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A metro smart card data-based analysis of group travel behaviour in Shanghai, China

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  • Zhang, Yongping
  • Manley, Ed
  • Martens, Karel
  • Batty, Michael

Abstract

Group travel behaviour widely exists in cities, but has not been well investigated by researchers. To fill this gap, this paper develops a co-existence-based methodological framework to systematically explore the spatiotemporal characteristics of group travel behaviour. We apply our framework to a case study of Shanghai, China, using a one-month tranche of metro smart card data. Results show that most travellers perform a small number of group trips, together with a small number of co-travellers. They usually travel in a dyad or triad group and form far more small social communities than large ones. Group travel behaviour is distinctly different from individual travel in terms of both time and space: group travellers are more likely to travel during weekends, on holidays, and in the afternoons and evenings. They also prefer to perform group behaviour near stations located in the city centre or the centres of new towns in suburban areas, and close to attractions and public facilities. The analysis we present has various potential applications such as improving the management of public events and supporting the design of group ticket policy.

Suggested Citation

  • Zhang, Yongping & Manley, Ed & Martens, Karel & Batty, Michael, 2024. "A metro smart card data-based analysis of group travel behaviour in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 114(C).
  • Handle: RePEc:eee:jotrge:v:114:y:2024:i:c:s0966692323002363
    DOI: 10.1016/j.jtrangeo.2023.103764
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    References listed on IDEAS

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    1. Changjoo Kim & Olivier Parent & Rainer vom Hofe, 2018. "The role of peer effects and the built environment on individual travel behavior," Environment and Planning B, , vol. 45(3), pages 452-469, May.
    2. Lin, Tao & Wang, Donggen, 2014. "Social networks and joint/solo activity–travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 68(C), pages 18-31.
    3. Maximiliano Lizana & Juan-Antonio Carrasco & Alejandro Tudela, 2020. "Studying the relationship between activity participation, social networks, expenditures and travel behavior on leisure activities," Transportation, Springer, vol. 47(4), pages 1765-1786, August.
    4. Yang Zhang & Yongping Zhang & Jiangping Zhou, 2021. "A novel excess commuting framework: Considering commuting efficiency and equity simultaneously," Environment and Planning B, , vol. 48(1), pages 151-168, January.
    5. Sivaramakrishnan Srinivasan & Chandra Bhat, 2008. "An exploratory analysis of joint-activity participation characteristics using the American time use survey," Transportation, Springer, vol. 35(3), pages 301-327, May.
    6. Xiao Fu & William H. K. Lam, 2018. "Modelling joint activity-travel pattern scheduling problem in multi-modal transit networks," Transportation, Springer, vol. 45(1), pages 23-49, January.
    7. Frank Goetzke & Regine Gerike & Antonio Páez & Elenna Dugundji, 2015. "Social interactions in transportation: analyzing groups and spatial networks," Transportation, Springer, vol. 42(5), pages 723-731, September.
    8. Zhu, Kangli & Yin, Haodong & Qu, YunChao & Wu, Jianjun, 2021. "Group travel behavior in metro system and its relationship with house price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    9. Sui Tao & Sylvia Y. He, 2021. "Job accessibility and joint household travel: a study of Hong Kong with a particular focus on new town residents," Transportation, Springer, vol. 48(3), pages 1379-1407, June.
    10. Federico Librino & M. Elena Renda & Paolo Santi & Francesca Martelli & Giovanni Resta & Fabio Duarte & Carlo Ratti & Jinhua Zhao, 2020. "Home-work carpooling for social mixing," Transportation, Springer, vol. 47(5), pages 2671-2701, October.
    11. Fu, Xiao & Zuo, Yufan & Zhang, Shanqi & Liu, Zhiyuan, 2022. "Measuring joint space-time accessibility in transit network under travel time uncertainty," Transport Policy, Elsevier, vol. 116(C), pages 355-368.
    12. Ed Manley & Chen Zhong & Michael Batty, 2018. "Spatiotemporal variation in travel regularity through transit user profiling," Transportation, Springer, vol. 45(3), pages 703-732, May.
    13. Michael Batty & Robin Morphet & Paolo Masucci & Kiril Stanilov, 2014. "Entropy, complexity, and spatial information," Journal of Geographical Systems, Springer, vol. 16(4), pages 363-385, October.
    14. Wang, Yaoli & Kutadinata, Ronny & Winter, Stephan, 2019. "The evolutionary interaction between taxi-sharing behaviours and social networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 170-180.
    15. Christian Martin Mützel & Joachim Scheiner, 2022. "Investigating spatio-temporal mobility patterns and changes in metro usage under the impact of COVID-19 using Taipei Metro smart card data," Public Transport, Springer, vol. 14(2), pages 343-366, June.
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