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Bibliometric statistical properties of the 100 largest European research universities: Prevalent scaling rules in the science system

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  • Anthony F.J. van Raan

Abstract

The statistical properties of bibliometric indicators related to research performance, field citation density, and journal impact were studied for the 100 largest European research universities. A size‐dependent cumulative advantage was found for the impact of universities in terms of total number of citations. In the author's previous work, a similar scaling rule was found at the level of research groups. Therefore, this scaling rule is conjectured to be a prevalent property of the science system. The lower performance universities have a larger size‐dependent cumulative advantage for receiving citations than top performance universities. For the lower performance universities, the fraction of noncited publications decreases considerably with size. Generally, the higher the average journal impact of the publications of a university, the lower the number of noncited publications. The average research performance was found not to dilute with size. Evidently, large universities, particularly top performance universities are characterized by being “big and beautiful.” They succeed in keeping a high performance over a broad range of activities. This most probably is an indication of their overall attractive scientific and intellectual power. It was also found that particularly for the lower performance universities, the field citation density provides a strong cumulative advantage in citations per publication. The relation between number of citations and field citation density found in this study can be considered as a second basic scaling rule of the science system. Top performance universities publish in journals with significantly higher journal impact as compared to the lower performance universities. A significant decrease of the fraction of self‐citations with increasing research performance, average field citation density, and average journal impact was found.

Suggested Citation

  • Anthony F.J. van Raan, 2008. "Bibliometric statistical properties of the 100 largest European research universities: Prevalent scaling rules in the science system," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(3), pages 461-475, February.
    • Handle: RePEc:bla:jamist:v:59:y:2008:i:3:p:461-475
    DOI: 10.1002/asi.20761
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    Cited by:

    1. Sylvan Katz, 2012. "Science Policy, Complex Innovation Systems and Performance Measures," SPRU Working Paper Series 198, SPRU - Science Policy Research Unit, University of Sussex Business School.
    2. Maxim Kotsemir & Sergey Shashnov, 2017. "Measuring, analysis and visualization of research capacity of university at the level of departments and staff members," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1659-1689, September.
    3. Lutz Bornmann & Adam Y. Ye & Fred Y. Ye, 2018. "Identifying “hot papers” and papers with “delayed recognition” in large-scale datasets by using dynamically normalized citation impact scores," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 655-674, August.
    4. Lutz Bornmann & Werner Marx, 2014. "How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 487-509, January.
    5. Antonoyiannakis, Manolis, 2018. "Impact Factors and the Central Limit Theorem: Why citation averages are scale dependent," Journal of Informetrics, Elsevier, vol. 12(4), pages 1072-1088.
    6. Guillermo Armando Ronda-Pupo & J. Sylvan Katz, 2018. "The power law relationship between citation impact and multi-authorship patterns in articles in Information Science & Library Science journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 919-932, March.
    7. Erjia Yan, 2014. "Topic-based Pagerank: toward a topic-level scientific evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 407-437, August.
    8. Benedetto Lepori & Valerio Veglio & Barbara Heller-Schuh & Thomas Scherngell & Michael Barber, 2015. "Participations to European Framework Programs of higher education institutions and their association with organizational characteristics," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2149-2178, December.
    9. Giovanni Abramo & Corrado Costa & Ciriaco Andrea D’Angelo, 2015. "A multivariate stochastic model to assess research performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1755-1772, February.
    10. Barbara S. Lancho-Barrantes & Francisco J. Cantu-Ortiz, 2021. "Quantifying the publication preferences of leading research universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2269-2310, March.
    11. Vieira, Elizabeth S. & Lepori, Benedetto, 2016. "The growth process of higher education institutions and public policies," Journal of Informetrics, Elsevier, vol. 10(1), pages 286-298.
    12. Fetscherin, Marc & Heinrich, Daniel, 2015. "Consumer brand relationships research: A bibliometric citation meta-analysis," Journal of Business Research, Elsevier, vol. 68(2), pages 380-390.
    13. Anthony F J van Raan, 2013. "Universities Scale Like Cities," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-14, March.
    14. Viktoria Maria Radler, 2018. "20 Years of brand personality: a bibliometric review and research agenda," Journal of Brand Management, Palgrave Macmillan, vol. 25(4), pages 370-383, July.
    15. Gao, Xia & Guan, Jiancheng, 2009. "A scale-independent analysis of the performance of the Chinese innovation system," Journal of Informetrics, Elsevier, vol. 3(4), pages 321-331.
    16. Lepori, B. & Seeber, M. & Bonaccorsi, A., 2015. "Competition for talent. Country and organizational-level effects in the internationalization of European higher education institutions," Research Policy, Elsevier, vol. 44(3), pages 789-802.
    17. Yan, Erjia & Ding, Ying & Cronin, Blaise & Leydesdorff, Loet, 2013. "A bird's-eye view of scientific trading: Dependency relations among fields of science," Journal of Informetrics, Elsevier, vol. 7(2), pages 249-264.
    18. Saeed Roshani & Mohammad-Reza Bagherylooieh & Melika Mosleh & Mario Coccia, 2021. "What is the relationship between research funding and citation-based performance? A comparative analysis between critical disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7859-7874, September.
    19. Isabel Gómez & María Bordons & M. Teresa Fernández & Fernanda Morillo, 2009. "Structure and research performance of Spanish universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(1), pages 131-146, April.
    20. Wang, Jian, 2014. "Unpacking the Matthew effect in citations," Journal of Informetrics, Elsevier, vol. 8(2), pages 329-339.
    21. Daniel Teodorescu & Tudorel Andrei, 2014. "An examination of “citation circles” for social sciences journals in Eastern European countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 209-231, May.
    22. Ilan Alon & John Anderson & Ziaul Haque Munim & Alice Ho, 2018. "A review of the internationalization of Chinese enterprises," Asia Pacific Journal of Management, Springer, vol. 35(3), pages 573-605, September.
    23. Önder Nomaler & Koen Frenken & Gaston Heimeriks, 2014. "On Scaling of Scientific Knowledge Production in U.S. Metropolitan Areas," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-6, October.
    24. Huang, Ding-wei, 2016. "Positive correlation between quality and quantity in academic journals," Journal of Informetrics, Elsevier, vol. 10(2), pages 329-335.

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