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Job-worker spatial dynamics in Beijing: Insights from Smart Card Data

Author

Listed:
  • Jie Huang
  • David Levinson

    (TransportLab, School of Civil Engineering, University of Sydney)

  • Jiaoe Wang
  • Haitao Jin

Abstract

As a megacity, Beijing has experienced traffic congestion, unaffordable housing issues and jobs-housing imbalance. Recent decades have seen policies and projects aiming at decentralizing urban structure and job-worker patterns, such as subway network expansion, the suburbanization of housing and firms. But it is unclear whether these changes produced a more balanced spatial configuration of jobs and workers. To answer this question, this paper evaluated the ratio of jobs to workers from Smart Card Data at the transit station level and offered a longitudinal study for regular transit commuters. The method identifies the most preferred station around each commuter's workpalce and home location from individual smart datasets according to their travel regularity, then the amounts of jobs and workers around each station are estimated. A year-to-year evolution of job to worker ratios at the station level is conducted. We classify general cases of steepening and flattening job-worker dynamics, and they can be used in the study of other cities. The paper finds that (1) only temporary balance appears around a few stations; (2) job-worker ratios tend to be steepening rather than flattening, influencing commute patterns; (3) the polycentric configuration of Beijing can be seen from the spatial pattern of job centers identified.

Suggested Citation

  • Jie Huang & David Levinson & Jiaoe Wang & Haitao Jin, 2019. "Job-worker spatial dynamics in Beijing: Insights from Smart Card Data," Working Papers 2019-01, University of Minnesota: Nexus Research Group.
  • Handle: RePEc:nex:wpaper:beijingsmartcard
    DOI: 10.1016/j.cities.2018.11.021
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    File URL: http://hdl.handle.net/2123/21180
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    References listed on IDEAS

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    Cited by:

    1. Xia Zhao & Mengying Cui & David Levinson, 2023. "Exploring temporal variability in travel patterns on public transit using big smart card data," Environment and Planning B, , vol. 50(1), pages 198-217, January.
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    3. Chen, Wendong & Chen, Xuewu & Cheng, Long & Liu, Xize & Chen, Jingxu, 2022. "Delineating borders of urban activity zones with free-floating bike sharing spatial interaction network," Journal of Transport Geography, Elsevier, vol. 104(C).
    4. Dawei Mei & Chunliang Xiu & Xinghua Feng & Ye Wei, 2019. "Study of the School–Residence Spatial Relationship and the Characteristics of Travel-to-School Distance in Shenyang," Sustainability, MDPI, vol. 11(16), pages 1-15, August.
    5. Rong, Peijun & Kwan, Mei-Po & Qin, Yaochen & Zheng, Zhicheng, 2022. "A review of research on low-carbon school trips and their implications for human-environment relationship," Journal of Transport Geography, Elsevier, vol. 99(C).
    6. Lu Yu & Tao Yu & Yongxiang Wu & Guangdong Wu, 2020. "Rethinking the Identification of Urban Centers from the Perspective of Function Distribution: A Framework Based on Point-of-Interest Data," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    7. Huikun Hong & Ting Liu & Heping Liao & Zhicong Cai & Gang Wang, 2022. "Analysis of the Housing–Jobs Separation Characteristics of Different Village Types in the Mountainous and Hilly Region of Southwest China," Land, MDPI, vol. 11(11), pages 1-18, November.
    8. Zuo, Yufan & Fu, Xiao & Liu, Zhiyuan & Huang, Di, 2021. "Short-term forecasts on individual accessibility in bus system based on neural network model," Journal of Transport Geography, Elsevier, vol. 93(C).
    9. Shenzhen Tian & Xueming Li & Jun Yang & Hui Wang & Jianke Guo, 2023. "Spatiotemporal evolution of pseudo human settlements: case study of 36 cities in the three provinces of Northeast China from 2011 to 2018," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1742-1772, February.
    10. Jiaoe Wang & Yanan Li & Jingjuan Jiao & Haitao Jin & Fangye Du, 2023. "Bus ridership and its determinants in Beijing: A spatial econometric perspective," Transportation, Springer, vol. 50(2), pages 383-406, April.
    11. Fangye Du & Jiaoe Wang & Yu Liu & Zihao Zhou & Haitao Jin, 2022. "Equity in Health-Seeking Behavior of Groups Using Different Transportations," IJERPH, MDPI, vol. 19(5), pages 1-16, February.

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    More about this item

    Keywords

    Jobs-housing balance; Smart Card Data; Spatial dynamics; Longitudinal analysis; Urban subway network;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns

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