{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/105838"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/105838","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"The impact of ride-hailing services on travel behaviour","abstract":"The introduction of Ride- hailing Services into our transport systems has rapidly transformed travel behavior. Ride-hailing services provide multi-modality and fill transit gaps, but they also impact the modal share of other modes such as public transit and car ownership. This study delves into links between ride-hailing services and private vehicles ownership. It also questions the impact of ridesharing services on public transport use and the role neighborhood context plays on the link between ride-hailing and car-ownership. This is studied through a Path Analysis implemented through Structural Equation Modelling (SEM). It describes the relationships the relationship between ‘ride-hailing usage’, ‘public transit usage’, ‘car ownership’, ‘sociodemographic characteristics’, ‘urban form’ and ‘technology dependence’. It factors in Ewing’s sprawl index to represent urban form and takes into consideration the number of years since rideshare was introduced in specific cities as part of calculations. The primary database for the research is the NHTS 2017 survey. Data compilation is done to establish a dataset of cities with TNCs operating in them and the duration of operation. The first of the three key questions analyzed in this study is the relationship between public transit and ridesharing. Although the statistical model shows an insignificant covariance, initial findings suggest that ride sharing services complement public transit more in small towns and less in urban areas. The second topic analyzed through this model was the link between ridesharing and car ownership. The model estimates that ride-hailing has a significant and comparatively large impact on car ownership. Due to the bidirectional nature of the model, we were able to study the reverse relationship as well. The model did not show car-ownership having a significant impact on frequency of rideshare use. The final relationship to be studied was the impact of neighborhood context on the links between car ownership and ride-hailing. It was suggested through a moderation estimation that urban form does play a significant role in impacting the role of rideshare on car ownership. The length of duration since the introduction of TNCs in a city plays an important role on car ownership. The longer TNCs have been around, the smaller the value of car ownership is. Denser Urban forms deepen this relationship while sprawled neighborhoods weaken the correlation. Based on this research a few areas have been identified as areas with critical data deficiency which are needed to understand and properly manage the ever-changing travel behavior. These areas include the links between city types, public transit and rideshare.","abstract_html":"The introduction of Ride- hailing Services into our transport systems has rapidly transformed travel behavior. Ride-hailing services provide multi-modality and fill transit gaps, but they also impact the modal share of other modes such as public transit and car ownership. This study delves into links between ride-hailing services and private vehicles ownership. It also questions the impact of ridesharing services on public transport use and the role neighborhood context plays on the link between ride-hailing and car-ownership. This is studied through a Path Analysis implemented through Structural Equation Modelling (SEM). It describes the relationships the relationship between ‘ride-hailing usage’, ‘public transit usage’, ‘car ownership’, ‘sociodemographic characteristics’, ‘urban form’ and ‘technology dependence’. It factors in Ewing’s sprawl index to represent urban form and takes into consideration the number of years since rideshare was introduced in specific cities as part of calculations. The primary database for the research is the NHTS 2017 survey. Data compilation is done to establish a dataset of cities with TNCs operating in them and the duration of operation. The first of the three key questions analyzed in this study is the relationship between public transit and ridesharing. Although the statistical model shows an insignificant covariance, initial findings suggest that ride sharing services complement public transit more in small towns and less in urban areas. The second topic analyzed through this model was the link between ridesharing and car ownership. The model estimates that ride-hailing has a significant and comparatively large impact on car ownership. Due to the bidirectional nature of the model, we were able to study the reverse relationship as well. The model did not show car-ownership having a significant impact on frequency of rideshare use. The final relationship to be studied was the impact of neighborhood context on the links between car ownership and ride-hailing. It was suggested through a moderation estimation that urban form does play a significant role in impacting the role of rideshare on car ownership. The length of duration since the introduction of TNCs in a city plays an important role on car ownership. The longer TNCs have been around, the smaller the value of car ownership is. Denser Urban forms deepen this relationship while sprawled neighborhoods weaken the correlation. Based on this research a few areas have been identified as areas with critical data deficiency which are needed to understand and properly manage the ever-changing travel behavior. These areas include the links between city types, public transit and rideshare.","abstract_has_math":false,"creators":["Mishra, Anusha"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.U.P.","degree_level":"Thesis","degree_discipline":"Urban Planning","degree_department":null,"school":null,"contributors":["Lee, Bumsoo","Braun, Lindsay Maurer"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-11-26T20:49:33Z","date_published":"2019-11-26T20:49:33Z","updated_at":"2026-07-22T22:24:45Z","subjects":["Ride- Hailing, Travel Mobility, Car Ownership, Public Transit, NHTS"],"languages":["en"],"rights":["Copyright 2019 Anusha Mishra"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/105838","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Lee, Bumsoo","Braun, Lindsay Maurer"]},{"key":"dc:creator","label":"Author","values":["Mishra, Anusha"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-11-26T20:49:33Z","2021-11-27T10:15:37Z","2019-07-18","2019-08"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Urban Planning"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.U.P."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Ride- Hailing, Travel Mobility, Car Ownership, Public Transit, NHTS"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Anusha Mishra"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/105838"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The introduction of Ride- hailing Services into our transport systems has rapidly transformed travel behavior. Ride-hailing services provide multi-modality and fill transit gaps, but they also impact the modal share of other modes such as public transit and car ownership. This study delves into links between ride-hailing services and private vehicles ownership. It also questions the impact of ridesharing services on public transport use and the role neighborhood context plays on the link between ride-hailing and car-ownership. This is studied through a Path Analysis implemented through Structural Equation Modelling (SEM). It describes the relationships the relationship between ‘ride-hailing usage’, ‘public transit usage’, ‘car ownership’, ‘sociodemographic characteristics’, ‘urban form’ and ‘technology dependence’. It factors in Ewing’s sprawl index to represent urban form and takes into consideration the number of years since rideshare was introduced in specific cities as part of calculations. The primary database for the research is the NHTS 2017 survey. Data compilation is done to establish a dataset of cities with TNCs operating in them and the duration of operation. The first of the three key questions analyzed in this study is the relationship between public transit and ridesharing. Although the statistical model shows an insignificant covariance, initial findings suggest that ride sharing services complement public transit more in small towns and less in urban areas. The second topic analyzed through this model was the link between ridesharing and car ownership. The model estimates that ride-hailing has a significant and comparatively large impact on car ownership. Due to the bidirectional nature of the model, we were able to study the reverse relationship as well. The model did not show car-ownership having a significant impact on frequency of rideshare use. The final relationship to be studied was the impact of neighborhood context on the links between car ownership and ride-hailing. It was suggested through a moderation estimation that urban form does play a significant role in impacting the role of rideshare on car ownership. The length of duration since the introduction of TNCs in a city plays an important role on car ownership. The longer TNCs have been around, the smaller the value of car ownership is. Denser Urban forms deepen this relationship while sprawled neighborhoods weaken the correlation. Based on this research a few areas have been identified as areas with critical data deficiency which are needed to understand and properly manage the ever-changing travel behavior. 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Ride-hailing services provide multi-modality and fill transit gaps, but they also impact the modal share of other modes such as public transit and car ownership. This study delves into links between ride-hailing services and private vehicles ownership. It also questions the impact of ridesharing services on public transport use and the role neighborhood context plays on the link between ride-hailing and car-ownership. This is studied through a Path Analysis implemented through Structural Equation Modelling (SEM). It describes the relationships the relationship between ‘ride-hailing usage’, ‘public transit usage’, ‘car ownership’, ‘sociodemographic characteristics’, ‘urban form’ and ‘technology dependence’. It factors in Ewing’s sprawl index to represent urban form and takes into consideration the number of years since rideshare was introduced in specific cities as part of calculations. The primary database for the research is the NHTS 2017 survey. Data compilation is done to establish a dataset of cities with TNCs operating in them and the duration of operation. The first of the three key questions analyzed in this study is the relationship between public transit and ridesharing. Although the statistical model shows an insignificant covariance, initial findings suggest that ride sharing services complement public transit more in small towns and less in urban areas. The second topic analyzed through this model was the link between ridesharing and car ownership. The model estimates that ride-hailing has a significant and comparatively large impact on car ownership. Due to the bidirectional nature of the model, we were able to study the reverse relationship as well. The model did not show car-ownership having a significant impact on frequency of rideshare use. The final relationship to be studied was the impact of neighborhood context on the links between car ownership and ride-hailing. It was suggested through a moderation estimation that urban form does play a significant role in impacting the role of rideshare on car ownership. The length of duration since the introduction of TNCs in a city plays an important role on car ownership. The longer TNCs have been around, the smaller the value of car ownership is. Denser Urban forms deepen this relationship while sprawled neighborhoods weaken the correlation. Based on this research a few areas have been identified as areas with critical data deficiency which are needed to understand and properly manage the ever-changing travel behavior. 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