The Impact of Ride-Hailing Services on Congestion: Evidence from Indian Cities

Saharsh Agarwal (), Deepa Mani () and Rahul Telang ()
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Saharsh Agarwal: Indian School of Business, Hyderabad, Telangana 500111, India
Deepa Mani: Indian School of Business, Hyderabad, Telangana 500111, India
Rahul Telang: Heinz College, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213

Manufacturing & Service Operations Management, 2023, vol. 25, issue 3, 862-883

Abstract: Problem definition : Early research has documented significant growth in ride-hailing services worldwide and allied benefits. However, growing evidence of their negative externalities is leading to significant policy scrutiny. Despite demonstrated socioeconomic benefits and consumer surplus worth billions of dollars, cities are choosing to curb these services in a bid to mitigate first order urban mobility problems. Existing studies on the congestion effects of ride-hailing are limited, report mixed evidence, and exclusively focus on the United States, where the supply consists primarily of part-time drivers. Methodology/results : We study how the absence of ride-hailing services affects congestion levels in three major cities in India, a market where most ride-hailing drivers participate full time. Using rich real-time traffic and route trajectory data from Google Maps, we show that in, all three cities, periods of ride-hailing unavailability due to driver strikes see a discernible drop in travel time. The effects are largest for the most congested regions during the busiest hours, which see 10.1%–14.8% reduction in travel times. Additionally, we provide suggestive evidence for some of the mechanisms behind the observed effects, including deadheading elimination, substitution with public transit, and opening up of shorter alternative routes. Managerial implications : These results suggest that despite their paltry modal share, ride-hailing vehicles are substituting more sustainable means of transport and are contributing significantly to congestion in the cities studied. The reported effect sizes quantify the maximum travel time gains that can be expected on curbing them.

Keywords: ride-hailing; externality; ride-sharing; ridesourcing; transportation; congestion; sharing economy; traffic; Uber; Ola (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:25:y:2023:i:3:p:862-883

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