Abstract
The potential success of shared mobility services in the urban area strongly depends on careful tariff planning, adequate sizing of the fleet and efficient integrated public transport system, as well as on the application of policies in favor of sustainable modes of transport. The balance between earnings and expenses is not always an easy target for the companies in those cities where these services are not well-rooted in the citizens’ mobility habits. Often only large operators in the sector can continue to offer a service generating profit. However, several factors can determine the success or the failure of shared mobility services. The objective of this study is to identify, thanks to the help of a case study, success and failure factors, developing an approach that is supportive for companies in managing the services and optimizing fares and fleet to increase the number of members and maximize profits. The city of Palermo has been chosen as a case study: the “Amigo” carsharing service - partly station-based, partly free-floating - is a service managed by the municipal company AMAT S.p.A., which operates also the public transport service.
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References
Balac, M., Ciari, F.: Enhancement of the carsharing fleet utilization. In: 15th Swiss Transport Research Conference (2015)
Balac, M., Ciari, F., Axhausen, K.W.: Modeling the impact of parking price policy on free-floating carsharing: case study for Zurich, Switzerland. Transp. Res. Part C Emerg. Technol. 77, 207–225 (2017). https://doi.org/10.1016/J.TRC.2017.01.022
Barrios, J.A., Godier, J.D.: Fleet sizing for flexible carsharing systems: simulation-based approach. Transp. Res. Rec. 2416(1), 1–9 (2014). https://doi.org/10.3141/2416-01
Boyacı, B., Zografos, K.G., Geroliminis, N.: An optimization framework for the development of efficient one-way car-sharing systems. Eur. J. Oper. Res. 240, 718–733 (2015). https://doi.org/10.1016/J.EJOR.2014.07.020
Celsor, C., Millard-Ball, A.: Where does carsharing work? Using geographic information systems to assess market potential. Transp. Res. Rec. (2007). https://doi.org/10.3141/1992-08
D’Orso, G., Migliore, M.: A GIS-based method for evaluating the walkability of a pedestrian environment and prioritized investments. J. Transp. Geogr. 82, 102555 (2020). https://doi.org/10.1016/j.jtrangeo.2019.102555
George, D.K., Xia, C.H.: Fleet-sizing and service availability for a vehicle rental system via closed queueing networks. Eur. J. Oper. Res. 211, 198–207 (2011). https://doi.org/10.1016/J.EJOR.2010.12.015
Hu, L., Liu, Y.: Joint design of parking capacities and fleet size for one-way station-based carsharing systems with road congestion constraints. Transp. Res. Part B Methodol. 93, 268–299 (2016). https://doi.org/10.1016/J.TRB.2016.07.021
Jorge, D., Molnar, G., de Almeida Correia, G.H.: Trip pricing of one-way station-based carsharing networks with zone and time of day price variations. Transp. Res. Part B Methodol. 81, 461–482 (2015). https://doi.org/10.1016/J.TRB.2015.06.003
Li, X., Ma, J., Cui, J., Ghiasi, A., Zhou, F.: Design framework of large-scale one-way electric vehicle sharing systems: A continuum approximation model. Transp. Res. Part B Methodol. 88, 21–45 (2016). https://doi.org/10.1016/J.TRB.2016.01.014
Migliore, M., D’Orso, G., Caminiti, D.: The current and future role of carsharing in palermo: analysis of collected data and results of a customer satisfaction survey. In: 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Palermo, pp. 1–6 (2018). https://doi.org/10.1109/eeeic.2018.8494010
Nobis, C.: Carsharing as key contribution to multimodal and sustainable mobility behavior: carsharing in Germany. Transp. Res. Rec. 1986(1), 89–97 (2006). https://doi.org/10.1177/0361198106198600112
Nourinejad, M., Roorda, M.J.: A dynamic carsharing decision support system. Transp. Res. Part E Logist. Transp. Rev. 66, 36–50 (2014). https://doi.org/10.1016/j.tre.2014.03.003
Perboli, G., Ferrero, F., Musso, S., Vesco, A.: Business models and tariff simulation in car-sharing services. Transp. Res. Part A Policy Pract. 115, 32–48 (2018). https://doi.org/10.1016/j.tra.2017.09.011
Xu, M., Meng, Q.: Fleet sizing for one-way electric carsharing services considering dynamic vehicle relocation and nonlinear charging profile. Transp. Res. Part B Methodol. 128, 23–49 (2019). https://doi.org/10.1016/J.TRB.2019.07.016
Xu, M., Meng, Q., Liu, Z.: Electric vehicle fleet size and trip pricing for one-way carsharing services considering vehicle relocation and personnel assignment. Transp. Res. Part B Methodol. 111, 60–82 (2018). https://doi.org/10.1016/J.TRB.2018.03.001
Yoon, T., Cherry, C.R., Jones, L.R.: One-way and round-trip carsharing: a stated preference experiment in Beijing. Transp. Res. Part D Transp. Environ. 53, 102–114 (2017). https://doi.org/10.1016/J.TRD.2017.04.009
Yoon, T., Cherry, C.R., Ryerson, M.S., Bell, J.E.: Carsharing demand estimation and fleet simulation with EV adoption. J. Clean. Prod. 206, 1051–1058 (2019). https://doi.org/10.1016/J.JCLEPRO.2018.09.124
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Capodici, A.E., D’Orso, G., Migliore, M. (2020). Understanding the Key Factors of Shared Mobility Services: Palermo as a Case Study. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12250. Springer, Cham. https://doi.org/10.1007/978-3-030-58802-1_63
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