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Do Artificial Intelligence (AI) and Finance Matter for Renewable Energy Development? Fresh Evidence From Waste-Recycled Economies

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F25%3A105986" target="_blank" >RIV/60460709:41110/25:105986 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1002/ese3.70323" target="_blank" >https://doi.org/10.1002/ese3.70323</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/ese3.70323" target="_blank" >10.1002/ese3.70323</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Do Artificial Intelligence (AI) and Finance Matter for Renewable Energy Development? Fresh Evidence From Waste-Recycled Economies

  • Original language description

    Over the last few decades, the Globe has become an eyewitness to a blend of socioeconomic and environmental issues. Interestingly, the globe has performed well in adopting green initiatives, compelling nations to strive for social, economic, and environmental sustainability. Recently, economies have primarily focused on developing renewable energy plans to promote affordable energy under the framework of SDG 7. However, most policymakers are unaware of the critical issues and their best alternative in renewable energy development (RED) plans. For the first time, this study introduces the essential factors of RED that may contribute to improving the actual situation of renewable energy development. In terms of these factors, this study encompasses public-private partnerships (PPPs), the circular economy, artificial intelligence, financial activities, income, and skilled labor for nine waste-recycled economies over the period from 2000 to 2022. However, this study utilizes the most robust estimators to obtain valuable outcomes. The investigated outcomes demonstrate a positive relationship between financial development and income, as measured by RED. Surprisingly, artificial intelligence significantly contributes to RED by 7.875%. On the other hand, public-private partnerships and the circular economy exhibit an inverse connection with RED, which is unusual for selected nations. Similarly, the impact of skilled labor remains insignificant for the selected countries. Overall, the financial development performance is considerable, as it supports all sectors of the economy through its financial services. Thus, this study uses financial depth, efficiency, and stability as additional RED determinants. Outcomes describe the significant contribution of financial stability in the RED. In addition, the present research examines the moderate effect of the FD on the circular economy, public-private partnerships, and artificial intelligence. This study makes a significant contribution only in the case of the circular economy. Ultimately, this study suggests green implications for strengthening sustainable renewable energy development.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    50202 - Applied Economics, Econometrics

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    ENERGY SCIENCE & ENGINEERING

  • ISSN

    2050-0505

  • e-ISSN

    2050-0505

  • Volume of the periodical

    13

  • Issue of the periodical within the volume

    12

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    21

  • Pages from-to

    6362-6382

  • UT code for WoS article

    001598234800001

  • EID of the result in the Scopus database

    2-s2.0-105019561492