demand Ride-sharing and Traffic Congestion
dc.typeConference Paper
dc.type.dcmiText

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