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Understanding the Dynamics of the Pick-Up and Drop-Off Locations of Taxicabs in the Context of a Subsidy War among E-Hailing Apps

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  • Rongxiang Su

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Luoyu Road 129, Wuhan 430079, China)

  • Zhixiang Fang

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Luoyu Road 129, Wuhan 430079, China
    Collaborative Innovation Center of Geospatial Technology, 129 Luoyu Road, Wuhan 430079, China)

  • Ningxin Luo

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Luoyu Road 129, Wuhan 430079, China)

  • Jingwei Zhu

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Luoyu Road 129, Wuhan 430079, China)

Abstract

The locations where taxicabs pick up and drop off passengers are crucial to understanding the dynamics of taxi trip demand. Investigating their spatial distribution and derived dynamic features is still a key task in the fields of urban geography and transportation. Such investigations are urgently needed, considering the competition created by new communication technology services, specifically e-hailing apps such as Uber, Didi and Kuaidi. For example, a subsidy war between two e-hailing apps occurred in China in 2014. However, how the pick-up and drop-off locations of taxicabs change during subsidy wars is still an open question. This paper introduces a methodological framework that can be used to derive the pick-up and drop-off dynamics of taxicabs. It also proposes three indexes that can be used to assess the dynamics of the pick-up and drop-off locations at the city and sub-district scales, namely the numbers of daily pick ups and drop offs per taxi, average transfer distance per unit area of weighted mean centers of pick-up and drop-off locations, and degree of dispersion in the spatial distribution of pick-up and drop-off locations. This paper employs data from taxicabs in the city of Shenzhen to uncover the dynamics of their pick-up and drop-off locations. The results show that the methodological framework and the indexes introduced are powerful tools for uncovering the dynamics of the pick-up and drop-off locations of taxicabs in urban environments.

Suggested Citation

  • Rongxiang Su & Zhixiang Fang & Ningxin Luo & Jingwei Zhu, 2018. "Understanding the Dynamics of the Pick-Up and Drop-Off Locations of Taxicabs in the Context of a Subsidy War among E-Hailing Apps," Sustainability, MDPI, vol. 10(4), pages 1-24, April.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:1256-:d:142083
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    References listed on IDEAS

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    Cited by:

    1. Ting Wang & Yong Zhang & Meiye Li & Lei Liu, 2019. "How Do Passengers with Different Using Frequencies Choose between Traditional Taxi Service and Online Car-Hailing Service? A Case Study of Nanjing, China," Sustainability, MDPI, vol. 11(23), pages 1-18, November.
    2. 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.
    3. Shuxin Jin & Juan Su & Zhouhao Wu & Di Wang & Ming Cai, 2022. "What Makes a Good Cabman? Behavioral Patterns Correlated with High-Earning and Low-Earning Taxi Driving," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
    4. 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.

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