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    <responseDate>2026-10-13T23:56:53Z</responseDate>
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    <identifier>10.57760/sciencedb.j00289.00135</identifier>
    <datestamp>2026-04-16T14:37:14Z</datestamp>
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  <dc:date>2026-04-16</dc:date>
  <dc:title>Research on the Configuration Path of Disruptive Innovation under Network Embeddedness and Enterprise Feature Matching</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.j00289.00135</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This data is mainly used to analyze the disruptive innovation configuration paths under the conditions of network embedding and enterprise characteristics matching. Taking 179 autonomous driving technology enterprises as the observation sample, it includes variable data such as network embedding (knowledge embedding, social embedding, structural embedding and relationship embedding) and enterprise characteristics (enterprise scale and enterprise nature). The data sources include the patent database of China National Knowledge Infrastructure, Guotai Anlysis Database and Ruisi Financial Research Data. The calculation process is all explained in the main text.</dc:description>
  <dc:subject>Disruptive innovation; network embedding; enterprise characteristics</dc:subject>
  <dc:creator>cao yang chun</dc:creator>
  <dc:rights>RESTRICTED</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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