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Demand-Responsive Transport (DRT) promises to improve public transport in urban peripheries, but many real-world implementations fail due to a misalignment with travel demand. While analytical models have established theoretical thresholds for DRT viability, they often rely on idealised assumptions that cannot fully capture the complex interactions between network topology, traveller behaviour, fleet operations, and intermodal transfers. This study addresses this gap by using an agent-based simulation to test a DRT service area delineation policy. We apply this method to create feeder-oriented zones — which target peripheral areas with poor public transport access to encourage a shift from cars — and compare their performance against a ridership-maximising operator-oriented approach, which focuses on high-demand inner-city areas to maximise pooling and fleet efficiency. This comparison includes an explicit distinction between standalone and feeder DRT trips, enabling a direct evaluation of the trade-offs between operational efficiency and environmental impact. Results show these two strategies produce distinct patterns of mode shift: feeder-oriented zones achieve a more sustainable mode shift by facilitating intermodal journeys that substitute car trips (albeit with low pooling efficiency), whereas operator-oriented zones achieve higher ridership at the cost of drawing users from sustainable modes. As DRT struggles for viability in both scenarios, the findings from this study indicate that simply implementing a DRT service is insufficient to deliver meaningful environmental benefit; its success depends on its integration within a wider policy environment that actively manages car use and improves public transport.
Mahfouz et al. (Fri,) studied this question.