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  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>عنوان مجله</JournalTitle>
      <Issn></Issn>
      <Volume>2</Volume>
      <Issue>Serial Number 5</Issue>
      <PubDate PubStatus="epublish">
        <Year>2025</Year>
        <Month>05</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>From Classical Management Systems to Intelligent Organizations: A Bibliometric Review of Management Evolution Research</ArticleTitle>
    <VernacularTitle>From Classical Management Systems to Intelligent Organizations: A Bibliometric Review of Management Evolution Research</VernacularTitle>
    <FirstPage>32</FirstPage>
    <LastPage>41</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <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;This study aimed to explore how management systems have evolved from classical models of hierarchy, control, and administrative rationality toward intelligent organizational forms shaped by digital transformation, knowledge integration, adaptive learning, and artificial intelligence. The study adopted a qualitative exploratory design based on semi-structured interviews with 24 management scholars, senior executives, organizational consultants, and digital transformation experts in Tehran, Iran. Participants were selected through purposive and snowball sampling according to their expertise in management systems, organizational development, digital transformation, and intelligent organizations. Data collection continued until theoretical saturation was reached after the twenty-first interview, followed by three confirmatory interviews. Interviews lasted between 45 and 75 minutes and were transcribed verbatim. Data were analyzed using thematic coding in NVivo software through open, axial, and selective coding procedures informed by qualitative thematic and grounded theory traditions The analysis produced five main categories: the decline of command-and-control management logic, the rise of human-centered and learning-oriented systems, the emergence of systemic and adaptive organizational design, the transition toward data-driven and digitally integrated coordination, and the formation of intelligent organizations as socio-technical systems. Participants emphasized that management evolution is not a linear replacement of old theories but a cumulative transformation in which efficiency, bureaucracy, learning, agility, and intelligence coexist in different organizational layers. Intelligent organizations were described as entities capable of sensing environmental change, integrating distributed knowledge, augmenting decision-making through digital technologies, and maintaining ethical human oversight. The study concludes that management evolution reflects a shift from mechanical control toward adaptive intelligence. Intelligent organizations require not only advanced technologies but also dynamic capabilities, participatory leadership, organizational learning, ethical governance, and the redesign of managerial roles around interpretation, coordination, and responsible decision-making.&lt;/p&gt;</Abstract>
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      <Object Type="keyword">
        <Param Name="value">management evolution</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">intelligent organizations</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">digital transformation</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">qualitative research</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">organizational learning</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">management systems</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">artificial intelligence</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.msels.com/index.php/msels/article/download/32/30</ArchiveCopySource>
  </Article>
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