Abstract Accessing airports can be considered as a crucial issue since passengers need not miss their flights. This issue makes the mode choice to access the airports important to study on and develop policies regarding it. Many studies show destination type as domestic or international affects the airport access mode choice, along with other factors. In this study, we investigate the effect of destination type of mode choice using mixed logit, using market segmentation approach. Market segmentation regarding destination type as domestic or international is a first in airport access mode choice modeling. Revealed-preference data was collected by face-to-face passenger surveys at Ataturk International Airport in Istanbul, Turkey, in 2015. We did market segmentation analysis for Multinomial Logit (MNL) and Mixed Logit (ML) models. When MNL and ML models were compared, it was observed that ML was superior to MNL. Further, results of market segmentation analysis revealed that using segmented models produced more accurate results than using the pooled model; both in MNL and ML. This finding was also supported by the value of time estimates; there were significant differences between domestic and international travel markets in terms of airport access mode choice. These results showed that different transportation policies may be introduced for domestic and international traveler segments, which also were explained.

    Highlights Airport access mode choice was modeled using Multinomial Logit and Mixed Logit. Effects of domestic and international travel on mode choice were investigated. Segmented models showed improvement over the pooled model. There are taste variations across passengers for trip cost to the airport. VOT estimates are different for domestic and international travel markets.


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    Titel :

    Market segmentation analysis for airport access mode choice modeling with mixed logit


    Beteiligte:
    Gunay, Gurkan (Autor:in) / Gokasar, Ilgin (Autor:in)


    Erscheinungsdatum :

    2020-12-04




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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