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Knowledge Flows, Patent Citations and the Impact of Science on Technology

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  • onder Nomaler
  • Bart Verspagen

Abstract

Technological innovation depends on knowledge developed by scientific research. The number of citations made in patents to the scientific literature has been suggested as an indicator of this process of transfer of knowledge from science to technology. We provide an intersectoral insight into this indicator, by breaking down patent citations into a sector-to-sector matrix of knowledge flows. We then propose a method to analyze this matrix and construct various indicators of science intensity of sectors, and the pervasiveness of knowledge flows. Our results indicate that the traditional measure of the number of citations to science literature per patent captures important aspects of intersectoral knowledge flows, but that other aspects are not captured. In particular, we show that high science intensity implies that sectors are net suppliers of knowledge in the economic sector, but that science intensity does not say much about pervasiveness of either knowledge use or knowledge supply by sectors. We argue that these results are related to the specific and specialized nature of knowledge.

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  • onder Nomaler & Bart Verspagen, 2008. "Knowledge Flows, Patent Citations and the Impact of Science on Technology," Economic Systems Research, Taylor & Francis Journals, vol. 20(4), pages 339-366.
    • Handle: RePEc:taf:ecsysr:v:20:y:2008:i:4:p:339-366
    DOI: 10.1080/09535310802551315
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    Cited by:

    1. Suma Athreye & Martha Prevezer, 2008. "R&D offshoring and the domestic science base in India and China," Working Papers 26, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
    2. Julie Callaert & Joris Grouwels & Bart Looy, 2012. "Delineating the scientific footprint in technology: Identifying scientific publications within non-patent references," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 383-398, May.
    3. Tom Broekel & Matthias Brachert, 2015. "The structure and evolution of inter-sectoral technological complementarity in R&D in Germany from 1990 to 2011," Journal of Evolutionary Economics, Springer, vol. 25(4), pages 755-785, September.
    4. Ali Gazni & Zahra Ghaseminik, 2019. "The increasing dominance of science in the economy: Which nations are successful?," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1411-1426, September.
    5. Lyu, Haihua & Bu, Yi & Zhao, Zhenyue & Zhang, Jiarong & Li, Jiang, 2022. "Citation bias in measuring knowledge flow: Evidence from the web of science at the discipline level," Journal of Informetrics, Elsevier, vol. 16(4).
    6. Taalbi, Josef, 2020. "Evolution and structure of technological systems - An innovation output network," Research Policy, Elsevier, vol. 49(8).
    7. José Bestier Padilla Bejarano & Jhon Wilder Zartha Sossa & Carlos Ocampo-López & Margarita Ramírez-Carmona, 2023. "University Technology Transfer from a Knowledge-Flow Approach—Systematic Literature Review," Sustainability, MDPI, vol. 15(8), pages 1-21, April.
    8. Ruimin Ma & Erjia Yan, 2016. "Uncovering inter-specialty knowledge communication using author citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 839-854, November.
    9. Maria Abreu & Pelin Demirel & Vadim Grinevich & Mine Karataş-Özkan, 2016. "Entrepreneurial practices in research-intensive and teaching-led universities," Small Business Economics, Springer, vol. 47(3), pages 695-717, October.
    10. Adams, Pamela & Fontana, Roberto & Malerba, Franco, 2013. "The magnitude of innovation by demand in a sectoral system: The role of industrial users in semiconductors," Research Policy, Elsevier, vol. 42(1), pages 1-14.
    11. Mei Hsiu-Ching Ho & John S. Liu, 2013. "The motivations for knowledge transfer across borders: the diffusion of data envelopment analysis (DEA) methodology," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 397-421, January.
    12. Francisco Mas-Verdú & Anthony Wensley & Martin Alba & José García Álvarez-Coque, 2011. "How much does KIBS contribute to the generation and diffusion of innovation?," Service Business, Springer;Pan-Pacific Business Association, vol. 5(3), pages 195-212, September.
    13. Fabrizio Fusillo & Sandro Montresor & Giuseppe Vittucci Marzetti, 2021. "The global network of embodied R&D flows," Discussion Paper series in Regional Science & Economic Geography 2021-05, Gran Sasso Science Institute, Social Sciences, revised Apr 2021.
    14. Alessandro Caiani, 2017. "Innovation Dynamics and Industry Structure Under Different Technological Spaces," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 307-341, November.
    15. Yan, Erjia & Ding, Ying & Cronin, Blaise & Leydesdorff, Loet, 2013. "A bird's-eye view of scientific trading: Dependency relations among fields of science," Journal of Informetrics, Elsevier, vol. 7(2), pages 249-264.
    16. Taalbi, Josef, 2015. "Development Blocks in Innovation Networks. The Swedish Manufacturing Industry, 1970-2007," MPRA Paper 64549, University Library of Munich, Germany, revised 23 May 2015.
    17. Pan, Xuelian & Yan, Erjia & Cui, Ming & Hua, Weina, 2018. "Examining the usage, citation, and diffusion patterns of bibliometric mapping software: A comparative study of three tools," Journal of Informetrics, Elsevier, vol. 12(2), pages 481-493.
    18. Josef Taalbi, 2017. "Development blocks in innovation networks," Journal of Evolutionary Economics, Springer, vol. 27(3), pages 461-501, July.
    19. Talya Ponchek, 2016. "To Collaborate or Not to Collaborate? A Study of the Value of Innovation from a Sectoral Perspective," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 7(1), pages 43-79, March.
    20. Vadim Grinevich, 2013. "Region-specific productivity competitiveness and the universityindustry interface," Chapters, in: Tüzin Baycan (ed.), Knowledge Commercialization and Valorization in Regional Economic Development, chapter 9, pages 184-208, Edward Elgar Publishing.

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    More about this item

    Keywords

    Knowledge input-output analysis; knowledge flow matrices; science-to-technology transfer;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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