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Relationship between Urban Floating Population Distribution and Livability Environment: Evidence from Guangzhou’s Urban District, China

Author

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  • Yang Wang

    (Faculty of Geography, Yunnan Normal University, Kunming 650500, China)

  • Xiaoli Yue

    (School of Architecture and Urban Planning, Guangdong University of Technology, Guangzhou 510090, China
    Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China)

  • Hong’ou Zhang

    (Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China)

  • Yongxian Su

    (Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China)

  • Jing Qin

    (School of Tourism Sciences, Beijing International Studies University, Beijing 100024, China
    Research Center of Beijing Tourism Development, Beijing 100024, China)

Abstract

The livability environment is an important aspect of urban sustainable development. The floating population refers to people without local hukou (also called ‘non- hukou migrants’). The floating population distribution is influenced by livability environment, but few studies have investigated this relationship. Especially, the influence of social environment on floating population distribution is rarely studied. Therefore, we study 1054 communities in Guangzhou’s urban district to explore the relationship between livability environment and floating population distribution. The purpose of this article is to study how livability environment affects floating population distribution. We develop a conceptual framework of livability environment, which consists of physical environment, social environment and life convenience. A cross-sectional dataset of the impact of livability environment on the floating population distribution is developed covering the proportion of floating population in the community as the dependent variable, eight factors of livability environment as the explanatory variables, and two factors of architectural characteristics and one factor of location characteristics as the control variables. We use spatial regression models to explore the degree of influence and direction of physical environment, social environment and life convenience on the floating population distribution in livability environment. The results show that the spatial error model is more effective than ordinary least squares and spatial lag model models. The five factors of the livability environment have statistical significance regarding floating population distribution, including four social environment factors (proportion of middle- and high-class occupation population, proportion of highly educated people in the population, proportion of rental households, and unemployment rate) and regarding life convenience factors (work and shopping convenience). The conclusion has value for understanding how the social environment affects the residential choice of the floating population. This study will help city administrators reasonably guide the residential pattern of the floating population and formulate reasonable management policies, thereby improving the city’s livability, attractiveness and sustainable development.

Suggested Citation

  • Yang Wang & Xiaoli Yue & Hong’ou Zhang & Yongxian Su & Jing Qin, 2021. "Relationship between Urban Floating Population Distribution and Livability Environment: Evidence from Guangzhou’s Urban District, China," Sustainability, MDPI, vol. 13(23), pages 1-15, December.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13477-:d:695928
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    as
    1. Raphael, Steven & Winter-Ember, Rudolf, 2001. "Identifying the Effect of Unemployment on Crime," Journal of Law and Economics, University of Chicago Press, vol. 44(1), pages 259-283, April.
    2. Vega, Amaya & Reynolds-Feighan, Aisling, 2009. "A methodological framework for the study of residential location and travel-to-work mode choice under central and suburban employment destination patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 401-419, May.
    3. Silvia Banfi & Massimo Filippini & Andrea Horehájová, 2008. "Valuation of Environmental Goods in Profit and Non-Profit Housing Sectors: Evidence from the Rental Market in the City of Zurich," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(IV), pages 631-654, December.
    4. Goodman, Allen C. & Thibodeau, Thomas G., 2003. "Housing market segmentation and hedonic prediction accuracy," Journal of Housing Economics, Elsevier, vol. 12(3), pages 181-201, September.
    5. Bhat, Chandra R. & Guo, Jessica Y., 2007. "A comprehensive analysis of built environment characteristics on household residential choice and auto ownership levels," Transportation Research Part B: Methodological, Elsevier, vol. 41(5), pages 506-526, June.
    6. Arthur C. Nelson & John Genereux & Michelle Genereux, 1992. "Price Effects of Landfills on House Values," Land Economics, University of Wisconsin Press, vol. 68(4), pages 359-365.
    7. Stevenson, Simon, 2004. "New empirical evidence on heteroscedasticity in hedonic housing models," Journal of Housing Economics, Elsevier, vol. 13(2), pages 136-153, June.
    8. David M. Brasington & Diane Hite, 2005. "Demand for Environmental Quality: A Spatial Hedonic Approach," Departmental Working Papers 2005-08, Department of Economics, Louisiana State University.
    9. Li, Shaoying & Lyu, Dijiang & Huang, Guanping & Zhang, Xiaohu & Gao, Feng & Chen, Yuting & Liu, Xiaoping, 2020. "Spatially varying impacts of built environment factors on rail transit ridership at station level: A case study in Guangzhou, China," Journal of Transport Geography, Elsevier, vol. 82(C).
    10. Cho, Eun Joo & Rodriguez, Daniel & Song, Yan, 2008. "The Role of Employment Subcenters in Residential Location Decisions," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 1(2), pages 121-151.
    11. Yang Wang & Kangmin Wu & Jing Qin & Changjian Wang & Hong’ou Zhang, 2020. "Examining Spatial Heterogeneity Effects of Landscape and Environment on the Residential Location Choice of the Highly Educated Population in Guangzhou, China," Sustainability, MDPI, vol. 12(9), pages 1-20, May.
    12. Mi Diao & Yu Qin & Tien Foo Sing, 2016. "Negative Externalities of Rail Noise and Housing Values: Evidence from the Cessation of Railway Operations in Singapore," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 44(4), pages 878-917, October.
    13. Brasington, David M. & Hite, Diane, 2005. "Demand for environmental quality: a spatial hedonic analysis," Regional Science and Urban Economics, Elsevier, vol. 35(1), pages 57-82, January.
    14. Ettema, Dick & Nieuwenhuis, Roy, 2017. "Residential self-selection and travel behaviour: What are the effects of attitudes, reasons for location choice and the built environment?," Journal of Transport Geography, Elsevier, vol. 59(C), pages 146-155.
    15. Nicole Gurran & Peter Phibbs, 2017. "When Tourists Move In: How Should Urban Planners Respond to Airbnb?," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(1), pages 80-92, January.
    16. Humphreys, John & Ahern, Aoife, 2019. "Is travel based residential self-selection a significant influence in modal choice and household location decisions?," Transport Policy, Elsevier, vol. 75(C), pages 150-160.
    17. Kim, Hyun No & Boxall, Peter C. & Adamowicz, W.L.(Vic), 2019. "Analysis of the economic impact of water management policy on residential prices: Modifying choice set formation in a discrete house choice analysis," Journal of choice modelling, Elsevier, vol. 33(C).
    18. Cassel, Eric & Mendelsohn, Robert, 1985. "The choice of functional forms for hedonic price equations: Comment," Journal of Urban Economics, Elsevier, vol. 18(2), pages 135-142, September.
    19. Schirmer, Patrick & van Eggermond, Michael & Axhausen, Kay, 2014. "The role of location in residential location choice models: a review of literature," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 7(2), pages 3-21.
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