Literatura científica citada en patentes: Un indicador de Transferencia Tecnológica en las universidades portuguesas

Galvez, Carmen Literatura científica citada en patentes: Un indicador de Transferencia Tecnológica en las universidades portuguesas. RISTI - Revista Ibérica de Sistemas e Tecnologias de Informação, 2023, n. E63, pp. 134-148. [Journal article (Paginated)]

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Alternative locations: https://hdl.handle.net/10481/89166

English abstract

The study aims to identify the process of transfer from science to technology that occurs in the main Portuguese public universities. The methodology was based on the analysis of the scientific literature cited in patents. Data was obtained from the Lens patent database. 10,514 scientific articles cited in patents were retrieved. A descriptive analysis of the data was performed. Science maps were created to visualize the main research trends. The results showed a valuable impact of academic research in certain scientific disciplines, such as Chemistry, Biology, Materials Sciences and Medicine. The main research fronts were cancer, nanoparticles, biomaterials, tissue engineering or molecular biology. In conclusion, the research produced by Portuguese universities has generated relevant knowledge for patented inventions and the science-technology flow within specific areas.

Spanish abstract

El estudio tiene como objetivo identificar el proceso de transferencia de la ciencia a la tecnología que se produce en las principales universidades públicas portuguesas. La metodología se basó en el análisis de la literatura científica citada en patentes. Los datos se obtuvieron de la base de datos de patentes Lens. Se recuperaron 10.514 artículos científicos citados en patentes. Se realizó un análisis descriptivo de los datos. Se crearon mapas científicos para visualizar las principales tendencias de investigación. Los resultados mostraron una repercusión valiosa de la investigación académica en determinadas disciplinas científicas, como Química, Biología, Ciencias de los Materiales y Medicina. Los principales frentes de la investigación fueron el cáncer, las nanopartículas, los biomateriales, la ingeniería de tejidos o la biología molecular. En conclusión, la investigación producida por las universidades portuguesas ha generado conocimiento relevante para las invenciones patentadas y el flujo ciencia-tecnología dentro de sectores específicos.

Item type: Journal article (Paginated)
Keywords: Transferencia de tecnología; Evaluación de la Investigación; Patentes; Citas; Universidades; Portugal
Subjects: B. Information use and sociology of information > BA. Use and impact of information.
B. Information use and sociology of information > BB. Bibliometric methods
B. Information use and sociology of information > BG. Information dissemination and diffusion.
Depositing user: Carmen Galvez
Date deposited: 14 Apr 2025 14:39
Last modified: 14 Apr 2025 14:39
URI: http://hdl.handle.net/10760/46521

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References

Acosta Seró, M., & Coronado Guerrero, D. (2002). Las relaciones ciencia-tecnología en España. Evidencias a partir de las citas científicas en patentes. Economía Industrial, 346, 27-46.

Aria, M., & Cuccurullo C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007

Börner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37, 179-255. https://doi.org/10.1002/aris.1440370106

Callaert, J., Landoni, P., Van Looy, B., & Verganti, R (2015). Scientific yield from collaboration with industry: The relevance of researchers’ strategic approaches. Research Policy, 44(4), 990-998. https://doi.org/10.1016/j.respol.2015.02.003

Callaert, J., Van Looy, B., Verbeek, A., DeBackere, K., & Thijs, B. (2006). Traces of Prior Art: An analysis of non-patent references found in patent documents. Scientometrics, 69, 3-20.

Callon, M., Courtial, J., & Penan, H. (1995). Cienciometría. Gijón: Trea.

Dias Daniel, A., & Alves, L. (2020). University-industry technology transfer: The commercialization of university’s patents. Knowledge Management Research & Practice, 18(3), 276-296. https://doi.org/10.1080/14778238.2019.1638741

Etzkowitz, H., Webster, A., & Healy, P. (1998). Capitalizing Knowledge: New Intersections of Industry and Academia. State University of New York Press, New York.

García-Escudero Márquez, P., & López López, P. (1997). Análisis bibliométrico y literatura de patentes. Revista General de Información y Documentación, 7(2), 181-199.

Greenacre, M., & Blasius, J. (Eds.). (2006). Multiple correspondence analysis and related methods. CRC Press. Londres, Chapman & Hall/CRC Press.

Harhoff, D., Narin, F., Scherer, F. M., & Vopel, K. (1999). Citation frequency and the value of patented inventions. Review of Economics and Statistics, 81, 511-515.

Harhoff, D., Scherer, F. M., & Katrin Vopel, K. (2003). Citations, family size, opposition and the value of patent rights. Research Policy, 32(8), 1343-1363. https://doi.org/10.1016/S0048-7333(02)00124-5

Jaffe, A. B., & Trajtenberg, M. (2002). Patents, citations, and innovations: A window on the knowledge economy. Cambridge, MA: MIT Press.

Jaffe, A. B., Trajtenberg, M., & Fogarty, M. S. (2000). Knowledge spillovers and patent citations: Evidence from a survey of inventors. American Economic Review, 90(2), 215-218. https://doi.org/10.1257/aer.90.2.215

Kim, D., & Kim, J. (2021). Is innovation design-or technology-driven? Citation as a measure of innovation pollination. World Patent Information, 64(102010). https://doi.org/10.1016/j.wpi.2020.102010

Leydesdorff, L., & Etzkowitz, H., (1998). Triple Helix of innovation: Introduction. Science and Public Policy, 25(6), 358-364.

Narin, F., & Olivastro, D. (1992). Status repor: Linkage between technology and science. Research Policy, 21(3), 237-249. https://doi.org/10.1016/0048-7333(92)90018-Y

Noruzi, A. (2022). Patent citations to journals: The innovation impact of the Lancet. Informology, 1(2), 1-10.

Noyons, E. C. M., Moed, H. F., & Van Raan, A. F. J. (1999). Integrating research performance analysis and science mapping. Scientometrics, 46, 591-604. DOI: https://doi.org/10.1007/BF02459614

Okubo, Y. (1997). Bibliometric Indicators and Analysis of Research Systems: Methods and Examples. OECD, Michigan.

Oldham, P., & Kitsara, I (2016). The WIPO Manual on Open Source Patent Analytics. World Intellectual Property Organization.

Rothaermel, F., Agung, S., & Jiang, L. (2007). University entrepreneurship: A taxonomy of the literature. Industrial and Corporate Change, 16(4), 691-791. https://doi.org/10.1093/icc/dtm023

Silverberg, G., & Verspagen, B. (2007). The size distribution of innovations revisited: An application of extreme value statistics to citation and value measures of patent significance. Journal of Econometrics, 139(2), 318-339. https://doi.org/10.1016/j.jeconom.2006.10.017

Van Eck, N. J., & Waltman, L. (2007). VOS: A new method for visualizing similarities between objects. In H. J. Lenz, & R. Decker (Eds.). Studies in classification, data analysis, and knowledge organization, (pp. 299-309). Springer, Berlin.

Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538.

Van Raan, A. F. J. (2017). Patent citations analysis and its value in research evaluation: A review and a new approach to map technology-relevant research. Journal of Data and Information Science, 2(1), 13-50. https://doi.org/10.1515/jdis-2017-0002

Velayos-Ortega, G., & López-Carreño, R. (2021). Google Patents versus Lens: citaciones de literatura científica en patentes. Revista General de Información y Documentación, 31(1), 303-316. https://dx.doi.org/10.5209/rgid.72257

Velayos-Ortega, G., & López-Carreño, R. (2023). Indicators for measuring the impact of scientific citations in patents. World Patent Information, 72, 102171. https://doi.org/10.1016/j.wpi.2023.102171

Waltman, L., Van Eck, N. J., & Noyons, E. C. M. (2010). A unified approach to mapping and clustering of bibliometric networks. Journal of Informetrics, 4(4), 629-635. https://doi.org/10.1016/j.joi.2010.07.002

Wang, M., Zhang, J., Jiao, S., & Zhang, T. (2019). Evaluating the impact of citations of articles based on knowledge flow patterns hidden in the citations. PloS one, 14(11): e0225276. https://doi.org/10.1371/journal.pone.0225276

Yamashita, Y. (2020). An attempt to identify technologically relevant papers based on their references. Scientometrics, 125, 1783-1800. https://doi.org/10.1007/s11192-020-03673-5

Yoon, B. (2010). Strategic visualisation tools for managing technological information. Technology Analysis & Strategic Management, 22(3), 377-397. https://doi.org/10.1080/09537321003647438

Zhang, Y., Qian, Y., Huang, Y., Guo, Y., Zhang, G., & Lu, J. (2017). An entropy-based indicator system for measuring the potential of patents in technological innovation: Rejecting moderation. Scientometrics, 111, 1925-1946. https://doi.org/10.1007/s11192-017-2337-7


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