Despite the potential benefits outlined in the literature, the widespread adoption of Demand Responsive Transport (DRT) services has been limited. Integrating passenger and freight transport within the same system can enhance DRT’s profitability and market suitability, especially in low-demand areas. This study introduces a model using low-capacity vehicles for both passenger transport and parcel delivery, acting as feeders to mass transit stations, where parcels are initially collected. An online matching algorithm identifies optimal trip configurations for passenger travel requests, dynamically updating vehicles’ routes and schedules. The model prioritizes passenger time windows while minimizing the additional time passengers experience to accommodate parcel deliveries, optimizing resource utilization for DRT systems. An agent-based model was developed to simulate the operation of the integrated service, allowing parameter adjustments within a synthetic environment. By varying input parameters such as service area size, number of vehicles and terminal stations, and the ratio of traveler to parcel demand, findings demonstrate the benefits of the integrated system in enhancing the service cost-effectiveness, with minimal increases in passenger travel times. Excluding the cost savings compared to carrying out parcel deliveries with a separate service, including parcel deliveries has a minor impact on overall unit costs, with increases of <6%. The system performs best in smaller areas with higher traveler demand rates, optimizing resource use and matching supply with demand. Larger service areas may increase passenger travel times but offer cost savings for operators due to a higher ratio of fleet size to traveler demand.