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How Do On‐demand Ridesharing Services Affect Traffic Congestion? The Moderating Role of Urban Compactness

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  • Ziru Li
  • Chen Liang
  • Yili Hong
  • Zhongju Zhang

Abstract

The role of information technology (IT) in managing operations that support environmentally sustainable growth has been emphasized a lot in operations management and information systems research. In this paper, we study the impact of the IT‐based on‐demand ridesharing platforms on an important aspect of sustainability—traffic congestion. Our theoretical prediction suggests two countervailing effects from the entry of ridesharing platforms to urban areas: the efficiency‐enhancing effect that reduces traffic congestion and the demand‐inducing effect that increases traffic congestion. We propose that the impacts of ridesharing services on traffic congestion should vary with urban spatial features. Given the theoretical tension, we investigate the impact of Uber entry on traffic congestion in urban areas of the United States with a focus on the moderating role of urban compactness. Based on a unique dataset that combines multiple archival sources, we empirically examine whether the entry of Uber's on‐demand ridesharing service affects traffic congestion by using a difference‐in‐differences framework. Our empirical evidence indicates that ridesharing services significantly increase traffic congestion in compact areas. Meanwhile, we find some marginal evidence that ridesharing services decrease traffic congestion in sprawling urban areas. The results are robust to a series of additional analyses, including the use of alternative measures, relative time model, entry exogeneity test, and placebo tests. We conclude that the efficiency‐enhancing and demand‐inducing effects shape traffic congestion and that the net effect varies according to different levels of urban compactness. We provide circumstantial evidence for the underlying mechanisms by analyzing public transit and commuting characteristic data.

Suggested Citation

  • Ziru Li & Chen Liang & Yili Hong & Zhongju Zhang, 2022. "How Do On‐demand Ridesharing Services Affect Traffic Congestion? The Moderating Role of Urban Compactness," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 239-258, January.
  • Handle: RePEc:bla:popmgt:v:31:y:2022:i:1:p:239-258
    DOI: 10.1111/poms.13530
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    Cited by:

    1. Tian, Guang & Ewing, Reid & Li, Han, 2023. "Exploring the influences of ride-hailing services on VMT and transit usage – Evidence from California," Journal of Transport Geography, Elsevier, vol. 110(C).
    2. Yingjie Zhang & Beibei Li & Sean Qian, 2023. "Ridesharing and Digital Resilience for Urban Anomalies: Evidence from the New York City Taxi Market," Information Systems Research, INFORMS, vol. 34(4), pages 1775-1790, December.
    3. Hao, Wu & Martin, Layla, 2022. "Prohibiting cherry-picking: Regulating vehicle sharing services who determine fleet and service structure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    4. Xuekai Cen & Kanghui Ren & Yiying Cai & Qun Chen, 2023. "Designing Flexible-Bus System with Ad-Hoc Service Using Travel-Demand Clustering," Mathematics, MDPI, vol. 11(4), pages 1-27, February.
    5. Jindong Pang & Shulin Shen, 2023. "Do ridesharing services cause traffic congestion?," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(2), pages 520-552, May.
    6. Yuan Liang & Bingjie Yu & Xiaojian Zhang & Yi Lu & Linchuan Yang, 2022. "The Short-term Impact of Congestion Taxes on Ridesourcing Demand and Traffic Congestion: Evidence from Chicago," Papers 2207.01793, arXiv.org, revised Feb 2023.

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