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Are the authors of highly cited articles also the most productive ones?

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  • Abramo, Giovanni
  • Cicero, Tindaro
  • D’Angelo, Ciriaco Andrea

Abstract

Ever more frequently, governments have decided to implement policy measures intended to foster and reward excellence in scientific research. This is in fact the intended purpose of national research assessment exercises. These are typically based on the analysis of the quality of the best research products; however, a different approach to analysis and intervention is based on the measure of productivity of the individual scientists, meaning the overall impact of their entire scientific production over the period under observation. This work analyzes the convergence of the two approaches, asking if and to what measure the most productive scientists achieve highly cited articles; or vice versa, what share of highly cited articles is achieved by scientists that are “non-top” for productivity. To do this we use bibliometric indicators, applied to the 2004–2008 publications authored by academics of Italian universities and indexed in the Web of Science.

Suggested Citation

  • Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2014. "Are the authors of highly cited articles also the most productive ones?," Journal of Informetrics, Elsevier, vol. 8(1), pages 89-97.
    • Handle: RePEc:eee:infome:v:8:y:2014:i:1:p:89-97
    DOI: 10.1016/j.joi.2013.10.011
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    References listed on IDEAS

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    1. Giovanni Abramo & Ciriaco Andrea D'Angelo & Flavia Di Costa, 2008. "Assessment of sectoral aggregation distortion in research productivity measurements," Research Evaluation, Oxford University Press, vol. 17(2), pages 111-121, June.
    2. Ciriaco Andrea D'Angelo & Cristiano Giuffrida & Giovanni Abramo, 2011. "A heuristic approach to author name disambiguation in bibliometrics databases for large‐scale research assessments," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(2), pages 257-269, February.
    3. Linda Butler, 2007. "Assessing university research: A plea for a balanced approach," Science and Public Policy, Oxford University Press, vol. 34(8), pages 565-574, October.
    4. Robert J W Tijssen, 2003. "Scoreboards of research excellence," Research Evaluation, Oxford University Press, vol. 12(2), pages 91-103, August.
    5. Lutz Bornmann & Loet Leydesdorff, 2011. "Which cities produce more excellent papers than can be expected? A new mapping approach, using Google Maps, based on statistical significance testing," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(10), pages 1954-1962, October.
    6. Anthony F. J. Raan, 2006. "Comparison of the Hirsch-index with standard bibliometric indicators and with peer judgment for 147 chemistry research groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 67(3), pages 491-502, June.
    7. Baccini, A. & Barabesi, L. & Marcheselli, M. & Pratelli, L., 2012. "Statistical inference on the h-index with an application to top-scientist performance," Journal of Informetrics, Elsevier, vol. 6(4), pages 721-728.
    8. Hicks, Diana, 2012. "Performance-based university research funding systems," Research Policy, Elsevier, vol. 41(2), pages 251-261.
    9. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2013. "Individual research performance: A proposal for comparing apples to oranges," Journal of Informetrics, Elsevier, vol. 7(2), pages 528-539.
    10. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    11. Rodrigo Costas & Thed N. Leeuwen & María Bordons, 2012. "Referencing patterns of individual researchers: Do top scientists rely on more extensive information sources?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2433-2450, December.
    12. Michel Zitt & Suzy Ramanana-Rahary & Elise Bassecoulard, 2005. "Relativity of citation performance and excellence measures: From cross-field to cross-scale effects of field-normalisation," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(2), pages 373-401, April.
    13. Amanda H Goodall, 2005. "Should top universities be led by top researchers, and are they?," General Economics and Teaching 0510003, University Library of Munich, Germany.
    14. Ciriaco Andrea D'Angelo & Cristiano Giuffrida & Giovanni Abramo, 2011. "A heuristic approach to author name disambiguation in bibliometrics databases for large-scale research assessments," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(2), pages 257-269, February.
    15. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2012. "Revisiting the scaling of citations for research assessment," Journal of Informetrics, Elsevier, vol. 6(4), pages 470-479.
    16. Rodrigo Costas & Thed N. van Leeuwen & María Bordons, 2012. "Referencing patterns of individual researchers: Do top scientists rely on more extensive information sources?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2433-2450, December.
    17. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Rosati, Francesco, 2013. "The importance of accounting for the number of co-authors and their order when assessing research performance at the individual level in the life sciences," Journal of Informetrics, Elsevier, vol. 7(1), pages 198-208.
    18. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2011. "A field-standardized application of DEA to national-scale research assessment of universities," Journal of Informetrics, Elsevier, vol. 5(4), pages 618-628.
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    2. Gutiérrez-Nieto, Begoña & Serrano-Cinca, Carlos, 2019. "20 years of research in microfinance: An information management approach," International Journal of Information Management, Elsevier, vol. 47(C), pages 183-197.
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    4. Liang, Liming & Zhong, Zhen & Rousseau, Ronald, 2015. "Uncited papers, uncited authors and uncited topics: A case study in library and information science," Journal of Informetrics, Elsevier, vol. 9(1), pages 50-58.
    5. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2015. "Ranking research institutions by the number of highly-cited articles per scientist," Journal of Informetrics, Elsevier, vol. 9(4), pages 915-923.
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    7. Lindahl, Jonas, 2018. "Predicting research excellence at the individual level: The importance of publication rate, top journal publications, and top 10% publications in the case of early career mathematicians," Journal of Informetrics, Elsevier, vol. 12(2), pages 518-533.
    8. Amanda Lucía Restrepo Londono & Claudia Inés Sepúlveda Rivillas, 2016. "Caracterización financiera de las empresas generadoras de energía colombianas (2005 – 2012)," Revista Facultad de Ciencias Económicas, Universidad Militar Nueva Granada, vol. 24(2), pages 63-84, October.
    9. Yu-Wei Chang, 2021. "Characteristics of high research performance authors in the field of library and information science and those of their articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3373-3391, April.
    10. Jonas Lindahl & Cristian Colliander & Rickard Danell, 2020. "Early career performance and its correlation with gender and publication output during doctoral education," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 309-330, January.
    11. Jenny Paola Lis Gutiérrez & Clorith Angélica Bahos Olivera, 2016. "La participación femenina en publicaciones colombianas de economía y administración indexadas en Scopus (1974 – junio de 2014)," Revista Facultad de Ciencias Económicas, Universidad Militar Nueva Granada, vol. 24(2), pages 183-212, October.
    12. Sergey Kolesnikov & Eriko Fukumoto & Barry Bozeman, 2018. "Researchers’ risk-smoothing publication strategies: Is productivity the enemy of impact?," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1995-2017, September.
    13. Díaz-Faes, Adrián A. & Costas, Rodrigo & Galindo, M. Purificación & Bordons, María, 2015. "Unravelling the performance of individual scholars: Use of Canonical Biplot analysis to explore the performance of scientists by academic rank and scientific field," Journal of Informetrics, Elsevier, vol. 9(4), pages 722-733.
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