Abstract The outbreak of coronavirus disease 2019 (COVID-19) has had severely disruptive impacts on transportation, particularly public transit. To understand metro ridership changes due to the COVID-19 pandemic, this study conducts an in-depth analysis of two Chinese megacities from January 1, 2020, to August 31, 2021. Generalized linear models are used to explore the impact of the COVID-19 pandemic on metro ridership. The dependent variable is the relative change in metro ridership, and the independent variables include COVID-19, socio-economic, and weather variables. The results suggested the following: (1) The COVID-19 pandemic has a significantly negative effect on the relative change in metro ridership, and the number of cumulative confirmed COVID-19 cases within 14 days performs better in regression models, which reflects the existence of the time lag effect of the COVID-19 pandemic. (2) Emergency responses are negatively associated with metro system usage according to severity and duration. (3) The marginal effects of the COVID-19 variables and emergency responses are larger on weekdays than on weekends. (4) The number of imported confirmed COVID-19 cases only significantly affects metro ridership in the weekend and new-normal-phase models for Beijing. In addition, the daily gross domestic product and weather variables are significantly associated with metro ridership. These findings can aid in understanding the usage of metro systems in the outbreak and new-normal phases and provide transit operators with guidance to adjust services.

    Highlights This study uses generalized linear models to quantify the impact of COVID-19 on metro ridership in Beijing and Shanghai, China. Wecompare the impact of the two specifications of local COVID-19 cases on metro ridership, and the cumulative model performs better. We perform a heterogeneity analysis on the effect of the COVID-19 pandemic, such as weekday/ weekends and different phases. We further observet the number of imported COVID-19 cases is only significant in the weekend and new-normal-phase models for Beijing.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Unraveling the dynamic impacts of COVID-19 on metro ridership: An empirical analysis of Beijing and Shanghai, China


    Beteiligte:
    Jiang, Shixiong (Autor:in) / Cai, Canhuang (Autor:in)

    Erschienen in:

    Transport Policy ; 127 ; 158-170


    Erscheinungsdatum :

    2022-09-02


    Format / Umfang :

    13 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Initiatives boost metro ridership and revenue

    Anderson, Paul | IuD Bahn | 2005


    Impacts of COVID-19 on public transit ridership

    Yi Qi / Jinli Liu / Tao Tao et al. | DOAJ | 2023

    Freier Zugriff

    Spatiotemporal exploration of the non-linear impacts of accessibility on metro ridership

    Du, Qiang / Zhou, Yuqing / Huang, Youdan et al. | Elsevier | 2022


    Does Transit-Oriented Development Affect Metro Ridership?

    Lin, Jen-Jia / Shin, Ting-Yu | Transportation Research Record | 2008