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<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Journal of Resource Management and Decision Engineering</JournalTitle>
      <Issn></Issn>
      <Volume>3</Volume>
      <Issue>Serial Number 9</Issue>
      <PubDate PubStatus="epublish">
        <Year>2024</Year>
        <Month>11</Month>
        <Day>12</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Evaluation of the Role of Artificial Intelligence in Enhancing Consumption in Industrial Units</ArticleTitle>
    <VernacularTitle>Evaluation of the Role of Artificial Intelligence in Enhancing Consumption in Industrial Units</VernacularTitle>
    <FirstPage>30</FirstPage>
    <LastPage>38</LastPage>
    <ELocationID EIdType="doi">10.61838/kman.jrmde.3.4.4</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>
    <History>
      <PubDate PubStatus="received">
        <Year>2024</Year>
        <Month>09</Month>
        <Day>19</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;With the rapid advancement of modern technologies, particularly artificial intelligence (AI), significant transformations have occurred in the domains of marketing and customer engagement. This study examines the impact of artificial intelligence on enhancing customer experience in social media marketing, with a specific focus on the domestic automotive market in Iran. A mixed-methods research approach was employed. In the qualitative phase, Interpretive Structural Modeling (ISM) was used to identify the relationships among influential variables and to develop the initial conceptual model. In the quantitative phase, the model was validated using Structural Equation Modeling (SEM), and data were collected through a questionnaire developed based on grounded theory results. Additionally, the SWARA method was applied to determine the weight and significance of variables. The results indicated that artificial intelligence enhances customer experience by improving personalization, increasing engagement, and enabling rapid responsiveness in social media, thereby contributing to customer loyalty. The findings offer opportunities for automotive manufacturers and marketers to effectively leverage intelligent technologies. This research addresses existing gaps related to the cultural and market conditions of Iran and provides a practical framework for improving digital marketing strategies.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">energy consumption</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">energy efficiency</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">artificial intelligence</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">industrial electricity</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalrmde.com/index.php/jrmde/article/download/64/59</ArchiveCopySource>
  </Article>
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