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The future of transportation relies on the development of sustainable economic solutions for urban mobility problems. Although carsharing services help counter these challenges by providing a promising alternative to private car-ownership, several obstacles have prevented carsharing from reaching its full potential as a mainstream preference for daily commute. One such challenge prevalent among carsharing services is the lack of efficient vehicle relocation solutions capable of responding to dynamic customer vehicle demands.

We contribute to developing solutions for the vehicle relocation challenge through a cross-disciplinary perspective by applying an econophysical approach and utilizing knowledge from the field of physics. Following the Design Science Research paradigm, we developed a new approach of vehicle relocation capable of supporting station-based and free-floating carsharing as well as user-based and operator-based relocation strategies, called System Energy Relocation Algorithm (SERA). SERA was developed with the specific goals of not only automatically computing vehicle relocations but also to provide bases for informed decision making. Thus, SERA adds a new perspective to the vehicle supply and demand management discourse by not only addressing performance related aspects of vehicle relocation but also by exploring approaches for supporting the decision processes of carsharing providers.