Análisis estratégico de la producción científica española por campos: Ciencias Naturales, Médicas y de la Vida

Teodoro Luque-Martínez; Ignacio M. Luque-Raya

doi:10.3989/redc.2023.4.1409

Autores/as

Teodoro Luque-Martínez Departamento de Comercialización e Investigación de Mercados. Facultad de Ciencias Económicas y Empresariales. Universidad de Granada https://orcid.org/0000-0003-1282-6822
Ignacio M. Luque-Raya Departamento Comercialización e Investigación de Mercados. Facultad de Ciencias Sociales y Jurídicas de Melilla. Universidad de Granada https://orcid.org/0000-0003-3866-1958

DOI:

https://doi.org/10.3989/redc.2023.4.1409

Palabras clave:

Producción científica, ranking ARWU, universidades españolas, indicadores bibliométricos, ranking de especialidades

Resumen

La investigación es una misión fundamental de la universidad que determina la producción científica, que, a su vez, está asociada al desarrollo social y económico. Los indicadores bibliométricos proporcionan una medida de la producción científica. Por otro lado, la medida de dicha producción distinguiendo por campos y especialidades es mucho más útil y permite conocer interesantes detalles para la gestión, tanto de una universidad como de un sistema universitario. Utilizando los indicadores bibliométricos del ranking ARWU, se analiza por campos y especialidades con especial énfasis en las universidades españolas. Se identifican los puntos fuertes y débiles por especialidad en cuanto a volumen y calidad de la producción, impacto, reconocimiento y colaboración internacional, así como el posicionamiento internacional de las universidades españolas. De todo ello se derivan recomendaciones para la gestión.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

Allik, J. (2013). Factors affecting bibliometric indicators of scientific quality. Trames: A Journal of the Humanities and Social Sciences, 17(3), 199. https://doi.org/10.3176/tr.2013.3.01

Bornmann, L., y Leydesdorff, L. (2013a). The validation of (advanced) bibliometric indicators through peer assessments: A comparative study using data from InCites and F1000. Journal of Informetrics, 7(2), 286-291. https://doi.org/10.1016/j.joi.2012.12.003

Bornmann, L., y Leydesdorff, L. (2013b). Macro-indicators of citation impacts of six prolific countries: InCites data and the statistical significance of trends. PloS one, 8(2), e56768. https://doi.org/10.1371/journal.pone.0056768 PMid:23418600 PMCid:PMC3572076

Bornmann, L., y Mutz, R. (2015). Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references. Journal of the Association for Information Science and Technology, 66(11), 2215-2222. https://doi.org/10.1002/asi.23329

Bordons, M; Sancho, R.; Morillo, F.; Gómez, I. (2010) Perfil de la actividad científica de las universidades españolas en cuatro áreas temáticas: un enfoque multifactorial. Revista Española de Documentación Científica, 33 (1), 9-33. https://doi.org/10.3989/redc.2010.1.718

Chankseliani, M., Lovakov, A., y Pislyakov, V. (2021). A big picture: bibliometric study of academic publications from post-Soviet countries. Scientometrics, 126(10), 8701-8730. https://doi.org/10.1007/s11192-021-04124-5

Diem, A., y Wolter, S. C. (2013). The use of bibliometrics to measure research performance in education sciences. Research in higher education, 54(1), 86-114. https://doi.org/10.1007/s11162-012-9264-5

Docampo, D. (2010). On using the Shanghai ranking to assess the investigation performance of university systems. Scientometrics, 86 (1), 77-92. https://doi.org/10.1007/s11192-010-0280-y

Docampo, D. (2013). Reproducibility of the Shanghai academic ranking of world universities results. Scientometrics, 94(2), 567-587. https://doi.org/10.1007/s11192-012-0801-y

Etzkowitz, H., y Leydesdorff, L. (1998). The endless transition: A ''triple helix'' of university-industry-government relations. Minerva, 36, 203-208. https://doi.org/10.1023/A:1004348123030

Greco, A., Bornmann, L., y Marx, W. (2012). Bibliometric analysis of scientific development in countries of the Union of South American Nations (Unasur). Profesional de la Información, 21(6), 607-612. https://doi.org/10.3145/epi.2012.nov.07

Hodonu-Wusu, J. O., y Lazarus, G. N. (2018). Major trends in LIS research: A bibliometric analysis. Library Philosophy and Practice, 1. Disponible en: https://core.ac.uk/download/pdf/189483457.pdf.

Hood, W. W., y Wilson, C. S. (2003). Informetric studies using databases: Opportunities and challenges. Scientometrics, 58(3), 587-608. https://doi.org/10.1023/B:SCIE.0000006882.47115.c6

Hu, Z., Tian, W., Xu, S., Zhang, C., y Wang, X. (2018). Four pitfalls in normalizing citation indicators: An investigation of ESI's selection of highly cited papers. Journal of Informetrics, 12(4), 1133-1145. https://doi.org/10.1016/j.joi.2018.09.006

Katz, J. S. (2005). Scale-independent bibliometric indicators. Measurement: Interdisciplinary Research and Perspectives, 3(1), 24-28. https://doi.org/10.1207/s15366359mea0301_3

King, D.A. (2004). The scientific impact of nations. Nature, 430 (15), 311-316. https://doi.org/10.1038/430311a PMid:15254529

Korevaar, J. (1996). Validation of bibliometric indicators in the field of mathematics. Scientometrics, 37(1), 117-130. https://doi.org/10.1007/BF02093488

Li, Y., Xu, Z., Wang, X., y Wang, X. (2020). A bibliometric analysis on deep learning during 2007-2019. International Journal of Machine Learning and Cybernetics, 11(12), 2807-2826. https://doi.org/10.1007/s13042-020-01152-0

Li, F., Yi, Y., Guo, X., y Qi, W. (2012): Performance evaluation of research universities in Mainland China, Hong Kong and Taiwan: based on a two-dimensional approach. Scientometrics, 90:531-542. https://doi.org/10.1007/s11192-011-0544-1

Liu, N. C., y Cheng, Y. (2005). The Academic Ranking of World Universities. Higher Education in Europe, 30(2), 127-136. https://doi.org/10.1080/03797720500260116

Luque-Martínez, T. (2015). Actividad investigadora y contexto económico. El caso de las universidades públicas españolas. Revista Española de Documentación Científica, 38(1), e076-e076. https://doi.org/10.3989/redc.2015.1.1135

Luque-Martínez, T., del Barrio-García, S., Doña-Toledo, L., y Faraoni, N. (2022). Value generation and economic impact of the University of Granada. Studies in Higher Education, 1-14. https://doi.org/10.1080/03075079.2022.2138848

Luque-Martínez, T., y del Barrio-García, S. (2016). Constructing a synthetic indicator of research activity. Scientometrics, 108(3), 1049-1064. https://doi.org/10.1007/s11192-016-2037-8

Ming, H. W., Hui, Z. F., y Yuh, S. H. (2011). Comparison of universities' scientific performance using bibliometric indicators. Malaysian Journal of Library yAmp; Information Science, 16(2), 1-19. Disponible en: https://jati.um.edu.my/index.php/MJLIS/article/view/6693.

Moed, H.F. (2000). Bibliometric Indicators Reflect Publication and Management Strategies. Scientometrics 47, 323-346. https://doi.org/10.1023/A:1005695111622

Moed, H., Burger, W., Frankfort, J., y Van Raan, A. (1985). The application of bibliometric indicators: Important field-and time-dependent factors to be considered. Scientometrics, 8(3-4), 177-203. https://doi.org/10.1007/BF02016935

Morillo, F., Bordons, M., y Gómez, I. (2001). An approach to interdisciplinarity through bibliometric indicators. Scientometrics, 51(1), 203-222. https://doi.org/10.1023/A:1010529114941

Nagarkar, S., Veer, C., y Kumbhar, R. (2015). Bibliometric Analysis of Papers Published by Faculty of Life Science Departments of Savitribai Phule Pune University during 1999-2013. DESIDOC Journal of Library y Information Technology, 35(5) 368-375. https://doi.org/10.14429/djlit.35.5.8429

Nederhof, A.J., Zwaan, R.A., De Bruin, R.E. et al. (1989). Assessing the usefulness of bibliometric indicators for the humanities and the social and beha vioural sciences: A comparative study. Scientometrics 15, 423-435. https://doi.org/10.1007/BF02017063

Perez-Esparrells, C. y Orduna-Malea, E. (2018). Do the Technical Universities exhibit distinct behaviour in global university rankings? A Times Higher Education (THE) case study, Journal of Engineering and Technology Management, 48: 97-108. https://doi.org/10.1016/j.jengtecman.2018.04.007

Pislyakov, V. (2022). On some properties of medians, percentiles, baselines, and thresholds in empirical bibliometric analysis. Journal of Informetrics, 16(4), 101322. https://doi.org/10.1016/j.joi.2022.101322

Potter, R. W., Szomszor, M., y Adams, J. (2022). Comparing standard, collaboration and fractional CNCI at the institutional level: Consequences for performance evaluation. Scientometrics, 1-14. https://doi.org/10.1007/s11192-022-04303-y

Sun, Y., y Liu, F. (2012) Measuring international trade-related technology spillover: a composite approach of network analysis and information theory. Scientometrics, 94, 963-979. https://doi.org/10.1007/s11192-012-0860-0

Van Leeuwen, T. (2006). The application of bibliometric analyses in the evaluation of social science research. Who benefits from it, and why it is still feasible. Scientometrics, 66(1), 133-154. https://doi.org/10.1007/s11192-006-0010-7

Van Raan, A. F. (2006). Statistical properties of bibliometric indicators: Research group indicator distributions and correlations. Journal of the American Society for Information Science and Technology, 57(3), 408-430. https://doi.org/10.1002/asi.20284

Verbeek, A., Debackere, K., Luwel, M., y Zimmermann, E. (2002). Measuring progress and evolution in science and technology-I: The multiple uses of bibliometric indicators. International Journal of management reviews, 4(2), 179-211. https://doi.org/10.1111/1468-2370.00083

Waltman, L., y Schreiber, M. (2013). On the calculation of percentile‐based bibliometric indicators. Journal of the American Society for information Science and Technology, 64(2), 372-379. https://doi.org/10.1002/asi.22775

Waltman, L., Calero-Medina, C., Kosten, J., Noyons, E. C. M., Tijssen, R. J. W., van Eck, N. J., et al. (2012). The Leiden ranking 2011-2012: Data collection, indicators, and interpretation. Journal of the American Society for Information Science and Technology, 63(12), 2419-2432. https://doi.org/10.1002/asi.22708

Wang, X., y Zhang, Z. (2020). Improving the reliability of short-term citation impact indicators by taking into account the correlation between short-and long-term citation impact. Journal of Informetrics, 14(2), 101019. https://doi.org/10.1016/j.joi.2020.101019

Wu, Y., y Liu, N. C. (2017). Academic ranking of world universities (ARWU): Methodologies and trends. In Research Analytics (pp. 95-120). Auerbach Publications. https://doi.org/10.1201/9781315155890-6