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  <Article>
    <Journal>
      <PublisherName>KMAN Publication Inc.</PublisherName>
      <JournalTitle>AI and Tech in Behavioral and Social Sciences</JournalTitle>
      <Issn></Issn>
      <Volume>3</Volume>
      <Issue>Serial Number 10</Issue>
      <PubDate PubStatus="epublish">
        <Year>2025</Year>
        <Month>04</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Interconnected Worlds: Human-AI Collaboration in International Technology Transfer for Industry 5.0</ArticleTitle>
    <VernacularTitle>Interconnected Worlds: Human-AI Collaboration in International Technology Transfer for Industry 5.0</VernacularTitle>
    <FirstPage>127</FirstPage>
    <LastPage>140</LastPage>
    <ELocationID EIdType="doi">10.61838/kman.aitech.3.2.10</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>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <Abstract>&lt;p&gt;In the contemporary era marked by rapid technological advancements and intense competition across global markets, successful technology transfer has emerged as a strategic imperative for organizations. With the advent of the Industry 5.0 era, integrating cutting-edge artificial intelligence (AI) with human expertise and creativity unlocks new avenues for innovation and value creation. However, international technology transfer is fraught with numerous challenges, including cultural disparities, varying legal and regulatory frameworks, as well as technical and organizational complexities. This research endeavors to present an integrated model to facilitate seamless technology transfer within the Industry 5.0 framework, taking into account both human and technological factors. The research adopted a qualitative approach to data collection through the meta-synthesis method, encompassing a comprehensive review of the literature, analysis, and synthesis of existing findings. The validity of the research was affirmed based on established criteria, holding meetings with the research team members, leveraging expert insights, and conducting a thorough auditing process to achieve theoretical consensus, while its reliability was determined through the critical appraisal skills program. The findings identified 118 indicators and 31 components across 7 main dimensions: AI capabilities, human expertise, technology transfer processes, organizational factors, socio-cultural context, collaborative dynamics, and performance and impact. Based on these findings, it is proposed that organizations prioritize integrating AI and human expertise, fostering constructive interactions, developing an understanding of cultural contexts, nurturing an innovation-supportive environment, and embracing continuous learning to achieve successful technology transfer. Furthermore, continuous evaluation of the performance and impact of technology transfer is imperative for process optimization.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Human-AI Collaboration</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">International Technology Transfer</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Human-Centered Approach</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://journals.kmanpub.com/index.php/aitechbesosci/article/download/2222/7216</ArchiveCopySource>
  </Article>
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