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The Impact of COVID-19 on the Ride-Sharing Industry and Its Recovery: Causal Evidence from China

Wang, W; Miao, W; Liu, Y; Deng, Y; Cao, Y; (2022) The Impact of COVID-19 on the Ride-Sharing Industry and Its Recovery: Causal Evidence from China. Transportation Research Part A: Policy and Practice , 155 pp. 128-141. 10.1016/j.tra.2021.10.005. Green open access

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Abstract

The COVID-19 pandemic has brought unprecedented disruptions to many industries, and the transportation industry is among the most disrupted ones. We seek to address, in the context of a ride-sharing platform, the response of drivers to the pandemic and the post-pandemic recovery. We collected comprehensive trip data from one of the leading ride-sharing companies in China from September 2019 to August 2020, which cover pre-, during-, and post-pandemic phases in three major Chinese cities, and investigate the causal effect of the COVID-19 pandemic on driver behavior. We find that drivers only slightly reduced their shift decision in response to increased COVID-19 cases, likely because they have to make a living from providing ride-sharing services. Nevertheless, conditional on working, drivers exhibit strong risk aversion: As the number of new cases increases, drivers strategically adjust the scope of search for passengers, complete fewer trips, and as a result, make lower daily earnings. Finally, our heterogeneity analyses indicate that the effects appear to vary both across drivers and over time, with generally stronger effects on drivers who are older, more experienced, more active before the pandemic, and with higher status within the firm. Our findings have strong policy implications: These drivers tend to contribute more to the focal company, and also rely more on providing ride-sharing services to make a living. Therefore, they should be prioritized in stimulus plans offered by the government or the ride-sharing company.

Type: Article
Title: The Impact of COVID-19 on the Ride-Sharing Industry and Its Recovery: Causal Evidence from China
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.tra.2021.10.005
Publisher version: https://doi.org/10.1016/j.tra.2021.10.005
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: COVID-19, Causal Inference, Instrumental Variables, Recovery, Ride-sharing
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management
URI: https://discovery.ucl.ac.uk/id/eprint/10137925
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