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Patenting in 4IR Technologies and Firm Performance

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We investigate whether firm performance is related to the accumulated stock of technological knowledge associated with the Fourth Industrial Revolution (4IR) and, if so, whether the firm’s history in 4IR technology development affects such a relationship. We exploit a rich longitudinal matched patent-firm data set on the population of large firms that filed 4IR patents at the European Patent Office (EPO) between 2009 and 2014, while reconstructing their patent stocks from 1985 onwards. To identify 4IR patents, we use a novel two-step procedure proposed by EPO (2020), based on Cooperative Patent Classification (CPC) codes and on a full-text patent search. Our results show a positive and significant relationship between firms’ stocks of 4IR patents and labour and total factor productivity. We also find that firms with a long history in 4IR patent filings benefit more from the development of 4IR technological capabilities than later applicants. Conversely, we find that firm profitability is not significantly related to the stock of 4IR patents, which suggests that the returns from 4IR technological developments may be slow to be cashed in. Finally, we find that the positive relationship with productivity is stronger for 4IR-related wireless technology and for AI, cognitive computing and big data analytics.

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  • BENASSI Mario & GRINZA Elena & RENTOCCHINI Francesco & RONDI Laura, 2021. "Patenting in 4IR Technologies and Firm Performance," JRC Working Papers on Corporate R&D and Innovation 2021-01, Joint Research Centre.
    • Handle: RePEc:ipt:wpaper:202101
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    2. Cambini, Carlo & Grinza, Elena & Sabatino, Lorien, 2023. "Ultra-fast broadband access and productivity: Evidence from Italian firms," International Journal of Industrial Organization, Elsevier, vol. 86(C).
    3. Stan Metcalfe, 2024. "Joseph Schumpeter, Alfred Marshall and the nature of restless capitalism," MIOIR Working Paper Series 2024-02, The Manchester Institute of Innovation Research (MIoIR), The University of Manchester.
    4. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
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    6. Jiang, Cuiqing & Zhou, Yiru & Chen, Bo, 2023. "Mining semantic features in patent text for financial distress prediction," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    7. Davide Antonioli & Alberto Marzucchi & Francesco Rentocchini & Simone Vannuccini, 2024. "Robot Adoption and Product Innovation," GREDEG Working Papers 2024-01, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.

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    Keywords

    Fourth Industrial Revolution (4IR); patent applications; technology development; firm performance; longitudinal matched patent-firm data; Industry 4.0;
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