One-way car sharing allows users to pick up a vehicle at one location and drop it off at another. It provides flexibility for users but poses challenges in maintaining vehicle distribution, often requiring costly operator-based relocations. To address this, this study explores the potential of user-based relocation strategies supported by incentives through a scenario-based survey, with user preferences analysed using chi-squared tests and ordinal logistic regression to reveal behavioural patterns. Our analysis shows that relocation willingness is shaped more by demographics, experience, and contextual factors than by incentive value alone. Building on these insights, we developed an agent-based simulation that incorporates commuting behaviour and willingness data. The simulation demonstrates that user-based relocation can substantially reduce costs compared to operator-only strategies, particularly when participants are selectively incentivised. Overall, the findings advance the design of cost-efficient and sustainable relocation models and provide insights into enhancing the scalability of one-way car-sharing services.