IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i8p1763-d164022.html
   My bibliography  Save this article

Exploring the Relationship between Ridesharing and Public Transit Use in the United States

Author

Listed:
  • Yuanyuan Zhang

    (School of Management, Shandong University, Jinan 250100, China
    Stern School of Business, New York University, New York, NY 10012, USA)

  • Yuming Zhang

    (School of Management, Shandong University, Jinan 250100, China)

Abstract

Car travel accounts for the largest share of transportation-related greenhouse gas emissions in the United States (U.S.), leading to serious air pollution and negative health effects; approximately 76.3% of car trips are single-occupant. To reduce the negative externalities of cars, ridesharing and public transit are advocated as cost-effective and more environmentally sustainable alternatives. A better understanding of individuals’ uses of these two transport modes and their relationship is important for transport operators and policymakers; however, it is not well understood how ridesharing use is associated with public transit use. The objective of this study is to examine the relationships between the frequency and probability of ridesharing use and the frequency of public transit use in the U.S. Zero-inflated negative binomial regression models were employed to investigate the associations between these two modes, utilizing individual-level travel frequency data from the 2017 National Household Travel Survey. The survey data report the number of times the respondent had used ridesharing and public transit in the past 30 days. The results show that, generally, a one-unit increase in public transit use is significantly positively related to a 1.2% increase in the monthly frequency of ridesharing use and a 5.7% increase in the probability of ridesharing use. Additionally, the positive relationship between ridesharing and public transit use was more pronounced for people who live in areas with a high population density or in households with fewer vehicles. These findings highlight the potential for integrating public transit and ridesharing systems to provide easier multimodal transportation, promote the use of both modes, and enhance sustainable mobility, which are beneficial for the environment and public health.

Suggested Citation

  • Yuanyuan Zhang & Yuming Zhang, 2018. "Exploring the Relationship between Ridesharing and Public Transit Use in the United States," IJERPH, MDPI, vol. 15(8), pages 1-23, August.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:8:p:1763-:d:164022
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/8/1763/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/8/1763/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273.
    2. Efthymiou, Dimitrios & Antoniou, Constantinos & Waddell, Paul, 2013. "Factors affecting the adoption of vehicle sharing systems by young drivers," Transport Policy, Elsevier, vol. 29(C), pages 64-73.
    3. Yu, Biying & Ma, Ye & Xue, Meimei & Tang, Baojun & Wang, Bin & Yan, Jinyue & Wei, Yi-Ming, 2017. "Environmental benefits from ridesharing: A case of Beijing," Applied Energy, Elsevier, vol. 191(C), pages 141-152.
    4. Chakrabarti, Sandip, 2017. "How can public transit get people out of their cars? An analysis of transit mode choice for commute trips in Los Angeles," Transport Policy, Elsevier, vol. 54(C), pages 80-89.
    5. Ding, Chuan & Wang, Donggen & Liu, Chao & Zhang, Yi & Yang, Jiawen, 2017. "Exploring the influence of built environment on travel mode choice considering the mediating effects of car ownership and travel distance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 65-80.
    6. Schneider, Robert J., 2013. "Theory of routine mode choice decisions: An operational framework to increase sustainable transportation," Transport Policy, Elsevier, vol. 25(C), pages 128-137.
    7. Yuwei Liu & Hong Sheng & Norbert Mundorf & Colleen Redding & Yinjiao Ye, 2017. "Integrating Norm Activation Model and Theory of Planned Behavior to Understand Sustainable Transport Behavior: Evidence from China," IJERPH, MDPI, vol. 14(12), pages 1-16, December.
    8. Dea van Lierop & Madhav G. Badami & Ahmed M. El-Geneidy, 2018. "What influences satisfaction and loyalty in public transport? A review of the literature," Transport Reviews, Taylor & Francis Journals, vol. 38(1), pages 52-72, January.
    9. Lord, Dominique & Mannering, Fred, 2010. "The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 291-305, June.
    10. Biao Yin & Liu Liu & Nicolas Coulombel & Vincent Viguie, 2018. "Appraising the environmental benefits of ride-sharing: The Paris region case study," Post-Print hal-01695082, HAL.
    11. Masoud, Neda & Lloret-Batlle, Roger & Jayakrishnan, R., 2017. "Using bilateral trading to increase ridership and user permanence in ridesharing systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 102(C), pages 60-77.
    12. Gordon Burtch & Seth Carnahan & Brad N. Greenwood, 2018. "Can You Gig It? An Empirical Examination of the Gig Economy and Entrepreneurial Activity," Management Science, INFORMS, vol. 64(12), pages 5497-5520, December.
    13. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    14. Brian Taylor & Eric Morris, 2015. "Public transportation objectives and rider demographics: are transit’s priorities poor public policy?," Transportation, Springer, vol. 42(2), pages 347-367, March.
    15. Zolnik, Edmund J., 2015. "The effect of gasoline prices on ridesharing," Journal of Transport Geography, Elsevier, vol. 47(C), pages 47-58.
    16. Masoud, Neda & Jayakrishnan, R., 2017. "A real-time algorithm to solve the peer-to-peer ride-matching problem in a flexible ridesharing system," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 218-236.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Behram Wali & Paolo Santi & Carlo Ratti, 2023. "A joint demand modeling framework for ride-sourcing and dynamic ridesharing services: a geo-additive Markov random field based heterogeneous copula framework," Transportation, Springer, vol. 50(5), pages 1809-1845, October.
    2. Wei Chen & Jian Chen & Guopeng Yin, 2022. "Exploring side effects of ridesharing services in urban China: role of pollution–averting behavior," Electronic Commerce Research, Springer, vol. 22(4), pages 1007-1034, December.
    3. Hossain, Sanjana & Loa, Patrick & Ong, Felita & Habib, Khandker Nurul, 2022. "The determinants of commute mode usage frequency of post-secondary students in the Greater Toronto and Hamilton Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 164-185.
    4. Erhardt, Gregory D. & Hoque, Jawad Mahmud & Goyal, Vedant & Berrebi, Simon & Brakewood, Candace & Watkins, Kari E., 2022. "Why has public transit ridership declined in the United States?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 161(C), pages 68-87.
    5. Deng, Yuntian & Shao, Shiping & Mittal, Archak & Twumasi-Boakye, Richard & Fishelson, James & Gupta, Abhishek & Shroff, Ness B., 2022. "Incentive design and profit sharing in multi-modal transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 1-21.
    6. Csilla Bartucz & László Buics & Edit Süle, 2023. "Lack of Collaboration on the CEP Market and the Underlying Reasons—A Systematic Literature Review," Sustainability, MDPI, vol. 15(13), pages 1-22, June.
    7. Haoran Chen & Xuedong Yan & Xiaobing Liu & Tao Ma, 2023. "Exploring the operational performance discrepancies between online ridesplitting and carpooling transportation modes based on DiDi data," Transportation, Springer, vol. 50(5), pages 1923-1958, October.
    8. Zhang, Zhaolin & Zhai, Guocong & Xie, Kun & Xiao, Feng, 2022. "Exploring the nonlinear effects of ridesharing on public transit usage: A case study of San Diego," Journal of Transport Geography, Elsevier, vol. 104(C).
    9. Tian, Guang & Ewing, Reid & Li, Han, 2023. "Exploring the influences of ride-hailing services on VMT and transit usage – Evidence from California," Journal of Transport Geography, Elsevier, vol. 110(C).
    10. de Oliveira, Gisliany L.A. & Silva, Ivanovitch & Lima, Luciana & Costa, Daniel G., 2023. "A composite indicator of liveability based on sociodemographic and Uber quality service dimensions: A data-driven approach," Transport Policy, Elsevier, vol. 141(C), pages 97-115.
    11. Loa, Patrick & Ong, Felita & Hawkins, Jason & Nurul Habib, Khandker, 2023. "Unravelling the relationship between ride-sourcing services and conventional modes in the city of Toronto: A stated preference study," Transport Policy, Elsevier, vol. 141(C), pages 209-220.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuanyuan Zhang & Yuming Zhang, 2018. "Examining the Relationship between Household Vehicle Ownership and Ridesharing Behaviors in the United States," Sustainability, MDPI, vol. 10(8), pages 1-24, August.
    2. Altieri, Marcelo & Silva, Cecília & Terabe, Shintaro, 2020. "Give public transit a chance: A comparative analysis of competitive travel time in public transit modal share," Journal of Transport Geography, Elsevier, vol. 87(C).
    3. Ha, Jaehyun & Lee, Sugie & Ko, Joonho, 2020. "Unraveling the impact of travel time, cost, and transit burdens on commute mode choice for different income and age groups," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 147-166.
    4. Yi, Wenjing & Yan, Jie, 2020. "Energy consumption and emission influences from shared mobility in China: A national level annual data analysis," Applied Energy, Elsevier, vol. 277(C).
    5. Zhang, Haoran & Chen, Jinyu & Li, Wenjing & Song, Xuan & Shibasaki, Ryosuke, 2020. "Mobile phone GPS data in urban ride-sharing: An assessment method for emission reduction potential," Applied Energy, Elsevier, vol. 269(C).
    6. Eva Malichová & Ghadir Pourhashem & Tatiana Kováčiková & Martin Hudák, 2020. "Users’ Perception of Value of Travel Time and Value of Ridesharing Impacts on Europeans’ Ridesharing Participation Intention: A Case Study Based on MoTiV European-Wide Mobility and Behavioral Pattern ," Sustainability, MDPI, vol. 12(10), pages 1-19, May.
    7. Jiang, Yuan & House, Lisa A., 2017. "Comparison of the Performance of Count Data Models under Different Zero-Inflation Scenarios Using Simulation Studies," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258342, Agricultural and Applied Economics Association.
    8. Lazkano, Itziar & Nøstbakken, Linda & Pelli, Martino, 2017. "From fossil fuels to renewables: The role of electricity storage," European Economic Review, Elsevier, vol. 99(C), pages 113-129.
    9. Drivas, Kyriakos & Economidou, Claire & Karamanis, Dimitrios & Sanders, Mark, 2020. "Mobility of highly skilled individuals and local innovation activity," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    10. Jose‐Maria Garcia‐Alvarez‐Coque & Ibtissem Taghouti & Victor Martinez‐Gomez, 2020. "Changes in Aflatoxin Standards: Implications for EU Border Controls of Nut Imports," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(3), pages 524-541, September.
    11. Hossein Kavand & Marcel Voia, 2018. "Estimation of Health Care Demand and its Implication on Income Effects of Individuals," Springer Proceedings in Business and Economics, in: William H. Greene & Lynda Khalaf & Paul Makdissi & Robin C. Sickles & Michael Veall & Marcel-Cristia (ed.), Productivity and Inequality, pages 275-304, Springer.
    12. Bian, Zheyong & Liu, Xiang & Bai, Yun, 2020. "Mechanism design for on-demand first-mile ridesharing," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 77-117.
    13. Luigi Aldieri & Maxim N. Kotsemir & Concetto Paolo Vinci, 2020. "The Effects of Collaboration on Research Performance of Universities: an Analysis by Federal District and Scientific Fields in Russia," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 11(2), pages 766-787, June.
    14. Tekleselassie, Tsegay Gebrekidan, 2016. "Three essays on the impact of institutions and policies on socio-economic outcomes," Economics PhD Theses 1316, Department of Economics, University of Sussex Business School.
    15. Moritz Berger & Gerhard Tutz, 2021. "Transition models for count data: a flexible alternative to fixed distribution models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(4), pages 1259-1283, October.
    16. Bian, Zheyong & Liu, Xiang, 2019. "Mechanism design for first-mile ridesharing based on personalized requirements part I: Theoretical analysis in generalized scenarios," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 147-171.
    17. Taghouti, Ibtissem & Martinez-Gomez, Victor & Coque, José María Garcia Alvarez, 2015. "Exploring Eu Food Safety Notifications On Agro-Food Imports: Are Mediterranean Partner Countries Discriminated?," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 3(2), pages 1-15, April.
    18. Mourad, Abood & Puchinger, Jakob & Chu, Chengbin, 2019. "A survey of models and algorithms for optimizing shared mobility," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 323-346.
    19. Morfi, Chrysa & Ollila, Petri & Nilsson, Jerker & Surry, Yves & Feng, Li & Karantininis, Konstantinos, 2014. "The switching behaviour of Finnish co-operative members in relation to their commitment and loyalty," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182774, European Association of Agricultural Economists.
    20. Aldieri, Luigi & Kotsemir, Maxim & Vinci, Concetto Paolo, 2017. "The impact of research collaboration on academic performance: An empirical analysis for Russian Universities," MPRA Paper 76408, University Library of Munich, Germany.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:15:y:2018:i:8:p:1763-:d:164022. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.