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MA Thesis Shefa Arabia Shioma.pdf (1.14 MB)

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Ride-sourcing and Ridesharing: Factors influencing users’ adaptation and their trip characteristics analysis

Shioma, Shefa Arabia
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1639702567291383

Abstract Details

2021, Master of Arts, University of Toledo, Geography.
On-demand ride services- Ride-sourcing and Ridesharing- are rapidly changing the way how people used to travel by shifting to newer alternatives day by day since it allows them to fix the ride even sitting at their house. This flexible mode of transportation is getting more popular for its dynamic features and easy availability around the world. Yet there are few research available in this sector, for which this study will be a great help for the policymakers and researchers in this sector as well. It investigates the factors influencing the adoption of this emerging ride service and finds out the trip behavior among the users. The study is done on the data covering the entire United States and uses the 2017 NHTS dataset. The study estimates both descriptive analysis and logit model. Three binary logistic regression models have been established using the same variables but on different geographical scales. It allows us to understand the difference in factor’s effectiveness for geographical variation. Results show that respondents’ age, race, Hispanic group, annual household income, education level, homeownership, number of vehicles in the household, driver status, trip length and duration, population density, home location, etc. have a direct relation to individual’s decision to adopt ride service. Both categorical and numerical variables are used in these models. All three models (urban-rural combined, urban-only, and rural-only data) show that with the increase of respondents’ age, the probability of using ride service also increases. Though the likelihood of choosing an on-demand ride service is higher for the White respondents in both the combined and rural data models, it shows a different result for the urban area where the probability of using the ride service is higher for the Black respondents. People in the urban areas use this service more on the weekdays, whereas the likelihood is higher on weekends in rural areas. For all the models, the result suggests that those who have non-driver status, are more likely to adopt ride-sourcing or ridesharing. People with higher income groups are more inclined to choose this on-demand ride service over other transport modes. Also, those who have a higher education status are more likely to choose this service. In the combined model, the result suggests that people living in the urban area choose ride-service more frequently than those who live in rural areas. Homeownership has also a direct influence found in this study. Both in the combined and urban-only model, it is observed that people who rent the house are more likely to use ride service, whereas, in the rural area, the service is ore adopted by those who are owners of the house. Trip distance and travel duration also have a significant impact on choosing a ride service. An important aspect of this study is that it is conducted on the data covering the whole United States. It finds out that the percentage of the on-demand ride service users are the highest in California, then in New York, Texas, Georgia, and Wisconsin accordingly. The spatial autocorrelation conducted in this study also suggests that data are randomly distributed over the states. This study also investigates the reasons behind choosing a ride service for making the trip. The highest percentage is found for commuting to home. The second-highest number of trips are made for personal business, and then comes work-related trips and others accordingly.
Dr. Bhuiyan M Alam (Committee Chair)
Dr. Daniel J Hammel (Committee Member)
Dr. Ashok Kumar (Committee Member)
Geography; Transportation Planning

Recommended Citations

Citations

  • Shioma, S. A. (2021). Ride-sourcing and Ridesharing: Factors influencing users’ adaptation and their trip characteristics analysis [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1639702567291383

    APA Style (7th edition)

  • Shioma, Shefa Arabia. Ride-sourcing and Ridesharing: Factors influencing users’ adaptation and their trip characteristics analysis. 2021. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1639702567291383.

    MLA Style (8th edition)

  • Shioma, Shefa Arabia. "Ride-sourcing and Ridesharing: Factors influencing users’ adaptation and their trip characteristics analysis." Master's thesis, University of Toledo, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1639702567291383

    Chicago Manual of Style (17th edition)

toledo1639702567291383
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This open access ETD is published by University of Toledo and OhioLINK.