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Identifying the Technology Profiles of R&D Performing Firms — A Matching of R&D and Patent Data

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  • Peter Neuhäusler

    (Fraunhofer Institute for Systems and Innovation Research ISI, Breslauer Strasse 48, 76139 Karlsruhe, Germany2Berlin University of Technology, VWS 2, Müller-Breslau-Straße, 10623 Berlin, Germany)

  • Rainer Frietsch

    (Fraunhofer Institute for Systems and Innovation Research ISI, Breslauer Strasse 48, 76139 Karlsruhe, Germany)

  • Carolin Mund

    (Fraunhofer Institute for Systems and Innovation Research ISI, Breslauer Strasse 48, 76139 Karlsruhe, Germany)

  • Verena Eckl

    (Wissenschaftsstatistik des Stifterverbands für die Deutsche, Wissenschaft (SV Wissenschaftsstatistik) Barkhovenallee 1, 45239 Essen, Germany)

Abstract

Since the statistical classification of economic activities is not able to adequately display companies’ R&D expenditures, the aim of this paper is to create a concordance list between industry sectors and technologies, enabling us to report the business R&D expenditures not only by industries but also by technology fields. To construct the concordance, we match data on R&D expenditures with patent data at the micro-level, i.e. at the level of companies and patent applicants, respectively. In a further step the business R&D expenditures are aggregated at the level of technology fields. This concordance table also allows us to provide patent statistics at the level of industries. The patent data for the matching were extracted from the “EPO Worldwide Patent Statistical Database” (PATSTAT). The data on German business R&D expenditures are provided by the SV Wissenschaftsstatistik. The two data sources are matched by applying a string matching algorithm based on the distance between two text strings. The matching covers 44% of all German patent applicants and 83% of all patent filings at the EPO and the German Patent and Trademark Office in 2009.

Suggested Citation

  • Peter Neuhäusler & Rainer Frietsch & Carolin Mund & Verena Eckl, 2017. "Identifying the Technology Profiles of R&D Performing Firms — A Matching of R&D and Patent Data," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 1-30, February.
  • Handle: RePEc:wsi:ijitmx:v:14:y:2017:i:01:n:s021987701740003x
    DOI: 10.1142/S021987701740003X
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    References listed on IDEAS

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    1. Gehrke, Birgit & Cordes, Alexander & John, Katrin & Frietsch, Rainer & Michels, Carolin & Neuhäusler, Peter & Pohlmann, Tim & Ohnemus, Jörg & Rammer, Christian & Leidmann, Mark, 2014. "Informations- und Kommunikationstechnologien in Deutschland und im internationalen Vergleich – ausgewählte Innovationsindikatoren," Studien zum deutschen Innovationssystem 11-2014, Expertenkommission Forschung und Innovation (EFI) - Commission of Experts for Research and Innovation, Berlin.
    2. Raffo, Julio & Lhuillery, Stéphane, 2009. "How to play the "Names Game": Patent retrieval comparing different heuristics," Research Policy, Elsevier, vol. 38(10), pages 1617-1627, December.
    3. Kirner, Eva & Kinkel, Steffen & Jaeger, Angela, 2009. "Innovation paths and the innovation performance of low-technology firms--An empirical analysis of German industry," Research Policy, Elsevier, vol. 38(3), pages 447-458, April.
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    Cited by:

    1. Dorner, Matthias & Harhoff, Dietmar, 2018. "A novel technology-industry concordance table based on linked inventor-establishment data," Research Policy, Elsevier, vol. 47(4), pages 768-781.
    2. Salman Ali & Syed Mizanur Rahman, 2020. "R&D Expenditure in a Competitive Landscape: A Game Theoretic Approach," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 19(1), pages 47-60, June.
    3. Patricia Laurens & Pierluigi Toma & Antoine Schoen & Cinzia Daraio & Philippe Larédo, 2022. "How does Internationalisation affect the productivity of R&D activities in large innovative firms? A conditional nonparametric investigation," Post-Print hal-03840316, HAL.
    4. Onken, James & Miklos, Andrew C. & Dorsey, Travis F. & Aragon, Richard & Calcagno, Anna Maria, 2019. "Using database linkages to measure innovation, commercialization, and survival of small businesses," Evaluation and Program Planning, Elsevier, vol. 77(C).

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