<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Journal of Management and Business Solutions</JournalTitle>
      <Issn>3092-7226</Issn>
      <Volume>3</Volume>
      <Issue>Serial Number 15</Issue>
      <PubDate PubStatus="epublish">
        <Year>2025</Year>
        <Month>10</Month>
        <Day>10</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Designing a Bioeconomy-Based Sustainable Supply Chain Model in the Era of the Fourth Industrial Revolution (Case Study: Gas Industry)</ArticleTitle>
    <VernacularTitle>Designing a Bioeconomy-Based Sustainable Supply Chain Model in the Era of the Fourth Industrial Revolution (Case Study: Gas Industry)</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>11</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>2025</Year>
        <Month>07</Month>
        <Day>17</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;The primary objective of the present study was to design a bioeconomy-based sustainable supply chain model in the era of the Fourth Industrial Revolution for Iran’s gas industry; a model capable of addressing the triple bottom line sustainability challenges (economic, environmental, and social) by leveraging two key global trends, namely the bioeconomy and the Fourth Industrial Revolution. The research approach was a combination of deductive and inductive reasoning. The research strategy was grounded in numerical data analysis and quantitative modeling. Data analysis indicated that, using a meta-synthesis approach, the global literature was systematically reviewed, leading to the extraction of 148 initial codes, 37 specialized concepts, and 7 overarching categories. These categories, which included (1) theoretical infrastructure, (2) strategic orientation, (3) environmental requirements, (4) operational instruments, and others, constituted the foundational components of the proposed model. The findings of the present study were classified into two main domains: thematic analysis (qualitative model) and network optimization (quantitative model), thereby providing the necessary foundations for proposing a comprehensive bioeconomy-based sustainable supply chain management (SSCM) model for the gas industry. The results of this research were obtained across two principal domains, namely the qualitative model (meta-synthesis) and the quantitative model (optimization). Interpreting these results through comparison with prior studies reveals both the alignment and the innovative contribution of the proposed model.&lt;/p&gt;</Abstract>
    <ArchiveCopySource DocType="pdf">https://www.journalmbs.com/index.php/jmbs/article/download/202/142</ArchiveCopySource>
  </Article>
</ArticleSet>
