<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Journal of Resource Management and Decision Engineering</JournalTitle>
      <Issn></Issn>
      <Volume></Volume>
      <Issue>In Press</Issue>
      <PubDate PubStatus="epublish">
        <Year>2027</Year>
        <Month>05</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Presenting a Green Government Model for Renewable Energy Development in Iran’s Electricity Industry</ArticleTitle>
    <VernacularTitle>Presenting a Green Government Model for Renewable Energy Development in Iran’s Electricity Industry</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>20</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2026</Year>
        <Month>04</Month>
        <Day>22</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;The development of renewable energy in Iran’s electricity industry faces numerous structural, institutional, and policy-related barriers, among which the absence of a coherent and domestically adapted governance framework is one of the most significant. The present study aimed to design and validate a green government model for renewable energy development in Iran’s electricity industry. The study employed an exploratory sequential mixed-methods approach grounded in the pragmatist paradigm. In the qualitative phase, an interpretive approach and Braun and Clarke’s thematic analysis method were applied. Data were collected through semi-structured interviews with 20 experts, and sampling continued until theoretical saturation was achieved. In the quantitative phase, based on statistical power calculations conducted using G*Power, a sample of 188 experts and managers from the electricity industry was selected. The data were analyzed through variance-based structural equation modeling using SPSS version 24 and SmartPLS version 3. The findings of the qualitative phase resulted in the extraction of 102 basic themes, categorized into 33 organizing themes and 11 global constructs: green institutional capacity, green energy policymaking, green financing, green economic support, green diplomacy, green energy infrastructure, green technological innovation, green human capital, green social participation, environmental sustainability, and energy security. In the quantitative validation phase, the measurement and structural model fit indices were found to be satisfactory, and all 26 relationships in the model were confirmed with statistically significant path coefficients (p &amp;lt; .001). The strongest causal relationship was observed between green energy policymaking and green financing (β = .836).&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">green government</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">renewable energy</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">thematic analysis</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">structural equation modeling</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://journalrmde.com/index.php/jrmde/article/download/399/367</ArchiveCopySource>
  </Article>
</ArticleSet>
