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Government R&D spending as a driving force of technology convergence: a case study of the Advanced Sequencing Technology Program

Author

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  • Chen Zhu

    (Department of Technology Management for Innovation, The University of Tokyo)

  • Kazuyuki Motohashi

    (Department of Technology Management for Innovation, The University of Tokyo
    Research Institute of Economy, Trade and Industry (RIETI))

Abstract

This study investigates the impact of government R&D spending on promoting technology convergence. We test the hypotheses that a government funding program positively affects technology convergence, and that the effects vary depending on the participant (i.e., academic and industrial inventors). We used the Advanced Sequencing Technology Program (ASTP) as an example to investigate this issue. We develop a novel dataset by linking the ASTP grantee information with the PATSTAT patent database. On this basis, we develop inventor-level characteristics for propensity score matching, selecting a control group of inventors from among those enrolled in the ASTP. Then, we employ difference-in-difference models to assess the program’s impact on the matched sample. The results support the program’s role as a driving force of technology convergence. The findings also indicate that the program has a greater influence on industry inventors than on academic counterparts. Furthermore, we conceptualize the program’s “leverage effect” and demonstrate that it can attract more external industrial inventors than academic inventors. The work advances our understanding of the role of a government-funded program in encouraging convergence and has implications for developing convergence-related R&D programs in the future.

Suggested Citation

  • Chen Zhu & Kazuyuki Motohashi, 2023. "Government R&D spending as a driving force of technology convergence: a case study of the Advanced Sequencing Technology Program," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3035-3065, May.
  • Handle: RePEc:spr:scient:v:128:y:2023:i:5:d:10.1007_s11192-023-04682-w
    DOI: 10.1007/s11192-023-04682-w
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    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Bruce Kogut, 1988. "Joint ventures: Theoretical and empirical perspectives," Strategic Management Journal, Wiley Blackwell, vol. 9(4), pages 319-332, July.
    3. Martin, Stephen & Scott, John T., 2000. "The nature of innovation market failure and the design of public support for private innovation," Research Policy, Elsevier, vol. 29(4-5), pages 437-447, April.
    4. Vikas A. Aggarwal & David H. Hsu & Andy Wu, 2020. "Organizing Knowledge Production Teams Within Firms for Innovation," Strategy Science, INFORMS, vol. 5(1), pages 1-16, March.
    5. Park, Hyunwoo & Lee, Jeongsik (Jay) & Kim, Byung-Cheol, 2015. "Project selection in NIH: A natural experiment from ARRA," Research Policy, Elsevier, vol. 44(6), pages 1145-1159.
    6. Meyer, Martin, 2000. "Does science push technology? Patents citing scientific literature," Research Policy, Elsevier, vol. 29(3), pages 409-434, March.
    7. Klein, Julie Thompson & Falk-Krzesinski, Holly J., 2017. "Interdisciplinary and collaborative work: Framing promotion and tenure practices and policies," Research Policy, Elsevier, vol. 46(6), pages 1055-1061.
    8. Karvonen, Matti & Kässi, Tuomo, 2013. "Patent citations as a tool for analysing the early stages of convergence," Technological Forecasting and Social Change, Elsevier, vol. 80(6), pages 1094-1107.
    9. Christine Greenhalgh & Mark Rogers, 2010. "Innovation, Intellectual Property, and Economic Growth," Economics Books, Princeton University Press, edition 1, volume 0, number 9221.
    10. Jeong, Seongkyoon, 2014. "Strategic collaboration of R&D entities for technology convergence: Exploring organizational differences within the triple helix," Journal of Management & Organization, Cambridge University Press, vol. 20(2), pages 227-249, March.
    11. Kim, Tae San & Sohn, So Young, 2020. "Machine-learning-based deep semantic analysis approach for forecasting new technology convergence," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    12. Arnold, Austin & Cafer, Anne & Green, John & Haines, Seena & Mann, Georgianna & Rosenthal, Meagen, 2021. "“Perspective: Promoting and fostering multidisciplinary research in universities”," Research Policy, Elsevier, vol. 50(9).
    13. Appio, Francesco Paolo & Martini, Antonella & Fantoni, Gualtiero, 2017. "The light and shade of knowledge recombination: Insights from a general-purpose technology," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 154-165.
    14. Zhu, Chen & Motohashi, Kazuyuki, 2022. "Identifying the technology convergence using patent text information: A graph convolutional networks (GCN)-based approach," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    15. Littler, Dale & Coombs, Rod, 1988. "Current and future trends in European technological development: New patterns in the funding of R&D," European Management Journal, Elsevier, vol. 6(2), pages 102-113, June.
    16. Seongkyoon Jeong & Jae Young Choi & Jaeyun Kim, 2011. "The determinants of research collaboration modes: exploring the effects of research and researcher characteristics on co-authorship," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 967-983, December.
    17. Veugelers, Reinhilde & Wang, Jian, 2019. "Scientific novelty and technological impact," Research Policy, Elsevier, vol. 48(6), pages 1362-1372.
    18. Manuel Trajtenberg & Rebecca Henderson & Adam Jaffe, 1997. "University Versus Corporate Patents: A Window On The Basicness Of Invention," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 5(1), pages 19-50.
    19. Feldman, Maryann P. & Kelley, Maryellen R., 2006. "The ex ante assessment of knowledge spillovers: Government R&D policy, economic incentives and private firm behavior," Research Policy, Elsevier, vol. 35(10), pages 1509-1521, December.
    20. Wirsich, Alexander & Kock, Alexander & Strumann, Christoph & Schultz, Carsten, 2016. "Effects of University Industry Collaboration on Technological Newness," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 85098, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    21. Henry Sauermann & Paula Stephan, 2013. "Conflicting Logics? A Multidimensional View of Industrial and Academic Science," Organization Science, INFORMS, vol. 24(3), pages 889-909, June.
    22. Kim, Dong-hyu & Lee, Heejin & Kwak, Jooyoung, 2017. "Standards as a driving force that influences emerging technological trajectories in the converging world of the Internet and things: An investigation of the M2M/IoT patent network," Research Policy, Elsevier, vol. 46(7), pages 1234-1254.
    23. Seongkyoon Jeong & Jong-Chan Kim & Jae Young Choi, 2015. "Technology convergence: What developmental stage are we in?," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 841-871, September.
    24. Kenneth Arrow, 1962. "Economic Welfare and the Allocation of Resources for Invention," NBER Chapters, in: The Rate and Direction of Inventive Activity: Economic and Social Factors, pages 609-626, National Bureau of Economic Research, Inc.
    25. Mowery, David & Rosenberg, Nathan, 1993. "The influence of market demand upon innovation: A critical review of some recent empirical studies," Research Policy, Elsevier, vol. 22(2), pages 107-108, April.
    26. Scott Shane, 2001. "Technological Opportunities and New Firm Creation," Management Science, INFORMS, vol. 47(2), pages 205-220, February.
    27. Michelle Gittelman & Bruce Kogut, 2003. "Does Good Science Lead to Valuable Knowledge? Biotechnology Firms and the Evolutionary Logic of Citation Patterns," Management Science, INFORMS, vol. 49(4), pages 366-382, April.
    28. Euiseok Kim & Yongrae Cho & Wonjoon Kim, 2014. "Dynamic patterns of technological convergence in printed electronics technologies: patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 975-998, February.
    29. Gambardella, Alfonso & Giarratana, Marco S., 2013. "General technological capabilities, product market fragmentation, and markets for technology," Research Policy, Elsevier, vol. 42(2), pages 315-325.
    30. Andrei Rikkiev & Saku J. Mäkinen, 2013. "Technology Convergence And Intercompany R&D Collaboration: Across Business Ecosystems Boundaries," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 10(04), pages 1-28.
    31. Kim, Juram & Kim, Seungho & Lee, Changyong, 2019. "Anticipating technological convergence: Link prediction using Wikipedia hyperlinks," Technovation, Elsevier, vol. 79(C), pages 25-34.
    32. Roessner, J. David, 1989. "Evaluating government innovation programs: Lessons from the U.S. experience," Research Policy, Elsevier, vol. 18(6), pages 343-359, December.
    33. Zhou, Yuan & Dong, Fang & Kong, Dejing & Liu, Yufei, 2019. "Unfolding the convergence process of scientific knowledge for the early identification of emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 205-220.
    34. Caviggioli, Federico, 2016. "Technology fusion: Identification and analysis of the drivers of technology convergence using patent data," Technovation, Elsevier, vol. 55, pages 22-32.
    35. Jeeeun Kim & Sungjoo Lee, 2017. "Forecasting and identifying multi-technology convergence based on patent data: the case of IT and BT industries in 2020," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 47-65, April.
    36. Erika Check Hayden, 2014. "Technology: The $1,000 genome," Nature, Nature, vol. 507(7492), pages 294-295, March.
    37. Wang, Jian & Lee, You-Na & Walsh, John P., 2018. "Funding model and creativity in science: Competitive versus block funding and status contingency effects," Research Policy, Elsevier, vol. 47(6), pages 1070-1083.
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    More about this item

    Keywords

    Technology convergence; NIH program; Policy analysis;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

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