Understanding taxi ridership with spatial spillover effects and temporal dynamics

Zhu, P., Huang, J., Wang, J., Liu, Y., Li, J., Wang, M. and Qiang, W. (2022) Understanding taxi ridership with spatial spillover effects and temporal dynamics. Cities, 125, 103637. (doi: 10.1016/j.cities.2022.103637)

[img] Text
265604.pdf - Accepted Version
Restricted to Repository staff only until 16 August 2023.
Available under License Creative Commons Attribution Non-commercial No Derivatives.



In urban transportation systems, taxis are regarded as flexible, convenient, and time-saving. Taxi demand is affected by various built-environment factors and by the time of the day. Although many studies have investigated correlations between taxi demand and the built environment, the direct and spillover effects of built environment factors on taxi demand have not been examined at a fine spatial scale. To address this gap in the literature, this paper employs spatial econometric models using GPS-tracked taxi trips, mobile signaling data, and points of interest (POIs) to study taxi demand in Beijing at a 1-kilometer square grid resolution. The results show that, in the morning and evening peak hours, road network density has the strongest (positive) direct and indirect impact on taxi ridership. A relationship is also found between public transportation and taxi ridership: bus coverage has positive direct effects and insignificant indirect effects on taxi pick-ups and drop-offs, while subway coverage has negative indirect effects, suggesting that it may absorb taxi demand from surrounding grids. Results also indicate that various built-environment factors affect taxi demand differently at morning and evening peak times. This study reveals the complex nature of taxi ridership and has important implications for policymakers, transport planners, and other stakeholders in megacities around the world.

Item Type:Articles
Additional Information:This research was financially supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA19040402), Youth Innovation Promotion Association of Chinese Academy of Sciences (Grant No. 2021049), National Natural Science Foundation of China (Grant No. 71573232), Natural Science Foundation of Guangdong Province (Grant Number: 2021A1515011250), Guangzhou Basic Research Scheme, and 2019 Open Fund of the Key Laboratory of Regional Sustainable Development Modeling, Chinese Academy of Sciences (Grant No. KF2018-09).
Glasgow Author(s) Enlighten ID:Wang, Dr Mingshu
Creator Roles:
Wang, M.Visualization, Writing – review and editing
Authors: Zhu, P., Huang, J., Wang, J., Liu, Y., Li, J., Wang, M., and Qiang, W.
College/School:College of Science and Engineering > School of Geographical and Earth Sciences
Journal Name:Cities
ISSN (Online):1873-6084
Published Online:16 February 2022
Copyright Holders:Copyright © 2022 Elsevier Ltd.
First Published:First published in Cities 125: 103637
Publisher Policy:Reproduced in accordance with the publisher copyright policy

University Staff: Request a correction | Enlighten Editors: Update this record