IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i15p7051-d1716905.html
   My bibliography  Save this article

Drivers of Population Dynamics in High-Altitude Counties of Sichuan Province, China

Author

Listed:
  • Xiangyu Dong

    (Graduate School of Human-Environment Studies, Kyushu University, Fukuoka 819-0395, Japan)

  • Mengge Du

    (College of Architecture, Tianjin University, Tianjin 300072, China)

  • Shichen Zhao

    (Faculty of Human Environment Studies, Kyushu University, 744 Motooka Nishi-ku, Fukuoka 819-0395, Japan)

Abstract

The population dynamics of high-altitude mountainous areas are shaped by a complex interplay of socioeconomic and environmental drivers. Despite their significance, such regions have received limited scholarly attention. This research identifies and examines the principal determinants of population changes in the high-altitude mountainous zones of Sichuan Province, China. Utilizing a robust quantitative framework, we introduce the Sustainable Population Migration Index (SPMI) to systematically analyze the migration potential over two decades. The findings indicate healthcare accessibility as the most significant determinant influencing resident and rural population changes, while economic factors notably impact urban populations. The SPMI reveals a pronounced deterioration in migration attractiveness, decreasing by 0.27 units on average from 2010 to 2020. Furthermore, a fixed-effects panel regression confirmed the predictive capability of SPMI regarding population trends, emphasizing its value for demographic forecasting. We also develop a Digital Twin-based Simulation and Decision-support Platform (DTSDP) to visualize policy impacts effectively. Scenario simulations suggest that targeted enhancements in healthcare and infrastructure could significantly alleviate demographic pressures. This research contributes critical insights for sustainable regional development strategies and provides an effective tool for informed policymaking.

Suggested Citation

  • Xiangyu Dong & Mengge Du & Shichen Zhao, 2025. "Drivers of Population Dynamics in High-Altitude Counties of Sichuan Province, China," Sustainability, MDPI, vol. 17(15), pages 1-25, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:15:p:7051-:d:1716905
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/15/7051/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/15/7051/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:gam:jsusta:v:17:y:2025:i:15:p:7051-:d:1716905. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.