Modeling the choice to switch from traditional modes to ridesourcing services for social/recreational trips in Lebanon

dc.contributor.authorTarabay, Rana
dc.contributor.authorAbou-Zeid, Maya
dc.contributor.departmentDepartment of Civil and Environmental Engineering
dc.contributor.facultyMaroun Semaan Faculty of Engineering and Architecture (MSFEA)
dc.contributor.institutionAmerican University of Beirut
dc.date.accessioned2025-01-24T11:27:53Z
dc.date.available2025-01-24T11:27:53Z
dc.date.issued2020
dc.description.abstractThis study investigates the current and potential uptake of ridesourcing services, such as Uber and Careem, by the students of the American University of Beirut, Lebanon. A hybrid choice model is developed to predict the switching choice from traditional modes of transport to ridesourcing services for social/recreational trips made by these students in Lebanon. Data are provided by a web-based survey that includes revealed and stated preferences, besides demographics. It is found that the switching choice is determined by several observed factors, such as door-to-door travel time, waiting time for pick-up, and one-way fares, in addition to a latent variable that captures individual differences in perceptions and attitudes towards ridesourcing services. A base switching probability from traditional modes to ridesourcing services (calculated under a base scenario representing realistic values of the attributes of ridesourcing services if the latter were used to make the most recent social/recreational trip) is estimated to be 0.22. This probability is expected to reach 0.31 under a forecasted policy scenario consisting of 40% reduction in ridesourcing fares. Car users will be more sensitive to switch to ridesourcing services for their social/recreational trips if the ridesourcing fare reduction (40%) is associated with restricted parking conditions consisting of (a) 100% increase of parking fees from actual prices, and (b) 20-minute increase of parking search time and parking time from the actual car travel time. In this case, the resulting switching probability is expected to reach 0.38. By using the estimated choice model to forecast policy scenarios as such, this study can guide planners, policymakers, and service operators to prioritize effective policies in response to the behavioral change caused by the diffusion of innovative transport services and technologies. The study also contributes to a better understanding of the uptake of ridesourcing services in developing country contexts where public transport services are often inadequate. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
dc.identifier.doihttps://doi.org/10.1007/s11116-019-09973-x
dc.identifier.eid2-s2.0-85060986923
dc.identifier.urihttp://hdl.handle.net/10938/26966
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofTransportation
dc.sourceScopus
dc.subjectDisruptive mobility
dc.subjectForecasting
dc.subjectHybrid choice model
dc.subjectRidesourcing
dc.subjectSocial/recreational trips
dc.subjectUrban transport
dc.subjectBeyrouth
dc.subjectLebanon
dc.subjectDeveloping countries
dc.subjectSwitching
dc.subjectTravel time
dc.subjectChoice model
dc.subjectIndividual differences
dc.subjectPublic transport service
dc.subjectSwitching probability
dc.subjectTransport services
dc.subjectNumerical model
dc.subjectProbability
dc.subjectPublic transport
dc.subjectRoad transport
dc.subjectTransportation development
dc.subjectTransportation planning
dc.subjectUrban transportation
dc.titleModeling the choice to switch from traditional modes to ridesourcing services for social/recreational trips in Lebanon
dc.typeArticle

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