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Technical research innovations of the US national security system

Author

Listed:
  • R. Fileto Maciel

    (Universidade Federal de Minas Gerais
    Erasmus University)

  • P. Saskia Bayerl

    (Sheffield Hallam University)

  • Marta Macedo Kerr Pinheiro

    (Universidade Federal de Minas Gerais
    Universidade FUMEC)

Abstract

Since the Second World War the US defense has been a major participant in the development of radical innovations in information and communication technologies (ICT’s), most famously probably the digital computer and the internet. A regularly present, but less known creator of R&D innovations is the intelligence community. To understand the role and impact of defense and intelligence-related research for driving ICT innovations, we analyzed which technological paradigms were promoted by US defense and intelligence agencies and the development of these research trajectories over time. Using bibliographic analysis, we clustered 82,239 scientific papers funded by the US national security system, published between 2009–2017, in research fronts, and after that aggregated the research fronts into technological paradigms. Our analysis identified main technological paradigms promoted by the US defense’s sectoral system of innovation, such as quantum science and graphene as fields that could generate high impact in the new generation of radical technologies. The efforts of intelligence agencies was highly concentrated on quantum science, social forecasting, computer cognition and signal processing. Our research highlights the role of US security players in shaping research fields.

Suggested Citation

  • R. Fileto Maciel & P. Saskia Bayerl & Marta Macedo Kerr Pinheiro, 2019. "Technical research innovations of the US national security system," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 539-565, August.
    • Handle: RePEc:spr:scient:v:120:y:2019:i:2:d:10.1007_s11192-019-03148-2
    DOI: 10.1007/s11192-019-03148-2
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    1. Miray Kas & Alla G. Khadka & William Frankenstein & Ahmed Y. Abdulla & Frank Kunkel & L. Richard Carley & Kathleen M. Carley, 2012. "Analyzing scientific networks for nuclear capabilities assessment," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(7), pages 1294-1312, July.
    2. Ludo Waltman & Nees Eck, 2013. "A smart local moving algorithm for large-scale modularity-based community detection," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(11), pages 1-14, November.
    3. Manuel Acosta & Daniel Coronado & Rosario Marín & Pedro Prats, 2013. "Factors affecting the diffusion of patented military technology in the field of weapons and ammunition," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 1-22, January.
    4. Ruttan, Vernon W., 2006. "Is War Necessary for Economic Growth?: Military Procurement and Technology Development," OUP Catalogue, Oxford University Press, number 9780195188042.
    5. Nicola Grassano & Daniele Rotolo & Joshua Hutton & Frédérique Lang & Michael M. Hopkins, 2017. "Funding Data from Publication Acknowledgments: Coverage, Uses, and Limitations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 999-1017, April.
    6. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    7. Miray Kas & Alla G. Khadka & William Frankenstein & Ahmed Y. Abdulla & Frank Kunkel & L. Richard Carley & Kathleen M. Carley, 2012. "Analyzing scientific networks for nuclear capabilities assessment," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(7), pages 1294-1312, July.
    8. Manuel Trajtenberg, 2003. "Defense R&D Policy in the Anti-terrorist Era," NBER Working Papers 9725, National Bureau of Economic Research, Inc.
    9. Nees Jan Eck & Ludo Waltman, 2017. "Citation-based clustering of publications using CitNetExplorer and VOSviewer," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1053-1070, May.
    10. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    11. Dosi, Giovanni, 1993. "Technological paradigms and technological trajectories : A suggested interpretation of the determinants and directions of technical change," Research Policy, Elsevier, vol. 22(2), pages 102-103, April.
    12. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    13. Boyack, Kevin W. & Klavans, Richard, 2014. "Including cited non-source items in a large-scale map of science: What difference does it make?," Journal of Informetrics, Elsevier, vol. 8(3), pages 569-580.
    14. Blaise Cronin, 2011. "The intelligence disconnect," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(10), pages 1867-1868, October.
    15. Malerba, Franco, 2002. "Sectoral systems of innovation and production," Research Policy, Elsevier, vol. 31(2), pages 247-264, February.
    16. Ludo Waltman & Nees Jan van Eck, 2012. "A new methodology for constructing a publication‐level classification system of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    17. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    18. Steven A. Morris & G. Yen & Zheng Wu & Benyam Asnake, 2003. "Time line visualization of research fronts," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(5), pages 413-422, March.
    19. María del Carmen Calatrava Moreno & Thomas Auzinger & Hannes Werthner, 2016. "On the uncertainty of interdisciplinarity measurements due to incomplete bibliographic data," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(1), pages 213-232, April.
    20. Blaise Cronin, 2011. "The intelligence disconnect," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1867-1868, October.
    21. Mu-Hsuan Huang & Chia-Pin Chang, 2014. "Detecting research fronts in OLED field using bibliographic coupling with sliding window," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1721-1744, March.
    22. S. Phineas Upham & Henry Small, 2010. "Emerging research fronts in science and technology: patterns of new knowledge development," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(1), pages 15-38, April.
    23. Dirk Libaers, 2009. "Industry relationships of DoD-funded academics and institutional changes in the US university system," The Journal of Technology Transfer, Springer, vol. 34(5), pages 474-489, October.
    24. Alan L. Porter & Ismael Rafols, 2009. "Is science becoming more interdisciplinary? Measuring and mapping six research fields over time," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 719-745, December.
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    More about this item

    Keywords

    Innovation; Technological paradigm; Technological trajectory; National security; Intelligence; Bibliographic analysis;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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