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Cluster methods for assessing research performance: exploring Spanish computer science

Author

Listed:
  • Alfonso Ibáñez

    (Universidad Politécnica de Madrid)

  • Pedro Larrañaga

    (Universidad Politécnica de Madrid)

  • Concha Bielza

    (Universidad Politécnica de Madrid)

Abstract

The objective of this paper is to propose a cluster analysis methodology for measuring the performance of research activities in terms of productivity, visibility, quality, prestige and international collaboration. The proposed methodology is based on bibliometric techniques and permits a robust multi-dimensional cluster analysis at different levels. The main goal is to form different clusters, maximizing within-cluster homogeneity and between-cluster heterogeneity. The cluster analysis methodology has been applied to the Spanish public universities and their academic staff in the computer science area. Results show that Spanish public universities fall into four different clusters, whereas academic staff belong into six different clusters. Each cluster is interpreted as providing a characterization of research activity by universities and academic staff, identifying both their strengths and weaknesses. The resulting clusters could have potential implications on research policy, proposing collaborations and alliances among universities, supporting institutions in the processes of strategic planning, and verifying the effectiveness of research policies, among others.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:97:y:2013:i:3:d:10.1007_s11192-013-0985-9
    DOI: 10.1007/s11192-013-0985-9
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    1. Erik Cobo & Albert Selva-O'Callagham & Josep-Maria Ribera & Francesc Cardellach & Ruth Dominguez & Miquel Vilardell, 2007. "Statistical Reviewers Improve Reporting in Biomedical Articles: A Randomized Trial," PLOS ONE, Public Library of Science, vol. 2(3), pages 1-8, March.
    2. Bornmann, Lutz & Leydesdorff, Loet, 2012. "Which are the best performing regions in information science in terms of highly cited papers? Some improvements of our previous mapping approaches," Journal of Informetrics, Elsevier, vol. 6(2), pages 336-345.
    3. Giovanni Abramo & Ciriaco Andrea D’Angelo & Fabio Pugini, 2008. "The measurement of Italian universities’ research productivity by a non parametric-bibliometric methodology," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(2), pages 225-244, August.
    4. Daniel Torres-Salinas & Jose G. Moreno-Torres & Emilio Delgado-López-Cózar & Francisco Herrera, 2011. "A methodology for Institution-Field ranking based on a bidimensional analysis: the IFQ 2 A index," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(3), pages 771-786, September.
    5. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2011. "National-scale research performance assessment at the individual level," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 347-364, February.
    6. Rodrigo Costas & Thed N. van Leeuwen & María Bordons, 2010. "A bibliometric classificatory approach for the study and assessment of research performance at the individual level: The effects of age on productivity and impact," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(8), pages 1564-1581, August.
    7. Jacques Wainer & Eduardo C. Xavier & Fabio Bezerra, 2009. "Scientific production in Computer Science: A comparative study of Brazil and other countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(2), pages 535-547, November.
    8. Raquel Rojo & Isabel Gómez, 2006. "Analysis of the Spanish scientific and technological output in the ICT sector," Scientometrics, Springer;Akadémiai Kiadó, vol. 66(1), pages 101-121, January.
    9. Chris Fraley & Adrian E. Raftery, 1999. "MCLUST: Software for Model-Based Cluster Analysis," Journal of Classification, Springer;The Classification Society, vol. 16(2), pages 297-306, July.
    10. Anthony F. J. van Raan, 2005. "Fatal attraction: Conceptual and methodological problems in the ranking of universities by bibliometric methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 62(1), pages 133-143, January.
    11. Alfonso Ibáñez & Concha Bielza & Pedro Larrañaga, 2013. "Relationship among research collaboration, number of documents and number of citations: a case study in Spanish computer science production in 2000–2009," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 689-716, May.
    12. Ying He & Jiancheng Guan, 2008. "Contribution of Chinese publications in computer science: A case study on LNCS," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 519-534, June.
    13. Alfonso Ibáñez & Pedro Larrañaga & Concha Bielza, 2011. "Using Bayesian networks to discover relationships between bibliometric indices. A case study of computer science and artificial intelligence journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(2), pages 523-551, November.
    14. Adela García Aracil & Davinia Palomares Montero, 2010. "Fuzzy cluster analysis on Spanish public universities," Investigaciones de Economía de la Educación volume 5, in: María Jesús Mancebón-Torrubia & Domingo P. Ximénez-de-Embún & José María Gómez-Sancho & Gregorio Gim (ed.), Investigaciones de Economía de la Educación 5, edition 1, volume 5, chapter 49, pages 976-994, Asociación de Economía de la Educación.
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