IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-96-6495-5_4.html
   My bibliography  Save this book chapter

Mapping the Evolution of Artificial Intelligence (AI) in Sustainable Finance: A Bibliometric Analysis

In: Green Horizons

Author

Listed:
  • Gurdas Singh

    (Maharaja Ranjit Singh Punjab Technical University)

  • Poonam Rani

    (Chandigarh University)

  • Mohammed Abul Khair

    (Al-Baha University)

Abstract

The primary objective of the present study is to examine the current academic research on the evolution of sustainable finance and AI in scientific research. The authors have combed through the Scopus database and 1081 papers were extracted from the 2020–2023 year. The authors employed the statistical program R-studio and VOSviewer software for conducting bibliometric analysis using methods such as scientific mapping (co-authorship analysis, co-word analysis, bibliographic coupling) and performance analysis (most influential authors, publications, countries, institutions, and journals). The scientific mapping reveals four niche topics that prior research has focused on such as blockchain as a future of sustainable finance, digital innovation in sustainable entrepreneurship, and blockchain technology in supply chain management. In addition, the findings offer a comprehensive look at the interdisciplinary nature of the subject. Through the presentation of fresh perspectives and important ideas, the authors aimed to enhance the theoretical advancement of artificial intelligence's application in promoting sustainability within the financial sector. Artificial intelligence approaches are gaining popularity as effective alternatives to traditional methods, showing promising results. This article has both theoretical and practical implications, providing researchers with an overview of the theoretical development and intellectual framework for future studies in this field.

Suggested Citation

  • Gurdas Singh & Poonam Rani & Mohammed Abul Khair, 2025. "Mapping the Evolution of Artificial Intelligence (AI) in Sustainable Finance: A Bibliometric Analysis," Springer Books, in: Shakeb Akhtar & Mahfooz Alam & Nassir Ul Haq Wani & Syed Hasan Jafar (ed.), Green Horizons, chapter 0, pages 55-76, Springer.
  • Handle: RePEc:spr:sprchp:978-981-96-6495-5_4
    DOI: 10.1007/978-981-96-6495-5_4
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:sprchp:978-981-96-6495-5_4. 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.