Carsharing systems provide sustainable, environmentally friendly short-distance inner urban transportation. One-way carsharing systems, a type of carsharing system with a significant portion of registered members worldwide, allow users to leave their vehicles at any station or anywhere in the region. However, this leads to vehicle stock imbalances since the demand is not symmetrical. One-way carsharing systems require demand-balancing relocation activities with the involvement of personnel bringing vehicles where and when needed. Therefore, one-way carsharing systems are complex regarding strategic and operational decisions. The main goal of this thesis is to contribute to the one-way carsharing literature by providing i) new mathematical models and heuristic algorithms for the strategic decisions in infrastructure investments regarding the new technological developments in electric vehicle chargers ii) an in-depth literature review for user-based relocation and pricing studies and iii) new mathematical models and heuristic algorithms for operational decisions where users are offered counteroffers that increase the operational profitability.

The first work conducted in this thesis exploits new technological developments corresponding to electric vehicle chargers. A new mathematical model is proposed to determine the number and location of fast/rapid chargers to be implemented in one-way carsharing systems with an electric vehicle fleet. The proposed model takes into account vehicle relocation, battery availability and partial charging. As the model becomes intractable for large-sized instances, we introduce heuristic algorithms that reduce the size of the variables and constraints created. The results suggest that the proposed algorithms increase profitability by providing charger infrastructure upgrade decisions at the stations.

The second work of this thesis presents a literature review on user-based relocations and pricing studies. Other than operator-based relocations, user-based relocations (providing alternative trips to users) and pricing are powerful tools to balance the vehicle supply and trip demand. This part of the thesis provides a discussion on the main lines of the research pertinent to user-based relocation and pricing methods applied to carsharing systems by categorizing the literature based on the aim and methods of the studies. Furthermore, we identified current research gaps and shed some light on directions for future research.

Finally, the last work presented here provides an operational-level decision support system in one-way carsharing systems. The users are offered counteroffers (user-based relocations) to increase profitability by mainly decreasing operator-based relocation costs. A mathematical model is introduced to find the best possible offer to the user at each trip request. The model considers the users' acceptance and rejection rates of the offers. Additionally, heuristic algorithms that work efficiently are presented. The results suggest that incorporating user-based relocations in operational level decisions increase profitability.