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Treating patent as relational data: Knowledge transfers and spillovers across Italian provinces


  • Mario A. Maggioni


  • Teodora Erika Uberti


  • Stefano Usai



The paper adopts a new perspective to investigate the characteristics of innovation clusters within and across Italian NUTS3 regions (province). Patents are used as relational data connecting inventors to applicants along a dual interpretation of a “knowledge production” and a “knowledge utilization” function. The paper intends to map and measure the structure and the evolution of a series of innovation sub-systems (both at territorial level and at the industry level) in two different periods of time, 1987-1991 and 1997-2001 to detect how networks of inventors and applicants have changed over time. The paper uses the CRENoS database on regional patenting, built on EPO data, spanning from 1978 to 2001 and uses two complementary analytical tools (network analysis and spatial econometrics) in order to analyse the behaviours of inventors and applicants within 103 Italian NUTS3 regions (province) and 5 specific industries chosen according to the Pavitt’s taxonomy (Footwear, Textiles, Chemicals, Personal Computers and Machine). The paper deals with the following research questions. Is the polarisation of the geographical structure of the innovative activity in Italy, replicated both at the inventors and at the applicant level? Which are the relevant changes in the 20 years? Can we distinguish between a “knowledge production function” and a “knowledge utilisation function”? Which is the structure of knowledge flows between inventors and applicants in Italian provinces? Are there industry-specific differences? Which are the determinants of the knowledge flows between Italian provinces?

Suggested Citation

  • Mario A. Maggioni & Teodora Erika Uberti & Stefano Usai, 2008. "Treating patent as relational data: Knowledge transfers and spillovers across Italian provinces," DISEIS - Quaderni del Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo dis0802, Università Cattolica del Sacro Cuore, Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo (DISEIS).
  • Handle: RePEc:dis:wpaper:dis0802

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    References listed on IDEAS

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    Cited by:

    1. Francesco Bogliacino & Mario Pianta, 2016. "The Pavitt Taxonomy, revisited: patterns of innovation in manufacturing and services," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 33(2), pages 153-180, August.
    2. Mirko Titze & Matthias Brachert, 2014. "European Cluster Networks ? Insights from 7th EU Framework Program," ERSA conference papers ersa14p552, European Regional Science Association.
    3. D'Ambrosio, Anna & Montresor, Sandro & Parrilli, Mario Davide & Quatraro, Francesco, 2017. "Migration, communities-on-the-move and international innovation networks: An empirical analysis of Spanish regions," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201701, University of Turin.
    4. Raffaele Paci & Emanuela Marrocu & Stefano Usai, 2014. "The Complementary Effects of Proximity Dimensions on Knowledge Spillovers," Spatial Economic Analysis, Taylor & Francis Journals, vol. 9(1), pages 9-30, March.
    5. Martina Fromhold-Eisebith & Claudia Werker, 2013. "Universities’ functions in knowledge transfer: a geographical perspective," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 51(3), pages 621-643, December.
    6. Stefano Usai & Emanuela Marrocu & Raffaele Paci, 2017. "Networks, Proximities, and Interfirm Knowledge Exchanges," International Regional Science Review, , vol. 40(4), pages 377-404, July.
    7. Jackie Krafft & Francesco Quatraro & Pier Paolo Saviotti, 2014. "The Dynamics of Knowledge-intensive Sectors' Knowledge Base: Evidence from Biotechnology and Telecommunications," Industry and Innovation, Taylor & Francis Journals, vol. 21(3), pages 215-242, April.
    8. repec:taf:regstd:v:51:y:2017:i:8:p:1246-1258 is not listed on IDEAS
    9. Sun, Yutao, 2016. "The structure and dynamics of intra- and inter-regional research collaborative networks: The case of China (1985–2008)," Technological Forecasting and Social Change, Elsevier, vol. 108(C), pages 70-82.
    10. Favaro, Donata & Ninka, Eniel & Turvani, Margherita, 2012. "Productivity in innovation: the role of inventor connections and mobility," MPRA Paper 38950, University Library of Munich, Germany.
    11. Yutao Sun & Kai Liu, 2016. "Proximity effect, preferential attachment and path dependence in inter-regional network: a case of China’s technology transaction," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 201-220, July.
    12. Francesco Quatraro & Stefano Usai, 2017. "Are knowledge flows all alike? Evidence from European regions," Regional Studies, Taylor & Francis Journals, vol. 51(8), pages 1246-1258, August.
    13. Favaro, Donata & Ninka, Eniel & Turvani, Margherita, 2014. "Knowledge externalities and knowledge creation: the role of inventors’ working relationships and mobility," MPRA Paper 64527, University Library of Munich, Germany.
    14. Marrocu, Emanuela & Paci, Raffaele & Usai, Stefano, 2013. "Proximity, networking and knowledge production in Europe: What lessons for innovation policy?," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1484-1498.
    15. Mario Maggioni & Teodora Uberti, 2011. "Networks and geography in the economics of knowledge flows," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(5), pages 1031-1051, August.
    16. Mario Maggioni & Teodora Uberti & Mario Nosvelli, 2014. "Does intentional mean hierarchical? Knowledge flows and innovative performance of European regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(2), pages 453-485, September.

    More about this item


    patents; Italian innovation system; gravity equation; spatial econometrics;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives


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