IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v120y2019i2d10.1007_s11192-019-03148-2.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-019-03148-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-019-03148-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Malerba, Franco, 2002. "Sectoral systems of innovation and production," Research Policy, Elsevier, vol. 31(2), pages 247-264, February.
    2. 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.
    3. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Ruttan, Vernon W., 2006. "Is War Necessary for Economic Growth?: Military Procurement and Technology Development," OUP Catalogue, Oxford University Press, number 9780195188042, December.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. Manuel Trajtenberg, 2003. "Defense R&D Policy in the Anti-terrorist Era," NBER Working Papers 9725, National Bureau of Economic Research, Inc.
    24. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sjögårde, Peter & Ahlgren, Per, 2018. "Granularity of algorithmically constructed publication-level classifications of research publications: Identification of topics," Journal of Informetrics, Elsevier, vol. 12(1), pages 133-152.
    2. Michel Zitt, 2015. "Meso-level retrieval: IR-bibliometrics interplay and hybrid citation-words methods in scientific fields delineation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2223-2245, March.
    3. Lovro Šubelj & Nees Jan van Eck & Ludo Waltman, 2016. "Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-23, April.
    4. 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.
    5. Xu, Shuo & Hao, Liyuan & An, Xin & Yang, Guancan & Wang, Feifei, 2019. "Emerging research topics detection with multiple machine learning models," Journal of Informetrics, Elsevier, vol. 13(4).
    6. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    7. Jochen Gläser & Wolfgang Glänzel & Andrea Scharnhorst, 2017. "Same data—different results? Towards a comparative approach to the identification of thematic structures in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 981-998, May.
    8. Ugo Moschini & Elena Fenialdi & Cinzia Daraio & Giancarlo Ruocco & Elisa Molinari, 2020. "A comparison of three multidisciplinarity indices based on the diversity of Scopus subject areas of authors’ documents, their bibliography and their citing papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1145-1158, November.
    9. Yi-Ming Wei & Jin-Wei Wang & Tianqi Chen & Bi-Ying Yu & Hua Liao, 2018. "Frontiers of Low-Carbon Technologies: Results from Bibliographic Coupling with Sliding Window," CEEP-BIT Working Papers 116, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    10. Ignacio Rodríguez-Rodríguez & José-Víctor Rodríguez & Niloofar Shirvanizadeh & Andrés Ortiz & Domingo-Javier Pardo-Quiles, 2021. "Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining," IJERPH, MDPI, vol. 18(16), pages 1-29, August.
    11. Xuefeng Wang & Shuo Zhang & Yuqin liu, 2022. "ITGInsight–discovering and visualizing research fronts in the scientific literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6509-6531, November.
    12. Li, Menghui & Yang, Liying & Zhang, Huina & Shen, Zhesi & Wu, Chensheng & Wu, Jinshan, 2017. "Do mathematicians, economists and biomedical scientists trace large topics more strongly than physicists?," Journal of Informetrics, Elsevier, vol. 11(2), pages 598-607.
    13. Yun, Jinhyuk & Ahn, Sejung & Lee, June Young, 2020. "Return to basics: Clustering of scientific literature using structural information," Journal of Informetrics, Elsevier, vol. 14(4).
    14. Rakas, Marija & Hain, Daniel S., 2019. "The state of innovation system research: What happens beneath the surface?," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    15. Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    16. Kevin W. Boyack, 2017. "Investigating the effect of global data on topic detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 999-1015, May.
    17. Mu-hsuan Huang & Chia-Pin Chang, 2015. "A comparative study on detecting research fronts in the organic light-emitting diode (OLED) field using bibliographic coupling and co-citation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2041-2057, March.
    18. Yun, Jinhyuk, 2022. "Generalization of bibliographic coupling and co-citation using the node split network," Journal of Informetrics, Elsevier, vol. 16(2).
    19. Shome, Samik & Hassan, M. Kabir & Verma, Sushma & Panigrahi, Tushar Ranjan, 2023. "Impact investment for sustainable development: A bibliometric analysis," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 770-800.
    20. Rons, Nadine, 2018. "Bibliometric approximation of a scientific specialty by combining key sources, title words, authors and references," Journal of Informetrics, Elsevier, vol. 12(1), pages 113-132.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:120:y:2019:i:2:d:10.1007_s11192-019-03148-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.