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Integrating Big Data and a Travel Survey to Understand the Gender Gap in Ride-Hailing Usage: Evidence from Chengdu, China

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Intelligence for Future Cities (CUPUM 2023)

Part of the book series: The Urban Book Series ((UBS))

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Abstract

Improving transport systems to increase women's access to social opportunities and essential facilities has been key to reducing gender inequality. Studies have examined the gendered nature of travel from the perspective of a mismatch between women’s needs and availability of transport services, including fragmentized activity space, low affordability, and sensitization to safety. However, minimal attention has been given to the gender gap in the age of ride-hailing. Thus, this paper examines the nexus between gender and ride-hailing usage from the aspect of activity space and affordability. Two key questions are explored: (a) Are women dependent on ride-hailing? (b) If ride-hailing serves women differentially, how does this gender difference in the use of ride-hailing services occur? An innovative integration of big data and a travel survey is developed to examine such questions in Chengdu, China. Survey results and modelling analysis indicate that gender gaps in mobility is relatively mitigated by ride-hailing.

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Notes

  1. 1.

    Telecom agencies could obtain gender and age from the registered ID card information linking to the mobile phone number.

  2. 2.

    To identify whether or not mobile phone users are ride-hailing users, we record the communication data between user phone as data sender and ride-hailing companies as data receiver.

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Acknowledgements

This study received institutional ethics approval from the University of Hong Kong, Reference HREC: EA210312). This work is an extension from “Mind the gender gap in ride-hailing from demand side” (Qiao, Zhang, and Yeh 2023). We would like to thank the financial support from the Dissertation Fellowship of Peking University-Lincoln Institute Center for Urban Development and Land Policy (Grant Number DS04-20211001-QS); Chan To-Haan Endowed Professorship Fund of the University of Hong Kong; Joint Programming Initiative (JPI) Urban Europe and National Natural Foundation of China (NSFC) (Grant Number: 71961137003); and Guangdong–Hong Kong-Macau Joint Laboratory Program of the 2020 Guangdong New Innovative Strategic Research Fund, Guangdong Science and Technology Department (Project No.: 2020B1212030009).

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Authors and Affiliations

  1. Department of Urban Planning and Design, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China

    Si Qiao & Anthony Gar-On Yeh

  2. School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, China

    Mengzhu Zhang

Authors
  1. Si Qiao
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  2. Anthony Gar-On Yeh
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  3. Mengzhu Zhang
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Correspondence to Anthony Gar-On Yeh .

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Editors and Affiliations

  1. Taubman College of Architecture and Urban Planning, University of Michigan, Ann Arbor, MI, USA

    Robert Goodspeed

  2. Department of Geography, McGill University, Montreal, QC, Canada

    Raja Sengupta

  3. Department of Built Environment, Aalto University, Aalto, Finland

    Marketta Kyttä

  4. City Futures Research Centre, University of New South Wales, Sydney, NSW, Australia

    Christopher Pettit

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Qiao, S., Yeh, A.GO., Zhang, M. (2023). Integrating Big Data and a Travel Survey to Understand the Gender Gap in Ride-Hailing Usage: Evidence from Chengdu, China. In: Goodspeed, R., Sengupta, R., Kyttä, M., Pettit, C. (eds) Intelligence for Future Cities. CUPUM 2023. The Urban Book Series. Springer, Cham. https://doi.org/10.1007/978-3-031-31746-0_10

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  • DOI: https://doi.org/10.1007/978-3-031-31746-0_10

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