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    <identifier>10.57760/sciencedb.psych.00688</identifier>
    <datestamp>2025-06-30T08:35:46Z</datestamp>
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  <dc:date>2025-06-30</dc:date>
  <dc:title>Effect of Algorithmic Decisions on the Work Well-being of Civil Servants in Incentive Contexts</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.psych.00688</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The rapid advancement of artificial intelligence (AI) technology has driven government organizations to widely adopt algorithmic tools in human resource management decision-making. However, existing research has yet to reach a consensus on the effectiveness of algorithmic decision-making, and there remains a lack of exploration into its relationship with civil servants&amp;rsquo; work-related well-being in incentive contexts. Grounded in social information processing theory, this study constructs a theoretical model to examine how algorithmic decision-making influences civil servants&amp;rsquo; work well-being, employing a mixed-method approach combining scenario-based experiments and critical incident techniques. The findings reveal that algorithm in human resource decisions significantly enhance organizational fairness perceived by civil servants, thereby improving their work well-being. Public service climate serves as a moderator in this process, amplifying the positive effect of organizational fairness on well-being when public service climate is high. This study not only expands the theoretical boundaries of algorithmic decision-making in the public sector but also offers policy insights for governments to optimize digital management and incentive practices for civil servants.</dc:description>
  <dc:subject>algorithm in human resource decisions; organization incentive; perceived organizational fairness; work well-being; public service climate</dc:subject>
  <dc:creator>cheng jin kai</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
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  <dc:publisher>Science Data Bank</dc:publisher>
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