An empirical analysis of on-demand ride-sharing and traffic congestion

Ziru Li, Yili Hong, Zhongju Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 50th Annual Hawaii International Conference on System Sciences, HICSS 2017
EditorsTung X. Bui, Ralph Sprague
PublisherIEEE Computer Society
Pages4-13
Number of pages10
ISBN (Electronic)9780998133102
StatePublished - 2017
Externally publishedYes
Event50th Annual Hawaii International Conference on System Sciences, HICSS 2017 - Big Island, United States
Duration: Jan 3 2017Jan 7 2017

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2017-January
ISSN (Print)1530-1605

Conference

Conference50th Annual Hawaii International Conference on System Sciences, HICSS 2017
Country/TerritoryUnited States
CityBig Island
Period1/3/171/7/17

Keywords

  • Digital platforms
  • Ride-sharing services
  • Sharing economy
  • Traffic congestion

ASJC Scopus subject areas

  • Engineering(all)

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