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    <journal-meta>
      <journal-title-group>
        <journal-title>Journal of Human-Social Nexus</journal-title>
        <abbrev-journal-title>JHSN</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">3136-4519</issn>
      <publisher>
        <publisher-name>ABS Research Academy</publisher-name>
      </publisher>
      <self-uri xlink:href="https://journals.absresearchacademy.com"/>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.64939/jhsn.1.2.0010</article-id>
      
      <notes notes-type="doi">
        <p><ext-link ext-link-type="doi" xlink:href="https://doi.org/10.64939/jhsn.1.2.0010">https://doi.org/10.64939/jhsn.1.2.0010</ext-link></p>
      </notes>
      <title-group>
        <article-title>Artificial Intelligence and Green Total Factor Energy Efficiency: Role of Green Innovation</article-title>
        
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Siddique</surname>
            <given-names>Meherun</given-names>
          </name>
          
          <email>meherunsid@gmail.com</email>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Hossain</surname>
            <given-names>Md. Amzad</given-names>
          </name>
          
          <email>amzad@iiuc.ac.bd</email>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib></contrib-group>
      
      <aff id="aff1"><label>1</label>Department of Economics &amp; Banking, International Islamic University Chittagong, Chittagong, 4318, Bangladesh</aff>
      <pub-date pub-type="ppub"><year>2026</year></pub-date>
      <volume>1</volume>
      <issue>2</issue>
      
      
      
      
      <permissions>
        <copyright-year>2026</copyright-year>
        <copyright-holder>Authors</copyright-holder>
        <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
          <license-p>This article is distributed under the terms of the Creative Commons Attribution License.</license-p>
        </license>
      </permissions>
      <counts>
        <word-count count="0"/>
        <fig-count count="0"/>
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        <page-count count="2"/>
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      <history>
        <date date-type="received"><year>2026</year><month>04</month><day>10</day></date>
        <date date-type="rev-recd"><year>2026</year><month>08</month><day>24</day></date>
        <date date-type="accepted"><year>2026</year><month>08</month><day>26</day></date>
      </history>
      <abstract><p>Achieving high-quality economic growth while reducing energy consumption and emissions has become a pressing global challenge. As a frontier technology of the digital era, artificial intelligence (AI) is increasingly recognized for its potential to transform industrial systems and accelerate the transition toward cleaner energy use. Yet, empirical evidence on whether AI truly enhances green total factor energy efficiency (GTFEE), and under what conditions this effect strengthens, remains limited. This study investigates the effect of artificial intelligence on green total factor energy efficiency in OECD countries from 2005 to 2022 and examines the moderating role of green innovation. We employ Tobit regression and two-stage least squares (2SLS) instrumental variable estimation to address key econometric challenges, including slope homogeneity and endogeneity. The findings reveal that: (1) AI significantly enhances GTFEE; (2) the mechanism analysis indicates that AI improves GTFEE by increasing productive capacity; and (3) green innovation strengthens the impact of AI on GTFEE. The results suggest that governments should promote the adoption of advanced AI technologies and invest in digital infrastructure to support the green transformation of energy systems. Furthermore, policy frameworks that incentivize green innovation can magnify AI&apos;s environmental benefits and help economies achieve sustainable and energy efficient growth.</p></abstract>
      
      <kwd-group><kwd>Green total factor energy efficiency</kwd><kwd>AI</kwd><kwd>green innovation</kwd><kwd>environmental technology</kwd><kwd>productive capacity</kwd></kwd-group>
      <custom-meta-group>
        <custom-meta><meta-name>citation</meta-name><meta-value>Siddique, M., &amp; Hossain, M. A. (2026). Artificial Intelligence and Green Total Factor Energy Efficiency: Role of Green Innovation. Journal of Human-Social Nexus, 1(2). https://doi.org/10.64939/jhsn.1.2.0010</meta-value></custom-meta>
        <custom-meta><meta-name>check-for-updates</meta-name><meta-value>https://doi.org/10.64939/jhsn.1.2.0010</meta-value></custom-meta>
        
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    <notes notes-type="contributor-roles"><title>Author contributions</title><p><named-content content-type="author">Meherun Siddique</named-content>: Conceptualization, Investigation, Software, Writing – review &amp; editing, Formal analysis.</p><p><named-content content-type="author">Md. Amzad Hossain</named-content>: Validation, Supervision, Methodology, Conceptualization, Writing – original draft, Writing – review &amp; editing.</p></notes>
    <ref-list>
      <title>References</title>
    </ref-list>
    <notes notes-type="disclaimer"><p>Disclaimer/Publisher&apos;s Note: All views and opinions expressed in this publication are those of the author(s) and do not necessarily reflect those of the editors or ABS Research Academy. The publisher and editors accept no responsibility for any consequences arising from the use of the information contained herein.</p></notes>
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