, Volume 83, Issue 1, pp 1–13 | Cite as

Evaluating scholars based on their academic collaboration activities: two indices, the RC-index and the CC-index, for quantifying collaboration activities of researchers and scientific communities

  • Alireza Abbasi
  • Jörn Altmann
  • Junseok Hwang


Although there are many studies for quantifying the academic performance of researchers, such as measuring the scientific performance based on the number of publications, there are no studies about quantifying the collaboration activities of researchers. This study addresses this shortcoming. Based on three measures, namely the collaboration network structure of researchers, the number of collaborations with other researchers, and the productivity index of co-authors, two new indices, the RC-Index and CC-Index, are proposed for quantifying the collaboration activities of researchers and scientific communities. After applying these indices on a data set generated from publication lists of five schools of information systems, this study concludes with a discussion of the shortcomings and advantages of these indices.


Collaborative networks Collaboration activities Social network analysis Collaboration evaluation Individual and community productivity Collaboration measures Indices Empirical data analysis 

JEL Classification

C43 D80 D85 L25 M12 M21 



This paper was partly funded by Ministry of Knowledge Economy of the Republic of Korea.


  1. Abbasi, A., & Altmann, J. (2009). AcaSoNet: Social network system for the academic community. TEMEP Working Paper Series, Seoul National University, South Korea. Google Scholar
  2. Altmann, J., Abbasi, A., & Hwang, J. (2009). Evaluating the productivity of researchers and their communities: The RP-index and the CP-index. International Journal of Computer Science and Applications, 6(2), 104–118.Google Scholar
  3. Batista, P. D., Campiteli, M. G., & Kinounchi, O. (2006). Is it possible to compare researchers with different scientific interests? Scientometrics, 68(1), 179–189.CrossRefGoogle Scholar
  4. Borgman, C., & Furner, J. (2002). Scholarly communication and bibliometrics. Annual Review of Information Science and Technology, 36, 3–72.CrossRefGoogle Scholar
  5. Braun, T., Glanzel, W., & Schubert, A. (2005). A Hirsch-type index for journals. The Scientist, 19(22), 8.Google Scholar
  6. Dainesi, S. M., & Pietrobon, R. (2007). Scientific indicators of productivity: Time for action. Revista Brasileira de Psiquiatria [Online], 29(2), 100–101.Google Scholar
  7. Egghe, L. (2006). Theory and practice of the g-Index. Scientometrics, 69(1), 131–152.CrossRefMathSciNetGoogle Scholar
  8. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572.CrossRefGoogle Scholar
  9. Jiang, Y. (2008). Locating active actors in the scientific collaboration communities based on interaction topology analyses. Scientometrics, 74(3), 471–482.CrossRefGoogle Scholar
  10. Jin, B. H. (2006). h-Index: An evaluation indicator proposed by scientist. Science Focus, 1(1), 8–9. (in Chinese).Google Scholar
  11. Kousha, K., & Thelwall, M. (2007). Google scholar citations and Google Web/URL citations: A multi-discipline exploratory analysis. Journal of the American Society for Information Science and Technology, 58(7), 1055–1065.CrossRefGoogle Scholar
  12. Laudel, G. (2002). What do we measure by co-authorships? Research Evaluation, 11(13), 3–15.CrossRefGoogle Scholar
  13. Leclerc, M., & Gagn, J. (1994). International Scientific Cooperation: The continentalization of science. Scientometrics, 31(3), 261–292.CrossRefGoogle Scholar
  14. Lehmann, S., Jackson, A. D., & Lautrup, B. (2006). Measures for measure. Nature, 444, 1003.CrossRefGoogle Scholar
  15. Melin, G. (2000). Pragmatism and self-organization research collaboration on the individual level. Research Policy, 29(1), 31–40.CrossRefGoogle Scholar
  16. Melin, G., & Persson, O. (1996). Studying research collaboration using co-authorships. Scientometrics, 36, 363–377.CrossRefGoogle Scholar
  17. Prathap, G. (2006). Hirsch-type indices for ranking institutions’ scientific research output. Current Science, 91(11), 1439.Google Scholar
  18. Ruane, F. P., & Tol, R. S. J. (2008). Rational (successive) h-indices: An application to economics in the Republic of Ireland. Scientometrics, 75(2), 395–405.CrossRefGoogle Scholar
  19. Schubert, A. (2007). Successive h-indices. Scientometrics, 70(1), 201–205.CrossRefGoogle Scholar
  20. Sidiropoulos, A., Katsaros, D., & Manolopoulos, Y. (2007). Generalized h-index for disclosing latent facts in citation networks. Scientometrics, 72(2), 253–280.CrossRefGoogle Scholar
  21. Suresh, V., Raghupathy, N., Shekar, B., & Madhavan, C. E. V. (2007). Discovering mentorship information from author collaboration networks. Lecture notes in computer science. Discovery Science, 4755, 197–208.Google Scholar
  22. Tol, R. S. J. (2008). A rational, successive g-index applied to economics departments in Ireland. Journal of Informetrics, 2, 149–155.CrossRefGoogle Scholar
  23. Van Raan, A. F. J. (2006). Measuring science. In H. F. Moed, W. Glanzel, & U. Schmoch (Eds.), Handbook of quantitative science and technology research. Germany: Kluwer Academic Publishers.Google Scholar
  24. Ziman, J. (1994). Prometheus bound, science in a dynamic steady state. Cambridge: Cambridge University Press.Google Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2009

Authors and Affiliations

  1. 1.Technology Management, Economics and Policy Program, Department of Industrial Engineering, College of EngineeringSeoul National UniversitySeoulSouth Korea
  2. 2.Research and Development DivisionInternational Affairs, National Iranian Oil CompanyTehranIran

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