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The different flavors of research collaboration: a case study of their influence on university excellence in four world regions

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Listed:
  • Maria Benavent-Pérez

    (CSIC)

  • Juan Gorraiz

    (University of Vienna)

  • Christian Gumpenberger

    (University of Vienna)

  • Félix Moya-Anegón

    (CSIC)

Abstract

This study on research collaboration (RC) is an attempt to estimate the degree of internationalization of academic institutions and regions. Furthermore potential influences of RC on excellence initiatives of modern universities are investigated relying on source data obtained from SCImago Institutions Rankings. A positive correlation exists between the degree of collaboration and the normalized impact. However, in contrast to output the normalized impact increase progression is non-linear and fluctuating. Differences occur regarding output volume and normalized impact at geographical region level for the leading universities. Different patterns of the Brute force distribution for each collaboration type were also observed at region level as well as at subject area level. A continuously reduced percentage of the domestic (non-collaboration) academic output is a world trend, whereas a steady increase of “international + national” collaboration is observed globally, however, less distinctive in Asia than in the other regions. The impact of Latin American papers originating from domestic production as well as from national collaboration remains considerably below world average values.

Suggested Citation

  • Maria Benavent-Pérez & Juan Gorraiz & Christian Gumpenberger & Félix Moya-Anegón, 2012. "The different flavors of research collaboration: a case study of their influence on university excellence in four world regions," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(1), pages 41-58, October.
    • Handle: RePEc:spr:scient:v:93:y:2012:i:1:d:10.1007_s11192-012-0638-4
    DOI: 10.1007/s11192-012-0638-4
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    References listed on IDEAS

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    3. Bornmann, Lutz & Leydesdorff, Loet, 2017. "Skewness of citation impact data and covariates of citation distributions: A large-scale empirical analysis based on Web of Science data," Journal of Informetrics, Elsevier, vol. 11(1), pages 164-175.
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    5. Cesar H. Limaymanta & Rosalía Quiroz-de-García & Jesús A. Rivas-Villena & Andrea Rojas-Arroyo & Orlando Gregorio-Chaviano, 2022. "Relationship between collaboration and normalized scientific impact in South American public universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6391-6411, November.
    6. de Moya-Anegon, Felix & Guerrero-Bote, Vicente P. & Lopez-Illescas, Carmen & Moed, Henk F., 2018. "Statistical relationships between corresponding authorship, international co-authorship and citation impact of national research systems," Journal of Informetrics, Elsevier, vol. 12(4), pages 1251-1262.
    7. Bornmann, Lutz, 2019. "Does the normalized citation impact of universities profit from certain properties of their published documents – such as the number of authors and the impact factor of the publishing journals? A mult," Journal of Informetrics, Elsevier, vol. 13(1), pages 170-184.
    8. Ping Zhou & Huibao Tian, 2014. "Funded collaboration research in mathematics in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 695-715, June.
    9. Manganote, Edmilson J.T. & Araujo, Mariana S. & Schulz, Peter A., 2014. "Visualization of ranking data: Geographical signatures in international collaboration, leadership and research impact," Journal of Informetrics, Elsevier, vol. 8(3), pages 642-649.
    10. Frederik T. Verleysen & Tim C. E. Engels, 2014. "Internationalization of peer reviewed and non-peer reviewed book publications in the Social Sciences and Humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1431-1444, November.
    11. Fan, Lingxu & Guo, Lei & Wang, Xinhua & Xu, Liancheng & Liu, Fangai, 2022. "Does the author’s collaboration mode lead to papers’ different citation impacts? An empirical analysis based on propensity score matching," Journal of Informetrics, Elsevier, vol. 16(4).
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