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  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Journal of Resource Management and Decision Engineering</JournalTitle>
      <Issn></Issn>
      <Volume></Volume>
      <Issue>In Press</Issue>
      <PubDate PubStatus="epublish">
        <Year>2027</Year>
        <Month>07</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Identification of Causal, Contextual, and Intervening Factors in Existing Performance Evaluation Systems in the Electricity Industry</ArticleTitle>
    <VernacularTitle>Identification of Causal, Contextual, and Intervening Factors in Existing Performance Evaluation Systems in the Electricity Industry</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>23</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>
      <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>2026</Year>
        <Month>05</Month>
        <Day>26</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;This study aimed to identify and explain the causal, contextual, and intervening factors influencing existing performance evaluation systems in the electricity industry. This applied qualitative study was conducted using the grounded theory approach. Participants consisted of managers, experts, and specialists with professional experience in performance evaluation, human resource management, organizational development, and organizational learning within the electricity industry. Participants were selected through purposive snowball sampling, and data collection continued until theoretical saturation was achieved. Data were gathered through semi-structured interviews based on open-ended questions addressing current performance evaluation practices, organizational barriers, learning mechanisms, and factors affecting the effectiveness of evaluation systems. Interviews were audio-recorded with informed consent, transcribed verbatim, and analyzed through open, axial, and selective coding. The constant comparative method was used throughout the analytical process, and MAXQDA software supported data organization and coding. Credibility, transferability, dependability, and confirmability were enhanced through member checking, detailed methodological documentation, rich contextual description, reflexivity, and external review of selected coding and interpretations. The analysis identified three major dimensions affecting existing performance evaluation systems. Causal conditions included pressure to achieve organizational objectives, the need for accountability, the need for resource efficiency, and the need for performance transparency. Contextual conditions comprised the bureaucratic structure of the electricity industry, the prevailing organizational culture, and organizational readiness for learning. Intervening conditions included the compensation system, employee motivation, information technology infrastructure, and leadership style. The findings indicated that performance evaluation effectiveness resulted from the interaction of organizational demands, structural and cultural conditions, and facilitating or constraining organizational mechanisms. Performance evaluation in the electricity industry should be understood as an integrated organizational process rather than an isolated human resource function; improving its effectiveness requires simultaneous attention to strategic alignment, organizational learning, cultural readiness, motivational mechanisms, digital infrastructure, reward systems, and developmental leadership.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Performance Evaluation</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Electricity Industry</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Grounded Theory</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Organizational Learning</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Causal Conditions</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Contextual Conditions</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Intervening Conditions</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalrmde.com/index.php/jrmde/article/download/415/392</ArchiveCopySource>
  </Article>
</ArticleSet>
