Shared Use Travel Behavior for Improving Rural Mobility: Insights from Greene County, Pennsylvania
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 150, Issue 8
Abstract
Rural communities are considered disadvantaged communities as they suffer from a lack of transport options. Thus, rural regions provide less accessibility for commuters to reach their destination as opposed to urban regions. However, the issues of transport disadvantage and shared use mobility in rural areas within the United States (US) have not been well investigated. Furthermore, transport disadvantage differs between communities and regions across the globe; thus, there is a need to study the behavioral choices of rural commuters within the US context. This study contributes by analyzing the behavioral choices of rural communities within the US through a case study site of Waynesburg, Pennsylvania, for adopting a shared use shuttle service. K-means clusters showed that trips from the survey data were a good representation of real trips from Ecolane. Furthermore, random parameter-based binary logit models were calibrated using data collected from students, faculty, and residents in Waynesburg, Greene County, to study the behavioral choices of commuters. The findings for the faculty and students group revealed that prior experience with shared services increases the likelihood of using a shared shuttle. An important personal characteristic of inconvenience showed a higher propensity toward using existing modes as opposed to a shared shuttle. Such commuters value personal vehicles as more convenient as they have childcare responsibilities and varying schedules for work that require them to move back and forth across locations, thus making a shared shuttle less attractive for them. The socioeconomic factors of age and gender show a higher propensity for using shared shuttles. The findings from this study could be helpful for agencies in improving rural mobility and considering such shared mobility services for rural communities.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This project is based upon work supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Vehicle Technology Office’s award number DE-EE0008883. The contents of this paper reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. The views expressed herein do not necessarily represent the views of the U.S. Department of Energy or the United States Government. The authors would like to thank Melinda Walls, Cassy Dorsch, Ezekiel Olagoke, and Stacey Brodak with Waynesburg University for helping conduct the surveys. Dr. Bin Gui’s work on processing and validating the survey data is greatly appreciated.
References
Ahmed, M. M., R. Franke, K. Ksaibati, and D. S. Shinstine. 2018. “Effects of truck traffic on crash injury severity on rural highways in Wyoming using Bayesian binary logit models.” Accid. Anal. Prev. 117 (Aug): 106–113. https://doi.org/10.1016/j.aap.2018.04.011.
Anderson, M., and A. Perrin. 2017. Technology use among seniors. Washington, DC: Pew Research Center for Internet & Technology.
Ao, Y., Y. Zhang, Y. Wang, Y. Chen, and L. Yang. 2020. “Influences of rural built environment on travel mode choice of rural residents.” J. Transp. Geogr. 85 (May): 102708. https://doi.org/10.1016/j.jtrangeo.2020.102708.
Ben-Akiva, M., and S. R. Lerman. 1985. Discrete choice analysis. Cambridge, MA: MIT Press.
Chan, N. D., and S. A. Shaheen. 2012. “Ridesharing in North America: Past, present, and future.” Transp. Rev. 32 (1): 93–112. https://doi.org/10.1080/01441647.2011.621557.
Chen, C., H. Gong, and R. Paaswell. 2008. “Role of the built environment on mode choice decisions: Additional evidence on the impact of density.” Transportation 35 (3): 285–299. https://doi.org/10.1007/s11116-007-9153-5.
Christiansen, P., Ø. Engebretsen, N. Fearnley, and J. Usterud Hanssen. 2017. “Parking facilities and the built environment: Impacts on travel behavior.” Transp. Res. Part A: Policy Pract. 95 (Jan): 198–206. https://doi.org/10.1016/j.tra.2016.10.025.
Contreras, S. D., and A. Paz. 2018. “The effects of ride-hailing companies on the taxicab industry in Las Vegas, Nevada.” Transp. Res. Part A: Policy Pract. 115 (Sep): 63–70. https://doi.org/10.1016/j.tra.2017.11.008.
Coutinho, F. M., N. van Oort, Z. Christoforou, M. J. Alonso-González, O. Cats, and S. Hoogendoorn. 2020. “Impacts of replacing a fixed public transport line by a demand responsive transport system: Case study of a rural area in Amsterdam.” Res. Transp. Econ. 83 (Nov): 100910. https://doi.org/10.1016/j.retrec.2020.100910.
Delhomme, P., and A. Gheorghiu. 2016. “Comparing French carpoolers and non-carpoolers: Which factors contribute the most to carpooling?” Transp. Res. Part D: Transp. Environ. 42 (Jan): 1–15. https://doi.org/10.1016/j.trd.2015.10.014.
Eckhardt, J., A. Lauhkonen, and A. Aapaoja. 2020. “Impact assessment of rural PPP MaaS pilots.” Eur. Transport Res. Rev. 12 (Dec): 1–14. https://doi.org/10.1186/s12544-020-00443-5.
Ewing, R., K. Bartholomew, S. Winkelman, J. Walters, and D. Chen. 2008. Growing cooler: Evidence on urban development and climate change. Washington, DC: Urban Land Institute.
Greene, W. H. 2008. Econometric analysis. Upper Saddle River, NJ: Pearson Prentice Hall.
Grue, B., K. Veisten, and Ø. Engebretsen. 2020. “Exploring the relationship between the built environment, trip chain complexity, and auto mode choice, applying a large national data set.” Transp. Res. Interdiscip. Perspect. 5 (May): 100134. https://doi.org/10.1016/j.trip.2020.100134.
Halton, J. 1960. “On the efficiency of evaluating certain quasi-random sequences of points in evaluating multi-dimensional integrals.” Numer. Math. 2 (1): 84–90. https://doi.org/10.1007/BF01386213.
Hult, Å., L. Perjo, and G. Smith. 2021. “Shared mobility in rural contexts: Organizational insights from five mobility-as-a-service pilots in Sweden.” Sustainability 13 (18): 10134. https://doi.org/10.3390/su131810134.
Jeffrey, T. B. 2018. “29.2% of U.S. Households Had Incomes of $100,000+ in 2017.” CNSNews.Com, July 1, 2018.
Khattak, Z. H., M. J. Magalotti, J. S. Miller, and M. D. Fontaine. 2017. “Using New mode choice model nesting structures to address emerging policy questions: A case study of the Pittsburgh central business district.” Sustainability 9 (11): 2120. https://doi.org/10.3390/su9112120.
Knierim, L., and J. C. Schlüter. 2021. “The attitude of potentially less mobile people towards demand responsive transport in a rural area in central Germany.” J. Transp. Geogr. 96 (Oct): 103202. https://doi.org/10.1016/j.jtrangeo.2021.103202.
Lee, B. H., L. Aultman-Hall, M. Coogan, and T. Adler. 2016. “Rideshare mode potential in non-metropolitan areas of the northeastern United States.” J. Transp. Land Use 9 (3): 111–126. https://doi.org/10.5198/jtlu.2015.669.
Leistner, D. L., and R. L. Steiner. 2017. “Uber for seniors? Exploring transportation options for the future.” Transp. Res. Rec. 2660 (1): 22–29. https://doi.org/10.3141/2660-04.
Madani, N., L. Creemers, M. Moeinaddini, I. Saadi, and M. Cools. 2022. “Low-cost shared mobility alternatives in rural areas: A case study of ride-sharing benches in the German-speaking community of Belgium.” Case Stud. Transp. Policy 10 (4): 2393–2400. https://doi.org/10.1016/j.cstp.2022.11.002.
Maeder, S., M. Stauffacher, and F. Knaus. 2023. “Zooming in and out on everyday mobility practices in a rural, mountainous area of Switzerland.” J. Transp. Geogr. 112 (Oct): 103680. https://doi.org/10.1016/j.jtrangeo.2023.103680.
Mannering, F. L., V. Shankar, and C. R. Bhat. 2016. “Unobserved heterogeneity and the statistical analysis of highway accident data.” Anal. Methods Accid. Res. 11 (Sep): 1–16. https://doi.org/10.1016/j.amar.2016.04.001.
Mattson, J. 2017. Rural transit fact book. Fargo, ND: Upper Great Plains Transportation Institute.
Mattson, J., D. Peterson, D. Ripplinger, W. Thoms, and J. Hough. 2010. “An assessment of demand for rural intercity transportation services in a changing environment.” Transp. Res. Rec. 2145 (1): 108–114. https://doi.org/10.3141/2145-13.
Mulley, C., J. D. Nelson, C. Ho, and D. A. Hensher. 2023. “MaaS in a regional and rural setting: Recent experience.” Transp. Policy 133 (Mar): 75–85. https://doi.org/10.1016/j.tranpol.2023.01.014.
National Academies of Sciences, Engineering and Medicine. 2012. Travel demand forecasting: Parameters and techniques. Washington, DC: National Academies Press.
Neoh, J. G., M. Chipulu, and A. Marshall. 2017. “What encourages people to carpool? An evaluation of factors with meta-analysis.” Transportation 44 (2): 423–447. https://doi.org/10.1007/s11116-015-9661-7.
Ng, W. S., and A. Acker. 2018. “Understanding urban travel behaviour by gender for efficient and equitable transport policies, 1–21. Paris: International Transport Forum.
Pike, S., C. Rodier, and J. Martinez. 2018. The potential for shared use mobility in affordable housing complexes in rural California. Los Angeles: Univ. of California Transportation Institute.
Polzin, S. E. 2016. Implications to public transportation of automated or connected vehicles. Los Angeles: National Center for Transit Research.
Pucher, J., and J. L. Renne. 2005. “Rural mobility and mode choice: Evidence from the 2001 national household travel survey.” Transportation 32 (2): 165–186. https://doi.org/10.1007/s11116-004-5508-3.
Rietveld, P., B. Zwart, B. Van Wee, and T. van den Hoorn. 1999. “On the relationship between travel time and travel distance of commuters.” Ann. Reg. Sci. 33 (3): 269–287. https://doi.org/10.1007/s001680050105.
Rodier, C., B. Harold, and Y. Zhang. 2021. Early results from an electric vehicle carsharing service in rural disadvantaged communities in the San Joaquin Valley. Los Angeles: Univ. of California Institute of Transportation Studies.
Rogalsky, J. 2010. “The working poor and what GIS reveals about the possibilities of public transit.” J. Transp. Geogr. 18 (2): 226–237. https://doi.org/10.1016/j.jtrangeo.2009.06.008.
Rosenbloom, S. 2003. “Facing societal challenges: The need for new paradigms in rural transit service.” J. Public Transp. 6 (1): 1–17. https://doi.org/10.5038/2375-0901.6.1.1.
Sandow, E., and K. Westin. 2010. “People’s preferences for commuting in sparsely populated areas: The case of Sweden.” J. Transp. Land Use 2 (3).
Schwanen, T., F. M. Dieleman, and M. Dijst. 2004. “The impact of metropolitan structure on commute behavior in the Netherlands: A multilevel approach.” Growth Change 35 (3): 304–333. https://doi.org/10.1111/j.1468-2257.2004.00251.x.
Shaheen, S., N. Chan, A. Bansal, and A. Cohen. 2015. Shared mobility: A sustainability and technologies workshop. Berkeley, CA: Univ. of California Berkeley Transportation Sustainability Research Center.
Tirachini, A., and M. Del Río. 2019. “Ride-hailing in Santiago de Chile: Users’ characterisation and effects on travel behavior.” Transp. Policy 82 (Oct): 46–57. https://doi.org/10.1016/j.tranpol.2019.07.008.
Train, K. 2003. Discrete choice methods with simulation. 1st ed. Cambridge, UK: Cambridge University Press.
US Census Bureau. 2015. American community survey. Hillcrest Heights, MD: US Census Bureau.
US Census Bureau. 2019. “ACS demographic and housing estimates: 2013–2017 American community survey 5-year estimates.” Accessed April 8, 2024. https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=CF.
US Census Bureau. 2023. “United States Census Bureau.” Accessed April 8, 2024. https://www.census.gov.
Wang, C., M. Quddus, M. Enoch, T. Ryley, and L. Davison. 2015. “Exploring the propensity to travel by demand responsive transport in the rural area of Lincolnshire in England.” Case Stud. Transp. Policy 3 (2): 129–136. https://doi.org/10.1016/j.cstp.2014.12.006.
Xie, M., W. Cheng, G. S. Gill, J. Zhou, X. Jia, and S. Choi. 2018. “Investigation of hit-and-run crash occurrence and severity using real-time loop detector data and hierarchical Bayesian binary logit model with random effects.” Traffic Inj. Prev. 19 (2): 207–213. https://doi.org/10.1080/15389588.2017.1371302.
Zhou, X., H. Du, Y. Liu, H. Huang, and B. Ran. 2017. “Investigating the intention of rural residents to use transit in Cixi, China.” J. Urban Plann. Dev. 143 (2): 05016017. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000367.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 150 • Issue 8 • August 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Sep 28, 2023
Accepted: Feb 7, 2024
Published online: May 22, 2024
Published in print: Aug 1, 2024
Discussion open until: Oct 22, 2024
ASCE Technical Topics:
- Age factors
- Business management
- Case studies
- Colleges and universities
- Commute
- Education
- Engineering fundamentals
- Faculty
- Geography
- Geomatics
- Infrastructure
- Methodology (by type)
- Practice and Profession
- Research methods (by type)
- Rural areas
- Students
- Traffic engineering
- Transportation engineering
- Travel patterns
- Workplace diversity
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.