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<ArticleSet>
  <Article>
    <Journal>
      <PublisherName>KMAN Publication Inc.</PublisherName>
      <JournalTitle>AI and Tech in Behavioral and Social Sciences</JournalTitle>
      <Issn></Issn>
      <Volume>4</Volume>
      <Issue>Serial Number 13</Issue>
      <PubDate PubStatus="epublish">
        <Year>2026</Year>
        <Month>02</Month>
        <Day>06</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Developing a Resilient Supply Chain Model Based on Industry 4.0 in the Circular Printing Industry</ArticleTitle>
    <VernacularTitle>Developing a Resilient Supply Chain Model Based on Industry 4.0 in the Circular Printing Industry</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>15</LastPage>
    <ELocationID EIdType="doi">10.61838/kman.aitech.5033</ELocationID>
    <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>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <Abstract>&lt;p&gt;Today, enhancing supply chain resilience has become one of the fundamental responsibilities of management, which can be improved through emerging Industry 4.0 technologies. This study aims to develop a resilient supply chain model based on Industry 4.0 within the circular printing industry. The study was conducted in two qualitative and quantitative phases. In the qualitative phase, the research method was hybrid content analysis (deductive–inductive), and in the quantitative phase, causal and correlational methods were employed. The research population in the qualitative phase included participants such as senior managers, senior experts, consultants from the printing industry, and university faculty members specializing in technology management, supply chain management, and environmental management. These participants were selected using purposive non-probability sampling, totaling 20 individuals. In the quantitative phase, the statistical population consisted of experts working in the printing company, and a complete census method was used to select 107 individuals. The findings of the qualitative phase indicated that the model variables included “transformational capacity,” “absorptive capacity,” “adaptive capacity,” and “continuity capacity.” According to the fuzzy DEMATEL results, the variable “transformational capacity” was identified as the most influential factor, which sequentially affects “absorptive capacity,” “adaptive capacity,” and “continuity capacity.” The results of testing the developed model showed that “transformational capacity” has a positive and statistically significant effect on “absorptive capacity,” “adaptive capacity,” and “continuity capacity.” Furthermore, the effect of “absorptive capacity” on “adaptive capacity” and “continuity capacity” was confirmed to be positive and statistically significant. Finally, “adaptive capacity” has a positive and statistically significant relationship with “continuity capacity.” The results of the study indicate the critical role of digital strategic transformation in enhancing supply chain resilience capacity within the circular economy.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Digital transformation</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Resilient supply chain</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Circular economy</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Printing industry</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://journals.kmanpub.com/index.php/aitechbesosci/article/download/5033/9263</ArchiveCopySource>
  </Article>
</ArticleSet>
