IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v96y2020icp128-140.html
   My bibliography  Save this article

Real trip costs: Modelling intangible costs of urban online car-hailing in Haikou

Author

Listed:
  • Bi, Hui
  • Ye, Zhirui
  • Zhao, Jiahui
  • Chen, Enhui

Abstract

Prearranged and on-demand ride services that match passengers and drivers using smartphone applications over a network have developed rapidly across the world. However, the maximum efficiency of the entire hailing demand market and the driver deserve further attention to identify potential improvements. This paper makes the first attempt to conduct a quantitative analysis of the intangible costs generated from ridesourcing trips using an observed ridesourcing dataset provided by Didi Chuxing, including the waiting time costs attributable to waiting for the passenger and the future opportunity costs of different Trip Order Markets. Then, a quantitative method is developed to calculate the specific value of the above intangible costs of each ridesourcing trip. The results show that the average cost of a trip drops by 9.64% when intangible costs are considered, and a large difference exists among the values under various spatial-temporal conditions. In addition, the relative relationship between two types of intangible costs shows a large discrepancy in some sensitive areas. The findings of this study can help transit agencies better understand ridesourcing service and develop strategies for setting reasonable prices and allocating capacity.

Suggested Citation

  • Bi, Hui & Ye, Zhirui & Zhao, Jiahui & Chen, Enhui, 2020. "Real trip costs: Modelling intangible costs of urban online car-hailing in Haikou," Transport Policy, Elsevier, vol. 96(C), pages 128-140.
  • Handle: RePEc:eee:trapol:v:96:y:2020:i:c:p:128-140
    DOI: 10.1016/j.tranpol.2020.06.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X19307929
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tranpol.2020.06.009?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. Zhou, Xiaolu & Wang, Mingshu & Li, Dongying, 2019. "Bike-sharing or taxi? Modeling the choices of travel mode in Chicago using machine learning," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    2. Zhao, Pengjun & Li, Peilin, 2019. "Travel satisfaction inequality and the role of the urban metro system," Transport Policy, Elsevier, vol. 79(C), pages 66-81.
    3. Ou, Hui & Wang, Tao & Tang, Tie-Qiao, 2019. "Analysis of trip cost in a two-lane traffic corridor with one entry and one exit," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 65-72.
    4. Wu, Tian & Shen, Qu & Xu, Ming & Peng, Tianduo & Ou, Xunmin, 2018. "Development and application of an energy use and CO2 emissions reduction evaluation model for China's online car hailing services," Energy, Elsevier, vol. 154(C), pages 298-307.
    5. Cetin, Tamer & Deakin, Elizabeth, 2019. "Regulation of taxis and the rise of ridesharing," Transport Policy, Elsevier, vol. 76(C), pages 149-158.
    6. 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.
    7. Hu, Beibei & Xia, Xuanxuan & Sun, Huijun & Dong, Xianlei, 2019. "Understanding the imbalance of the taxi market: From the high-quality customer’s perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    8. Vinayak, Pragun & Dias, Felipe F. & Astroza, Sebastian & Bhat, Chandra R. & Pendyala, Ram M. & Garikapati, Venu M., 2018. "Accounting for multi-dimensional dependencies among decision-makers within a generalized model framework: An application to understanding shared mobility service usage levels," Transport Policy, Elsevier, vol. 72(C), pages 129-137.
    9. Rayle, Lisa & Dai, Danielle & Chan, Nelson & Cervero, Robert & Shaheen, Susan, 2016. "Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco," Transport Policy, Elsevier, vol. 45(C), pages 168-178.
    10. Oh, Cheol & Choi, Jinheoun & Jung, Soyoung, 2016. "Proactive vehicle emissions quantification from crash potential under stop-and-go traffic conditions," Transport Policy, Elsevier, vol. 49(C), pages 86-92.
    11. Shaheen, Susan PhD & Chan, Nelson, 2016. "Mobility and the Sharing Economy: Potential to Overcome First- and Last-Mile Public Transit Connections," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8042k3d7, Institute of Transportation Studies, UC Berkeley.
    12. Jun, Myung-Jin & Choi, Keechoo & Jeong, Ji-Eun & Kwon, Ki-Hyun & Kim, Hee-Jae, 2015. "Land use characteristics of subway catchment areas and their influence on subway ridership in Seoul," Journal of Transport Geography, Elsevier, vol. 48(C), pages 30-40.
    13. Hasnine, Md Sami & Lin, TianYang & Weiss, Adam & Habib, Khandker Nurul, 2018. "Determinants of travel mode choices of post-secondary students in a large metropolitan area: The case of the city of Toronto," Journal of Transport Geography, Elsevier, vol. 70(C), pages 161-171.
    14. Wang, Yihong & Correia, Gonçalo Homem de Almeida & de Romph, Erik & Timmermans, H.J.P., 2017. "Using metro smart card data to model location choice of after-work activities: An application to Shanghai," Journal of Transport Geography, Elsevier, vol. 63(C), pages 40-47.
    15. Wu, Tian & Zhang, Mengbo & Tian, Xin & Wang, Shouyang & Hua, Guowei, 2020. "Spatial differentiation and network externality in pricing mechanism of online car hailing platform," International Journal of Production Economics, Elsevier, vol. 219(C), pages 275-283.
    16. Keuchel, Stephan & Jacobs, Leif & Laurenz, Karolyn, 2019. "Owners of energy-efficient houses as a target group for sustainable electric mobility," Transport Policy, Elsevier, vol. 81(C), pages 254-262.
    17. Papu Carrone, Andrea & Hoening, Valerie Maria & Jensen, Anders Fjendbo & Mabit, Stefan Eriksen & Rich, Jeppe, 2020. "Understanding car sharing preferences and mode substitution patterns: A stated preference experiment," Transport Policy, Elsevier, vol. 98(C), pages 139-147.
    18. Tu, Meiting & Li, Ye & Li, Wenxiang & Tu, Minchao & Orfila, Olivier & Gruyer, Dominique, 2019. "Improving ridesplitting services using optimization procedures on a shareability network: A case study of Chengdu," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    19. Shaheen, Susan PhD & Chan, Nelson & Gaynor, Theresa, 2016. "Casual Carpooling in the San Francisco Bay Area: Understanding User Characteristics, Behaviors, and Motivations," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt4dh2h0rf, Institute of Transportation Studies, UC Berkeley.
    20. Tirachini, Alejandro & del Río, Mariana, 2019. "Ride-hailing in Santiago de Chile: Users’ characterisation and effects on travel behaviour," Transport Policy, Elsevier, vol. 82(C), pages 46-57.
    21. Gan, Zuoxian & Feng, Tao & Wu, Yunteng & Yang, Min & Timmermans, Harry, 2019. "Station-based average travel distance and its relationship with urban form and land use: An analysis of smart card data in Nanjing City, China," Transport Policy, Elsevier, vol. 79(C), pages 137-154.
    22. Cheng, Han & Mao, Chao & Madanat, Samer & Horvath, Arpad, 2018. "Minimizing the total costs of urban transit systems can reduce greenhouse gas emissions: The case of San Francisco," Transport Policy, Elsevier, vol. 66(C), pages 40-48.
    23. Kim, Jinwon, 2019. "Estimating the social cost of congestion using the bottleneck model," Economics of Transportation, Elsevier, vol. 19(C), pages 1-1.
    24. Shaheen, Susan A. & Chan, Nelson D. & Gaynor, Teresa, 2016. "Casual carpooling in the San Francisco Bay Area: Understanding user characteristics, behaviors, and motivations," Transport Policy, Elsevier, vol. 51(C), pages 165-173.
    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. Bi, Hui & Ye, Zhirui & Hu, Liyang & Zhu, He, 2021. "Why they don't choose bus service? Understanding special online car-hailing behavior near bus stops," Transport Policy, Elsevier, vol. 114(C), pages 280-297.

    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. Xiong, Ziyue & Jian Li, & Wu, Hangbin, 2021. "Understanding operation patterns of urban online ride-hailing services: A case study of Xiamen," Transport Policy, Elsevier, vol. 101(C), pages 100-118.
    2. He, Zhengbing, 2021. "Portraying ride-hailing mobility using multi-day trip order data: A case study of Beijing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 146(C), pages 152-169.
    3. 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).
    4. 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.
    5. Soria, Jason & Stathopoulos, Amanda, 2021. "Investigating socio-spatial differences between solo ridehailing and pooled rides in diverse communities," Journal of Transport Geography, Elsevier, vol. 95(C).
    6. Punel, Aymeric & Stathopoulos, Amanda, 2017. "Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 18-38.
    7. Tang, Jinjun & Gao, Fan & Han, Chunyang & Cen, Xuekai & Li, Zhitao, 2021. "Uncovering the spatially heterogeneous effects of shared mobility on public transit and taxi," Journal of Transport Geography, Elsevier, vol. 95(C).
    8. Zou, Zhenpeng & Cirillo, Cinzia, 2021. "Does ridesourcing impact driving decisions: A survey weighted regression analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 146(C), pages 1-12.
    9. 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.
    10. Bi, Hui & Ye, Zhirui & Hu, Liyang & Zhu, He, 2021. "Why they don't choose bus service? Understanding special online car-hailing behavior near bus stops," Transport Policy, Elsevier, vol. 114(C), pages 280-297.
    11. Kumar, Akshay & Gupta, Akshay & Parida, Manoranjan & Chauhan, Vivek, 2022. "Service quality assessment of ride-sourcing services: A distinction between ride-hailing and ride-sharing services," Transport Policy, Elsevier, vol. 127(C), pages 61-79.
    12. Prateek Bansal & Akanksha Sinha & Rubal Dua & Ricardo Daziano, 2019. "Eliciting Preferences of Ridehailing Users and Drivers: Evidence from the United States," Papers 1904.06695, arXiv.org.
    13. Tu, Meiting & Li, Ye & Li, Wenxiang & Tu, Minchao & Orfila, Olivier & Gruyer, Dominique, 2019. "Improving ridesplitting services using optimization procedures on a shareability network: A case study of Chengdu," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    14. Young, Mischa & Allen, Jeff & Farber, Steven, 2020. "Measuring when Uber behaves as a substitute or supplement to transit: An examination of travel-time differences in Toronto," Journal of Transport Geography, Elsevier, vol. 82(C).
    15. Yang, Jie & Zhao, Daozhi & Wang, Zeyu & Xu, Chunqiu, 2022. "Impact of regulation on on-demand ride-sharing service: Profit-based target vs demand-based target," Research in Transportation Economics, Elsevier, vol. 92(C).
    16. Aghaabbasi, Mahdi & Shekari, Zohreh Asadi & Shah, Muhammad Zaly & Olakunle, Oloruntobi & Armaghani, Danial Jahed & Moeinaddini, Mehdi, 2020. "Predicting the use frequency of ride-sourcing by off-campus university students through random forest and Bayesian network techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 262-281.
    17. Loa, Patrick & Nurul Habib, Khandker, 2021. "Examining the influence of attitudinal factors on the use of ride-hailing services in Toronto," Transportation Research Part A: Policy and Practice, Elsevier, vol. 146(C), pages 13-28.
    18. Zgheib, Najib & Abou-Zeid, Maya & Kaysi, Isam, 2020. "Modeling demand for ridesourcing as feeder for high capacity mass transit systems with an application to the planned Beirut BRT," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 70-91.
    19. Wong, Yale Z. & Hensher, David A. & Mulley, Corinne, 2020. "Mobility as a service (MaaS): Charting a future context," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 5-19.
    20. Qiao, Si & Yeh, Anthony Gar-On, 2021. "Is ride-hailing a valuable means of transport in newly developed areas under TOD-oriented urbanization in China? Evidence from Chengdu City," Journal of Transport Geography, Elsevier, vol. 96(C).

    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:trapol:v:96:y:2020:i:c:p:128-140. 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/30473/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.