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Inventions shaping technological trajectories: do existing patent indicators provide a comprehensive picture?

Author

Listed:
  • Sam Arts

    (Faculty of Business and Economics, KU Leuven
    FWO)

  • Francesco Paolo Appio

    (Scuola Superiore Sant’Anna, Istituto di Management)

  • Bart Looy

    (Faculty of Business and Economics, KU Leuven
    Expertisecentrum O&O Monitoring (ECOOM) and Research Division INCENTIM, KU Leuven
    School of Management and Governance, University of Twente)

Abstract

Since Schumpeter’s (The theory of economic development, 1934) seminal work on economic development, innovation is considered as one of the main drivers of firm performance and economic growth. At the same time, technological innovations vary considerably in terms of impact with only a minority of new inventions contributing significantly to technological progress and economic growth. More recently a number of indicators derived from patent documents have been advanced to capture the nature and impact of technological inventions. In this paper, we compare and validate these indicators within the field of biotechnology. An extensive analysis of the recent history of biotechnology allows us to identify the most important inventions (n = 214) that shaped the field of biotechnology in the time period 1976–2001. A considerable number of these inventions have been patented between 1976 and 2001 (n = 117, 55 %). For all USPTO biotech patents filed between 1976 and 2001 (n = 84,119), relevant indicators have been calculated. In a subsequent step, we assess which indicators allow us to distinguish between the most important patented inventions and their less influential counterparts by means of logistic regression models. Our findings show that the use of multiple, complementary indicators provides the most comprehensive picture. In addition, it is clear that ex-post indicators reflecting impact and value outperform ex-ante indicators reflecting the nature and novelty of the invention in terms of precision and recall.

Suggested Citation

  • Sam Arts & Francesco Paolo Appio & Bart Looy, 2013. "Inventions shaping technological trajectories: do existing patent indicators provide a comprehensive picture?," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 397-419, November.
  • Handle: RePEc:spr:scient:v:97:y:2013:i:2:d:10.1007_s11192-013-1045-1
    DOI: 10.1007/s11192-013-1045-1
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    3. Verhoeven, Dennis & Bakker, Jurriën & Veugelers, Reinhilde, 2016. "Measuring technological novelty with patent-based indicators," Research Policy, Elsevier, vol. 45(3), pages 707-723.
    4. Bernardo Caldarola & Dario Mazzilli & Lorenzo Napolitano & Aurelio Patelli & Angelica Sbardella, 2023. "Economic complexity and the sustainability transition: A review of data, methods, and literature," Papers 2308.07172, arXiv.org, revised Mar 2024.
    5. Francesco de Cunzo & Alberto Petri & Andrea Zaccaria & Angelica Sbardella, 2022. "The trickle down from environmental innovation to productive complexity," Papers 2206.07537, arXiv.org.
    6. Jurriën Bakker & Dennis Verhoeven & Lin Zhang & Bart Van Looy, 2016. "Patent citation indicators: One size fits all?," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 187-211, January.
    7. Nils Grashof & Alexander Kopka, 2023. "Artificial intelligence and radical innovation: an opportunity for all companies?," Small Business Economics, Springer, vol. 61(2), pages 771-797, August.
    8. Francesco Paolo Appio & Luigi de Luca & Robert Morgan & Antonella Martini, 2019. "Patent portfolio diversity and firm profitability: A question of specialization or diversification?," Post-Print halshs-02292360, HAL.
    9. Manuel Acosta & Daniel Coronado & Esther Ferrándiz & Manuel Jiménez, 2022. "Effects of knowledge spillovers between competitors on patent quality: what patent citations reveal about a global duopoly," The Journal of Technology Transfer, Springer, vol. 47(5), pages 1451-1487, October.
    10. Ardito, Lorenzo & Petruzzelli, Antonio Messeni & Ghisetti, Claudia, 2019. "The impact of public research on the technological development of industry in the green energy field," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 25-35.
    11. 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.
    12. 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.
    13. Angelica Sbardella & Andrea Zaccaria & Luciano Pietronero & Pasquale Scaramozzino, 2021. "Behind the Italian Regional Divide: An Economic Fitness and Complexity Perspective," LEM Papers Series 2021/30, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    14. Jip Leendertse & Frank J. van Rijnsoever & Chris P. Eveleens, 2021. "The sustainable start‐up paradox: Predicting the business and climate performance of start‐ups," Business Strategy and the Environment, Wiley Blackwell, vol. 30(2), pages 1019-1036, February.
    15. Michele Pezzoni & Reinhilde Veugelers & Fabiana Visentin, 2018. "Is This Novel Technology Going to be a Hit? Antecedents Predicting Technological Novelty Diffusion," GREDEG Working Papers 2018-22, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    16. Waßenhoven, Anna & Rennings, Michael & Laibach, Natalie & Bröring, Stefanie, 2023. "What constitutes a “Key Enabling Technology” for transition processes: Insights from the bioeconomy's technological landscape," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    17. Christopher L Benson & Christopher L Magee, 2015. "Quantitative Determination of Technological Improvement from Patent Data," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-23, April.
    18. Louis Knuepling & Colin Wessendorf & Stefano Basilico, 2022. "Revisiting innovation typology: A systemic approach," Jena Economics Research Papers 2022-002, Friedrich-Schiller-University Jena.
    19. Kim, Nami & Kim, Eonsoo & Lee, Jongseon, 2021. "Innovating by eliminating: Technological resource divestiture and firms’ innovation performance," Journal of Business Research, Elsevier, vol. 123(C), pages 176-187.
    20. Appio, Francesco Paolo & Baglieri, Daniela & Cesaroni, Fabrizio & Spicuzza, Lucia & Donato, Alessia, 2022. "Patent design strategies: Empirical evidence from European patents," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    21. Scaringella, Laurent & Miles, Raymond E. & Truong, Yann, 2017. "Customers involvement and firm absorptive capacity in radical innovation: The case of technological spin-offs," Technological Forecasting and Social Change, Elsevier, vol. 120(C), pages 144-162.
    22. Francesco de Cunzo & Davide Consoli & Francois Perruchas & Angelica Sbardella, 2023. "Mapping Critical Raw Materials in Green Technologies," Papers in Evolutionary Economic Geography (PEEG) 2322, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Dec 2023.
    23. Veugelers, Reinhilde & Pezzoni, Michele, 2019. "How fast is this novel technology going to be a hit?," CEPR Discussion Papers 13447, C.E.P.R. Discussion Papers.
    24. Noh, Heeyong & Lee, Sungjoo, 2020. "What constitutes a promising technology in the era of open innovation? An investigation of patent potential from multiple perspectives," Technological Forecasting and Social Change, Elsevier, vol. 157(C).

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