Abstract We investigate the ground access and airport choice behavior of individual air passengers that use rail transit in their ground transport to airports. Using a novel dataset of payment transaction records of rail transit trips, we calibrate a binomial logit model of individual's choice between two airports in Beijing, China to examine air passengers' preferences for ground rail service attributes including travel time, travel cost and number of transfers and compute the implied value of travel time and transfer penalty. We further visualize the spatial distribution of access and egress air ridership across the city at the rail transit station level with a set of heat maps and develop a gravity model to understand factors that affect the air ridership at individual stations. Our findings have significant implications for airport planner and transit authorities in assessing the potential benefit of airport rail link projects and improving the efficiency of regional airport systems.

    Highlights We present a big-data-based approach to model airport choice behavior. We assess preference for rail service in ground transport of air passengers. VOT of air passengers in ground transport by rail is 12.94 RMB yuan (2 US$)/hour. The implied transfer penalty is 15.06 RMB yuan (2.3 US$)/transfer.


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    Title :

    Understanding the ground access and airport choice behavior of air passengers using transit payment transaction data


    Contributors:
    Wang, Zi-Jia (author) / Jia, Hui-Hui (author) / Dai, Fangzhou (author) / Diao, Mi (author)

    Published in:

    Transport Policy ; 127 ; 179-190


    Publication date :

    2022-09-01


    Size :

    12 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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