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Integrating AI-Driven Green Finance Strategies for Sustainable Development: A Comparative Analysis of Renewable Energy Investments in Germany and Denmark

Author

Listed:
  • Sara Ravan Ramzani

    (GISMA University of Applied Sciences, Germany)

  • Peter Konhaeusner

    (GISMA University of Applied Sciences, Germany)

  • Oluwasegun Akinola Olaniregun

    (Arden University, UK)

  • Ahmad Abu-Alkheil

    (GISMA University of Applied Sciences, Germany)

  • Nizar Alsharari

    (Jackson State University, USA)

Abstract

This research explores the convergence of synthetic intelligence (SI) and inexperienced finance techniques in influencing the development of renewable power sectors, with a specific focus on Denmark and Germany for the critical periods of 2019 and 2020. ANOVA, paired sample t-tests, and regression analysis were used as part of a strict method to look into how the production of renewable energy has changed and how AI-driven financial techniques have affected it. The results spotlight the effectiveness of AI-driven green finance solutions in bringing approximately enormous ameliorations, establishing Denmark as a probable exemplar for sustainable progress. In evaluation, Germany’s consistent power infrastructure, blended with a fantastic correlation exposed in regression evaluation, highlights the durability of its environmentally pleasant economic methods. This study presents a well-timed and informative guide for developing effective, inexperienced finance rules that guide a greener and more sustainable future as international locations all around the world address environmental-demanding situations.

Suggested Citation

  • Sara Ravan Ramzani & Peter Konhaeusner & Oluwasegun Akinola Olaniregun & Ahmad Abu-Alkheil & Nizar Alsharari, 2024. "Integrating AI-Driven Green Finance Strategies for Sustainable Development: A Comparative Analysis of Renewable Energy Investments in Germany and Denmark," European Journal of Business and Management Research, European Open Science, vol. 9(2), pages 43-55, March.
    • Handle: RePEc:epw:ejbmr0:v:9:y:2024:i:2:id:52277
    DOI: 10.24018/ejbmr.2024.9.2.2277
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