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<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Future of Work and Digital Management Journal</JournalTitle>
      <Issn></Issn>
      <Volume>2</Volume>
      <Issue>Serial Number 5</Issue>
      <PubDate PubStatus="epublish">
        <Year>2024</Year>
        <Month>09</Month>
        <Day>25</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Dynamic Modeling of the Reverse Logistics Supply Chain for Gas Refining Industry Waste Management</ArticleTitle>
    <VernacularTitle>Dynamic Modeling of the Reverse Logistics Supply Chain for Gas Refining Industry Waste Management</VernacularTitle>
    <FirstPage>34</FirstPage>
    <LastPage>53</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>2024</Year>
        <Month>05</Month>
        <Day>20</Day>
      </PubDate>
    </History>
    <Abstract>&lt;table&gt;
&lt;tbody&gt;
&lt;tr&gt;
&lt;td&gt;
&lt;p&gt;This study aimed to design and present a dynamic model for industrial waste management in Iran’s gas refining industry using the reverse logistics supply chain approach. The main objective was to identify key factors affecting this chain and provide solutions to improve efficiency and reduce costs associated with industrial waste management. The research method combined grounded theory and system dynamics. In the first stage, semi-structured interviews were conducted with 17 academic experts and managers in the gas refining industry to identify the key variables influencing the reverse logistics supply chain. These variables were then categorized into a paradigmatic model. In the second stage, the relationships among these variables were dynamically modeled using Vensim software. This modeling process examined the impact of different variables on the efficiency of the supply chain and the costs of waste management. The findings indicated that improving infrastructure, advancing recycling technologies, and achieving alignment among the components of the supply chain can significantly enhance the efficiency of the reverse logistics supply chain and reduce industrial waste management costs. Moreover, increasing employee training and top management support were identified as critical facilitators for the success of this system. Sensitivity analysis results also confirmed that improving community satisfaction and reducing environmental pollution directly affect system performance. This dynamic model can serve as an effective decision-making tool for industrial waste management and the improvement of supply chain sustainability. Enhancing infrastructure, recycling technologies, alignment among supply chain components, employee training, and top management support are among the key factors that can significantly improve system efficiency and reduce costs. Additionally, emphasizing community satisfaction and reducing environmental pollution are highlighted as essential elements in the success of industrial waste management systems. This study may also serve as a foundation for future research and improvements in waste management systems across other industries.&lt;/p&gt;
&lt;/td&gt;
&lt;/tr&gt;
&lt;/tbody&gt;
&lt;/table&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Reverse logistics supply chain</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">industrial waste management</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value"> system dynamics</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">grounded theory</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">dynamic modeling</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalfwdmj.com/index.php/fwdmj/article/download/146/133</ArchiveCopySource>
  </Article>
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