A comprehensive review of shared mobility for sustainable transportation systems

References

• Aarhaug, J., & Olsen, S. (2018). Implications of ride-sourcing and self-driving vehicles on the need for regulation in unscheduled passenger transport. Research in Transportation Economics, 69, 573–582. https://doi.org/10.1016/j.retrec.2018.07.026
   Web of Science ®Google Scholar
• Acheampong, R. A., Siiba, A., Okyere, D. K., & Tuffour, J. P. (2020). Mobility-on-demand: An empirical study of internet-based ride-hailing adoption factors, travel characteristics and mode substitution effects. Transportation Research Part C: Emerging Technologies, 115, 102638. https://doi.org/10.1016/j.trc.2020.102638
   Web of Science ®Google Scholar
• Agatz, N., Erera, A. L., Savelsbergh, M. W., & Wang, X. (2011). Dynamic ridesharing: A simulation study in metro Atlanta. Transportation Research Part B: Methodological, 45(9), 1450–1464. https://doi.org/10.1016/j.trb.2011.05.017
   Web of Science ®Google Scholar
• Ahn, Y., & Yeo, H. (2015). An analytical planning model to estimate the optimal density of charging stations for electric vehicles. PLoS One, 10(11), e0141307. https://doi.org/10.1371/journal.pone.0141307
   PubMed Web of Science ®Google Scholar
• Aïvodji, U. M., Gambs, S., Huguet, M. J., & Killijian, M. O. (2016). Meeting points in ridesharing: A privacy-preserving approach. Transportation Research Part C: Emerging Technologies, 72, 239–253. https://doi.org/10.1016/j.trc.2016.09.017
   Web of Science ®Google Scholar
• Alemi, F., Circella, G., Mokhtarian, P., & Handy, S. (2019). What drives the use of ridehailing in California? Ordered probit models of the usage frequency of Uber and Lyft. Transportation Research Part C: Emerging Technologies, 102, 233–248. https://doi.org/10.1016/j.trc.2018.12.016
   Web of Science ®Google Scholar
• Alonso-Mora, J., Samaranayake, S., Wallar, A., Frazzoli, E., & Rus, D. (2017). On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment. Proceedings of the National Academy of Sciences, 114(3), 462–467. https://doi.org/10.1073/pnas.1611675114
   PubMed Web of Science ®Google Scholar
• Asgari, H., Jin, X., & Corkery, T. (2018). A stated preference survey approach to understanding mobility choices in light of shared mobility services and automated vehicle technologies in the U.S. Transportation Research Record: Journal of the Transportation Research Board, 2672(47), 12–22. https://doi.org/10.1177/0361198118790124
   Web of Science ®Google Scholar
• Asghari, M., & Shahabi, C. (2018). Adapt-pricing: A dynamic and predictive technique for pricing to maximize revenue in ridesharing platforms. In Proceedings of the 26th ACM SIGSPATIAL international conference on advances in geographic information systems (pp. 189–198).
   Google Scholar
• Bai, L., Yao, L., Kanhere, S. S., Wang, X., Liu, W., & Yang, Z. (2019). Spatio-temporal graph convolutional and recurrent networks for citywide passenger demand prediction [Paper presentation]. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (pp. 2293–2296). https://doi.org/10.1145/3357384.3358097
   Google Scholar
• Bai, J., So, K. C., Tang, C. S., Chen, X., & Wang, H. (2019). Coordinating supply and demand on an on-demand service platform with impatient customers. Manufacturing & Service Operations Management, 21(3), 556–570. https://doi.org/10.1287/msom.2018.0707
   Web of Science ®Google Scholar
• Balac, M., Ciari, F., & Axhausen, K. W. (2017). Modeling the impact of parking price policy on free-floating carsharing: Case study for Zurich, Switzerland. Transportation Research Part C: Emerging Technologies, 77, 207–225. https://doi.org/10.1016/j.trc.2017.01.022
   Web of Science ®Google Scholar
• Banerjee, S., Johari, R., & Riquelme, C. (2015). Pricing in ride-sharing platforms: A queueing-theoretic approach [Paper presentation]. In Proceedings of the Sixteenth ACM Conference on Economics and Computation (pp. 639–639).
   Google Scholar
• Baptista, P., Melo, S., & Rolim, C. (2014). Energy, environmental and mobility impacts of car-sharing systems. Empirical results from Lisbon, Portugal. Procedia – Social and Behavioral Sciences, 111, 28–37. https://doi.org/10.1016/j.sbspro.2014.01.035
   Google Scholar
• Barbour, N., Zhang, Y., & Mannering, F. (2019). A statistical analysis of bike sharing usage and its potential as an auto-trip substitute. Journal of Transport & Health, 12, 253–262. https://doi.org/10.1016/j.jth.2019.02.004
   Web of Science ®Google Scholar
• Barrios, J. A., & Godier, J. D. (2014). Fleet sizing for flexible carsharing systems: Simulation-based approach. Transportation Research Record: Journal of the Transportation Research Board, 2416(1), 1–9. https://doi.org/10.3141/2416-01
   Google Scholar
• Bauer, G. S., Phadke, A., Greenblatt, J. B., & Rajagopal, D. (2019). Electrifying urban ridesourcing fleets at no added cost through efficient use of charging infrastructure. Transportation Research Part C: Emerging Technologies, 105, 385–404. https://doi.org/10.1016/j.trc.2019.05.041
   Web of Science ®Google Scholar
• Beojone, C. V., & Geroliminis, N. (2021). On the inefficiency of ride-sourcing services towards urban congestion. Transportation Research Part C: Emerging Technologies, 124, 102890. https://doi.org/10.1016/j.trc.2020.102890
   Web of Science ®Google Scholar
• Bhatti, A. R., Salam, Z., Abdul, M. J. B., & Yee, K. P. (2016). A comprehensive overview of electric vehicle charging using renewable energy. International Journal of Power Electronics and Drive Systems, 7(1), 114.
   Google Scholar
• Bimpikis, K., Candogan, O., & Saban, D. (2019). Spatial pricing in ride-sharing networks. Operations Research, 67(3), 744–769. https://doi.org/10.1287/opre.2018.1800
   Web of Science ®Google Scholar
• Bösch, P. M., Ciari, F., & Axhausen, K. W. (2018). Transport policy optimization with autonomous vehicles. Transportation Research Record: Journal of the Transportation Research Board, 2672(8), 698–707. https://doi.org/10.1177/0361198118791391
   Web of Science ®Google Scholar
• Bruck, B. P., Incerti, V., Iori, M., & Vignoli, M. (2017). Minimizing CO2 emissions in a practical daily carpooling problem. Computers & Operations Research, 81, 40–50. https://doi.org/10.1016/j.cor.2016.12.003
   Web of Science ®Google Scholar
• Bryan, K. A., & Gans, J. S. (2019). A theory of multihoming in rideshare competition. Journal of Economics & Management Strategy, 28(1), 89–96. https://doi.org/10.1111/jems.12306
   Web of Science ®Google Scholar
• Buck, D., Buehler, R., Happ, P., Rawls, B., Chung, P., & Borecki, N. (2013). Are Bikeshare users different from regular cyclists? A first look at short-term users, annual members, and area cyclists in the Washington, DC, region. Transportation Research Record: Journal of the Transportation Research Board, 2387(1), 112–119. https://doi.org/10.3141/2387-13
   Web of Science ®Google Scholar
• Buliung, R. N., Soltys, K., Bui, R., Habel, C., & Lanyon, R. (2010). Catching a ride on the information super-high-way: Toward an understanding of internet-based carpool formation and use. Transportation, 37(6), 849–873. https://doi.org/10.1007/s11116-010-9266-0
   Web of Science ®Google Scholar
• Caspi, O., Smart, M. J., & Noland, R. B. (2020). Spatial associations of dockless shared e-scooter usage. Transportation Research Part D: Transport and Environment, 86, 102396. https://doi.org/10.1016/j.trd.2020.102396
   PubMed Web of Science ®Google Scholar
• Chan, N. D., & Shaheen, S. A. (2012). Ridesharing in North America: Past, present, and future. Transport Reviews, 32(1), 93–112. https://doi.org/10.1080/01441647.2011.621557
   Web of Science ®Google Scholar
• Chen, M., Wang, D., Sun, Y., Liu, C., & Bai, Z. (2017). Service evaluation of public bicycle scheme from a user perspective: A case study in Hangzhou, China. Transportation Research Record: Journal of the Transportation Research Board, 2634(1), 28–34. https://doi.org/10.3141/2634-04
   Google Scholar
• Chen, T. D., & Kockelman, K. M. (2016). Carsharing's life-cycle impacts on energy use and greenhouse gas emissions. Transportation Research Part D: Transport and Environment, 47, 276–284. https://doi.org/10.1016/j.trd.2016.05.012
   Web of Science ®Google Scholar
• Chen, T. D., Kockelman, K. M., & Hanna, J. P. (2016). Operations of a shared, autonomous, electric vehicle fleet: Implications of vehicle & charging infrastructure decisions. Transportation Research Part A: Policy and Practice, 94, 243–254.
   Web of Science ®Google Scholar
• Chen, X. M., Chen, C., Ni, L., & Li, L. (2018). Spatial visitation prediction of on-demand ride services using the scaling law. Physica A: Statistical Mechanics and Its Applications, 508, 84–94. https://doi.org/10.1016/j.physa.2018.05.005
   Web of Science ®Google Scholar
• Chen, X. M., Zahiri, M., & Zhang, S. (2017). Understanding ridesplitting behavior of on-demand ride services: An ensemble learning approach. Transportation Research Part C: Emerging Technologies, 76, 51–70. https://doi.org/10.1016/j.trc.2016.12.018
   Web of Science ®Google Scholar
• Chen, X. M., Zheng, H., Ke, J., & Yang, H. (2020). Dynamic optimization strategies for on-demand ride services platform: Surge pricing, commission rate, and incentives. Transportation Research Part B: Methodological, 138, 23–45. https://doi.org/10.1016/j.trb.2020.05.005
   Web of Science ®Google Scholar
• Clewlow, R. R. (2016). Carsharing and sustainable travel behavior: Results from the San Francisco Bay Area. Transport Policy, 51, 158–164. https://doi.org/10.1016/j.tranpol.2016.01.013
   Web of Science ®Google Scholar
• Cohen, B., & Kietzmann, J. (2014). Ride on! Mobility business models for the sharing economy. Organization & Environment, 27(3), 279–296. https://doi.org/10.1177/1086026614546199
   Web of Science ®Google Scholar
• Cohen, T., & Cavoli, C. (2019). Automated vehicles: exploring possible consequences of government (non)intervention for congestion and accessibility. Transport Reviews, 39(1), 129–151. https://doi.org/10.1080/01441647.2018.1524401
   Web of Science ®Google Scholar
• Concas, S., Winters, P. L., & Wambalaba, F. W. (2005). Fare pricing elasticity, subsidies, and demand for vanpool services. Transportation Research Record: Journal of the Transportation Research Board, 1924(1), 215–223. https://doi.org/10.1177/0361198105192400127
   Google Scholar
• Costain, C., Ardron, C., & Habib, K. N. (2012). Synopsis of users' behaviour of a carsharing program: A case study in Toronto. Transportation Research Part A: Policy and Practice, 46(3), 421–434.
   Web of Science ®Google Scholar
• De Lorimier, A., & El-Geneidy, A. M. (2013). Understanding the factors affecting vehicle usage and availability in carsharing networks: A case study of Communauto carsharing system from Montréal. Canada. International Journal of Sustainable Transportation, 7(1), 35–51. https://doi.org/10.1080/15568318.2012.660104
   Web of Science ®Google Scholar
• De Luca, S., & Di Pace, R. (2015). Modelling users’ behaviour in inter-urban carsharing program: A stated preference approach. Transportation Research Part A: Policy and Practice, 71, 59–76.
   Web of Science ®Google Scholar
• Deb, S., Tammi, K., Kalita, K., & Mahanta, P. (2018). Review of recent trends in charging infrastructure planning for electric vehicles. WIREs Energy and Environment, 7(6), e306. https://doi.org/10.1002/wene.306
   Google Scholar
• Delhomme, P., & Gheorghiu, A. (2016). Comparing French carpoolers and non-carpoolers: Which factors contribute the most to carpooling? Transportation Research Part D: Transport and Environment, 42, 1–15. https://doi.org/10.1016/j.trd.2015.10.014
   Web of Science ®Google Scholar
• Ding, Z. J., Dai, Z., Chen, X. M., & Jiang, R. (2020). Simulating on-demand ride services in a Manhattan-like urban network considering traffic dynamics. Physica A: Statistical Mechanics and Its Applications, 545, 123621. https://doi.org/10.1016/j.physa.2019.123621
   Web of Science ®Google Scholar
• Dong, J., & Ibrahim, R. (2020). Managing supply in the on-demand economy: Flexible workers, full-time employees, or both? Operations Research, 68(4), 1238–1264. https://doi.org/10.1287/opre.2019.1916
   Web of Science ®Google Scholar
• Dong, T., Xu, Z., Luo, Q., Yin, Y., Wang, J., & Ye, J. (2021). Optimal contract design for ride-sourcing services under dual sourcing. Transportation Research Part B: Methodological, 146, 289–313. https://doi.org/10.1016/j.trb.2021.01.014
   Web of Science ®Google Scholar
• Dong, Z., & Leng, M. (2021). Managing on-demand ridesharing operations: Optimal pricing decisions for a ridesharing platform. International Journal of Production Economics, 232, 107958. https://doi.org/10.1016/j.ijpe.2020.107958
   Web of Science ®Google Scholar
• Dowling, R., & Kent, J. (2015). Practice and public-private partnerships in sustainable transport governance: The case of car sharing in Sydney, Australia. Transport Policy, 40, 58–64. https://doi.org/10.1016/j.tranpol.2015.02.007
   Web of Science ®Google Scholar
• Eren, E., & Uz, V. E. (2020). A review on bike-sharing: The factors affecting bike-sharing demand. Sustainable Cities and Society, 54, 101882. https://doi.org/10.1016/j.scs.2019.101882
   Web of Science ®Google Scholar
• Fagnant, D. J., & Kockelman, K. (2014). The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios. Transportation Research Part C: Emerging Technologies, 40, 1–13. https://doi.org/10.1016/j.trc.2013.12.001
   Web of Science ®Google Scholar
• Fagnant, D. J., & Kockelman, K. (2015). Preparing a nation for autonomous vehicles: Opportunities, barriers and policy recommendations. Transportation Research Part A: Policy and Practice, 77, 167–181.
   Web of Science ®Google Scholar
• Fagnant, D. J., Kockelman, K. M., & Bansal, P. (2015). Operations of shared autonomous vehicle fleet for Austin, Texas, market. Transportation Research Record: Journal of the Transportation Research Board, 2563(1), 98–106. https://doi.org/10.3141/2536-12
   Google Scholar
• Fishman, E., Washington, S., & Haworth, N. (2013). Bike share: A synthesis of the literature. Transport Reviews, 33(2), 148–165. https://doi.org/10.1080/01441647.2013.775612
   Web of Science ®Google Scholar
• Fishman, E., Washington, S., & Haworth, N. (2014). Bike share's impact on car use: Evidence from the United States, Great Britain, and Australia. Transportation Research Part D: Transport and Environment, 31, 13–20. https://doi.org/10.1016/j.trd.2014.05.013
   Web of Science ®Google Scholar
• Frade, I., & Ribeiro, A. (2015). Bike-sharing stations: A maximal covering location approach. Transportation Research Part A: Policy and Practice, 82, 216–227.
   Web of Science ®Google Scholar
• Gawron, J. H., Keoleian, G. A., De Kleine, R. D., Wallington, T. J., & Kim, H. C. (2019). Deep decarbonization from electrified autonomous taxi fleets: Life cycle assessment and case study in Austin, TX. Transportation Research Part D: Transport and Environment, 73, 130–141. https://doi.org/10.1016/j.trd.2019.06.007
   Web of Science ®Google Scholar
• Global e-Sustainability Initiative. (2008). SMART 2020: Enabling the low carbon economy in the information age. United States Report Addendum. Retreived June 6, 2011 frpm http://www.smart2020.org/_assets/files/Smart2020UnitedStatesReportAddendum.pdf.
   Google Scholar
• Greenblatt, J. B., & Saxena, S. (2015). Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles. Nature Climate Change, 5(9), 860–863. https://doi.org/10.1038/nclimate2685
   Web of Science ®Google Scholar
• Gu, T., Kim, I., & Currie, G. (2019). To be or not to be dockless: Empirical analysis of dockless bikeshare development in China. Transportation Research Part A: Policy and Practice, 119, 122–147.
   Web of Science ®Google Scholar
• Habib, K. M. N., Tian, Y., & Zaman, H. (2011). Modeling commuting mode choice with explicit consideration of carpool in the choice set formation. Transportation, 38(4), 587–604. https://doi.org/10.1007/s11116-011-9333-1
   Web of Science ®Google Scholar
• Hampshire, R., & Gaites, C. (2011). Peer-to-peer car-sharing: Market analysis and potential growth. Transportation Research Record: Journal of the Transportation Research Board, 2217(1), 119–126. https://doi.org/10.3141/2217-15
   Google Scholar
• He, F., Wu, D., Yin, Y., & Guan, Y. (2013). Optimal deployment of public charging stations for plug-in hybrid electric vehicles. Transportation Research Part B: Methodological, 47, 87–101. https://doi.org/10.1016/j.trb.2012.09.007
   Web of Science ®Google Scholar
• Hollingsworth, J., Copeland, B., & Johnson, J. X. (2019). Are e-scooters polluters? The environmental impacts of shared dockless electric scooters. Environmental Research Letters, 14(8), 084031. https://doi.org/10.1088/1748-9326/ab2da8
   Web of Science ®Google Scholar
• Hong, Z., Chen, Y., Mahmassani, H. S., & Xu, S. (2017). Commuter ride-sharing using topology-based vehicle trajectory clustering: Methodology, application and impact evaluation. Transportation Research Part C: Emerging Technologies, 85, 573–590. https://doi.org/10.1016/j.trc.2017.10.020
   Web of Science ®Google Scholar
• Hu, J.-W., Javaid, A., & Creutzig, F. (2021). Leverage points for accelerating adoption of shared electric cars: Perceived benefits and environmental impact of NEVs. Energy Policy, 155, 112349. https://doi.org/10.1016/j.enpol.2021.112349
   Web of Science ®Google Scholar
• Hu, L., & Liu, Y. (2016). Joint design of parking capacities and fleet size for one-way station-based carsharing systems with road congestion constraints. Transportation Research Part B: Methodological, 93, 268–299. https://doi.org/10.1016/j.trb.2016.07.021
   Web of Science ®Google Scholar
• Huang, K., An, K., & de Almeida Correia, G. H. (2020). Planning station capacity and fleet size of one-way electric carsharing systems with continuous state of charge functions. European Journal of Operational Research, 287(3), 1075–1091. https://doi.org/10.1016/j.ejor.2020.05.001
   Web of Science ®Google Scholar
• Hyland, M., & Mahmassani, H. S. (2018). Dynamic autonomous vehicle fleet operations: Optimization-based strategies to assign AVs to immediate traveler demand requests. Transportation Research Part C: Emerging Technologies, 92, 278–297. https://doi.org/10.1016/j.trc.2018.05.003
   Web of Science ®Google Scholar
• Javanshour, F., Dia, H., & Duncan, G. (2019). Exploring the performance of autonomous mobility on-demand systems under demand uncertainty. Transportmetrica A: Transport Science, 15(2), 698–721. https://doi.org/10.1080/23249935.2018.1528485
   Web of Science ®Google Scholar
• Jian, S., Liu, W., Wang, X., Yang, H., & Waller, S. T. (2020). On integrating carsharing and parking sharing services. Transportation Research Part B: Methodological, 142, 19–44. https://doi.org/10.1016/j.trb.2020.09.013
   Web of Science ®Google Scholar
• Jian, S., Rashidi, T. H., & Dixit, V. (2017). An analysis of carsharing vehicle choice and utilization patterns using multiple discrete-continuous extreme value (MDCEV) models. Transportation Research Part A: Policy and Practice, 103, 362–376.
   Web of Science ®Google Scholar
• Jian, S., Rashidi, T. H., Wijayaratna, K. P., & Dixit, V. V. (2016). A spatial hazard-based analysis for modelling vehicle selection in station-based carsharing systems. Transportation Research Part C: Emerging Technologies, 72, 130–142. https://doi.org/10.1016/j.trc.2016.09.008
   Web of Science ®Google Scholar
• Johnson, R. E. (2005). Doubling personal rapid transit capacity with ridesharing. Transportation Research Record: Journal of the Transportation Research Board, 1930(1), 107–112. https://doi.org/10.1177/0361198105193000113
   Google Scholar
• Jorge, D., Correia, G. H., & Barnhart, C. (2014). Comparing optimal relocation operations with simulated relocation policies in one-way carsharing systems. IEEE Transactions on Intelligent Transportation Systems, 15(4), 1667–1675. https://doi.org/10.1109/TITS.2014.2304358
   Web of Science ®Google Scholar
• Jorge, D., Molnar, G., & de Almeida Correia, G. H. (2015). Trip pricing of one-way station-based carsharing networks with zone and time of day price variations. Transportation Research Part B: Methodological, 81, 461–482. https://doi.org/10.1016/j.trb.2015.06.003
   Web of Science ®Google Scholar
• Kaddoura, I., Bischoff, J., & Nagel, K. (2020). Towards welfare optimal operation of innovative mobility concepts: External cost pricing in a world of shared autonomous vehicles. Transportation Research Part A: Policy and Practice, 136, 48–63.
   Web of Science ®Google Scholar
• Ke, J., Cen, X., Yang, H., Chen, X., & Ye, J. (2019). Modelling drivers’ working and recharging schedules in a ride-sourcing market with electric vehicles and gasoline vehicles. Transportation Research Part E: Logistics and Transportation Review, 125, 160–180. https://doi.org/10.1016/j.tre.2019.03.010
   Web of Science ®Google Scholar
• Ke, J., Qin, X., Yang, H., Zheng, Z., Zhu, Z., & Ye, J. (2021a). Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network. Transportation Research Part C: Emerging Technologies, 122, 102858. https://doi.org/10.1016/j.trc.2020.102858
   Web of Science ®Google Scholar
• Ke, J., Yang, H., Zheng, H., Chen, X., Jia, Y., Gong, P., & Ye, J. (2018). Hexagon-based convolutional neural network for supply-demand forecasting of ride-sourcing services. IEEE Transactions on Intelligent Transportation Systems, 20(11), 4160–4173. https://doi.org/10.1109/TITS.2018.2882861
   Web of Science ®Google Scholar
• Ke, J., Zheng, H., Yang, H., & Chen, X. (2017). Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach. Transportation Research Part C: Emerging Technologies, 85, 591–608. https://doi.org/10.1016/j.trc.2017.10.016
   Web of Science ®Google Scholar
• Ke, J., Zhu, Z., Yang, H., & He, Q. (2021b). Equilibrium analyses and operational designs of a coupled market with substitutive and complementary ride-sourcing services to public transits. Transportation Research Part E: Logistics and Transportation Review, 148, 102236. https://doi.org/10.1016/j.tre.2021.102236
   Web of Science ®Google Scholar
• Kong, H., Jin, S. T., & Sui, D. Z. (2020a). Deciphering the relationship between bikesharing and public transit: Modal substitution, integration, and complementation. Transportation Research Part D: Transport and Environment, 85, 102392. https://doi.org/10.1016/j.trd.2020.102392
   Web of Science ®Google Scholar
• Kong, H., Zhang, X., & Zhao, J. (2020b). How does ridesourcing substitute for public transit? A geospatial perspective in Chengdu, China. Journal of Transport Geography, 86, 102769. https://doi.org/10.1016/j.jtrangeo.2020.102769
   Web of Science ®Google Scholar
• Konishi, H., & Mun, S. (2010). Carpooling and congestion pricing: HOV and HOT lanes. Regional Science and Urban Economics, 40(4), 173–186. https://doi.org/10.1016/j.regsciurbeco.2010.03.009
   Web of Science ®Google Scholar
• Kontou, E., Garikapati, V., & Hou, Y. (2020). Reducing ridesourcing empty vehicle travel with future travel demand prediction. Transportation Research Part C: Emerging Technologies, 121, 102826. https://doi.org/10.1016/j.trc.2020.102826
   Web of Science ®Google Scholar
• Kou, Z., Wang, X., Chiu, S. F. A., & Cai, H. (2020). Quantifying greenhouse gas emissions reduction from bike share systems: a model considering real-world trips and transportation mode choice patterns. Resources, Conservation and Recycling, 153, 104534. https://doi.org/10.1016/j.resconrec.2019.104534
   Web of Science ®Google Scholar
• Kramer, S., Hoffmann, C., Kuttler, T., & Hendzlik, M. (2014). Electric car sharing as an integrated part of public transport: Customers' needs and experience. In Evolutionary paths towards the mobility patterns of the future (pp. 101–112). Springer.
   Google Scholar
• Krishnaprasad, S., & Tripathi, R. R. (2020). A pricing mechanism to improve capacity utilisation in ridesharing. Journal of the Operational Research Society, in press. https://doi.org/10.1080/01605682.2020.1860660
   Google Scholar
• Krueger, R., Rashidi, T. H., & Rose, J. M. (2016). Preferences for shared autonomous vehicles. Transportation Research Part C: Emerging Technologies, 69, 343–355. https://doi.org/10.1016/j.trc.2016.06.015
   Web of Science ®Google Scholar
• Kumar, R. R., Chakraborty, A., & Mandal, P. (2021). Promoting electric vehicle adoption: Who should invest in charging infrastructure? Transportation Research Part E: Logistics and Transportation Review, 149, 102295. https://doi.org/10.1016/j.tre.2021.102295
   Web of Science ®Google Scholar
• Lavieri, P. S., Garikapati, V. M., Bhat, C. R., Pendyala, R. M., Astroza, S., & Dias, F. F. (2017). Modeling individual preferences for ownership and sharing of autonomous vehicle technologies. Transportation Research Record: Journal of the Transportation Research Board, 2665(1), 1–10. https://doi.org/10.3141/2665-01
   Google Scholar
• Lazarus, J., Pourquier, J., Feng, F., Hammel, H., & Shaheen, S. (2020). Micromobility evolution and expansion: Understanding how docked and dockless bikesharing models complement and compete – A case study of San Francisco. Journal of Transport Geography, 84, 102620. https://doi.org/10.1016/j.jtrangeo.2019.102620
   Web of Science ®Google Scholar
• Lee, D., Mulrow, J., Haboucha, C. J., Derrible, S., & Shiftan, Y. (2019). Attitudes on autonomous vehicle adoption using interpretable gradient boosting machine. Transportation Research Record: Journal of the Transportation Research Board, 2673(11), 865–878. https://doi.org/10.1177/0361198119857953
   Web of Science ®Google Scholar
• Lee, J. B., Byun, W., Lee, S. H., & Do, M. (2014). Correlation between optimal carsharing locations and carbon dioxide emissions in urban areas. International Journal of Environmental Science and Technology, 11(8), 2319–2328. https://doi.org/10.1007/s13762-014-0640-x
   Web of Science ®Google Scholar
• Lei, C., Jiang, Z., & Ouyang, Y. (2020). Path-based dynamic pricing for vehicle allocation in ridesharing systems with fully compliant drivers. Transportation Research Part B: Methodological, 132, 60–75. https://doi.org/10.1016/j.trb.2019.01.017
   Web of Science ®Google Scholar
• Levin, M. W. (2017). Congestion-aware system optimal route choice for shared autonomous vehicles. Transportation Research Part C: Emerging Technologies, 82, 229–247. https://doi.org/10.1016/j.trc.2017.06.020
   Web of Science ®Google Scholar
• Levin, M. W., Odell, M., Samarasena, S., & Schwartz, A. (2019). A linear program for optimal integration of shared autonomous vehicles with public transit. Transportation Research Part C: Emerging Technologies, 109, 267–288. https://doi.org/10.1016/j.trc.2019.10.007
   Web of Science ®Google Scholar
• Li, S., Poolla, K., & Varaiya, P. (2021). Impact of congestion charge and minimum wage on TNCs: A case study for San Francisco. Transportation Research Part A: Policy and Practice, 148, 237–261.
   Web of Science ®Google Scholar
• Li, S., Tavafoghi, H., Poolla, K., & Varaiya, P. (2019). Regulating TNCs: Should Uber and Lyft set their own rules? Transportation Research Part B: Methodological, 129, 193–225. https://doi.org/10.1016/j.trb.2019.09.008
   Web of Science ®Google Scholar
• Li, X., Zhang, Y., Du, M., & Yang, J. (2020). The forecasting of passenger demand under hybrid ridesharing service modes: A combined model based on WT-FCBF-LSTM. Sustainable Cities and Society, 62, 102419. https://doi.org/10.1016/j.scs.2020.102419
   Web of Science ®Google Scholar
• Li, Y., Taeihagh, A., & De Jong, M. (2018). The governance of risks in ridesharing: A revelatory case from Singapore. Energies, 11(5), 1277. https://doi.org/10.3390/en11051277
   Web of Science ®Google Scholar
• Liang, X., Correia, G. H., de, A., & van Arem, B. (2016). Optimizing the service area and trip selection of an electric automated taxi system used for the last mile of train trips. Transportation Research Part E: Logistics and Transportation Review, 93, 115–129. https://doi.org/10.1016/j.tre.2016.05.006
   Web of Science ®Google Scholar
• Liu, J., & Wei, Q. (2018). Risk evaluation of electric vehicle charging infrastructure public-private partnership projects in China using fuzzy TOPSIS. Journal of Cleaner Production, 189, 211–222. https://doi.org/10.1016/j.jclepro.2018.04.103
   Web of Science ®Google Scholar
• Liu, J., Kockelman, K. M., Boesch, P. M., & Ciari, F. (2017). Tracking a system of shared autonomous vehicles across the Austin, Texas network using agent-based simulation. Transportation, 44(6), 1261–1278. https://doi.org/10.1007/s11116-017-9811-1
   Web of Science ®Google Scholar
• Liu, X., Yan, X., Liu, F., Wang, R., & Leng, Y. (2019). A trip-specific model for fuel saving estimation and subsidy policy making of carpooling based on empirical data. Applied Energy, 240, 295–311. https://doi.org/10.1016/j.apenergy.2019.02.003
   Web of Science ®Google Scholar
• Liu, Y., & Li, Y. (2017). Pricing scheme design of ridesharing program in morning commute problem. Transportation Research Part C: Emerging Technologies, 79, 156–177. https://doi.org/10.1016/j.trc.2017.02.020
   Web of Science ®Google Scholar
• Loeb, B., & Kockelman, K. M. (2019). Fleet performance and cost evaluation of a shared autonomous electric vehicle (SAEV) fleet: A case study for Austin, Texas. Transportation Research Part A: Policy and Practice, 121, 374–385.
   Web of Science ®Google Scholar
• Lu, M., Hsu, S.-C., Chen, P.-C., & Lee, W.-Y. (2018). Improving the sustainability of integrated transportation system with bike-sharing: A spatial agent-based approach. Sustainable Cities and Society, 41, 44–51. https://doi.org/10.1016/j.scs.2018.05.023
   Web of Science ®Google Scholar
• Luna, T. F., Uriona-Maldonado, M., Silva, M. E., & Vaz, C. R. (2020). The influence of e-carsharing schemes on electric vehicle adoption and carbon emissions: An emerging economy study. Transportation Research Part D: Transport and Environment, 79, 102226. https://doi.org/10.1016/j.trd.2020.102226
   Web of Science ®Google Scholar
• Ma, H., Fang, F., & Parkes, D. C. (2020). Spatio-temporal pricing for ridesharing platforms. ACM SIGecom Exchanges, 18(2), 53–57. https://doi.org/10.1145/3440968.3440975
   Google Scholar
• Ma, J., Li, X., Zhou, F., & Hao, W. (2017). Designing optimal autonomous vehicle sharing and reservation systems: A linear programming approach. Transportation Research Part C: Emerging Technologies, 84, 124–141. https://doi.org/10.1016/j.trc.2017.08.022
   Web of Science ®Google Scholar
• Ma, J., Xu, M., Meng, Q., & Cheng, L. (2020). Ridesharing user equilibrium problem under OD-based surge pricing strategy. Transportation Research Part B: Methodological, 134, 1–24. https://doi.org/10.1016/j.trb.2020.02.001
   Web of Science ®Google Scholar
• Malokin, A., Circella, G., & Mokhtarian, P. L. (2019). How do activities conducted while commuting influence mode choice? Using revealed preference models to inform public transportation advantage and autonomous vehicle scenarios. Transportation Research Part A: Policy and Practice, 124, 82–114.
   Web of Science ®Google Scholar
• Martin, E., Shaheen, S., & Lidicker, J. (2010). Carsharing's impact on household vehicle holdings: Results from a North American shared-use vehicle survey. Transportation Research Record: Journal of the Transportation Research Board, 2143(1), 150–158. https://doi.org/10.3141/2143-19
   Web of Science ®Google Scholar
• Masoud, M.,Elhenawy, M.,Almannaa, M. H.,Liu, S. Q.,Glaser, S., &Rakotonirainy, A. (2019). Heuristic approaches to solve e-scooter assignment problem. IEEE Access, 7, 175093–175105.
   Web of Science ®Google Scholar
• McKenzie, G. (2019). Spatiotemporal comparative analysis of scooter-share and bike-share usage patterns in Washington, D.C. Journal of Transport Geography, 78, 19–28. https://doi.org/10.1016/j.jtrangeo.2019.05.007
   Web of Science ®Google Scholar
• McKenzie, G. (2020). Urban mobility in the sharing economy: A spatiotemporal comparison of shared mobility services. Computers, Environment and Urban Systems, 79, 101418. https://doi.org/10.1016/j.compenvurbsys.2019.101418
   Web of Science ®Google Scholar
• Menon, N., Barbour, N., Zhang, Y., Pinjari, A. R., & Mannering, F. (2019). Shared autonomous vehicles and their potential impacts on household vehicle ownership: An exploratory empirical assessment. International Journal of Sustainable Transportation, 13(2), 111–122. https://doi.org/10.1080/15568318.2018.1443178
   Web of Science ®Google Scholar
• Mo, B., Cao, Z., Zhang, H., Shen, Y., & Zhao, J. (2021). Competition between shared autonomous vehicles and public transit: A case study in Singapore. Transportation Research Part C: Emerging Technologies, 127, 103058. https://doi.org/10.1016/j.trc.2021.103058
   Web of Science ®Google Scholar
• Mo, D., Yu, J., & Chen, X. (2020). Modeling and managing heterogeneous ride-sourcing platforms with government subsidies on electric vehicles. Transportation Research Part B: Methodological, 139, 447–472. https://doi.org/10.1016/j.trb.2020.07.006
   Web of Science ®Google Scholar
• Mohamed, M. J., Rye, T., & Fonzone, A. (2019). Operational and policy implications of ridesourcing services: A case of Uber in London, UK. Case Studies on Transport Policy, 7(4), 823–836. https://doi.org/10.1016/j.cstp.2019.07.013
   Web of Science ®Google Scholar
• Moody, J., Middleton, S., & Zhao, J. (2019). Rider-to-rider discriminatory attitudes and ridesharing behavior. Transportation Research Part F: Traffic Psychology and Behaviour, 62, 258–273. https://doi.org/10.1016/j.trf.2019.01.003
   Web of Science ®Google Scholar
• Münzel, K., Piscicelli, L., Boon, W., & Frenken, K. (2019). Different business models – different users? Uncovering the motives and characteristics of business-to-consumer and peer-to-peer carsharing adopters in The Netherlands. Transportation Research Part D: Transport and Environment, 73, 276–306. https://doi.org/10.1016/j.trd.2019.07.001
   Web of Science ®Google Scholar
• Nair, G. S., Astroza, S., Bhat, C. R., Khoeini, S., & Pendyala, R. M. (2018). An application of a rank ordered probit modeling approach to understanding level of interest in autonomous vehicles. Transportation, 45(6), 1623–1637. https://doi.org/10.1007/s11116-018-9945-9
   Web of Science ®Google Scholar
• Nakanishi, W., Yamashita, Y., & Asakura, Y. (2021). Empirical analysis on long-distance peer-to-peer ridesharing service in Japan. International Journal of Sustainable Transportation, 15(8), 653-658.
   Web of Science ®Google Scholar
• Namazu, M., & Dowlatabadi, H. (2015). Characterizing the GHG emission impacts of carsharing: A case of Vancouver. Environmental Research Letters, 10(12), 124017. https://doi.org/10.1088/1748-9326/10/12/124017
   Web of Science ®Google Scholar
• Narayanan, S.,Chaniotakis, E., &Antoniou, C. (2020). Shared autonomous vehicle services: A comprehensive review. Transportation Research Part C: Emerging Technologies, 111, 255–293.
   Web of Science ®Google Scholar
• Nijland, H., & van Meerkerk, J. (2017). Mobility and environmental impacts of car sharing in the Netherlands. Environmental Innovation and Societal Transitions, 23, 84–91. https://doi.org/10.1016/j.eist.2017.02.001
   Web of Science ®Google Scholar
• Nourinejad, M., & Roorda, M. J. (2014). A dynamic carsharing decision support system. Transportation Research Part E: Logistics and Transportation Review, 66, 36–50. https://doi.org/10.1016/j.tre.2014.03.003
   Web of Science ®Google Scholar
• Nourinejad, M., & Roorda, M. J. (2015). Car-sharing operations policies: a comparison between one-way and two-way systems. Transportation, 42(3), 497–518. https://doi.org/10.1007/s11116-015-9604-3
   Web of Science ®Google Scholar
• Pandey, V., Monteil, J., Gambella, C., & Simonetto, A. (2019). On the needs for MaaS platforms to handle competition in ridesharing mobility. Transportation Research Part C: Emerging Technologies, 108, 269–288. https://doi.org/10.1016/j.trc.2019.09.021
   Web of Science ®Google Scholar
• Pelzer, D., Xiao, J., Zehe, D., Lees, M. H., Knoll, A. C., & Aydt, H. (2015). A partition-based match making algorithm for dynamic ridesharing. IEEE Transactions on Intelligent Transportation Systems, 16(5), 2587–2598. https://doi.org/10.1109/TITS.2015.2413453
   Web of Science ®Google Scholar
• Peters, L., & MacKenzie, D. (2019). The death and rebirth of bikesharing in Seattle: Implications for policy and system design. Transportation Research Part A: Policy and Practice, 130, 208–226.
   Web of Science ®Google Scholar
• Pinto, G. A., Vieira, K. C., Carvalho, E. G., & Sugano, J. Y. (2019). Applying the lazy user theory to understand the motivations for choosing carpooling over public transport. Sustainable Production and Consumption, 20, 243–252. https://doi.org/10.1016/j.spc.2019.07.002
   Web of Science ®Google Scholar
• Rahimi, A., Azimi, G., & Jin, X. (2020). Examining human attitudes toward shared mobility options and autonomous vehicles. Transportation Research Part F: Traffic Psychology and Behaviour, 72, 133–154. https://doi.org/10.1016/j.trf.2020.05.001
   Web of Science ®Google Scholar
• Rahman, I., Vasant, P. M., Singh, B. S. M., Abdullah-Al-Wadud, M., & Adnan, N. (2016). Review of recent trends in optimization techniques for plug-in hybrid, and electric vehicle charging infrastructures. Renewable and Sustainable Energy Reviews, 58, 1039–1047. https://doi.org/10.1016/j.rser.2015.12.353
   Web of Science ®Google Scholar
• Rodier, C., Alemi, F., & Smith, D. (2016). Dynamic ridesharing: Exploration of potential for reduction in vehicle miles traveled. Transportation Research Record: Journal of the Transportation Research Board, 2542(1), 120–126. https://doi.org/10.3141/2542-15
   Web of Science ®Google Scholar
• Rotaris, L., Danielis, R., & Maltese, I. (2019). Carsharing use by college students: The case of Milan and Rome. Transportation Research Part A: Policy and Practice, 120, 239–251.
   Web of Science ®Google Scholar
• Sánchez, D., Martínez, S., & Domingo-Ferrer, J. (2016). Co-utile P2P ridesharing via decentralization and reputation management. Transportation Research Part C: Emerging Technologies, 73, 147–166. https://doi.org/10.1016/j.trc.2016.10.017
   Web of Science ®Google Scholar
• Santos, G. (2017). Incentives to encourage shared mobility. Centre Regulation Eur.
   Google Scholar
• Shaheen, S.,Cohen, A.,Chan, N., &Bansal, A. (2020). Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes. In Transportation, land use, and environmental planning (pp. 237-262). Elsevier.
   Google Scholar
• Shaheen, S., Cohen, A., Zohdy, I. (2016a). Shared mobility: current practices and guiding principles. Federal Highway Administration.
   Google Scholar
• Shaheen, S., Chan, N., Bansal, A., Cohen, A. (2015) Shared Mobility: A Sustainability & Technologies Workshop: Definitions, Industry Developments, and Early Understanding. UC Berkeley.
   Google Scholar
• Shaheen, S., Bell, C., Cohen, A., Yelchuru, B.(2017). Travel Behavior: Shared Mobility and Transportation Equity. Federal Highway Administration.
   Google Scholar
• Shaheen, S. A., & Cohen, A. P. (2013). Carsharing and personal vehicle services: worldwide market developments and emerging trends. International Journal of Sustainable Transportation, 7(1), 5–34. https://doi.org/10.1080/15568318.2012.660103
   Web of Science ®Google Scholar
• Shaheen, S. A., Chan, N. D., & Gaynor, T. (2016b). Casual carpooling in the San Francisco Bay Area: Understanding user characteristics, behaviors, and motivations. Transport Policy, 51, 165–173. https://doi.org/10.1016/j.tranpol.2016.01.003
   Web of Science ®Google Scholar
• Shaheen, S. A., Cohen, A. P., & Martin, E. (2010). Carsharing parking policy: Review of North American practices and San Francisco, California, Bay Area Case Study. Transportation Research Record: Journal of the Transportation Research Board, 2187(1), 146–156. https://doi.org/10.3141/2187-19
   Google Scholar
• Shaheen, S., & Cohen, A. (2019). Shared micromoblity policy toolkit: Docked and dockless bike and scooter sharing. UC Berkeley Transportation Sustainability Research Center. Retrieved from https://escholarship.org/uc/item/00k897b5.
   Google Scholar
• Shaheen, S., Guzman, S., & Zhang, H. (2010). Bikesharing in Europe, the Americas, and Asia: Past, present, and future. Transportation Research Record: Journal of the Transportation Research Board, 2143(1), 159–167. https://doi.org/10.3141/2143-20
   Web of Science ®Google Scholar
• Shen, Y., Zhang, H., & Zhao, J. (2018). Integrating shared autonomous vehicle in public transportation system: A supply-side simulation of the first-mile service in Singapore. Transportation Research Part A: Policy and Practice, 113, 125–136.
   Web of Science ®Google Scholar
• Sheppard, C. J., Bauer, G. S., Gerke, B. F., Greenblatt, J. B., Jenn, A. T., & Gopal, A. R. (2019). Joint optimization scheme for the planning and operations of shared autonomous electric vehicle fleets serving mobility on demand. Transportation Research Record: Journal of the Transportation Research Board, 2673(6), 579–597. https://doi.org/10.1177/0361198119838270
   Web of Science ®Google Scholar
• Sioui, L., Morency, C., & Trepanier, M. (2013). How carsharing affects the travel behavior of households: A case study of Montréal. Canada. International Journal of Sustainable Transportation, 7(1), 52–69. https://doi.org/10.1080/15568318.2012.660109
   Web of Science ®Google Scholar
• Song, J., Cho, Y. J., Kang, M. H., & Hwang, K. Y. (2020). An application of reinforced learning-based dynamic pricing for improvement of ridesharing platform service in Seoul. Electronics, 9(11), 1818. https://doi.org/10.3390/electronics9111818
   Web of Science ®Google Scholar
• Soria, J., Chen, Y., & Stathopoulos, A. (2020). K-Prototypes segmentation analysis on large-scale ridesourcing trip data. Transportation Research Record: Journal of the Transportation Research Board, 2674(9), 383–394. https://doi.org/10.1177/0361198120929338
   Web of Science ®Google Scholar
• Stasko, T. H., Buck, A. B., & Gao, H. O. (2013). Carsharing in a university setting: Impacts on vehicle ownership, parking demand, and mobility in Ithaca. NY. Transport Policy, 30, 262–268. https://doi.org/10.1016/j.tranpol.2013.09.018
   Web of Science ®Google Scholar
• Stiglic, M., Agatz, N., Savelsbergh, M., & Gradisar, M. (2018). Enhancing urban mobility: Integrating ride-sharing and public transit. Computers & Operations Research, 90, 12–21. https://doi.org/10.1016/j.cor.2017.08.016
   Web of Science ®Google Scholar
• Sui, Y., Zhang, H., Song, X., Shao, F., Yu, X., Shibasaki, R., Sun, R., Yuan, M., Wang, C., Li, S., & Li, Y. (2019). GPS data in urban online ride-hailing: A comparative analysis on fuel consumption and emissions. Journal of Cleaner Production, 227, 495–505. https://doi.org/10.1016/j.jclepro.2019.04.159
   Web of Science ®Google Scholar
• Sun, D., & Ding, X. (2018). Spatiotemporal evolution of ridesourcing markets under the new restriction policy: A case study in Shanghai. Transportation Research Part A: Policy and Practice, 130, 227–239.
   Web of Science ®Google Scholar
• Tafreshian, A., & Masoud, N. (2020). Using subsidies to stabilize peer-to-peer ridesharing markets with role assignment. Transportation Research Part C: Emerging Technologies, 120, 102770. https://doi.org/10.1016/j.trc.2020.102770
   Web of Science ®Google Scholar
• Tan, R., & Lin, B. (2020). Are people willing to support the construction of charging facilities in China? Energy Policy, 143, 111604. https://doi.org/10.1016/j.enpol.2020.111604
   Web of Science ®Google Scholar
• Ter Schure, J., Napolitan, F., & Hutchinson, R. (2012). Cumulative impacts of carsharing and unbundled parking on vehicle ownership and mode choice. Transportation Research Record: Journal of the Transportation Research Board, 2319(1), 96–104. https://doi.org/10.3141/2319-11
   Google Scholar
• Thaithatkul, P., Seo, T., Kusakabe, T., & Asakura, Y. (2019). Adoption of dynamic ridesharing system under influence of information on social network. Transportation Research Procedia, 37, 401–408. https://doi.org/10.1016/j.trpro.2018.12.209
   Google Scholar
• Tian, L. J., Sheu, J. B., & Huang, H. J. (2019). The morning commute problem with endogenous shared autonomous vehicle penetration and parking space constraint. Transportation Research Part B: Methodological, 123, 258–278. https://doi.org/10.1016/j.trb.2019.04.001
   Web of Science ®Google Scholar
• Tirachini, A., & del Río, M. (2019). Ride-hailing in Santiago de Chile: Users' characterisation and effects on travel behavior. Transport Policy, 82, 46–57. https://doi.org/10.1016/j.tranpol.2019.07.008
   Web of Science ®Google Scholar
• Tirachini, A., & Gomez-Lobo, A. (2020). Does ride-hailing increase or decrease vehicle kilometers traveled (VKT)? A simulation approach for Santiago de Chile. International Journal of Sustainable Transportation, 14(3), 187–204. https://doi.org/10.1080/15568318.2018.1539146
   Web of Science ®Google Scholar
• Turan, B., Pedarsani, R., & Alizadeh, M. (2020). Dynamic pricing and fleet management for electric autonomous mobility on demand systems. Transportation Research Part C: Emerging Technologies, 121, 102829. https://doi.org/10.1016/j.trc.2020.102829
   Web of Science ®Google Scholar
• Uteng, T. P., Julsrud, T. E., & George, C. (2019). The role of life events and context in type of car share uptake: Comparing users of peer-to-peer and cooperative programs in Oslo, Norway. Transportation Research Part D: Transport and Environment, 71, 186–206. https://doi.org/10.1016/j.trd.2019.01.009
   Web of Science ®Google Scholar
• Vanoutrive, T., Van De Vijver, E., Van Malderen, L., Jourquin, B., Thomas, I., Verhetsel, A., & Witlox, F. (2012). What determines carpooling to workplaces in Belgium: location, organisation, or promotion? Journal of Transport Geography, 22, 77–86. https://doi.org/10.1016/j.jtrangeo.2011.11.006
   Web of Science ®Google Scholar
• Vosooghi, R., Puchinger, J., Jankovic, M., & Vouillon, A. (2019). Shared autonomous vehicle simulation and service design. Transportation Research Part C: Emerging Technologies, 107, 15–33. https://doi.org/10.1016/j.trc.2019.08.006
   Web of Science ®Google Scholar
• Wang, H., &Yang, H. (2019). Ridesourcing systems: A framework and review. Transportation Research Part B: Methodological, 129, 122–155.
   Web of Science ®Google Scholar
• Wang, L., Zhong, H., Ma, W., Zhong, Y., & Wang, L. (2020). Multi-source data-driven prediction for the dynamic pickup demand of one-way carsharing systems. Transportmetrica B: Transport Dynamics, 8(1), 90–107.
   Web of Science ®Google Scholar
• Wang, L., Zhong, Y., & Ma, W. (2018). GPS-data-driven dynamic destination prediction for on-demand one-way carsharing system. IET Intelligent Transport Systems, 12(10), 1291–1299. https://doi.org/10.1049/iet-its.2018.5250
   Web of Science ®Google Scholar
• Wang, M., & Zhou, X. (2017). Bike-sharing systems and congestion: Evidence from US cities. Journal of Transport Geography, 65, 147–154. https://doi.org/10.1016/j.jtrangeo.2017.10.022
   Web of Science ®Google Scholar
• Wang, N., Guo, J., Liu, X., & Fang, T. (2020). A service demand forecasting model for one-way electric car-sharing systems combining long short-term memory networks with Granger causality test. Journal of Cleaner Production, 244, 118812. https://doi.org/10.1016/j.jclepro.2019.118812
   Web of Science ®Google Scholar
• Wang, S., Jiang, Z., Noland, R. B., & Mondschein, A. S. (2020). Attitudes towards privately-owned and shared autonomous vehicles. Transportation Research Part F: Traffic Psychology and Behaviour, 72, 297–306. https://doi.org/10.1016/j.trf.2020.05.014
   Web of Science ®Google Scholar
• Wang, T., & Chen, C. (2012). Attitudes, mode switching behavior, and the built environment: A longitudinal study in the Puget Sound Region. Transportation Research Part A: Policy and Practice, 46(10), 1594–1607.
   Web of Science ®Google Scholar
• Wang, Z., Chen, X., & Chen, X. M. (2019). Ridesplitting is shaping young people’s travel behavior: Evidence from comparative survey via ride-sourcing platform. Transportation Research Part D: Transport and Environment, 75, 57–71. https://doi.org/10.1016/j.trd.2019.08.017
   Web of Science ®Google Scholar
• Ward, J. W., Michalek, J. J., Azevedo, I. L., Samaras, C., & Ferreira, P. (2019). Effects of on-demand ridesourcing on vehicle ownership, fuel consumption, vehicle miles traveled, and emissions per capita in US States. Transportation Research Part C: Emerging Technologies, 108, 289–301. https://doi.org/10.1016/j.trc.2019.07.026
   Web of Science ®Google Scholar
• Xie, X. F., & Wang, Z. J. (2018). Examining travel patterns and characteristics in a bikesharing network and implications for data-driven decision supports: Case study in the Washington DC area. Journal of Transport Geography, 71, 84–102. https://doi.org/10.1016/j.jtrangeo.2018.07.010
   Web of Science ®Google Scholar
• Xiong, Y., Gan, J., An, B., Miao, C., & Bazzan, A. L. C. (2018). Optimal electric vehicle fast charging station placement based on game theoretical framework. IEEE Transactions on Intelligent Transportation Systems, 19(8), 2493–2504. https://doi.org/10.1109/TITS.2017.2754382
   Web of Science ®Google Scholar
• Xu, H., Ordóñez, F., & Dessouky, M. (2015). A traffic assignment model for a ridesharing transportation market. Journal of Advanced Transportation, 49(7), 793–816. https://doi.org/10.1002/atr.1300
   Web of Science ®Google Scholar
• Xu, M., Meng, Q., & Liu, Z. (2018). Electric vehicle fleet size and trip pricing for one-way carsharing services considering vehicle relocation and personnel assignment. Transportation Research Part B: Methodological, 111, 60–82. https://doi.org/10.1016/j.trb.2018.03.001
   Web of Science ®Google Scholar
• Xu, Z., Yin, Y., & Zha, L. (2017). Optimal parking provision for ride-sourcing services. Transportation Research Part B: Methodological, 105, 559–578. https://doi.org/10.1016/j.trb.2017.10.003
   Web of Science ®Google Scholar
• Yang, H., Shao, C., Wang, H., & Ye, J. (2020). Integrated reward scheme and surge pricing in a ridesourcing market. Transportation Research Part B: Methodological, 134, 126–142. https://doi.org/10.1016/j.trb.2020.01.008
   Web of Science ®Google Scholar
• Yao, F., Zhu, J., Yu, J., Chen, C., & Chen, X. (2020). Hybrid operations of human driving vehicles and automated vehicles with data-driven agent-based simulation. Transportation Research Part D: Transport and Environment, 86, 102469. https://doi.org/10.1016/j.trd.2020.102469
   Web of Science ®Google Scholar
• Yu, B., Ma, Y., Xue, M., Tang, B., Wang, B., Yan, J., & Wei, Y. M. (2017). Environmental benefits from ridesharing: A case of Beijing. Applied Energy, 191, 141–152. https://doi.org/10.1016/j.apenergy.2017.01.052
   Web of Science ®Google Scholar
• Yu, J. J., Tang, C. S., Shen, Z. J. M., & Chen, X. (2020). A balancing act of regulating on-demand ride services. Management Science, 66(7), 2975–2992. https://doi.org/10.1287/mnsc.2019.3351
   Web of Science ®Google Scholar
• Zha, L., Yin, Y., & Du, Y. (2018). Surge pricing and labor supply in the ride-sourcing market. Transportation Research Part B: Methodological, 117, 708–722. https://doi.org/10.1016/j.trb.2017.09.010
   Web of Science ®Google Scholar
• Zha, L., Yin, Y., & Yang, H. (2016). Economic analysis of ride-sourcing markets. Transportation Research Part C: Emerging Technologies, 71, 249–266. https://doi.org/10.1016/j.trc.2016.07.010
   Web of Science ®Google Scholar
• Zhai, Y., Liu, J., Du, J., & Wu, H. (2019). Fleet size and rebalancing analysis of dockless bike-sharing stations based on Markov chain. ISPRS International Journal of Geo-Information, 8(8), 334.
   Web of Science ®Google Scholar
• Zhang, J., Wen, D., & Zeng, S. (2015). A discounted trade reduction mechanism for dynamic ridesharing pricing. IEEE Transactions on Intelligent Transportation Systems, 17(6), 1586–1595. https://doi.org/10.1109/TITS.2015.2506660
   Web of Science ®Google Scholar
• Zhang, L., Zhao, Z., & Kan, Z. (2019). Private-sector partner selection for public-private partnership projects of electric vehicle charging infrastructure. Energy Science & Engineering, 7(5), 1469–1484. https://doi.org/10.1002/ese3.367
   Web of Science ®Google Scholar
• Zhang, W., & Guhathakurta, S. (2017). Parking spaces in the age of shared autonomous vehicles: How much parking will we need and where? Transportation Research Record: Journal of the Transportation Research Board, 2651(1), 80–91. https://doi.org/10.3141/2651-09
   Google Scholar
• Zhang, Y., & Mi, Z. (2018). Environmental benefits of bike sharing: A big data-based analysis. Applied Energy, 220, 296–301. https://doi.org/10.1016/j.apenergy.2018.03.101
   Web of Science ®Google Scholar
• Zhang, Y., Lin, D., & Mi, Z. (2019). Electric fence planning for dockless bike-sharing services. Journal of Cleaner Production, 206, 383–393. https://doi.org/10.1016/j.jclepro.2018.09.215
   Web of Science ®Google Scholar
• Zheng, H., Chen, X., & Chen, X. M. (2019). How does on-demand ridesplitting influence vehicle use and purchase willingness? A case study in Hangzhou, China. IEEE Intelligent Transportation Systems Magazine, 11(3), 143–157. https://doi.org/10.1109/MITS.2019.2919503
   Web of Science ®Google Scholar
• Zhong, Y., Lin, Z., Zhou, Y. W., Cheng, T. C. E., & Lin, X. (2019). Matching supply and demand on ride-sharing platforms with permanent agents and competition. International Journal of Production Economics, 218, 363–374. https://doi.org/10.1016/j.ijpe.2019.07.009
   Web of Science ®Google Scholar
• Zhou, Y., Yang, H., Ke, J., Wang, H., & Li, X. (2020). Competitive ride-sourcing market with a third-party integrator. Working Paper.
   Google Scholar
• Zhu, R., Zhang, X., Kondor, D., Santi, P., & Ratti, C. (2020a). Understanding spatio-temporal heterogeneity of bike-sharing and scooter-sharing mobility. Computers, Environment and Urban Systems, 81, 101483. https://doi.org/10.1016/j.compenvurbsys.2020.101483
   Web of Science ®Google Scholar
• Zhu, Z., Qin, X., Ke, J., Zheng, Z., & Yang, H. (2020b). Analysis of multi-modal commute behavior with feeding and competing ridesplitting services. Transportation Research Part A: Policy and Practice, 132, 713–727. https://doi.org/10.1016/j.tra.2019.12.018
   Web of Science ®Google Scholar
• Zhu, Z., Xu, A., He, Q. C., & Yang, H. (2021c). Competition between the transportation network company and the government with subsidies to public transit riders. Transportation Research Part E: Logistics and Transportation Review, 152, 102426. https://doi.org/10.1016/j.tre.2021.102426
   Web of Science ®Google Scholar
• Zou, Z., Younes, H., Erdoğan, S., & Wu, J. (2020). Exploratory analysis of real-time e-scooter trip data in Washington, DC. Transportation Research Record: Journal of the Transportation Research Board, 2674(8), 285–299. https://doi.org/10.1177/0361198120919760
   Web of Science ®Google Scholar