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Were ride-hailing fares affected by the COVID-19 pandemic? Empirical analyses in Atlanta and Boston

Author

Listed:
  • Tulio Silveira-Santos

    (Universidad Politécnica de Madrid)

  • Ana Belén Rodríguez González

    (Universidad Politécnica de Madrid)

  • Thais Rangel

    (Universidad Politécnica de Madrid
    Universidad Politécnica de Madrid)

  • Rubén Fernández Pozo

    (Universidad Politécnica de Madrid)

  • Jose Manuel Vassallo

    (Universidad Politécnica de Madrid)

  • Juan José Vinagre Díaz

    (Universidad Politécnica de Madrid)

Abstract

Ride-hailing services such as Lyft, Uber, and Cabify operate through smartphone apps and are a popular and growing mobility option in cities around the world. These companies can adjust their fares in real time using dynamic algorithms to balance the needs of drivers and riders, but it is still scarcely known how prices evolve at any given time. This research analyzes ride-hailing fares before and during the COVID-19 pandemic, focusing on applications of time series forecasting and machine learning models that may be useful for transport policy purposes. The Lyft Application Programming Interface was used to collect data on Lyft ride supply in Atlanta and Boston over 2 years (2019 and 2020). The Facebook Prophet model was used for long-term prediction to analyze the trends and global evolution of Lyft fares, while the Random Forest model was used for short-term prediction of ride-hailing fares. The results indicate that ride-hailing fares are affected during the COVID-19 pandemic, with values in the year 2020 being lower than those predicted by the models. The effects of fare peaks, uncontrollable events, and the impact of COVID-19 cases are also investigated. This study comes up with crucial policy recommendations for the ride-hailing market to better understand, regulate and integrate these services.

Suggested Citation

  • Tulio Silveira-Santos & Ana Belén Rodríguez González & Thais Rangel & Rubén Fernández Pozo & Jose Manuel Vassallo & Juan José Vinagre Díaz, 2024. "Were ride-hailing fares affected by the COVID-19 pandemic? Empirical analyses in Atlanta and Boston," Transportation, Springer, vol. 51(3), pages 791-822, June.
    • Handle: RePEc:kap:transp:v:51:y:2024:i:3:d:10.1007_s11116-022-10349-x
    DOI: 10.1007/s11116-022-10349-x
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    References listed on IDEAS

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    1. Malte Schröder & David-Maximilian Storch & Philip Marszal & Marc Timme, 2020. "Anomalous supply shortages from dynamic pricing in on-demand mobility," Nature Communications, Nature, vol. 11(1), pages 1-8, December.
    2. Haitao Yu & Zhong-Ren Peng, 2020. "The impacts of built environment on ridesourcing demand: A neighbourhood level analysis in Austin, Texas," Urban Studies, Urban Studies Journal Limited, vol. 57(1), pages 152-175, January.
    3. Judd Cramer & Alan B. Krueger, 2016. "Disruptive Change in the Taxi Business: The Case of Uber," American Economic Review, American Economic Association, vol. 106(5), pages 177-182, May.
    4. Berger, Thor & Chen, Chinchih & Frey, Carl Benedikt, 2018. "Drivers of disruption? Estimating the Uber effect," European Economic Review, Elsevier, vol. 110(C), pages 197-210.
    5. Malte Schroder & David-Maximilian Storch & Philip Marszal & Marc Timme, 2020. "Anomalous supply shortages from dynamic pricing in on-demand mobility," Papers 2003.07736, arXiv.org.
    6. Alessandra Buja & Matteo Paganini & Silvia Cocchio & Manuela Scioni & Vincenzo Rebba & Vincenzo Baldo, 2020. "Demographic and socio-economic factors, and healthcare resource indicators associated with the rapid spread of COVID-19 in Northern Italy: An ecological study," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-13, December.
    7. Shaheen, Susan PhD & Chan, Nelson & Bansal, Apaar & Cohen, Adam, 2015. "Shared Mobility: A Sustainability & Technologies Workshop: Definitions, Industry Developments, and Early Understanding," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2f61q30s, Institute of Transportation Studies, UC Berkeley.
    8. Kuo-Ying Wang, 2014. "How Change of Public Transportation Usage Reveals Fear of the SARS Virus in a City," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-10, March.
    9. Yan, Xiang & Liu, Xinyu & Zhao, Xilei, 2020. "Using machine learning for direct demand modeling of ridesourcing services in Chicago," Journal of Transport Geography, Elsevier, vol. 83(C).
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