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Modelling Multiple Interactions in Science and Technology Networks

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  • Domenico De Stefano
  • Susanna Zaccarin

Abstract

Empirical studies have shown that the extent of innovation diffusion is greatly affected by the structure of the network in which innovation processes take place. This contribution aims to identify the complex structure of relationships at the basis of knowledge and innovation diffusion among actors from various organizations (firms, academic and research institutions) in a given territory. A multiplex approach is proposed to explain co-authorship and co-invention interaction among Author--Inventors community in a specific geographic area. To this end, we carry out a case study of the Trieste area (North-East Italy), characterized by a very high concentration of research organizations and by the emergence of a lively sector of small R&D firms.

Suggested Citation

  • Domenico De Stefano & Susanna Zaccarin, 2013. "Modelling Multiple Interactions in Science and Technology Networks," Industry and Innovation, Taylor & Francis Journals, vol. 20(3), pages 221-240, April.
    • Handle: RePEc:taf:indinn:v:20:y:2013:i:3:p:221-240
    DOI: 10.1080/13662716.2013.791130
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    3. Abbasiharofteh, Milad & Kogler, Dieter F. & Lengyel, Balázs, 2023. "Atypical combinations of technologies in regional co-inventor networks," Research Policy, Elsevier, vol. 52(10).
    4. Erlend Osland Simensen & Milad Abbasiharofteh, 2022. "Sectoral patterns of collaborative tie formation: investigating geographic, cognitive, and technological dimensions [Endogenous effects and cluster transition: a conceptual framework for cluster po," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 31(5), pages 1223-1258.
    5. Santini, Mateus Augusto Fassina & Faccin, Kadígia & Balestrin, Alsones & Volkmer Martins, Bibiana, 2021. "How the relational structure of universities influences research and development results," Journal of Business Research, Elsevier, vol. 125(C), pages 155-163.
    6. Hermans, Frans, 2021. "The contribution of statistical network models to the study of clusters and their evolution," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 100(2), pages 379-403.
    7. Saveria Capellari & Domenico Stefano, 2014. "University-owned and university-invented patents: a network analysis on two Italian universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 313-329, May.
    8. Abbasiharofteh, Milad, 2020. "Endogenous effects and cluster transition: a conceptual framework for cluster policy," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 28(12), pages 2508-2531.
    9. Sándor Juhász, 2021. "Spinoffs and tie formation in cluster knowledge networks," Small Business Economics, Springer, vol. 56(4), pages 1385-1404, April.
    10. Wei, Shanting & Zhang, Zhuo & Ke, Ginger Y. & Chen, Xintong, 2019. "The more cooperation, the better? Optimizing enterprise cooperative strategy in collaborative innovation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    11. Angelou, K. & Maragakis, M. & Kosmidis, K. & Argyrakis, P., 2021. "The evolution of triangular research and innovation collaborations in the European area," Journal of Informetrics, Elsevier, vol. 15(3).

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