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Do Neighborhoods with Highly Diverse Built Environment Exhibit Different Socio-Economic Profiles as Well? Evidence from Shanghai

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  • George Grekousis

    (School of Geography and Planning, Department of Urban and Regional Planning, Sun Yat-sen University, Guangzhou 510275, China
    Guangdong Key Laboratory for Urbanization and Geo-Simulation, Sun Yat-sen University, Guangzhou 510275, China)

  • Zhuolin Pan

    (School of Geography and Planning, Department of Urban and Regional Planning, Sun Yat-sen University, Guangzhou 510275, China
    Guangdong Key Laboratory for Urbanization and Geo-Simulation, Sun Yat-sen University, Guangzhou 510275, China)

  • Ye Liu

    (School of Geography and Planning, Department of Urban and Regional Planning, Sun Yat-sen University, Guangzhou 510275, China
    Guangdong Key Laboratory for Urbanization and Geo-Simulation, Sun Yat-sen University, Guangzhou 510275, China)

Abstract

The link between the built environment and residential segregation has long been of interest to the discussion for sustainable and socially resilient cities. However, direct assessments on how extensively diverse built environments affect the social landscapes of cities at the neighborhood level are rare. Here, we investigate whether neighborhoods with a diverse built environment also exhibit different socio-economic profiles. Through a geodemographic approach, we scrutinize the socio-economic composition of Shanghai’s neighborhoods. We statistically compare the top 10% (very high values) to the bottom 10% (very low values) of the following built environment variables: density, land use mix, land use balance, and greenness. We show that high-density areas have three times the percentage of divorced residents than low-density areas. Neighborhoods with a high level of greenness have median values of 30% more residents aged between 25–44 years old and five times the percentage of houses between 60 to 119 m 2 than low-greenness areas. In high land-use mix areas, the share of people that live on a pension is 30% more than the low land-use mix areas. The findings of this study can be used to improve the designs of modern, sustainable cities at the neighborhood level, significantly improving quality of life.

Suggested Citation

  • George Grekousis & Zhuolin Pan & Ye Liu, 2021. "Do Neighborhoods with Highly Diverse Built Environment Exhibit Different Socio-Economic Profiles as Well? Evidence from Shanghai," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7544-:d:589365
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    References listed on IDEAS

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    1. Tian, Li & Liang, Yinlong & Zhang, Bo, 2017. "Measuring residential and industrial land use mix in the peri-urban areas of China," Land Use Policy, Elsevier, vol. 69(C), pages 427-438.
    2. Manaugh, Kevin & Kreider, Tyler, 2013. "What is mixed use? Presenting an interaction method for measuring land use mix," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 6(1), pages 63-72.
    3. Pu Hao & Stan Geertman & Pieter Hooimeijer & Richard Sliuzas, 2013. "Spatial Analyses of the Urban Village Development Process in Shenzhen, China," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 37(6), pages 2177-2197, November.
    4. Fulong Wu, 2002. "Sociospatial Differentiation in Urban China: Evidence from Shanghai's Real Estate Markets," Environment and Planning A, , vol. 34(9), pages 1591-1615, September.
    5. Li, Han & Wei, Yehua Dennis & Wu, Yangyi, 2019. "Analyzing the private rental housing market in Shanghai with open data," Land Use Policy, Elsevier, vol. 85(C), pages 271-284.
    6. George Grekousis, 2018. "Further Widening or Bridging the Gap? A Cross-Regional Study of Unemployment across the EU Amid Economic Crisis," Sustainability, MDPI, vol. 10(6), pages 1-18, May.
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