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Although the four-step model is the most common method in transportation demand modelling, it is exposed to a considerable criticism in terms of representing the actual choice behaviours of travellers. For example, the four steps are presented in a fixed sequence and independently from each other. Such assumption may be correct in case of obligatory trips (e.g. work trips) where travellers’ behaviour has usually no effect on trip generation or trip distribution stages. However, in discretionary trips, they may simultaneously decide on various trip dimensions. This paper tries to overcome the limitations of traditional four-step model associated with discretionary trips by using a joint discrete choice modelling approach that represents destination, departure time and travel mode choices under a unified framework. The proposed model to be used is the Ordered Generalized Extreme Value model where potential spatial correlation among discretionary destinations can be considered as well. The research methodology has been tested by using shopping and entertainment trips data of Eskisehir city in Turkey. The proposed framework seemed to be more effective and offered an accurate alternative to the first three stages of the traditional four-step model in a setting with a limited number of discretionary destinations.

This study investigated the underlying reasons for the improper use of bus bays in Istanbul, Turkey, one of the megacities in the developing world. Improper use occurs when a bus driver elects to enter a bus bay partially or not at all. Data were compiled from field studies during peak and off-peak hours at three selected bus bays on Buyukdere Street, which was one of the most important urban arterials on the European side of Istanbul. During the field study, information was collected about bus bay use preferences, in addition to data on arrival time, departure time, bus occupancy, number of passengers waiting at a bus stop, illegal parking in the bus bay, and traffic volume on the road. These data were used to estimate three multinomial logit bus bay use models by stratifying the sample with respect to bus bay occupancy and bus stop location. The results showed that illegally parked vehicles were a major factor that led to improper use of bus bays, and the effect was similar to that of the presence of one or more buses in a bus bay on a new bus’s arrival. Moreover, the occupancy of buses was found to be significant because relatively empty buses were more likely not to fully enter a bus bay, whereas packed buses tended toward full use, especially when passengers were alighting at each stop. In terms of policy, it is essential to prevent illegal parking through methods such as the installation of medians. Overall, the study revealed that the success of bus bays was questionable, and the need for them in megacities, such as Istanbul, disputable.