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Identification of university-based patents: A new large-scale approach

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  • Dornbusch, Friedrich
  • Schmoch, Ulrich
  • Schulze, Nicole
  • Bethke, Nadine

Abstract

This paper described a method to consistently and automatically identify all university-based patents by matching the names of inventors on patent filings with authors of scientific publications. This methodological procedure can be adjusted for different pur-poses. Handling selection criteria rigorously allows us to generate a dataset of universi-ty-based patents with high precision. A less restrictive setting of selection criteria yields a higher coverage in terms of the overall picture and total numbers of academic pa-tents. Using the authors of scientific publications allows us to identify research-active staff at universities without having to continuously compile and update staff lists for comparison with inventor lists. In particular, the author lists also cover research-active staff without official teaching functions who are often not covered by the official staff lists.

Suggested Citation

  • Dornbusch, Friedrich & Schmoch, Ulrich & Schulze, Nicole & Bethke, Nadine, 2012. "Identification of university-based patents: A new large-scale approach," Discussion Papers "Innovation Systems and Policy Analysis" 32, Fraunhofer Institute for Systems and Innovation Research (ISI).
  • Handle: RePEc:zbw:fisidp:32
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    References listed on IDEAS

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    1. Youtie, Jan & Shapira, Philip, 2008. "Building an innovation hub: A case study of the transformation of university roles in regional technological and economic development," Research Policy, Elsevier, vol. 37(8), pages 1188-1204, September.
    2. Sidonia von Ledebur, 2009. "University-owned Patents in West and East Germany and the Abolition of the Professors' Privilege," Working Papers on Innovation and Space 2009-02, Philipps University Marburg, Department of Geography.
    3. Thursby, Jerry & Fuller, Anne W. & Thursby, Marie, 2009. "US faculty patenting: Inside and outside the university," Research Policy, Elsevier, vol. 38(1), pages 14-25, February.
    4. Grid Thoma & Salvatore Torrisi, 2007. "Creating Powerful Indicators for Innovation Studies with Approximate Matching Algorithms. A test based on PATSTAT and Amadeus databases," KITeS Working Papers 211, KITeS, Centre for Knowledge, Internationalization and Technology Studies, Universita' Bocconi, Milano, Italy, revised Dec 2007.
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