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How fast is this novel technology going to be a hit? Antecedents predicting follow-on inventions

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  • Michele Pezzoni
  • Reinhilde Veugelers
  • Fabiana Visentin

Abstract

Despite the high interest of scholars in identifying successful inventions, little attention has been devoted to investigate how (fast) the novel ideas embodied in original inventions are re-used in follow-on inventions. We overcome this limitation by empirically mapping and characterizing the trajectory of novel technologies’ re-use in follow-on inventions. Specifically, we consider the factors affecting the time needed for a novel technology to be legitimated as well as to reach its full technological impact. We analyze how these diffusion dynamics are affected by the antecedent characteristics of the novel technology. We characterize novel technologies as those that make new combinations with existing technological components and trace these new combinations in follow-on inventions. We find that novel technologies combining for the first time technological components which are similar and which are familiar to the inventors’ community require a short time to be legitimated but show a low technological impact. In contrast, combining for the first time technological components with a science-based nature generates technologies with a long legitimation time but also high technological impact.

Suggested Citation

  • Michele Pezzoni & Reinhilde Veugelers & Fabiana Visentin, 2019. "How fast is this novel technology going to be a hit? Antecedents predicting follow-on inventions," Working Papers of Department of Management, Strategy and Innovation, Leuven 634946, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
    • Handle: RePEc:ete:msiper:634946
    Note: paper number MSI_1903
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    Cited by:

    1. Sam Arts & Nicola Melluso & Reinhilde Veugelers, 2023. "Beyond Citations: Measuring Novel Scientific Ideas and their Impact in Publication Text," Papers 2309.16437, arXiv.org, revised Oct 2024.
    2. Corvello, Vincenzo & Belas, Jaroslav & Giglio, Carlo & Iazzolino, Gianpaolo & Troise, Ciro, 2023. "The impact of business owners’ individual characteristics on patenting in the context of digital innovation," Journal of Business Research, Elsevier, vol. 155(PA).
    3. Matthias Niggli & Christian Rutzer, 2023. "Digital technologies, technological improvement rates, and innovations “Made in Switzerland”," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-31, December.
    4. Jie Liu, 2024. "“Divergent” cross-domain stretching for technology fusion: validating the knowledge partition search model using patent data," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3023-3043, June.
    5. Deyu Li & Floor Alkemade & Koen Frenken & Gaston Heimeriks, 2023. "Catching up in clean energy technologies: a patent analysis," The Journal of Technology Transfer, Springer, vol. 48(2), pages 693-715, April.
    6. Matte Hartog & Andres Gomez-Lievano & Ricardo Hausmann & Frank Neffke, 2024. "Inventing modern invention: the professionalization of technological progress in the US," Papers in Evolutionary Economic Geography (PEEG) 2408, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Apr 2024.

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    More about this item

    Keywords

    technological novelty; diffusion; combinatorial components; patent data;
    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

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