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ICT: A new taxonomy based on the international patent classification

Author

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  • Takashi Inaba
  • Mariagrazia Squicciarini

Abstract

This work proposes a definition of Information and Communication Technologies (ICT) based on the technology classes of the International Patent Classification (IPC) in which patents are classified. This new taxonomy, called the “J tag”, aligns with the definitions of the ICT sector (2007) and of ICT products (2008) put forward by the OECD, and stems from the in-depth knowledge of Japan Patent Office experts, as well of experts from the Intellectual Property (IP) Offices participating in the OECD-led IP Task Force. Expert judgment of patent class content, relevance for ICT-related products, completeness and accuracy are the principles guiding the inclusion of IPC classes in the “J tag” taxonomy. ICT technologies are subdivided into 13 areas defined with respect to the specific technical features and functions they are supposed to accomplish (e.g. mobile communication), and details provided about the ways in which technologies relate to ICT products.

Suggested Citation

  • Takashi Inaba & Mariagrazia Squicciarini, 2017. "ICT: A new taxonomy based on the international patent classification," OECD Science, Technology and Industry Working Papers 2017/1, OECD Publishing.
    • Handle: RePEc:oec:stiaaa:2017/1-en
    DOI: 10.1787/ab16c396-en
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    1. Kangas, H.L. & Ollikka, K. & Ahola, J. & Kim, Y., 2021. "Digitalisation in wind and solar power technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    2. Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021. "Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data," Working Papers of Department of Economics, Leuven 674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    3. Damioli, Giacomo & Van Roy, Vincent & Vertesy, Daniel & Vivarelli, Marco, 2021. "May AI Revolution Be Labour-Friendly? Some Micro Evidence from the Supply Side," IZA Discussion Papers 14309, Institute of Labor Economics (IZA).
    4. Igna, Ioana & Venturini, Francesco, 2023. "The determinants of AI innovation across European firms," Research Policy, Elsevier, vol. 52(2).
    5. Davide Consoli & Fabrizio Fusillo & Gianluca Orsatti & Francesco Quatraro, 2021. "Skill endowment, routinisation and digital technologies: evidence from U.S. Metropolitan Areas," Industry and Innovation, Taylor & Francis Journals, vol. 28(8), pages 1017-1045, September.
    6. Yang, Senmiao & Wang, Jianda & Dong, Kangyin & Jiang, Qingzhe, 2023. "A path towards China's energy justice: How does digital technology innovation bring about a just revolution?," Energy Economics, Elsevier, vol. 127(PA).
    7. Ekaterina Prytkova, 2021. "ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links," Jena Economics Research Papers 2021-005, Friedrich-Schiller-University Jena.
    8. Van Roy, Vincent & Vertesy, Daniel & Damioli, Giacomo, 2019. "AI and Robotics Innovation: a Sectoral and Geographical Mapping using Patent Data," GLO Discussion Paper Series 433, Global Labor Organization (GLO).
    9. 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.
    10. Matteo Laffi & Ron Boschma, 2022. "Does a local knowledge base in Industry 3.0 foster diversification in Industry 4.0 technologies? Evidence from European regions," Papers in Regional Science, Wiley Blackwell, vol. 101(1), pages 5-35, February.
    11. Werner Hölzl & Susanne Bärenthaler-Sieber & Julia Bock-Schappelwein & Klaus S. Friesenbichler & Agnes Kügler & Andreas Reinstaller & Peter Reschenhofer & Bernhard Dachs & Martin Risak, 2019. "Digitalisation in Austria. State of Play and Reform Needs," WIFO Studies, WIFO, number 61892, April.
    12. Giacomo Damioli & Vincent Van Roy & Daniel Vertesy & Marco Vivarelli, 2021. "Detecting the labour-friendly nature of AI product innovation," DISCE - Quaderni del Dipartimento di Politica Economica dipe0017, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    13. Damioli, Giacomo & Van Roy, Vincent & Vertesy, Daniel & Vivarelli, Marco, 2021. "Will the AI revolution be labour-friendly? Some micro evidence from the supply side," MERIT Working Papers 2021-016, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    14. Foster-McGregor, Neil & Nomaler, Onder & Verspagen, Bart, 2019. "Measuring the creation and adoption of new technologies using trade and patent data," MERIT Working Papers 2019-053, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    15. Rammer, Christian & Fernández, Gastón P. & Czarnitzki, Dirk, 2022. "Artificial intelligence and industrial innovation: Evidence from German firm-level data," Research Policy, Elsevier, vol. 51(7).
    16. Simone Vannuccini & Ekaterina Prytkova, 2021. "Artificial Intelligence’s New Clothes? From General Purpose Technology to Large Technical System," SPRU Working Paper Series 2021-02, SPRU - Science Policy Research Unit, University of Sussex Business School.

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