Ridesharing systems that reflect user preferences are critical for promoting adoption, improving efficiency, and supporting sustainable urban mobility. This paper proposes a multimodal mobility hub system that explicitly incorporates user preferences, including willingness to carpool and tolerance for detours. A case study in Québec evaluates how these behavioral factors influence system performance across four objectives: emissions, user costs, operator costs, and system-wide efficiency. Results show that greater willingness and flexibility substantially increase carpooling shares under emissions and system objectives. To reduce perceived user costs, incentive policies are also analyzed, and their interaction with behavioral factors is assessed. Full driving cost coverage for carpooling reduces user costs by 33.5% and increases ridesharing participation to 97.3% as willingness to carpool shifts from low to high. These findings demonstrate that embedding user preferences within the optimization framework captures realistic behavioral dynamics and supports the design of effective policies for sustainable and efficient multimodal transport systems.