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Knowledge patterns and sources of leadership: Mapping the semiconductor miniaturization trajectory

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  • Marianna Epicoco

    (BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - Université de Haute-Alsace (UHA) - Université de Haute-Alsace (UHA) Mulhouse - Colmar - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

This article examines the technological capabilities that national organizations generated and accumulated throughout the long-term evolution of the miniaturization trajectory, the main direction of technological change in the semiconductor industry. Having built an original dataset of patents granted between 1976 and 2008, and using three algorithms for the analysis of citation networks, we first map the pattern of technological knowledge underlying the advancement of the miniaturization trajectory. We identify three different dimensions of that pattern and characterize them in terms of distinctive knowledge properties. Second, we analyse the geographical and organizational distribution of the knowledge pattern. The results provide evidence of significant differences in the technological capabilities of national organizations, as revealed by the magnitude and properties of the technological knowledge that those organizations generated over time. We find, inter alia, that while US organizations remained strong throughout the whole time period, the capabilities of European organizations were considerably eroded in the most recent years by the emergence of latecomer Asian countries like South Korea and Taiwan.

Suggested Citation

  • Marianna Epicoco, 2013. "Knowledge patterns and sources of leadership: Mapping the semiconductor miniaturization trajectory," Post-Print hal-03381305, HAL.
  • Handle: RePEc:hal:journl:hal-03381305
    DOI: 10.1016/j.respol.2012.06.009
    Note: View the original document on HAL open archive server: https://hal.univ-lorraine.fr/hal-03381305
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    References listed on IDEAS

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    2. Jean-Claude Boldrini & Nathalie Schieb-Bienfait, 2015. "Collectively exploring the potential of technology derived from university research: the NanoMem case," Working Papers hal-01208517, HAL.
    3. Huenteler, Joern & Ossenbrink, Jan & Schmidt, Tobias S. & Hoffmann, Volker H., 2016. "How a product’s design hierarchy shapes the evolution of technological knowledge—Evidence from patent-citation networks in wind power," Research Policy, Elsevier, vol. 45(6), pages 1195-1217.
    4. Mariani, Manuel Sebastian & Medo, Matúš & Lafond, François, 2019. "Early identification of important patents: Design and validation of citation network metrics," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 644-654.
    5. Benjamin Cabanes & Pascal Le Masson & Benoît Weil, 2020. "Organiser la création de connaissance pour l’innovation de rupture. Des communautés aux sociétés proto-épistémiques d’experts," Revue française de gestion, Lavoisier, vol. 0(3), pages 35-60.
    6. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2019. "A few notes on main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 379-391, April.
    7. Flavia Filippin, 2021. "Do main paths reflect technological trajectories? Applying main path analysis to the semiconductor manufacturing industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6443-6477, August.
    8. Sepideh Kaffash & Marianna Marra, 2017. "Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds," Annals of Operations Research, Springer, vol. 253(1), pages 307-344, June.
    9. Huenteler, Joern & Schmidt, Tobias S. & Ossenbrink, Jan & Hoffmann, Volker H., 2016. "Technology life-cycles in the energy sector — Technological characteristics and the role of deployment for innovation," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 102-121.
    10. 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.
    11. Huang, Ying & Chen, Lixin & Zhang, Lin, 2020. "Patent citation inflation: The phenomenon, its measurement, and relative indicators to temper its effects," Journal of Informetrics, Elsevier, vol. 14(2).
    12. Nicolò Barbieri & Claudia Ghisetti & Marianna Gilli & Giovanni Marin & Francesco Nicolli, 2016. "A Survey Of The Literature On Environmental Innovation Based On Main Path Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 30(3), pages 596-623, July.
    13. Jakob Hoffmann & Johannes Glückler, 2023. "Technological Cohesion and Convergence: A Main Path Analysis of the Bioeconomy, 1900–2020," Sustainability, MDPI, vol. 15(16), pages 1-17, August.
    14. Ávila-Robinson, Alfonso & Islam, Nazrul & Sengoku, Shintaro, 2019. "Co-evolutionary and systemic study on the evolution of emerging stem cell-based therapies," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 324-339.
    15. Martin Ho & Henry CW Price & Tim S Evans & Eoin O'Sullivan, 2023. "Order in Innovation," Papers 2302.13076, arXiv.org.
    16. Marianna Epicoco, 2016. "Patterns of innovation and organizational demography in emerging sustainable fields: An analysis of the chemical sector," Post-Print hal-03381224, HAL.
    17. Blandinieres, Florence, 2019. "Anatomy of the medical innovation process: What are the consequences of replicability issues on innovation?," ZEW Discussion Papers 19-011, ZEW - Leibniz Centre for European Economic Research.
    18. Chen, Lixin, 2017. "Do patent citations indicate knowledge linkage? The evidence from text similarities between patents and their citations," Journal of Informetrics, Elsevier, vol. 11(1), pages 63-79.
    19. Fang Han & Sejun Yoon & Nagarajan Raghavan & Hyunseok Park, 2022. "Investigating Company’s Technical Development Directions Based on Internal Knowledge Inheritance and Inventor Capabilities: The Case of Samsung Electronics," Sustainability, MDPI, vol. 14(5), pages 1-19, March.

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