IDEAS home Printed from https://ideas.repec.org/a/eee/retrec/v80y2020ics0739885920300093.html
   My bibliography  Save this article

Impacts of trip characteristics and weather condition on ride-sourcing network: Evidence from Uber and Lyft

Author

Listed:
  • Shokoohyar, Sina
  • Sobhani, Ahmad
  • Sobhani, Anae

Abstract

This paper evaluates the impact of intracity routes and weather conditions on pick-up waiting time, trip duration, and ride fare with a focus on the ride-sourcing mode in the city of Philadelphia, in the U.S. For our analysis, ride estimate data has been collected from Uber and Lyft developers’ Application Program Interfaces (API), and weather information has been collected from Yahoo weather API during summer 2018. It should be noted that the generated trips for both ride-sourcing services are for solo and pool rides. Time fixed effect ordinary least squares model was adopted in this paper for analysis purposes.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:retrec:v:80:y:2020:i:c:s0739885920300093
    DOI: 10.1016/j.retrec.2020.100820
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0739885920300093
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.retrec.2020.100820?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. Harish Guda & Upender Subramanian, 2019. "Your Uber Is Arriving: Managing On-Demand Workers Through Surge Pricing, Forecast Communication, and Worker Incentives," Management Science, INFORMS, vol. 67(5), pages 1995-2014, May.
    2. Soh, Harold & Lim, Sonja & Zhang, Tianyou & Fu, Xiuju & Lee, Gary Kee Khoon & Hung, Terence Gih Guang & Di, Pan & Prakasam, Silvester & Wong, Limsoon, 2010. "Weighted complex network analysis of travel routes on the Singapore public transportation system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5852-5863.
    3. Cools, Mario & Creemers, Lieve, 2013. "The dual role of weather forecasts on changes in activity-travel behavior," Journal of Transport Geography, Elsevier, vol. 28(C), pages 167-175.
    4. Judd Cramer & Alan B. Krueger, 2016. "Disruptive Change in the Taxi Business: The Case of Uber," American Economic Review, American Economic Association, vol. 106(5), pages 177-182, May.
    5. de Souza Silva, Laize Andréa & de Andrade, Maurício Oliveira & Alves Maia, Maria Leonor, 2018. "How does the ride-hailing systems demand affect individual transport regulation?," Research in Transportation Economics, Elsevier, vol. 69(C), pages 600-606.
    6. Hughes, Ryan & MacKenzie, Don, 2016. "Transportation network company wait times in Greater Seattle, and relationship to socioeconomic indicators," Journal of Transport Geography, Elsevier, vol. 56(C), pages 36-44.
    7. 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.
    8. Christofer Laurell & Christian Sandström, 2016. "Analysing Uber In Social Media — Disruptive Technology Or Institutional Disruption?," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 20(05), pages 1-19, June.
    9. Brodeur, Abel & Nield, Kerry, 2018. "An empirical analysis of taxi, Lyft and Uber rides: Evidence from weather shocks in NYC," Journal of Economic Behavior & Organization, Elsevier, vol. 152(C), pages 1-16.
    10. Terrien, Clara & Maniak, Rémi & Chen, Bo & Shaheen, Susan, 2016. "Good Practices for Advancing Urban Mobility Innovation: A Case Study of One-Way Carsharing," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt53z3h2gt, Institute of Transportation Studies, UC Berkeley.
    11. Clara Terrien & Rémi Maniak & Bo Chen & Susan Shaheen, 2016. "Good practices for advancing urban mobility innovation: A case study of one-way carsharing," Post-Print hal-02458822, HAL.
    12. 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.
    13. Maren Outwater & Greg Spitz & John Lobb & Margaret Campbell & Bhargava Sana & Ram Pendyala & William Woodford, 2011. "Characteristics of premium transit services that affect mode choice," Transportation, Springer, vol. 38(4), pages 605-623, July.
    14. Lars Böcker & Martin Dijst & Jan Prillwitz, 2013. "Impact of Everyday Weather on Individual Daily Travel Behaviours in Perspective: A Literature Review," Transport Reviews, Taylor & Francis Journals, vol. 33(1), pages 71-91, January.
    15. Harding, Simon & Kandlikar, Milind & Gulati, Sumeet, 2016. "Taxi apps, regulation, and the market for taxi journeys," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 15-25.
    16. Schwieterman, Joseph & Smith, C. Scott, 2018. "Sharing the ride: A paired-trip analysis of UberPool and Chicago Transit Authority services in Chicago, Illinois," Research in Transportation Economics, Elsevier, vol. 71(C), pages 9-16.
    17. Singhal, Abhishek & Kamga, Camille & Yazici, Anil, 2014. "Impact of weather on urban transit ridership," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 379-391.
    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. Shokouhyar, Sajjad & Shokoohyar, Sina & Safari, Sepehr, 2020. "Research on the influence of after-sales service quality factors on customer satisfaction," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    2. Sehyun Tak & Soomin Woo & Sungjin Park & Sunghoon Kim, 2021. "The City-Wide Impacts of the Interactions between Shared Autonomous Vehicle-Based Mobility Services and the Public Transportation System," Sustainability, MDPI, vol. 13(12), pages 1-29, June.
    3. Ravula, Prashanth, 2022. "Monetary and hassle savings as strategic variables in the ride-sharing market," Research in Transportation Economics, Elsevier, vol. 94(C).
    4. Obada Asqool & Suhana Koting & Ahmad Saifizul, 2021. "Evaluation of Outlier Filtering Algorithms for Accurate Travel Time Measurement Incorporating Lane-Splitting Situations," Sustainability, MDPI, vol. 13(24), pages 1-23, December.

    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. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    2. Sun, Daniel(Jian) & Ding, Xueqing, 2019. "Spatiotemporal evolution of ridesourcing markets under the new restriction policy: A case study in Shanghai," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 227-239.
    3. 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).
    4. Faghih-Imani, Ahmadreza & Anowar, Sabreena & Miller, Eric J. & Eluru, Naveen, 2017. "Hail a cab or ride a bike? A travel time comparison of taxi and bicycle-sharing systems in New York City," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 11-21.
    5. Xu, Zhengtian & Yin, Yafeng & Zha, Liteng, 2017. "Optimal parking provision for ride-sourcing services," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 559-578.
    6. Nair, Gopindra S. & Bhat, Chandra R. & Batur, Irfan & Pendyala, Ram M. & Lam, William H.K., 2020. "A model of deadheading trips and pick-up locations for ride-hailing service vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 289-308.
    7. Aguilera-García, Álvaro & Gomez, Juan & Velázquez, Guillermo & Vassallo, Jose Manuel, 2022. "Ridesourcing vs. traditional taxi services: Understanding users’ choices and preferences in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 161-178.
    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. 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).
    10. Alejandro Tirachini, 2020. "Ride-hailing, travel behaviour and sustainable mobility: an international review," Transportation, Springer, vol. 47(4), pages 2011-2047, August.
    11. Yang, Xiaobao & Yue, Xianfei & Sun, Huijun & Gao, Ziyou & Wang, Wencheng, 2021. "Impact of weather on freeway origin-destination volume in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 143(C), pages 30-47.
    12. Goodspeed, Robert & Xie, Tian & Dillahunt, Tawanna R. & Lustig, Josh, 2019. "An alternative to slow transit, drunk driving, and walking in bad weather: An exploratory study of ridesourcing mode choice and demand," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    13. Fayed, Lynn & Nilsson, Gustav & Geroliminis, Nikolas, 2023. "On the utilization of dedicated bus lanes for pooled ride-hailing services," Transportation Research Part B: Methodological, Elsevier, vol. 169(C), pages 29-52.
    14. Sun, Luoyi & Teunter, Ruud H. & Hua, Guowei & Wu, Tian, 2020. "Taxi-hailing platforms: Inform or Assign drivers?," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 197-212.
    15. Kong, Hui & Zhang, Xiaohu & Zhao, Jinhua, 2020. "How does ridesourcing substitute for public transit? A geospatial perspective in Chengdu, China," Journal of Transport Geography, Elsevier, vol. 86(C).
    16. Schaller, Bruce, 2021. "Can sharing a ride make for less traffic? Evidence from Uber and Lyft and implications for cities," Transport Policy, Elsevier, vol. 102(C), pages 1-10.
    17. Morton, Craig, 2020. "The demand for cycle sharing: Examining the links between weather conditions, air quality levels, and cycling demand for regular and casual users," Journal of Transport Geography, Elsevier, vol. 88(C).
    18. Zhang, Kenan & Nie, Yu (Marco), 2022. "Mitigating traffic congestion induced by transportation network companies: A policy analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 96-118.
    19. 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.
    20. Zanni, Alberto M. & Ryley, Tim J., 2015. "The impact of extreme weather conditions on long distance travel behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 305-319.

    More about this item

    Keywords

    Ride-sourcing platform; On-demand transportation; Ordinary least squares model; Adaption fare policy; Accessibility; Weather condition; Uber; Lyft;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

    Statistics

    Access and download statistics

    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:retrec:v:80:y:2020:i:c:s0739885920300093. 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/620614/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.