Loyalty has been considered an important factor in increasing passenger satisfaction, operator’s profitability and the share of public transportation in the literature. While most previous studies on intercity services investigated passengers’ loyalty considering hypothetical statements, such as the probability of making a trip or suggesting a service to others in the future, which may come true or not, this study examines loyalty based on actual passenger behavior by adopting the frequency of use as a proxy to measure loyalty. Furthermore, previous case studies used a specific line or a station in their research, while this paper surveyed 20,543 individuals from 15 intercity railway stations, ranging from large metropolises to medium and small towns. The data were analyzed by developing a generalized ordered logit model which could provide novel and comprehensive insight. As a result, 16 factors affecting the frequency of use were identified including a wide range of demographic, trip attributes, and infrastructure variables. Using this model provides policies on the likelihood of service use and passenger loyalty that cannot be found in the literature. The validation of the model shows a reasonable accuracy of prediction with 60% exact matches and 87% with one category difference. Planners and operators can use the result of this study to develop customer retention strategies and improve the patronage of transit operators.


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    Titel :

    Modeling passenger loyalty in intercity rail services using a generalized ordered logit model


    Untertitel :

    Modeling passenger loyalty in intercity rail services… P. Akbari et al.


    Weitere Titelangaben:

    Public Transp


    Beteiligte:
    Akbari, Pedram (Autor:in) / Mesbah, Mahmoud (Autor:in) / Bagheri, Morteza (Autor:in)

    Erschienen in:

    Public Transport ; 17 , 2 ; 347-366


    Erscheinungsdatum :

    01.06.2025


    Format / Umfang :

    20 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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