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Exploring impacts of COVID-19 on city-wide taxi and ride-sourcing markets: Evidence from Ningbo, China

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  • Yu, Jingru
  • Xie, Ningke
  • Zhu, Jiangtao
  • Qian, Yiwei
  • Zheng, Sijing
  • Chen, Xiqun (Michael)

Abstract

The outbreak of the COVID-19 epidemic has brought enormous impacts and changes to human mobility. To better understand and quantify the impacts of COVID-19 on city-wide ride-sourcing and taxi markets, we present exploratory evidence on the factors such as coronavirus cases related attributes, policy-related attributes, operational status of transportation, socio-economic status related variables, demographics related variables, and other factors. Based on 5-month real-world ride-sourcing and taxi datasets in Ningbo, China, including 37-million trips, we study the temporal variations of drivers' working characteristics and productivity of ride-sourcing and taxi fleets. The spatial heterogeneity of the impacts of COVID-19 on taxi and ride-sourcing trips is demonstrated in terms of traffic analysis zones (TAZs). Regression models are established to examine the impacts of a variety of explanatory variables, including COVID-19 related variables, on the district-level productivity of taxi and ride-sourcing services. The results show that the accumulated cured coronavirus cases, policy of closed management, operational status of mass transit, and average fee spent on transportation per capita significantly impact the productivity of the taxi and ride-sourcing fleets. This paper empirically reveals the influence of the epidemic on ride-sourcing and taxi markets and the temporal and spatial variations. The findings can support decision-making to restore the ride-sourcing and taxi markets and benefit other COVID-19 related research efforts.

Suggested Citation

  • Yu, Jingru & Xie, Ningke & Zhu, Jiangtao & Qian, Yiwei & Zheng, Sijing & Chen, Xiqun (Michael), 2022. "Exploring impacts of COVID-19 on city-wide taxi and ride-sourcing markets: Evidence from Ningbo, China," Transport Policy, Elsevier, vol. 115(C), pages 220-238.
    • Handle: RePEc:eee:trapol:v:115:y:2022:i:c:p:220-238
    DOI: 10.1016/j.tranpol.2021.11.017
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    References listed on IDEAS

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    Cited by:

    1. Sen Li & Shitai Bao & Ceyi Yao & Lan Zhang, 2022. "Exploring the Spatio-Temporal and Behavioural Variations in Taxi Travel Based on Big Data during the COVID-19 Pandemic: A Case Study of New York City," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    2. Namgung, Hyewon & Fujiwara, Akimasa & Yamamoto, Jenny & Zhang, Junyi, 2023. "Small and medium-sized taxi firm operators' stated choices of future business models: A case study in Japan based on hybrid choice model with panel effects," Research in Transportation Economics, Elsevier, vol. 101(C).
    3. 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.
    4. Liang, Yuan & Yu, Bingjie & Zhang, Xiaojian & Lu, Yi & Yang, Linchuan, 2023. "The short-term impact of congestion taxes on ridesourcing demand and traffic congestion: Evidence from Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    5. Vizuete-Luciano, Emili & Guillén-Pujadas, Miguel & Alaminos, David & Merigó-Lindahl, José María, 2023. "Taxi and urban mobility studies: A bibliometric analysis," Transport Policy, Elsevier, vol. 133(C), pages 144-155.

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