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    <responseDate>2026-10-14T14:41:55Z</responseDate>
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    <identifier>10.57760/sciencedb.36354</identifier>
    <datestamp>2026-05-14T18:06:19Z</datestamp>
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<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:date>2026-05-14</dc:date>
  <dc:title>Dataset of Non-local Suppliers and Customers of Listed Enterprises (2016-2024)</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.36354</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>Some domestic databases only cover the data of the top five suppliers and customers of Chinese listed companies, with obvious data missing problems. To improve data accuracy, a larger-scale inter-enterprise supply relationship dataset was constructed based on the basic information of Chinese listed companies and combined with enterprise bidding and tendering data. The specific data acquisition and processing process is as follows: ① Extract the names of Chinese listed companies over the years from the CSMAR database; ② Obtain the names of suppliers and customer enterprises corresponding to listed companies over the years based on the bidding and tendering data from the Tianyancha platform; ③ Acquire the latest geographical location information of each enterprise through Tianyancha, and exclude enterprises registered overseas, in Hong Kong, Macao and Taiwan regions. Finally, the dataset of non-local suppliers and customers of listed companies from 2016 to 2024 was obtained, which can be used for urban network analysis research.</dc:description>
  <dc:subject>listed company; supplier; customer</dc:subject>
  <dc:creator>LI peiqing</dc:creator>
  <dc:rights>RESTRICTED</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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