IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v178y2023ics0965856423002951.html
   My bibliography  Save this article

Book-ahead ride-hailing trip and its determinants: Findings from large-scale trip records in China

Author

Listed:
  • Li, Wu
  • Zhao, Shengchuan
  • Ma, Jingwen
  • Nielsen, Otto Anker
  • Jiang, Yu

Abstract

The cruising of ride-hailing vehicles generates negative externalities such as traffic congestion and vehicular emissions. These externalities can be mitigated by reducing cruising driving via operating book-ahead ride-hailing services, where the platform dispatches and routes drivers based on precise information on travelers’ departure time and origin–destination (OD). However, the effects of factors influencing book-ahead ride-hailing trips have rarely been empirically examined with real data. Using six-month trip data from China, this study employs a gradient boosting decision tree (GBDT) method with hyperparameters optimized by the Bayesian optimization algorithm to examine the factors associated with book-ahead ride-hailing trips across OD pairs (hexagon cells-to-hexagon cells) at various spatial scales. The relative importance rankings generated from this study indicate that trip features, weather conditions, and accessibility to transportation hubs are significant determinants correlated with the usages of book-ahead ride-hailing. The partial dependence plots demonstrate the nonlinear threshold effects of these determinants on the hourly number of book-ahead ride-hailing per OD pair. Moreover, this study compares the differences in associations between peak and non-peak hours as well as weekdays and weekends. The disparity in the nonlinear threshold effects between weekdays and weekends is only observable during the evening peak period and not at other times. These findings provide valuable insights into developing practical strategies for promoting book-ahead ride-hailing services.

Suggested Citation

  • Li, Wu & Zhao, Shengchuan & Ma, Jingwen & Nielsen, Otto Anker & Jiang, Yu, 2023. "Book-ahead ride-hailing trip and its determinants: Findings from large-scale trip records in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:transa:v:178:y:2023:i:c:s0965856423002951
    DOI: 10.1016/j.tra.2023.103875
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856423002951
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2023.103875?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dimitris Bertsimas & Patrick Jaillet, & Sébastien Martin, 2019. "Online Vehicle Routing: The Edge of Optimization in Large-Scale Applications," Operations Research, INFORMS, vol. 67(1), pages 143-162, January.
    2. Dean, Matthew D. & Kockelman, Kara M., 2021. "Spatial variation in shared ride-hail trip demand and factors contributing to sharing: Lessons from Chicago," Journal of Transport Geography, Elsevier, vol. 91(C).
    3. Lamotte, Raphaël & de Palma, André & Geroliminis, Nikolas, 2017. "On the use of reservation-based autonomous vehicles for demand management," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 205-227.
    4. Nguyen-Phuoc, Duy Quy & Su, Diep Ngoc & Tran, Phuong Thi Kim & Le, Diem-Trinh Thi & Johnson, Lester W., 2020. "Factors influencing customer's loyalty towards ride-hailing taxi services – A case study of Vietnam," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 96-112.
    5. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    6. Shokoohyar, Sina & Sobhani, Ahmad & Sobhani, Anae, 2020. "Impacts of trip characteristics and weather condition on ride-sourcing network: Evidence from Uber and Lyft," Research in Transportation Economics, Elsevier, vol. 80(C).
    7. Xu, Yiming & Yan, Xiang & Liu, Xinyu & Zhao, Xilei, 2021. "Identifying key factors associated with ridesplitting adoption rate and modeling their nonlinear relationships," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 170-188.
    8. Mi Diao & Hui Kong & Jinhua Zhao, 2021. "Impacts of transportation network companies on urban mobility," Nature Sustainability, Nature, vol. 4(6), pages 494-500, June.
    9. Ding, Chuan & Cao, Xinyu (Jason) & Næss, Petter, 2018. "Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 107-117.
    10. Alejandro Tirachini, 2020. "Ride-hailing, travel behaviour and sustainable mobility: an international review," Transportation, Springer, vol. 47(4), pages 2011-2047, August.
    11. Rana Tarabay & Maya Abou-Zeid, 2020. "Modeling the choice to switch from traditional modes to ridesourcing services for social/recreational trips in Lebanon," Transportation, Springer, vol. 47(4), pages 1733-1763, August.
    12. Tao, Tao & Wang, Jueyu & Cao, Xinyu, 2020. "Exploring the non-linear associations between spatial attributes and walking distance to transit," Journal of Transport Geography, Elsevier, vol. 82(C).
    13. Yang, Linchuan & Ao, Yibin & Ke, Jintao & Lu, Yi & Liang, Yuan, 2021. "To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults," Journal of Transport Geography, Elsevier, vol. 94(C).
    14. Rayle, Lisa & Dai, Danielle & Chan, Nelson & Cervero, Robert & Shaheen, Susan PhD, 2016. "Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt60v8r346, Institute of Transportation Studies, UC Berkeley.
    15. Yu, Haitao & Peng, Zhong-Ren, 2019. "Exploring the spatial variation of ridesourcing demand and its relationship to built environment and socioeconomic factors with the geographically weighted Poisson regression," Journal of Transport Geography, Elsevier, vol. 75(C), pages 147-163.
    16. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    17. Ouyang, Yanfeng & Yang, Haolin & Daganzo, Carlos F., 2021. "Performance of reservation-based carpooling services under detour and waiting time restrictions," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 370-385.
    18. Li, Wu & Guan, Haotian & Qin, Wenwen & Ji, Xiaofeng, 2023. "Collective and individual spatial equity measure in public transit accessibility based on generalized travel cost," Research in Transportation Economics, Elsevier, vol. 98(C).
    19. Brown, Anne E., 2020. "Who and where rideshares? Rideshare travel and use in Los Angeles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 120-134.
    20. Ravula, Prashanth, 2022. "Monetary and hassle savings as strategic variables in the ride-sharing market," Research in Transportation Economics, Elsevier, vol. 94(C).
    21. Liao, Yuan, 2021. "Ride-sourcing compared to its public-transit alternative using big trip data," Journal of Transport Geography, Elsevier, vol. 95(C).
    22. Asamer, Johannes & Reinthaler, Martin & Ruthmair, Mario & Straub, Markus & Puchinger, Jakob, 2016. "Optimizing charging station locations for urban taxi providers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 233-246.
    23. Ding, Chuan & Cao, Xinyu & Liu, Chao, 2019. "How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds," Journal of Transport Geography, Elsevier, vol. 77(C), pages 70-78.
    24. Yang, Jiawen & Cao, Jason & Zhou, Yufei, 2021. "Elaborating non-linear associations and synergies of subway access and land uses with urban vitality in Shenzhen," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 74-88.
    Full references (including those not matched with items on IDEAS)

    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. Yang, Hongtai & Luo, Peng & Li, Chaojing & Zhai, Guocong & Yeh, Anthony G.O., 2023. "Nonlinear effects of fare discounts and built environment on ridesplitting adoption rates," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    2. Ding, Chuan & Cao, Xinyu & Yu, Bin & Ju, Yang, 2021. "Non-linear associations between zonal built environment attributes and transit commuting mode choice accounting for spatial heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 22-35.
    3. Liang, Yuan & Yu, Bingjie & Zhang, Xiaojian & Lu, Yi & Yang, Linchuan, 2023. "The short-term impact of congestion taxes on ridesourcing demand and traffic congestion: Evidence from Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    4. Tao, Tao & Cao, Jason, 2023. "Exploring nonlinear and collective influences of regional and local built environment characteristics on travel distances by mode," Journal of Transport Geography, Elsevier, vol. 109(C).
    5. Yin, Chun & Cao, Jason & Sun, Bindong & Liu, Jiahang, 2023. "Exploring built environment correlates of walking for different purposes: Evidence for substitution," Journal of Transport Geography, Elsevier, vol. 106(C).
    6. Du, Mingyang & Cheng, Lin & Li, Xuefeng & Liu, Qiyang & Yang, Jingzong, 2022. "Spatial variation of ridesplitting adoption rate in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 13-37.
    7. Yang, Hongtai & Zheng, Rong & Li, Xuan & Huo, Jinghai & Yang, Linchuan & Zhu, Tong, 2022. "Nonlinear and threshold effects of the built environment on e-scooter sharing ridership," Journal of Transport Geography, Elsevier, vol. 104(C).
    8. Loa, Patrick & Hossain, Sanjana & Liu, Yicong & Nurul Habib, Khandker, 2022. "How has the COVID-19 pandemic affected the use of ride-sourcing services? An empirical evidence-based investigation for the Greater Toronto Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 46-62.
    9. Tao, Tao & Cao, Jason, 2022. "Examining motivations for owning autonomous vehicles: Implications for land use and transportation," Journal of Transport Geography, Elsevier, vol. 102(C).
    10. Zhang, Xiaojian & Zhao, Xilei, 2022. "Machine learning approach for spatial modeling of ridesourcing demand," Journal of Transport Geography, Elsevier, vol. 100(C).
    11. Xu, Yiming & Yan, Xiang & Liu, Xinyu & Zhao, Xilei, 2021. "Identifying key factors associated with ridesplitting adoption rate and modeling their nonlinear relationships," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 170-188.
    12. Yuan Liang & Bingjie Yu & Xiaojian Zhang & Yi Lu & Linchuan Yang, 2022. "The Short-term Impact of Congestion Taxes on Ridesourcing Demand and Traffic Congestion: Evidence from Chicago," Papers 2207.01793, arXiv.org, revised Feb 2023.
    13. García-Herrera, Alisson & Basso, Leonardo J. & Tirachini, Alejandro, 2024. "Microeconomic analysis of ridesourcing market regulation policies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 186(C).
    14. Shao, Qifan & Zhang, Wenjia & Cao, Xinyu (Jason) & Yang, Jiawen, 2023. "Built environment interventions for emission mitigation: A machine learning analysis of travel-related CO2 in a developing city," Journal of Transport Geography, Elsevier, vol. 110(C).
    15. Xiaoxia Dong & Erick Guerra & Ricardo A. Daziano, 2022. "Impact of TNC on travel behavior and mode choice: a comparative analysis of Boston and Philadelphia," Transportation, Springer, vol. 49(6), pages 1577-1597, December.
    16. Tao, Tao & Cao, Jason, 2024. "Ineffective built environment interventions: How to reduce driving in American suburbs?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    17. Zhang, Xiaojian & Zhou, Zhengze & Xu, Yiming & Zhao, Xilei, 2024. "Analyzing spatial heterogeneity of ridesourcing usage determinants using explainable machine learning," Journal of Transport Geography, Elsevier, vol. 114(C).
    18. Liu, Jixiang & Wang, Bo & Xiao, Longzhu, 2021. "Non-linear associations between built environment and active travel for working and shopping: An extreme gradient boosting approach," Journal of Transport Geography, Elsevier, vol. 92(C).
    19. Gao, Kun & Yang, Ying & Gil, Jorge & Qu, Xiaobo, 2023. "Data-driven interpretation on interactive and nonlinear effects of the correlated built environment on shared mobility," Journal of Transport Geography, Elsevier, vol. 110(C).
    20. 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.

    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:eee:transa:v:178:y:2023:i:c:s0965856423002951. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.