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    <identifier>10.57760/sciencedb.39225</identifier>
    <datestamp>2026-06-16T09:24:01Z</datestamp>
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  <dc:date>2026-06-16</dc:date>
  <dc:title>AI-Hire and carbon performance</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.39225</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset examines the relationship between AI hiring and corporate carbon performance. Covering firm-level panel data, it includes core variables like aihire (AI hiring intensity) and cp (carbon performance), alongside controls for firm size, leverage, profitability, governance, and regional/industry characteristics. Additional variables capture AI exposure, policy adoption, and workforce composition to explore how AI integration shapes firms&amp;rsquo; environmental outcomes.</dc:description>
  <dc:subject>ai-hire; cabon performance; green development</dc:subject>
  <dc:creator>wenqi Liao</dc:creator>
  <dc:rights>RESTRICTED</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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