This paper presents the joint analysis of departure time choice for non-work activities and latent preferences toward the active and non-active mode. Utilizing the concept of smart growth design of neighborhoods, scheduling the travel activities considering active transport through smart phone applications is one of the efficient ways to promote active mode usage. The hypothesis of the current study states that departure time decision-making for non-work activities is influenced by disposition toward active modes such as cycling in addition to the socio-economic factors and dependency on mandatory activities. Information from this model is expected to provide the empirical support to the policies regarding the promotion of active mode usage. Departure time choice behavior with disposition toward non-active modes, such as car is also examined. Integrated choice latent variable modeling is used as methodological approach. The results of these two models are then compared and discussed in detail. Results indicate that both the models have contrary results to each other with respect to latent preferences for respective modes. Some socio-economic factors came to be more significant than latent preferences. Individuals who prefer active modes such as bicycle have more probability to choose morning departures to evening ones, while the opposite behavior is true for the ones who have latent preferences toward non-active modes. It is also found that car and bicycle mode preferences possess opposing elasticities. With the increase in latent preferences for active travel mode, probability for morning departure increases while opposite is true for latent preference for car.


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    Title :

    Incorporating active and non-active mode preferences for Departure time choice behavior


    Contributors:

    Published in:

    Transportation Letters ; 14 , 7 ; 697-709


    Publication date :

    2022-08-09


    Size :

    13 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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