Lots of cities have developed a bike sharing system, but how to deploy a bike sharing system reasonably is urgent issue in the cities like Kunming. A knowledge based on these factors that re-balancing on a bike sharing system will work on to support cities to design an efficient service bike sharing system while decreasing re-balancing costs. We collect traffic-zone-level bike sharing usage data in Kunming, analyze the bike sharing time-variation and daily variation characteristics of arrivals and departures. Especially, we built multiple regression model to quantify effect of socio-demographic characteristics and land-use characteristics on time-variation and daily variation characteristics of arrivals and departures. We then define the absolute value of arrivals minus departures as balance index, and develop a binary logit model to estimate the influence of socio-demographic characteristics, land-use characteristics, and public transit characteristics on re-balancing. The results provide a basis for the re-balancing of a bike sharing system.


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    Titel :

    Study on Bike Sharing Rebalancing: Evidence from Kunming


    Beteiligte:
    Yin, Anteng (Autor:in) / Ning, Bojin (Autor:in) / Wang, Yeqin (Autor:in)

    Kongress:

    13th Asia Pacific Transportation Development Conference ; 2020 ; Shanghai, China (Conference Cancelled)



    Erscheinungsdatum :

    29.06.2020




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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