IDEAS home Printed from https://ideas.repec.org/a/spr/jcsosc/v8y2025i4d10.1007_s42001-025-00416-5.html
   My bibliography  Save this article

Governance, quality of life and city performance: A study based on artificial intelligence

Author

Listed:
  • María J. Pazos-García

    (Universidade de Santiago de Compostela)

  • Vicente López-López

    (Universidade de Santiago de Compostela)

  • Guadalupe Vila-Vázquez

    (Universidade de Santiago de Compostela)

  • Xesús Pablo González

    (Universidade de Santiago de Compostela)

Abstract

The purpose of this study is to analyse the joint influence of several good governance variables (e-government, transparency and reputation) and quality of life (QoL) on the performance of Spanish cities. Using objective data with a time lag, this study employed artificial intelligence (AI) and the Konstanz Information Miner (KNIME) open-source tool platform to test the proposed model. The results of this study indicate that the city’s performance − measured by the employment ratio − is largely explained by good governance resources (e-government, transparency and reputation) and quality of life (QoL). The findings of this study contribute to fill the gap of studies that analyse the effect of city governance resources and QoL on city performance. Furthermore, they support the premises of the resource-based view (RBV) theory employing a novel methodology. The results of the study also provide important clues for city governments that want to improve and/or maintain the performance of their cities.

Suggested Citation

  • María J. Pazos-García & Vicente López-López & Guadalupe Vila-Vázquez & Xesús Pablo González, 2025. "Governance, quality of life and city performance: A study based on artificial intelligence," Journal of Computational Social Science, Springer, vol. 8(4), pages 1-14, November.
    • Handle: RePEc:spr:jcsosc:v:8:y:2025:i:4:d:10.1007_s42001-025-00416-5
    DOI: 10.1007/s42001-025-00416-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s42001-025-00416-5
    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/s42001-025-00416-5?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

    for a different version of it.

    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:spr:jcsosc:v:8:y:2025:i:4:d:10.1007_s42001-025-00416-5. 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.