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Balanced Scorecard-Based Project Priorities of Sustainable Energy Financing Via Artificial Intelligence-Enhanced Hybrid Quantum Decision-Making Modeling

Author

Listed:
  • Kurbanova Karlygash Abdullayevna

    (Al-Farabi Kazakh National University, Kazakhstan)

  • Nurmagambetova Azhar Zeynullayevna

    (Al-Farabi Kazakh National University, The Republic of Kazakhstan, Almaty)

  • Nurgaliyeva Aliya Miyazhdenovna

    (Narxoz University, The Republic of Kazakhstan, Almaty)

  • Dinçer Hasan

    (School of Business, Istanbul Medipol University, Istanbul, Turkey; Department of Economics and Management, Khazar University, Baku, Azerbaijan)

  • Yüksel Serhat

    (School of Business, Istanbul Medipol University, Istanbul, Turkey; Department of Economics and Management, Khazar University, Baku, Azerbaijan)

  • Sigayev Yerbol Abdrakhmanuly

    (Al-Farabi Kazakh National University, The Republic of Kazakhstan, Almaty)

Abstract

The most essential factors should be defined to increase the effectiveness of sustainable energy financing. Otherwise, businesses may face some financial and operational problems due to not using resources effectively. However, only a limited number of studies in the literature have identified these important factors. This situation shows a need for a new study to determine the variables that have the greatest impact on the effectiveness of sustainable energy financing. Thus, the purpose of this study is to identify significant determinants that affect the effectiveness of sustainable energy financing. For this situation, a 3-stage model is constructed to reach this purpose. The first stage prioritizes the experts with the help of artificial intelligence (AI). The second stage weights the assessment criteria of sustainable energy financing by quantum spherical fuzzy M-SWARA. Finally, the balanced scorecard-based project priorities of sustainable energy financing are ranked with quantum spherical fuzzy WASPAS. The main contribution of this study is that a detailed evaluation is performed to understand significant strategies for the improvements of sustainable energy financing with a novel model. Calculation of the expert weights with AI increases the quality and originality of the model. Similarly, considering M-SWARA, WASPAS, quantum theory, and spherical fuzzy sets also increases the effectiveness of the model because of managing uncertainties more effectively. The technical competence of the enterprise and Funding diversification are found as the most important items in increasing the effectiveness of sustainable energy financing. Additionally, according to the ranking results, it is determined that financial issues and customer needs are the most significant alternatives.

Suggested Citation

  • Kurbanova Karlygash Abdullayevna & Nurmagambetova Azhar Zeynullayevna & Nurgaliyeva Aliya Miyazhdenovna & Dinçer Hasan & Yüksel Serhat & Sigayev Yerbol Abdrakhmanuly, 2025. "Balanced Scorecard-Based Project Priorities of Sustainable Energy Financing Via Artificial Intelligence-Enhanced Hybrid Quantum Decision-Making Modeling," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 35(2), pages 113-139.
    • Handle: RePEc:vrs:suvges:v:35:y:2025:i:2:p:113-139:n:1005
    DOI: 10.2478/sues-2025-0010
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    References listed on IDEAS

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    More about this item

    Keywords

    sustainable energy; energy finance; balanced scorecard; artificial intelligence; fuzzy decision-making;
    All these keywords.

    JEL classification:

    • D25 - Microeconomics - - Production and Organizations - - - Intertemporal Firm Choice: Investment, Capacity, and Financing
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration

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