IDEAS home Printed from https://ideas.repec.org/a/taf/chosxx/v37y2022i8p1497-1518.html
   My bibliography  Save this article

Neighbourhood satisfaction in rural resettlement residential communities: the case of Suqian, China

Author

Listed:
  • Xing Gao
  • Zijia Wang
  • Mengqiu Cao
  • Yuqi Liu
  • Yuerong Zhang
  • Meiling Wu
  • Yue Qiu

Abstract

Against the background of large-scale urbanisation and rural land expropriation, rural resettlement residential housing has been built to accommodate local rural residents in the peripheral areas of China. To explore the context-specific policy implications for improving neighbourhood satisfaction (NS) of residents in rural resettlement residential communities (RRRCs), this paper examines the determinants of NS, and their spatial effects, in rural resettlement residential neighbourhoods using Suqian, in Jiangsu Province, as a case study. This study contributes to the current literature in two ways: it constitutes the first attempt to examine NS among RRRCs; second, our spatial model helps to gain further understanding of horizontal and vertical spatial dependence effects. Our results indicate that income, gender, age, family structure, number of years living in a community, transport and architectural age all have significant effects on NS in RRRCs.

Suggested Citation

  • Xing Gao & Zijia Wang & Mengqiu Cao & Yuqi Liu & Yuerong Zhang & Meiling Wu & Yue Qiu, 2022. "Neighbourhood satisfaction in rural resettlement residential communities: the case of Suqian, China," Housing Studies, Taylor & Francis Journals, vol. 37(8), pages 1497-1518, September.
  • Handle: RePEc:taf:chosxx:v:37:y:2022:i:8:p:1497-1518
    DOI: 10.1080/02673037.2020.1853068
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02673037.2020.1853068
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/02673037.2020.1853068?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guiwen Liu & Jiayue Zhao & Hongjuan Wu & Taozhi Zhuang, 2022. "Spatial Pattern of the Determinants for the Private Housing Rental Prices in Highly Dense Populated Chinese Cities—Case of Chongqing," Land, MDPI, vol. 11(12), pages 1-22, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:chosxx:v:37:y:2022:i:8:p:1497-1518. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/chos20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.