IDEAS home Printed from https://ideas.repec.org/a/spr/trosos/v12y2018i1d10.1007_s12626-018-0019-4.html
   My bibliography  Save this article

A Taxi Zoning Analysis Using Large-Scale Probe Data: A Case Study for Metropolitan Bangkok

Author

Listed:
  • Apantri Peungnumsai

    (Asian Institute of Technology)

  • Apichon Witayangkurn

    (University of Tokyo)

  • Masahiko Nagai

    (Yamaguchi University)

  • Hiroyuki Miyazaki

    (University of Tokyo)

Abstract

Taxis are considered one of the most convenient means of transportation, especially when people have to travel off-route, where public transportation is not a feasible option, and also when they need to reach a destination according to what is most convenient for them. However, many issues exist about taxi services, such as the problems of passengers who are unable to get taxi service at the location of their choice, or problems concerning when they need the taxi service to arrive. These problems may be due to the unavailability of the taxi at that particular location or due to the taxi driver not wanting to provide service. A taxi driver may not want to provide service to a potential passenger, because they may have preferences on the direction and areas they want to go or because of the different types of service zoning. Understanding the behaviors of taxi drivers and the characteristics of the trip/travel might be helpful to solving such issues. In this study, we conducted an analysis from a questionnaire survey and large-scale taxi probe data to understand taxi service behavior, travel characteristics, and to discover taxi service zoning characteristics. As a result, four types of taxi service zones including isolated zones, interactive zones, special service zones, and target zones were encountered. Travel characteristics were calculated and analyzed at different criteria, such as weekdays, weekends, and various time windows in a single day. The result of these characteristics was explained according to their similarities and dissimilarities in each type of zone. The discovery of the different zones and their respective definitions might be a good initiative for further development of a policy for taxi drivers to provide better service for passengers.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:trosos:v:12:y:2018:i:1:d:10.1007_s12626-018-0019-4
    DOI: 10.1007/s12626-018-0019-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12626-018-0019-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12626-018-0019-4?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. Sihai Zhang & Zhiyang Wang, 2016. "Inferring Passenger Denial Behavior of Taxi Drivers from Large-Scale Taxi Traces," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-21, November.
    2. Yang, Zhuo & Franz, Mark L. & Zhu, Shanjiang & Mahmoudi, Jina & Nasri, Arefeh & Zhang, Lei, 2018. "Analysis of Washington, DC taxi demand using GPS and land-use data," Journal of Transport Geography, Elsevier, vol. 66(C), pages 35-44.
    3. 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.
    4. Hunt, J.D. & Stefan, K.J., 2007. "Tour-based microsimulation of urban commercial movements," Transportation Research Part B: Methodological, Elsevier, vol. 41(9), pages 981-1013, November.
    5. Siti Nuryanah & Sardar M. N. Islam, 2015. "The Context of the Case Study," Palgrave Macmillan Books, in: Corporate Governance and Financial Management, chapter 5, pages 145-156, Palgrave Macmillan.
    6. 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. Apantri Peungnumsai & Hiroyuki Miyazaki & Apichon Witayangkurn & Sohee Minsun Kim, 2020. "A Grid-Based Spatial Analysis for Detecting Supply–Demand Gaps of Public Transports: A Case Study of the Bangkok Metropolitan Region," Sustainability, MDPI, vol. 12(24), pages 1-27, December.
    2. Songkorn Siangsuebchart & Sarawut Ninsawat & Apichon Witayangkurn & Surachet Pravinvongvuth, 2021. "Public Transport GPS Probe and Rail Gate Data for Assessing the Pattern of Human Mobility in the Bangkok Metropolitan Region, Thailand," Sustainability, MDPI, vol. 13(4), pages 1-29, February.

    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. 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.
    2. 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.
    3. Ying Ni & Jiaqi Chen, 2020. "Exploring the Effects of the Built Environment on Two Transfer Modes for Metros: Dockless Bike Sharing and Taxis," Sustainability, MDPI, vol. 12(5), pages 1-20, March.
    4. 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.
    5. 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.
    6. Tong Zhou & Xintao Liu & Zhen Qian & Haoxuan Chen & Fei Tao, 2019. "Dynamic Update and Monitoring of AOI Entrance via Spatiotemporal Clustering of Drop-Off Points," Sustainability, MDPI, vol. 11(23), pages 1-20, December.
    7. 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.
    8. 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.
    9. Roya Etminani-Ghasrodashti & Shima Hamidi, 2019. "Individuals’ Demand for Ride-hailing Services: Investigating the Combined Effects of Attitudinal Factors, Land Use, and Travel Attributes on Demand for App-based Taxis in Tehran, Iran," Sustainability, MDPI, vol. 11(20), pages 1-19, October.
    10. Sawssen Khlifi & Ghazi Zouari, 2021. "The Impact of CEO Overconfidence on Real Earnings Management: Evidence from M&A Transactions," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 20(3), pages 402-424, September.
    11. Benjamin Davies & David C. Maré, 2020. "Delineating functional labour market areas with estimable classification stabilities," Working Papers 20_08, Motu Economic and Public Policy Research.
    12. de Jong, Gerard & Kouwenhoven, Marco & Ruijs, Kim & van Houwe, Pieter & Borremans, Dana, 2016. "A time-period choice model for road freight transport in Flanders based on stated preference data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 20-31.
    13. He, Yifan & Zhao, Chen & Zeng, An, 2022. "Ranking locations in a city via the collective home-work relations in human mobility data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    14. Valentin-Marian Antohi & Monica Laura Zlati & Romeo Victor Ionescu & Mihaela Neculita & Raluca Rusu & Aurelian Constantin, 2020. "Attracting European Funds in the Romanian Economy and Leverage Points for Securing their Sustainable Management: A Critical Auditing Analysis," Sustainability, MDPI, vol. 12(13), pages 1-27, July.
    15. Carmenta, Rachel & Cammelli, Federico & Dressler, Wolfram & Verbicaro, Camila & Zaehringer, Julie G., 2021. "Between a rock and a hard place: The burdens of uncontrolled fire for smallholders across the tropics," World Development, Elsevier, vol. 145(C).
    16. Dai, Jiangyu & Wu, Shiqiang & Han, Guoyi & Weinberg, Josh & Xie, Xinghua & Wu, Xiufeng & Song, Xingqiang & Jia, Benyou & Xue, Wanyun & Yang, Qianqian, 2018. "Water-energy nexus: A review of methods and tools for macro-assessment," Applied Energy, Elsevier, vol. 210(C), pages 393-408.
    17. Cho, Joongkoo & Hu, Weihong, 2013. "Network-Based Simulation of Air Pollution Emissions Associated with Truck Operations," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 52(3).
    18. Anne Ventura & Van‐Loc Ta & Tristan Senga Kiessé & Stéphanie Bonnet, 2021. "Design of concrete : Setting a new basis for improving both durability and environmental performance," Journal of Industrial Ecology, Yale University, vol. 25(1), pages 233-247, February.
    19. Boris Rumanko & Zuzana Lušňáková & Monika Moravanská & Mária Šajbidorová, 2021. "Succession as a Risk Process in the Survival of a Family Business—Case of Slovakia," JRFM, MDPI, vol. 14(10), pages 1-20, September.
    20. Kong, Ling & Wang, Dongbo, 2020. "Comparison of citations and attention of cover and non-cover papers," Journal of Informetrics, Elsevier, vol. 14(4).

    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:spr:trosos:v:12:y:2018:i:1:d:10.1007_s12626-018-0019-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.