Time slot choice analysis for Demand-Responsive Transport service: evidence from Ragusa province, Italy

The transition to sustainable mobility requires the implementation of strategies that make the sector more environmentally friendly and efficient. In recent years, we have witnessed a transition phase, i.e. the implementation of policies and actions that reduce the use of private vehicles (especially those with combustion engines) and promote greener modes of transport such as public transport, cycling, walking and innovative, climate-friendly mobility solutions. It is therefore possible to implement a series of improvement measures and strategies (e.g. innovative tariffs, service quality, complementary services and greater efficiency, as well as the transition to green fleets). It is also essential to implement complementary transport services such as on-demand or shared. This research study analyses connections in the province of Ragusa—where a Demand Responsive Transport service (DRTs) operates—using a hub and spoke model to discretise travel patterns. This research analyses the aspects related to the time slots in which the service is used using a modelling linked to the Random Utility Models (RUMs) and through the definition of a binomial logit model (BNL). The choice of RUM enables identifying relationship between the chosen alternative and the individual decision. The calibrated model reveals that the most influential attribute in the choice of the time slot, for the service analysed, is the area of origin. This highlights how users choose the time slot mainly based on the area of origin, which, given the characteristics of the service, corresponds to the direction of travel; among other attributes tested, the availability of buses was found to be significant. The results are meaningful for improving the existing services and for defining a complementary service of local public transport and on-demand services. Furthermore, the proposed framework can be extended to other aspects of the decision process involved in DRT adoption.