Factors of research groups’ productivity: The case of the Ural Federal University

Daniil G. Sandler, Dmitry A. Gladyrev, Dmitry M. Kochetkov, Anna D. Zorina


Relevance. One of the main goals of state university support programs in Russia is to increase the number of scientific publications. In 2021, Project 5-100 was replaced by the program PRIORITY 2030 (Strategic Academic Leadership Program). The new program increased the significance of the factors affecting the number of publications in universities and the issue of the optimal allocation of funding among research groups.

Research objective. This study examines the factors that affect the productivity of research groups at the university. Unlike the majority of other studies on this topic, this study analyzes scientific productivity at the level of research groups.

Data and methods. The study was possible due to the availability of data for 79 research groups at the Ural Federal University for the period from 2014 to 2020. The total number of articles and the number of articles in journals with an impact factor of more than two were used as indicators of research groups’ performance. To determine the factors influencing these indicators, we used econometric models for panel data. We used two separate samples: for social sciences and humanities and for other sciences.

Results. We identified the following factors affecting the performance of research groups: the number of participants, the age of the research group, the supervisor’s scientific age, and the amount of funding (the possibility of obtaining more funds or being denied funds). The most interesting result is the following: the supervisor's scientific age and increased funding have a negative impact on the group’s performance. The article provides possible explanations for these results.

Conclusion. Since the purpose of creating and funding research groups is primarily to increase their productivity, the results may be in favor of younger supervisors. University managers may also be interested in the ambiguous impact of increased funding: we suppose that research groups are more motivated not by the actual funding but by the prospective amount they may get.


research groups, university economics, economics of higher education, science management, scientometrics, econometric analysis

Full Text:



Acs, Z.J., Audretsch, D.B., & Feldman, M.P. (1994) ‘R&D spillovers and recipient firm size’. The Review of Economics and Statistics, 76, 336–340.

Albert, C., Davia, M.A., & Legazpe, N. (2016). Determinants of research productivity in Spanish academia. European Journal of Education, 51(4), 535–549.

Adams, J.D., Black, G.C., Clemmons, J.R., & Stephan, P.E. (2005) ‘Scientific teams and institutional collaborations: Evidence from U.S. universities, 1981–1999’. Research Policy, 34(3), 259–285. https://doi.org/10.1016/j.respol.2005.01.014

Aldieri, L., Guida, G., Kotsemir, M., & Vinci, C.P. (2019). An investigation of impact of research collaboration on academic performance in Italy. Quality & Quantity, 53(4), 2003–2040.

Aldieri, L., Kotsemir, M., & Vinci, C.P. (2018). The impact of research collaboration on academic performance: An empirical analysis for some European countries. Socio-Economic Planning Sciences, 62, 13–30.

Beaudry, C., & Allaoui, S. (2012). Impact of public and private research funding on scientific production: The case of nanotechnology. Research Policy, 41(9), 1589–1606.

De Witte, K., & Rogge, N. (2010). To publish or not to publish? On the aggregation and drivers of research performance. Scientometrics, 85(3), 657–680.

Fischer, M. M. and Varga, A. (2003) ‘Spatial knowledge spillovers and university research: Evidence from Austria’. Annals of Regional Science, 37, 303–322.

Garcia, R., Araújo, V., Mascarini, S., Santos, E.G., & Costa, A.R. (2020). How long-term university-industry collaboration shapes the academic productivity of research groups. Innovation, 22(1), 56–70.

Geiger, R.L. (2004). Knowledge and money: Research universities and the paradox of the marketplace. Stanford University Press.

Griliches, Z. (1979) ‘Issues in assessing the contribution and development of research to productivity growth’. The Bell Journal of Economics, 10(1), 92–116. https://doi.org/10.2307/3003321

Hall, B.H., Griliches, Z., & Hausman, J.A. (1986). Patents and R and D: Is There A Lag? International Economic Review, 27, 265–283.

Hayati, Z., & Ebrahimy, S. (2009). Correlation between quality and quantity in scientific production: A case study of Iranian organizations from 1997 to 2006. Scientometrics, 80(3), 625–636.

Jaffe, A.B. (1989). Real effects of academic research. The American Economic Review, 79, 957–970.

Jaffe, A.B., & Trajtenberg, M. (1996). Flows of knowledge from universities and federal laboratories: Modeling the flow of patent citations over time and across institutional and geographic boundaries. Proceedings of the National Academy of Science, 93, 12671–12677.

Jung, H., Seo, I., Kim, J., & Kim, B.K. (2017). Factors affecting government-funded research quality. Asian Journal of Technology Innovation, 25(3), 447–469.

Landry, R., Traore, N., & Godin, B. (1996). An econometric analysis of the effect of collaboration on academic research productivity. Higher Education, 32(3), 283–301.

Lawani, S.M. (1986). Some bibliometric correlates of quality in scientific research. Scientometrics, 9(1-2), 13–25.

Levin, S.G., & Stephan, P.E. (1989). Age and research productivity of academic scientists. Research in Higher Education, 30(5), 531–549.

Martin, F. (1998). The economic impact of Canadian university R&D. Research Policy, 27, 677–687.

Maslennikov, V.V. (2013). Project management of scientific activities of the university. Methodological tools. Moscow: Paleotype

Michalska-Smith, M.J., & Allesina, S. (2017). And, not or: quality, quantity in scientific publishing. PloS ONE, 12(6).

Pakes, A.S. (1978). Economic incentives in the production and transmission of knowledge: an empirical analysis. Harvard University, Cambridge, MA.

Pardey, P.G. (1989). The Agricultural Knowledge Production Function : An Empirical Look. The Review of Economics and Statistics, 71(3), 453–461.

Perovic, S., Radovanovic, S., Sikimic, V. and Berber, A. (2016). Optimal research team composition: data envelopment analysis of Fermilab experiments. Scientometrics, 108(1), 83–111. https://doi.org/10.1007/s11192-016-1947-9

Rezapour, A., Ebadifard Azar, F., Yousef Zadeh, N., Roumiani, Y.A., & Bagheri Faradonbeh, S. (2015). Technical efficiency and resources allocation in university hospitals in Tehran, 2009–2012. Medical Journal of the Islamic Republic of Iran, 29(1), 839–850.

Riddel, M., & Schwer, R.K. (2003). Regional innovative capacity with endogenous employment: Empirical evidence from the U.S. Review of Regional Studies, 33, 73–84.

Sandler, D.G., & Gladyrev, D.A. (2020). Construction of a cost-effective system of target indicators for the development of university research activities, taking into account correlation dependencies. Statistics and Economics, 17(4), 71–84

Varga, A. (1998). University research and regional innovation: A spatial econometric analysis of academic technology transfers. Boston: Kluwer.

Varga, A. (2000). Local academic knowledge transfers and the concentration of economic activity. Journal of Regional Science, 40, 289–309.

Varga, A. (2001). Universities and regional economic development: Does agglomeration matter? In Johansson, B., Karlsson, C., & Stough, R. (eds). Theories of endogenous regional growth: Lessons for regional policies. New York/Berlin: Springer-Verlag, pp. 345–367.

Vlasova, N.Y., & Lyashenko, E.A. (2021). University-business-government relations in the development of the institutional environment of Russian regions. R-Economy, 7(4), 214–224.

Zinchenko D.I., Egorov A.A. (2019). Modeling the effectiveness of Russian universities. Economic Journal of the Higher School of Economics, 23(1), 143–172.

DOI: https://doi.org/10.15826/recon.2022.8.2.012

Copyright (c) 2022 Daniil G. Sandler, Dmitry A. Gladyrev, Dmitry M. Kochetkov, Anna D. Zorina

Сertificate of registration media №04-27008 от 28.04.2021
Online ISSN 2412-0731