In order to predict the urban bus ridership more accurately, this study focuses on the impact of social and economic factors and the supply service level of buses on urban bus ridership. It also considers the competition and cooperation between bus and other modes of transportation. Ruling out the impact of the COVID-19, based on the panel data of 35 central cities in China from 2015 to 2019, a fixed-effects model for regression of panel data is established to predict urban bus ridership. In addition, the model application study reveals the importance of supply service level of buses to maintain bus ridership, but the increase of per capita income has an impact on the bus ridership.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Bus Ridership Prediction Based on Fixed-effects Model


    Beteiligte:
    Shao Chenyang (Autor:in)


    Erscheinungsdatum :

    2024




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    A transit ridership‐revenue model

    Navin, F. P. D. / Button, K. J. | Taylor & Francis Verlag | 1984


    GTFS-Ride: Unifying Standard for Fixed-Route Ridership Data

    Carleton, Phillip / Hoover, Sylvan / Fields, Ben et al. | Transportation Research Record | 2019


    Adverse weather effects on bus ridership

    Kashfi, Syeed Anta | Online Contents | 2015


    Transit Ridership Model Based on Geographically Weighted Regression

    Chow, Lee-Fang / Zhao, Fang / Liu, Xuemei et al. | Transportation Research Record | 2006


    Transit Ridership Model Based on Geographically Weighted Regression

    Chow, Lee-Fang / Zhao, Fang / Liu, Xuemei et al. | Transportation Research Record | 2006