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Patent portfolio analysis of cities: statistics and maps of technological inventiveness

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  • Dieter Franz Kogler
  • Gaston Heimeriks
  • Loet Leydesdorff

Abstract

Cities can be considered as engines of the knowledge-based economy, because they are the primary sites of knowledge production activities that subsequently shape the rate and direction of technological change and economic growth. Patents provide rich information to analyse the knowledge specialization of specific places, such as technological details and information on inventors and entities involved. The technology codes attributed at the level of individual patent documents can be used to indicate the diversity and scope of the knowledge claims underlying a specific invention. In this study we introduce tools for portfolio analysis in terms of patents that provide insights into the technological specialization of cities. The mapping and analysis of patent portfolios of cities exploits data derived from the Unites States Patent and Trademark Office (USPTO) and dedicated tools (at https://leydesdorff.net/software/patents/). The results allow policy makers and other stakeholders to identify promising areas of further knowledge development, including smart specialization strategies.

Suggested Citation

  • Dieter Franz Kogler & Gaston Heimeriks & Loet Leydesdorff, 2018. "Patent portfolio analysis of cities: statistics and maps of technological inventiveness," European Planning Studies, Taylor & Francis Journals, vol. 26(11), pages 2256-2278, November.
    • Handle: RePEc:taf:eurpls:v:26:y:2018:i:11:p:2256-2278
    DOI: 10.1080/09654313.2018.1530147
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    Citations

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    Cited by:

    1. Keungoui Kim & Alberto Nonnis & Altay Özaygen & Dieter F. Kogler, 2023. "Green-tech firm creation in Germany: the role of regional knowledge," International Entrepreneurship and Management Journal, Springer, vol. 19(1), pages 97-120, March.
    2. Bernardo S Buarque & Ronald B Davies & Ryan M Hynes & Dieter F Kogler, 2020. "OK Computer: the creation and integration of AI in Europe," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 175-192.
    3. Alina Irina Popescu, 2020. "Long-Term City Innovation Trajectories and Quality of Urban Life," Sustainability, MDPI, vol. 12(24), pages 1-19, December.
    4. Giambattista Albora & Matteo Straccamore & Andrea Zaccaria, 2024. "Machine learning-based similarity measure to forecast M&A from patent data," Papers 2404.07179, arXiv.org.
    5. Ekaterina Streltsova & Gleb Kuzmin, 2019. "Russian Technograds: The Technological Profiles of the Cities," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 13(3), pages 41-49.
    6. Hongjun Sun & Zuoxiang Zhao & Ding Han, 2024. "Growth Models and Influencing Mechanisms of Total Factor Productivity in China’s National High-Tech Zones," Sustainability, MDPI, vol. 16(8), pages 1-19, April.
    7. Xiaodong Yuan & Xiaotao Li, 2022. "Pledging Patent Rights for Fighting Against the COVID-19: From the Ethical and Efficiency Perspective," Journal of Business Ethics, Springer, vol. 179(3), pages 683-696, September.

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