IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v170y2024ics0148296323006860.html
   My bibliography  Save this article

Causal complexity analysis of ESG performance

Author

Listed:
  • Huarng, Kun-Huang
  • Yu, Tiffany Hui-Kuang

Abstract

Environmental, social, and governance (ESG) have merged into an acronym and core value of firms around the world. Based on the resource-based view (RBV), this research analyzes the causal complexity of ESG performance for TSE and OTC firms in Taiwan. The antecedents (or independent variables) related to RBV are chosen to measure the outcome (or dependent variable) of ESG performance. Fuzzy set/Qualitative Comparative Analysis is used as the research method to analyze the causal relationships. The empirical results show that most industries have multiple relationships, where each relationship consists of multiple antecedents. This indicates that various causal relationships can lead to high ESG performance in an industry. Furthermore, though industries are different intrinsically, some industries share the same relationship(s). Each industry has at least one relationship related to RBV. Hence, a firm in an industry can choose its favorable relationship to achieve high ESG performance.

Suggested Citation

  • Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2024. "Causal complexity analysis of ESG performance," Journal of Business Research, Elsevier, vol. 170(C).
  • Handle: RePEc:eee:jbrese:v:170:y:2024:i:c:s0148296323006860
    DOI: 10.1016/j.jbusres.2023.114327
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296323006860
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbusres.2023.114327?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:eee:jbrese:v:170:y:2024:i:c:s0148296323006860. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.