Shared e-mobility is a category of emerging mobility services that includes electric carsharing, e-bike sharing, and e-scooter sharing. These services are expected to reduce the negative externalities of road transport in cities, which is currently dominated by fossil-fuel-powered private car trips. In order to better inform the development and promotion of these services and indicate directions for further research, we conducted a comprehensive review of existing literature on the three shared e-mobility modes focusing on their usage pattern, demand estimation, and potential impacts. We found that despite the different vehicle capabilities, all three shared e-mobility services are mainly used for short trips, and their current users are mostly male, middle-aged people with relatively high income and education. The demand of all shared e-mobility modes share many common predictors: they appeal to people with similar socio-demographic characteristics and generate higher demand in locations with better transport connectivity and more points of interest. Shared e-mobility services can potentially lead to positive impacts on transportation and the environment, such as reducing car use, car ownership, and greenhouse gas emissions. However, the magnitude of these benefits depends on the specific operational conditions of the services such as the fuel type and lifetime of shared vehicles. The impact of each shared e-mobility mode is also expected to be affected by other coexisting shared e-mobility modes due to both complementarity and competition. Future directions should include studying the competition between and integration of multiple shared e-mobility modes.

One-way carsharing systems allow travelers to pick up a car at one station and return it to a different station, thereby causing vehicle imbalances across the stations. In this paper, a way to mitigate that imbalance is discussed, which is relocating vehicles between stations. For this purpose, two methods are presented, i.e., a new mathematical model to optimize the relocation operations that maximize the profitability of a carsharing service and a simulation model to study different real-time relocation policies. Both methods were applied to networks of stations in Lisbon, Portugal. Results show that relocating vehicles, using any of the methods developed, can produce significant increases in profit. For instance, in the case where the carsharing system provides maximum coverage of the city area, the imbalances in the network resulted in an operating loss of C1160/day when no relocation operations were performed. When relocation policies were applied, however, the simulation results indicate that profits of C854/day could be achieved, even with increased costs due to relocations. Using the mathematical model, the results are even better, with a reached profit of C3865.7/day. This improvement was achieved through reductions in the number of vehicles needed to satisfy the demand and the number of parking spaces needed at stations. These results demonstrate the importance of relocation operations for profitably providing a network of stations in one-way carsharing systems that covers the entire city, thus reaching a higher number of users.