Exploring shared travel behavior of university students

This study aims to identify young adults’ travel behavior using ridesharing services. The authors analyze data from an online survey of university students, regarding three free ridesharing services, including fixed-route, on-demand, and shared autonomous vehicles (SAVs). Ordinal regression and structural equation model (SEM) are employed to explore the frequency of service usage. Results indicate that most students had never taken a ride by available ridesharing services due to their preferences for using private vehicles and lack of service information. Regression results reveal that individuals’ usual mode of transportation and residential location significantly influence ridesharing behavior. The results also show significant associations between travel attitudes and students’ travel behavior. The authors also found that shared on-demand and autonomous vehicle services could complement fixed-route services. Further research is needed on the link between young people's adoption of integrated ridesharing transportation services.

• Record URL:
  https://doi.org/10.1080/03081060.2022.2160718
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/1767712
• Supplemental Notes:
  • © 2023 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
• Authors:
  • Etminani-Ghasrodashti, Roya
  • Hladik, Greg
  • Kermanshachi, Sharareh
  • Rosenberger, Jay Michael
  • Arif Khan, Muhammad
  • Foss, Ann
• Publication Date: 2023-1

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 22-44
• Serial:
  • Transportation Planning and Technology
  • Volume: 46
  • Issue Number: 1
  • Publisher: Taylor & Francis
  • ISSN: 0308-1060
  • Serial URL: https://www.tandfonline.com/toc/gtpt20/current

Subject/Index Terms

• TRT Terms: College students; Consumer preferences; Ridesharing; Travel behavior
• Subject Areas: Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01874407
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 23 2023 9:33AM