IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v115y2022icp75-87.html
   My bibliography  Save this article

Evaluating rail transit's comparative advantages in travel cost and time over taxi with open data in two U.S. cities

Author

Listed:
  • Kirtonia, Sajeeb
  • Sun, Yanshuo

Abstract

This paper presents a comparative analysis of rail transit and taxi by travel cost and time based on the large-scale taxi trip data and public transit schedule information in two major U.S. cities. To quantify the relative advantage of one mode over the other, we introduce the notion of travel gradient, which is travel cost difference divided by travel time difference. Based on the signs of travel cost and time differences, we classify all trips into four quadrants. Quadrant II trips are selected for further analysis because rail transit is identified to be competitive with taxi for such trips. We also explore the relation between various trip characteristics and travel gradient with and without considering the spatial variation of such a relation. Main research findings include: (1) around 70% of the taxi trips in the considered datasets can be substituted with rail transit trips if the maximum walking distance is 0.5 miles at each trip end; (2) for around 10% of taxi trips with both modes being viable, rail transit dominates taxi in both travel cost and time; for the rest, rail transit is competitive with taxi; (3) the marginal travel cost saving due to mode switching from taxi to rail transit is about $70; and (4) there exist clearly spatial variations of the relation between trip characteristics and travel gradient. The main policy recommendation from this study is that rail transit can be better marketed by highlighting its relative advantage over taxi in travel time and cost, especially for travels in certain directions and time periods.

Suggested Citation

  • Kirtonia, Sajeeb & Sun, Yanshuo, 2022. "Evaluating rail transit's comparative advantages in travel cost and time over taxi with open data in two U.S. cities," Transport Policy, Elsevier, vol. 115(C), pages 75-87.
    • Handle: RePEc:eee:trapol:v:115:y:2022:i:c:p:75-87
    DOI: 10.1016/j.tranpol.2021.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X21003164
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tranpol.2021.11.003?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. Kim, Kyoungok, 2018. "Exploring the difference between ridership patterns of subway and taxi: Case study in Seoul," Journal of Transport Geography, Elsevier, vol. 66(C), pages 213-223.
    2. Yu Liu & Chaogui Kang & Song Gao & Yu Xiao & Yuan Tian, 2012. "Understanding intra-urban trip patterns from taxi trajectory data," Journal of Geographical Systems, Springer, vol. 14(4), pages 463-483, October.
    3. Wong, R.C.P. & Yang, Linchuan & Szeto, W.Y. & Li, Y.C. & Wong, S.C., 2020. "The effects of accessible taxi service and taxi fare subsidy scheme on the elderly's willingness-to-travel," Transport Policy, Elsevier, vol. 97(C), pages 129-136.
    4. Chiou, Yu-Chiun & Jou, Rong-Chang & Yang, Cheng-Han, 2015. "Factors affecting public transportation usage rate: Geographically weighted regression," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 161-177.
    5. 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.
    6. Ghimire, Ramesh & Lancelin, Colby, 2019. "The relationship between financial incentives provided by employers and commuters' decision to use transit: Results from the Atlanta Regional Household Travel Survey," Transport Policy, Elsevier, vol. 74(C), pages 103-113.
    7. Gollini, Isabella & Lu, Binbin & Charlton, Martin & Brunsdon, Christopher & Harris, Paul, 2015. "GWmodel: An R Package for Exploring Spatial Heterogeneity Using Geographically Weighted Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i17).
    8. Munira, Sirajum & Sener, Ipek N., 2020. "A geographically weighted regression model to examine the spatial variation of the socioeconomic and land-use factors associated with Strava bike activity in Austin, Texas," Journal of Transport Geography, Elsevier, vol. 88(C).
    9. Andersson, Alfred & Winslott Hiselius, Lena & Adell, Emeli, 2020. "The effect of marketing messages on the motivation to reduce private car use in different segments," Transport Policy, Elsevier, vol. 90(C), pages 22-30.
    10. Cheng, Long & Shi, Kunbo & De Vos, Jonas & Cao, Mengqiu & Witlox, Frank, 2021. "Examining the spatially heterogeneous effects of the built environment on walking among older adults," Transport Policy, Elsevier, vol. 100(C), pages 21-30.
    11. Ulak, Mehmet Baran & Yazici, Anil & Aljarrah, Mohammad, 2020. "Value of convenience for taxi trips in New York City," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 85-100.
    12. 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.
    13. Muhammad Zudhy Irawan & Prawira Fajarindra Belgiawan & Ari Krisna Mawira Tarigan & Fajar Wijanarko, 2020. "To compete or not compete: exploring the relationships between motorcycle-based ride-sourcing, motorcycle taxis, and public transport in the Jakarta metropolitan area," Transportation, Springer, vol. 47(5), pages 2367-2389, October.
    14. Zhao, Pengjun & Cao, Yushu, 2020. "Commuting inequity and its determinants in Shanghai: New findings from big-data analytics," Transport Policy, Elsevier, vol. 92(C), pages 20-37.
    15. Cordera, Ruben & Chiarazzo, Vincenza & Ottomanelli, Michele & dell’Olio, Luigi & Ibeas, Angel, 2019. "The impact of undesirable externalities on residential property values: spatial regressive models and an empirical study," Transport Policy, Elsevier, vol. 80(C), pages 177-187.
    16. Zhong, Haotian & Li, Wei, 2016. "Rail transit investment and property values: An old tale retold," Transport Policy, Elsevier, vol. 51(C), pages 33-48.
    17. Fangru Wang & Catherine L. Ross, 2019. "New potential for multimodal connection: exploring the relationship between taxi and transit in New York City (NYC)," Transportation, Springer, vol. 46(3), pages 1051-1072, June.
    18. Zhang, Xiaohu & Xu, Yang & Tu, Wei & Ratti, Carlo, 2018. "Do different datasets tell the same story about urban mobility — A comparative study of public transit and taxi usage," Journal of Transport Geography, Elsevier, vol. 70(C), pages 78-90.
    19. Liu, Xi & Gong, Li & Gong, Yongxi & Liu, Yu, 2015. "Revealing travel patterns and city structure with taxi trip data," Journal of Transport Geography, Elsevier, vol. 43(C), pages 78-90.
    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. Xinyu Zhuang & Li Zhang & Jie Lu, 2022. "Past—Present—Future: Urban Spatial Succession and Transition of Rail Transit Station Zones in Japan," IJERPH, MDPI, vol. 19(20), pages 1-35, October.
    2. Lixun Liu & Yujiang Wang & Robin Hickman, 2023. "How Rail Transit Makes a Difference in People’s Multimodal Travel Behaviours: An Analysis with the XGBoost Method," Land, MDPI, vol. 12(3), pages 1-23, March.

    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. Liao, Yuan, 2021. "Ride-sourcing compared to its public-transit alternative using big trip data," Journal of Transport Geography, Elsevier, vol. 95(C).
    2. Chen Xie & Dexin Yu & Ciyun Lin & Xiaoyu Zheng & Bo Peng, 2022. "Exploring the Spatiotemporal Impacts of the Built Environment on Taxi Ridership Using Multisource Data," Sustainability, MDPI, vol. 14(10), pages 1-24, May.
    3. Song Li & Fei Xue & Chuyu Xia & Jian Zhang & Ao Bian & Yuexi Lang & Jun Zhou, 2022. "A Big Data-Based Commuting Carbon Emissions Accounting Method—A Case of Hangzhou," Land, MDPI, vol. 11(6), pages 1-18, June.
    4. 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.
    5. Tu, Wei & Cao, Rui & Yue, Yang & Zhou, Baoding & Li, Qiuping & Li, Qingquan, 2018. "Spatial variations in urban public ridership derived from GPS trajectories and smart card data," Journal of Transport Geography, Elsevier, vol. 69(C), pages 45-57.
    6. Yang, Xiping & Fang, Zhixiang & Xu, Yang & Yin, Ling & Li, Junyi & Lu, Shiwei, 2019. "Spatial heterogeneity in spatial interaction of human movements—Insights from large-scale mobile positioning data," Journal of Transport Geography, Elsevier, vol. 78(C), pages 29-40.
    7. Apantri Peungnumsai & Apichon Witayangkurn & Masahiko Nagai & Hiroyuki Miyazaki, 2018. "A Taxi Zoning Analysis Using Large-Scale Probe Data: A Case Study for Metropolitan Bangkok," The Review of Socionetwork Strategies, Springer, vol. 12(1), pages 21-45, June.
    8. Ling Zhang & Jingjing Hao & Xiaofeng Ji & Lan Liu, 2019. "Research on the Complex Characteristics of Freight Transportation from a Multiscale Perspective Using Freight Vehicle Trip Data," Sustainability, MDPI, vol. 11(7), pages 1-20, March.
    9. Zhao, Pengxiang & Kwan, Mei-Po & Qin, Kun, 2017. "Uncovering the spatiotemporal patterns of CO2 emissions by taxis based on Individuals' daily travel," Journal of Transport Geography, Elsevier, vol. 62(C), pages 122-135.
    10. Yang, Xiong & Zhuge, Chengxiang & Shao, Chunfu & Huang, Yuantan & Hayse Chiwing G. Tang, Justin & Sun, Mingdong & Wang, Pinxi & Wang, Shiqi, 2022. "Characterizing mobility patterns of private electric vehicle users with trajectory data," Applied Energy, Elsevier, vol. 321(C).
    11. Jing Yang & Disheng Yi & Jingjing Liu & Yusi Liu & Jing Zhang, 2019. "Spatiotemporal Change Characteristics of Nodes’ Heterogeneity in the Directed and Weighted Spatial Interaction Networks: Case Study within the Sixth Ring Road of Beijing, China," Sustainability, MDPI, vol. 11(22), pages 1-15, November.
    12. Wong, R.C.P. & Szeto, W.Y., 2022. "The effects of peak hour and congested area taxi surcharges on customers’ travel decisions: Empirical evidence and policy implications," Transport Policy, Elsevier, vol. 121(C), pages 78-89.
    13. Jiao, Hongzan & Huang, Shibiao & Zhou, Yu, 2023. "Understanding the land use function of station areas based on spatiotemporal similarity in rail transit ridership: A case study in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 109(C).
    14. Mepparambath, Rakhi Manohar & Soh, Yong Sheng & Jayaraman, Vasundhara & Tan, Hong En & Ramli, Muhamad Azfar, 2023. "A novel modelling approach of integrated taxi and transit mode and route choice using city-scale emerging mobility data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    15. Zhang, Shanqi & Yang, Yu & Zhen, Feng & Lobsang, Tashi & Li, Zhixuan, 2021. "Understanding the travel behaviors and activity patterns of the vulnerable population using smart card data: An activity space-based approach," Journal of Transport Geography, Elsevier, vol. 90(C).
    16. Fangye Du & Jiaoe Wang & Yu Liu & Zihao Zhou & Haitao Jin, 2022. "Equity in Health-Seeking Behavior of Groups Using Different Transportations," IJERPH, MDPI, vol. 19(5), pages 1-16, February.
    17. Zhao, Zhiyuan & Yao, Wei & Wu, Sheng & Yang, Xiping & Wu, Qunyong & Fang, Zhixiang, 2023. "Identifying the collaborative scheduling areas between ride-hailing and traditional taxi services based on vehicle trajectory data," Journal of Transport Geography, Elsevier, vol. 107(C).
    18. Tong, Zhaomin & An, Rui & Zhang, Ziyi & Liu, Yaolin & Luo, Minghai, 2022. "Exploring non-linear and spatially non-stationary relationships between commuting burden and built environment correlates," Journal of Transport Geography, Elsevier, vol. 104(C).
    19. Zhang, Xiaohu & Xu, Yang & Tu, Wei & Ratti, Carlo, 2018. "Do different datasets tell the same story about urban mobility — A comparative study of public transit and taxi usage," Journal of Transport Geography, Elsevier, vol. 70(C), pages 78-90.
    20. Liu, Xintao & Wu, Jiawei & Huang, Jianwei & Zhang, Junwei & Chen, Bi Yu & Chen, Anthony, 2021. "Spatial-interaction network analysis of built environmental influence on daily public transport demand," Journal of Transport Geography, Elsevier, vol. 92(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:115:y:2022:i:c:p:75-87. 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.