<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Future of Work and Digital Management Journal</JournalTitle>
      <Issn></Issn>
      <Volume>2</Volume>
      <Issue>Serial Number 5</Issue>
      <PubDate PubStatus="epublish">
        <Year>2024</Year>
        <Month>09</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Developing a Model of Human Resource Excellence in the Digital Era</ArticleTitle>
    <VernacularTitle>Developing a Model of Human Resource Excellence in the Digital Era</VernacularTitle>
    <FirstPage>76</FirstPage>
    <LastPage>93</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>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2024</Year>
        <Month>05</Month>
        <Day>20</Day>
      </PubDate>
    </History>
    <Abstract>&lt;table&gt;
&lt;tbody&gt;
&lt;tr&gt;
&lt;td&gt;
&lt;p&gt;The primary objective of this study is to develop a model of human resource excellence in the digital era. The research employed a mixed-methods approach (qualitative and quantitative). In the qualitative phase, data were collected through thematic analysis and the Delphi technique. The qualitative statistical population consisted of professors and experts in the field of human resources. Using purposive sampling, 12 experts were selected for the extraction of initial data (interviews), and 7 experts were selected to provide feedback in the Delphi process. Thematic analysis was conducted using the Attride-Stirling method with the aid of NVivo software. The results yielded 129 open codes, 50 basic codes, 15 organizing codes, and 3 global themes. In the quantitative phase, the statistical population comprised 1,200 experts and managers in the fields of human resources and technology across the country. Based on Cochran’s formula, a sample size of 291 participants was determined. Quantitative data were analyzed using SPSS and SmartPLS software. The findings of this study indicate that the model of human resource excellence in the digital era consists of three main dimensions: (1) Implementation Space (path coefficient = 0.384), with components including nature, formulation, environment, evaluation, and technology; (2) Human Resource Space (path coefficient = 0.353), with components including performance, goal setting, executive tools, control, and meritocracy; and (3) Digital Era Space (path coefficient = 0.301), with components including technological conditions, economic conditions, political conditions, communication barriers, and the structure of intelligent organizations. Among these, the Implementation Space, Human Resource Space, and Digital Era Space exert the greatest influence, respectively, on the formation of the model of human resource excellence in the digital era. Furthermore, within the Implementation dimension, the component of nature (path coefficient = 0.801) was identified as the most significant factor; within the Human Resource dimension, the performance component (path coefficient = 0.844) was found to be the most influential; and within the Digital Era dimension, technological conditions (path coefficient = 0.900) emerged as the most critical component.&lt;/p&gt;
&lt;/td&gt;
&lt;/tr&gt;
&lt;/tbody&gt;
&lt;/table&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Human Resource Excellence</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Digital Era</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Artificial Intelligence</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalfwdmj.com/index.php/fwdmj/article/download/173/175</ArchiveCopySource>
  </Article>
</ArticleSet>
