Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/ipt/wpaper/201607.html
   My bibliography  Save this paper

Technological diffusion as a recombinant process

Author

Listed:
  • Petros Gkotsis

    (European Commission JRC)

  • Antonio Vezzani

    (European Commission JRC Author-Workplace-Homepage: https://joint-research-centre.ec.europa.eu/index_en)

Abstract
In this work we analyse patterns of technological development using patent applications at the United States Patent and Trademark Office (USPTO) over the 1973-2012 period. Our study focuses on the combinations of technological fields within patent documents and their evolution in time, which can be modelled as a diffusion process. By focusing on the combinatorial dimension of the process we obtain insights that complement those from counting patents. Our results show that the density of the technological knowledge network increased and that the majority of technological fields became more interconnected over time. We find that most technologies follow a similar diffusion path that can be modelled as a Logistic or Gompertz function, which can then be used to estimate the time to maturity defined as the year at which the diffusion process for a specific technology slows down. This allows us to identify a set of promising technologies which are expected to reach maturity in the next decade. Our contribution represents a first step in assessing the importance of diffusion and cross-fertilization in the development of new technologies, which could support the design of targeted and effective Research & Innovation and Industrial policies.

Suggested Citation

  • Petros Gkotsis & Antonio Vezzani, 2016. "Technological diffusion as a recombinant process," JRC Working Papers on Corporate R&D and Innovation 2016-07, Joint Research Centre.
    • Handle: RePEc:ipt:wpaper:201607
    as

    Download full text from publisher

    File URL: https://publications.jrc.ec.europa.eu/repository/handle/JRC102638
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Benjamin F. Jones, 2009. "The Burden of Knowledge and the "Death of the Renaissance Man": Is Innovation Getting Harder?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 283-317.
    2. Jackie Krafft & Francesco Quatraro & Pier Paolo Saviotti, 2011. "The knowledge-base evolution in biotechnology: a social network analysis," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 20(5), pages 445-475.
    3. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    4. Alan L Porter & J David Roessner & Xiao-Yin Jin & Nils C Newman, 2002. "Measuring national ‘emerging technology’ capabilities," Science and Public Policy, Oxford University Press, vol. 29(3), pages 189-200, June.
    5. Verhoeven, Dennis & Bakker, Jurriën & Veugelers, Reinhilde, 2016. "Measuring technological novelty with patent-based indicators," Research Policy, Elsevier, vol. 45(3), pages 707-723.
    6. Martin L. Weitzman, 1998. "Recombinant Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(2), pages 331-360.
    7. Giovanni Dosi & Richard Nelson, 2013. "The Evolution of Technologies: An Assessment of the State-of-the-Art," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 3(1), pages 3-46, June.
    8. C. A. Hidalgo & B. Klinger & A. -L. Barabasi & R. Hausmann, 2007. "The Product Space Conditions the Development of Nations," Papers 0708.2090, arXiv.org.
    9. Weitzman, Martin L, 1996. "Hybridizing Growth Theory," American Economic Review, American Economic Association, vol. 86(2), pages 207-212, May.
    10. Bar, Talia & Leiponen, Aija, 2012. "A measure of technological distance," Economics Letters, Elsevier, vol. 116(3), pages 457-459.
    11. Breschi, Stefano & Lissoni, Francesco & Malerba, Franco, 2003. "Knowledge-relatedness in firm technological diversification," Research Policy, Elsevier, vol. 32(1), pages 69-87, January.
    12. Giovanni Dosi, 2000. "Sources, Procedures, and Microeconomic Effects of Innovation," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 2, pages 63-114, Edward Elgar Publishing.
    13. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    14. 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.
    15. Hélène Dernis & Mariagrazia Squicciarini & Roberto Pinho, 2016. "Detecting the emergence of technologies and the evolution and co-development trajectories in science (DETECTS): a ‘burst’ analysis-based approach," The Journal of Technology Transfer, Springer, vol. 41(5), pages 930-960, October.
    16. Boon, Wouter & Moors, Ellen, 2008. "Exploring emerging technologies using metaphors - A study of orphan drugs and pharmacogenomics," Social Science & Medicine, Elsevier, vol. 66(9), pages 1915-1927, May.
    17. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    18. Rinaldo Evangelista & Valentina Meliciani & Antonio Vezzani, 2015. "The Specialisation of EU Regions in Fast Growing and Key Enabling Technologies," JRC Research Reports JRC98111, Joint Research Centre.
    19. Hélène Dernis & Mafini Dosso & Fernando Hervas & Valentine Millot & Mariagrazia Squicciarini & Antonio Vezzani, 2015. "World Corporate Top R&D Investors: Innovation and IP bundles," JRC Research Reports JRC94932, Joint Research Centre.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lorenzo Napolitano & Evangelos Evangelou & Emanuele Pugliese & Paolo Zeppini & Graham Room, 2017. "Technology networks: the autocatalytic origins of innovation," Papers 1708.03511, arXiv.org, revised Apr 2018.

    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. Martin Kalthaus, 2020. "Knowledge recombination along the technology life cycle," Journal of Evolutionary Economics, Springer, vol. 30(3), pages 643-704, July.
    2. Ad van den Oord & Arjen van Witteloostuijn, 2018. "A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-27, May.
    3. Yoruk, Esin & Radosevic, Slavo & Fischer, Bruno, 2023. "Technological profiles, upgrading and the dynamics of growth: Country-level patterns and trajectories across distinct stages of development," Research Policy, Elsevier, vol. 52(8).
    4. Li, Munan & Porter, Alan L. & Suominen, Arho, 2018. "Insights into relationships between disruptive technology/innovation and emerging technology: A bibliometric perspective," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 285-296.
    5. Moehrle, Martin G. & Caferoglu, Hüseyin, 2019. "Technological speciation as a source for emerging technologies. Using semantic patent analysis for the case of camera technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 776-784.
    6. Krafft Jackie & Quatraro Francesco & Colombelli Alessandra, 2011. "High Growth Firms and Technological Knowledge: Do gazelles follow exploration or exploitation strategies?," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201114, University of Turin.
    7. Jackie Krafft & Francesco Quatraro, 2011. "The Dynamics of Technological Knowledge: From Linearity to Recombination," Chapters, in: Cristiano Antonelli (ed.), Handbook on the Economic Complexity of Technological Change, chapter 7, Edward Elgar Publishing.
    8. Jackie Krafft & Francesco Quatraro, 2011. "The dynamics of technological knowledge," Post-Print halshs-00727633, HAL.
    9. Dieter F. Kogler & Jürgen Essletzbichler & David L. Rigby, 2017. "The evolution of specialization in the EU15 knowledge space," Journal of Economic Geography, Oxford University Press, vol. 17(2), pages 345-373.
    10. Antonelli Cristiano & Colombelli Alessandra, 2013. "Knowledge cumulability and complementarity in the knowledge generation function," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201305, University of Turin.
    11. Pierre-Alexandre Balland & David L. Rigby, 2015. "The geography and evolution of complex knowledge," Papers in Evolutionary Economic Geography (PEEG) 1502, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jan 2015.
    12. Kolja Hesse & Dirk Fornahl, 2020. "Essential ingredients for radical innovations? The role of (un‐)related variety and external linkages in Germany," Papers in Regional Science, Wiley Blackwell, vol. 99(5), pages 1165-1183, October.
    13. Frank Neffke & Martin Svensson Henning, 2009. "Skill-relatedness and firm diversification," Papers on Economics and Evolution 2009-06, Philipps University Marburg, Department of Geography, revised Oct 2010.
    14. Ron Boschma & Ernest Miguelez & Rosina Moreno & Diego B. Ocampo-Corrales, 2021. "Technological breakthroughs in European regions: the role of related and unrelated combinations," Papers in Evolutionary Economic Geography (PEEG) 2118, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jun 2021.
    15. Konstantin Fursov & Alina Kadyrova, 2017. "How the analysis of transitionary references in knowledge networks and their centrality characteristics helps in understanding the genesis of growing technology areas," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1947-1963, June.
    16. Cristiano Antonelli & Alessandra Colombelli, 2018. "The cost of knowledge," Chapters, in: The Evolutionary Complexity of Endogenous Innovation, chapter 6, pages 128-150, Edward Elgar Publishing.
    17. Alessandra Colombelli & Francesco Quatraro, 2014. "The persistence of firms' knowledge base: a quantile approach to Italian data," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 23(7), pages 585-610, October.
    18. Porter, Alan L. & Garner, Jon & Carley, Stephen F. & Newman, Nils C., 2019. "Emergence scoring to identify frontier R&D topics and key players," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 628-643.
    19. Pierre-Alexandre Balland & Ron Boschma & Joan Crespo & David L. Rigby, 2017. "Smart Specialization policy in the EU: Relatedness, Knowledge Complexity and Regional Diversification," Papers in Evolutionary Economic Geography (PEEG) 1717, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jul 2017.
    20. Ron Boschma & Pierre-Alexandre Balland & Dieter Franz Kogler, 2015. "Relatedness and technological change in cities: the rise and fall of technological knowledge in US metropolitan areas from 1981 to 2010," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 24(1), pages 223-250.

    More about this item

    Keywords

    technological diffusion; patents; knowledge;
    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
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ipt:wpaper:201607. 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: Publication Officer (email available below). General contact details of provider: https://edirc.repec.org/data/ipjrces.html .

    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.