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Spanish scientific research by field and subject. Strategic analysis with ARWU indicators

Author

Listed:
  • Teodoro Luque-Martínez

    (Universidad de Granada)

  • Ignacio Luque-Raya

    (Universidad de Granada)

Abstract

In this study, the scientific production of universities across the world is analysed, disaggregating it by research fields and specialities. A particular focus is on the strategic analysis of Spanish universities within the international panorama. Data collected from the widely known and frequently consulted Academic Ranking of World Universities are used to which clustering techniques are applied. To do so, indicators are defined that are related with university presence (in both absolute and relative terms), university performance within a specialist field with respect to the rest of the world, and within each speciality with respect to the general level of the country. With all that information, strategic clusters of specialities were identified, and an analysis by scientific field at an aggregated level was completed. Among the results, it is worth highlighting the greater international presence of Spanish universities within the specialist clusters of Food Science & Technology and Hospitality & Tourism Management, and their performance below the general average with respect to all universities, except for Remote Sensing, Veterinary Science, and Civil Engineering. The research fields within which the Spanish universities showed greater competitiveness are Life Sciences and Natural Science, whereas the fields of Engineering and Social Science had the lowest presence and level of international competitiveness. A series of recommendations for improvement are advanced concerning measurement of resources, communicative activities, and the orientation of lines of action within some specialities.

Suggested Citation

  • Teodoro Luque-Martínez & Ignacio Luque-Raya, 2024. "Spanish scientific research by field and subject. Strategic analysis with ARWU indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5265-5285, September.
    • Handle: RePEc:spr:scient:v:129:y:2024:i:9:d:10.1007_s11192-024-05128-7
    DOI: 10.1007/s11192-024-05128-7
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    References listed on IDEAS

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    1. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2014. "Assessing national strengths and weaknesses in research fields," Journal of Informetrics, Elsevier, vol. 8(3), pages 766-775.
    2. Fredrik Niclas Piro & Dag W. Aksnes & Kristoffer Rørstad, 2013. "A macro analysis of productivity differences across fields: Challenges in the measurement of scientific publishing," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(2), pages 307-320, February.
    3. Massimo Franceschet, 2009. "A cluster analysis of scholar and journal bibliometric indicators," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(10), pages 1950-1964, October.
    4. Domingo Docampo, 2013. "Reproducibility of the Shanghai academic ranking of world universities results," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(2), pages 567-587, February.
    5. Henk F. Moed, 2000. "Bibliometric Indicators Reflect Publication and Management Strategies," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 323-346, February.
    6. Beatriz Junquera & María Mitre, 2007. "Value of bibliometric analysis for research policy: A case study of Spanish research into innovation and technology management," Scientometrics, Springer;Akadémiai Kiadó, vol. 71(3), pages 443-454, June.
    7. Philip G. Altbach & Jamil Salmi, 2011. "The Road to Academic Excellence : The Making of World-Class Research Universities [El camino hacia la excelencia académica : la constitución de universidades de investigación de rango mundial]," World Bank Publications - Books, The World Bank Group, number 2357.
    8. József Kabók & Slobodan Radišić & Bogdan Kuzmanović, 2017. "Cluster analysis of higher-education competitiveness in selected European countries," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 30(1), pages 845-857, January.
    9. Kathryn Rudie Harrigan, 1985. "An application of clustering for strategic group analysis," Strategic Management Journal, Wiley Blackwell, vol. 6(1), pages 55-73, January.
    10. Pedro Cosme Vieira & Aurora A. C. Teixeira, 2010. "Are finance, management, and marketing autonomous fields of scientific research? An analysis based on journal citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 627-646, December.
    11. Milan Dobrota & Marina Dobrota, 2016. "ARWU ranking uncertainty and sensitivity: What if the award factor was Excluded?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(2), pages 480-482, February.
    12. Keith Weigelt & Ian Macmillan, 1988. "An interactive strategic analysis framework," Strategic Management Journal, Wiley Blackwell, vol. 9(S1), pages 27-40, June.
    13. Shen, Zhesi & Yang, Liying & Pei, Jiansuo & Li, Menghui & Wu, Chensheng & Bao, Jianzhang & Wei, Tian & Di, Zengru & Rousseau, Ronald & Wu, Jinshan, 2016. "Interrelations among scientific fields and their relative influences revealed by an input–output analysis," Journal of Informetrics, Elsevier, vol. 10(1), pages 82-97.
    14. Ross W. K. Potter & Martin Szomszor & Jonathan Adams, 2022. "Comparing standard, collaboration and fractional CNCI at the institutional level: Consequences for performance evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7435-7448, December.
    15. Wildgaard, Lorna, 2016. "A critical cluster analysis of 44 indicators of author-level performance," Journal of Informetrics, Elsevier, vol. 10(4), pages 1055-1078.
    16. Daniel Fonseca Costa & Francisval de Melo Carvalho & Bruno César de Melo Moreira, 2019. "Behavioral Economics And Behavioral Finance: A Bibliometric Analysis Of The Scientific Fields," Journal of Economic Surveys, Wiley Blackwell, vol. 33(1), pages 3-24, February.
    17. Weishu Liu & Li Tang & Guangyuan Hu, 2020. "Funding information in Web of Science: an updated overview," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1509-1524, March.
    18. Marcel Ausloos & Francesca Bartolacci & Nicola G. Castellano & Roy Cerqueti, 2018. "Exploring how innovation strategies at time of crisis influence performance: a cluster analysis perspective," Papers 1808.05893, arXiv.org.
    19. Alfonso Ibáñez & Pedro Larrañaga & Concha Bielza, 2013. "Cluster methods for assessing research performance: exploring Spanish computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 571-600, December.
    20. Fredrik Niclas Piro & Dag W. Aksnes & Kristoffer Rørstad, 2013. "A macro analysis of productivity differences across fields: Challenges in the measurement of scientific publishing," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(2), pages 307-320, February.
    21. João M. Santos & Hugo Horta, 2015. "The generational gap of science: a dynamic cluster analysis of doctorates in an evolving scientific system," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 381-406, July.
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