IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v120y2024i5d10.1007_s11069-023-06392-1.html
   My bibliography  Save this article

Exploring key social capital indicators for disaster preparedness in rural disaster-prone areas: a boosted regression tree approach

Author

Listed:
  • Jing Tan

    (Chongqing University
    Chongqing University)

  • Lei Lin

    (Southwest University of Political Science and Law)

Abstract

Social capital provides a valuable theoretical framework for boosting disaster preparedness. However, the multidimensional and intricate nature of social capital poses challenges in its measurement. Achieving a balance between comprehensive and effective measurement of social capital indicators necessitates additional exploration, especially within the specific context of disasters. The current study utilizes the boosted regression tree (BRT) approach to identify key social capital indicators that influence disaster preparedness in rural disaster-prone areas of China. BRT is highly regarded for its ability to capture complex nonlinear relationships and interactions among variables, providing accurate predictions and facilitating interpretability for practical applications. Results reveal that geographic close social ties, social status, collective resources, non-farm employment assistance, gift exchange, interpersonal trust, and sense of belonging significantly impact disaster preparedness. The findings could offer valuable guidance to policymakers in designing targeted intervention strategies aimed at enhancing disaster resilience within these communities.

Suggested Citation

  • Jing Tan & Lei Lin, 2024. "Exploring key social capital indicators for disaster preparedness in rural disaster-prone areas: a boosted regression tree approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(5), pages 4159-4180, March.
    • Handle: RePEc:spr:nathaz:v:120:y:2024:i:5:d:10.1007_s11069-023-06392-1
    DOI: 10.1007/s11069-023-06392-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-023-06392-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-023-06392-1?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.

    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:spr:nathaz:v:120:y:2024:i:5:d:10.1007_s11069-023-06392-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.