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Time Allocation and the Activity-Space-Based Segregation of Different Income Groups: A Case Study of Nanjing

Author

Listed:
  • Hui Wang

    (College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China)

  • Mei-Po Kwan

    (Department of Geography and Resource Management, Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, Hong Kong, China)

  • Mingxing Hu

    (School of Architecture, Si Pailou Campus, Southeast University, Nanjing 210096, China)

  • Junheng Qi

    (School of Architecture, Si Pailou Campus, Southeast University, Nanjing 210096, China)

  • Jiemin Zheng

    (School of Architecture, Si Pailou Campus, Southeast University, Nanjing 210096, China)

  • Bin Han

    (School of Architecture, Si Pailou Campus, Southeast University, Nanjing 210096, China)

Abstract

Time allocation is closely related to life quality and is a potential indicator of urban space utilization and sociospatial differentiation. However, existing time allocation studies focus on how time is allocated to various activities but pay less attention to where individuals allocate their time. In the context of China’s transformation, this study examines the differences in time allocation in different urban spaces between low- and non-low-income groups based on two methods, descriptive statistics and social area analysis. The results show that low-income participants’ daily activities (especially work) are highly dependent on the central city area. However, they are at a disadvantage in accessing the central city area. Nevertheless, non-low-income individuals have diversified activity spaces and can better choose locations according to the purpose of activities and make fuller use of various types of urban areas. This study indicates that there are social differences in time allocation and urban space utilization among different income groups. The results obtained with regression models reveal that in addition to income, activity characteristics and built environment characteristics are significant factors affecting the differences. Social policies should support the equitable distribution of urban resources for different social groups, especially for vulnerable groups who live in affordable housing.

Suggested Citation

  • Hui Wang & Mei-Po Kwan & Mingxing Hu & Junheng Qi & Jiemin Zheng & Bin Han, 2022. "Time Allocation and the Activity-Space-Based Segregation of Different Income Groups: A Case Study of Nanjing," Land, MDPI, vol. 11(10), pages 1-17, October.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:10:p:1717-:d:933234
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    References listed on IDEAS

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    1. Hui Wang & Mei‐Po Kwan & Mingxing Hu, 2020. "Usage of Urban Space and Sociospatial Differentiation of Income Groups: A Case Study of Nanjing, China," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 111(4), pages 616-633, September.
    2. Wang, Donggen & Cao, Xinyu, 2017. "Impacts of the built environment on activity-travel behavior: Are there differences between public and private housing residents in Hong Kong?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 25-35.
    3. Nie, Peng & Sousa-Poza, Alfonso, 2018. "Commute time and subjective well-being in urban China," China Economic Review, Elsevier, vol. 48(C), pages 188-204.
    4. Junghwan Kim & Mei-Po Kwan, 2018. "Beyond Commuting: Ignoring Individuals’ Activity-Travel Patterns May Lead to Inaccurate Assessments of Their Exposure to Traffic Congestion," IJERPH, MDPI, vol. 16(1), pages 1-20, December.
    5. David Wong & Shih-Lung Shaw, 2011. "Measuring segregation: an activity space approach," Journal of Geographical Systems, Springer, vol. 13(2), pages 127-145, June.
    6. Chandra Bhat & Rajul Misra, 1999. "Discretionary activity time allocation of individuals between in-home and out-of-home and between weekdays and weekends," Transportation, Springer, vol. 26(2), pages 193-229, May.
    7. David Levinson & Ajay Kumar, 1995. "Activity, Travel, and the Allocation of Time," Working Papers 199505, University of Minnesota: Nexus Research Group.
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    Cited by:

    1. Xue Zhang & Yifan Tang & Yanwei Chai, 2023. "Spatiotemporal-Behavior-Based Microsegregation and Differentiated Community Ties of Residents with Different Types of Housing in Mixed-Housing Neighborhoods: A Case Study of Fuzhou, China," Land, MDPI, vol. 12(9), pages 1-23, August.

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