The concept of an adaptive vehicle fleet based on user preferences as an innovation in car-sharing services

Car-sharing services i.e. short-term car rentals, are ideologically driven systems aimed at modernizing contemporary transportation towards sustainable development and encouraging society to abandon individual motorization. Despite their noble goals, car-sharing systems face numerous operational challenges, both in terms of societal acceptance and management issues related to operators. Among the key problems are inadequately tailored vehicle fleets that do not meet user needs, and the operators' reluctance to implement changes and embrace open innovations, such as mobility accelerators. This paper introduces a novel approach to car-sharing services by integrating open innovation through the concept of an adaptive vehicle fleet. In this approach, users specify their vehicle and travel preferences through an application, and the system recommends vehicles that best meet their needs, measured by a percentage-based fleet satisfaction index (stars rate). Methodologically, the system is built on Conjoint Analysis and the multi-criteria decision support method ELECTRE III, ensuring a more personalized and efficient matching process. The proposed adaptive fleet concept represents a breakthrough in the car-sharing sector, emphasizing the role of open innovation in enhancing service personalization and operational flexibility. This approach is validated through a real-world case study, showcasing its potential for both car-sharing system operators and mobility accelerators. By fostering greater adaptability and innovation, the model significantly improves user satisfaction, supports wider adoption of car-sharing systems, and contributes to the sustainable development goals within the framework of smart cities.