Abstract
Our study contributes to a deeper understanding of the phenomenon of research engagement and productivity of academics, particularly those from developing country contexts that are currently not well-represented in the literature. Thirty-seven Romanian public universities grouped into three categories: research-intensive, teaching and research, and teaching, were analyzed using canonical multivariate methods based on their institutional and bibliometric data for a period spanning between 2012 and 2020. We found that the most important predictor for research productivity is the university category, associated with prestige. The institutional public budget has no significant impact on faculty research productivity; the amount and the impact of research are related to who is financed and not how much money from institutional financing is received. The teaching workload has a negative influence on research results, while the PhD students, analyzed separately, proved to be a significant predictor of all the scientific output indicators when considered as an absolute number. During the study period, there was a significant shift in the publication output from quantity (number of articles) towards quality—articles in highly cited journals, and this trend accelerated in the last two years. The process of universities' classification using research output is verified and tested, proving that it is an ongoing, highly variable process with continuously shifting demands. Although our research findings are specific to the Romanian context, many of them may contribute to a better understanding of the institutional drivers of research productivity and can be replicated in other contexts.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abramo, G., Cicero, T., & D’Angelo, C. A. (2013). The impact of unproductive and top researchers on overall university research performance. Journal of Informetrics, 7(1), 166–175. https://doi.org/10.1016/j.joi.2012.10.006
Abramo, G., & D’Angelo, C. A. (2014). How do you define and measure research productivity? Scientometrics, 101(2), 1129–1144.
Adams, J., Rogers, G., & Szomszor, M. (2019). The annual G20 scorecard: Research performance 2019. Institute for Scientific Information.
Altbach, P. G. (2012). The globalization of college and university rankings. Change: The Magazine of Higher Learning, 44(1), 26–31. https://doi.org/10.1080/00091383.2012.636001
Baltaru, R. D. (2019). Do non-academic professionals enhance universities’ performance? Reputation vs. organisation. Studies in Higher Education, 44(7), 1183–1196. https://doi.org/10.1080/03075079.2017.1421156
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67, 1–48. https://doi.org/10.18637/jss.v067.i01
Beerkens, M. (2013). Facts and fads in academic research management: The effect of management practices on research productivity in Australia. Research Policy, 42(9), 1679–1693. https://doi.org/10.1016/j.respol.2013.07.014
Benito, M., Gil, P., & Romera, R. (2020). Evaluating the influence of country characteristics on the Higher Education System Rankings’ progress. Journal of Informetrics, 14(3), 1–15. https://doi.org/10.1016/j.joi.2020.101051
Bland, C. J., & Ruffin, M. T. (1992). Characteristics of a productive research environment. Academic Medicine, 67(6), 385–397. https://doi.org/10.1097/00001888-199206000-00010
Bonaccorsi, A., Belingheri, P., & Secondi, L. (2021). The research productivity of universities. A multilevel and multidisciplinary analysis on European institutions. Journal of Informetrics, 15(2), 101129. https://doi.org/10.1016/j.joi.2020.101129
Bornmann, L., & Marx, W. (2014). How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations. Scientometrics, 98(1), 487–509. https://doi.org/10.1007/s11192-013-1161-y
Bornmann, L., & Williams, R. (2017). Can the journal impact factor be used as a criterion for the selection of junior researchers? A large-scale empirical study based on ResearcherID data. Journal of Informetrics, 11(3), 788–799. https://doi.org/10.1016/j.joi.2017.06.001
Boyadjieva, P. (2017). Invisible higher education: Higher education institutions from Central and Eastern Europe in global rankings. European Educational Research Journal, 16(5), 529–546. https://doi.org/10.1177/1474904116681016
Brito, R., & Rodríguez-Navarro, A. (2019). Evaluating research and researchers by the journal impact factor: Is it better than coin flipping? Journal of Informetrics, 13(1), 314–324. https://doi.org/10.1016/j.joi.2019.01.009
Buckner, E., & Zhang, Y. (2021). The quantity-quality tradeoff: A cross-national, longitudinal analysis of national student-faculty ratios in higher education. Higher Education, 82(1), 39–60.
Casadevall, A., & Fang, F. C. (2014). Causes for the persistence of impact factor mania. Mbio. https://doi.org/10.1128/mbio.00064-14
Curaj, A., Deca, L., Egron-Polak, E., & Salmi, J. (2015). Higher education reforms in Romania: Between the bologna process and national challenges (p. 226). Springer Nature.
Diem, A., & Wolter, S. C. (2013). The use of bibliometrics to measure research performance in education sciences. Research in Higher Education, 54(1), 86–114.
Dobbins, M. (2017). Exploring higher education governance in Poland and Romania: Re-convergence after divergence? European Educational Research Journal, 16(5), 684–704. https://doi.org/10.1177/1474904116684138
Dunbar, H., & Lewis, D. R. (1998). Determinants of research productivity in higher education. Research in Higher Education, 39(6), 607–631.
Krapels, J. et al. (2015). The relationship between research spending and research performance A cross-country and in-depth study. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/768161/RAND_Europe_Research_Performance_Report.PDF
Ministerul Educatiei. (n.d.). Ministerul Educatiei. Retrieved January 10, 2022, from https://www.edu.ro/
Fox, K. J., & Milbourne, R. (1999). What determines research output of academic economists? The Economic Record, 75, 256–267.
Fox, M. F. (1983). Publication productivity among scientists: A critical review. Social Studies of Science, 13, 285–305.
Garfield, E. (1979). Is citation analysis a legitimate evaluation tool?. Scientometrics, 1, 359–375.
Gavris, A. (2020). The Re(Production) of Meritocracy: Challenges from the Romanian education system under neoliberalism. Studia UBB Sociologia, 65(1), 69–89. https://doi.org/10.2478/subbs-2020-0003
Grossetti, M. (2014). From 18th century chemistry to the 21st century creative class: A sociological perspective on policies intended to promote local economic development based on innovation. In R. Sternberg & G. Krauss (Eds.), Handbook of research on entrepreneurship and creativity (pp. 275–295). Edward Elgar.
Harley, D., Acord, S. K., Earl-Novell, S., Lawrence, S., & King, C. J. (2010). Assessing the future landscape of scholarly communication: An exploration of faculty values and needs in seven disciplines. Center for Studies in Higher Education.
Harris, G. T. (1990). Research output in Australian university economics departments: An update for 1984–88. Australian Economic Papers, 29(55), 249–259.
Hauptman Komotar, M. (2019). Global university rankings and their impact on the internationalization of higher education. European Journal of Education, 54(2), 299–310. https://doi.org/10.1111/ejed.12332
Hazelkorn, E. (2015). Rankings and the reshaping of higher education: The battle for world-class excellence. Palgrave Macmillan.
Heng, K., Hamid, M., & Khan, A. (2020). Factors influencing academics’ research engagement and productivity: A developing countries perspective. Issues in Educational Research, 30(3), 965–987.
Horta, H., Velos, F. M., & Grediaga, R. (2010). Navel gazing: Academic inbreeding and scientific productivity. Management Science, 56(3), 414–429.
Kifor, C. V., Teodorescu, D., Andrei, T., & Săvescu, R. (2021). Research production and international visibility in higher education: The evolution of Romanian universities from 2011 to 2019. Sustainability, 13(23), 13362. https://doi.org/10.3390/su132313362
McKiernan, E. C., Schimanski, L. A., Muñoz Nieves, C., Matthias, L., Niles, M. T., & Alperin, J. P. (2019). Use of the Journal Impact Factor in academic review, promotion, and tenure evaluations. eLife, 8, 47338. https://doi.org/10.7554/elife.47338
Milborrow, S. (2020). rpart.plot: Plot 'rpart' Models: An Enhanced Version of 'plot.rpart'. R package version 3.0.9. https://CRAN.R-project.org/package=rpart.plot
Miroiu, A., Florian, B. (2015). Universitatea Romaneasca Azi. Editura Tritonic: Bucharest, Romania.
Negash, M., Lemma, T. T., & Samkin, G. (2019). Factors impacting accounting research output in developing countries: An exploratory study. The British Accounting Review, 51(2), 170–192. https://doi.org/10.1016/j.bar.2018.09.003
O’Meara, K. (2007). Striving for what? Exploring the pursuit of prestige. Higher education: Handbook of theory and research (Vol. 22, p. 121). Springer Publishing.
Potter, R. W., Szomszor, M., & Adams, J. (2020). Interpreting CNCIs on a country-scale: The effect of domestic and international collaboration type. Journal of Informetrics, 14(4), 101075. https://doi.org/10.1016/j.joi.2020.101075
R Core Development Team. (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing. http://www.r-project.org.
Ramsden, P. (1994). Describing and explaining research productivity. Higher education, 28(2), 207–226
Salmi, J. (2009). The challenge of establishing world class universities (directions in development). World Bank Publications.
Sandström, U., & Van den Besselaar, P. (2018). Funding, evaluation and the performance of national research systems. Journal of Informetrics, 12, 365–384. https://doi.org/10.1016/j.joi.2018.01.007
Schenker-Wicki, A., & Inauen, M. (2012). The economics of teaching. Higher Education Management and Policy, 23(3), 1–20.
Sîrbu, I., & Benedek, A. M. (2012). Ecologie practică. Editura Universităţii Lucian Blaga.
Šmilauer, P., & Lepš, J. (2014). Multivariate analysis of ecological data using Canoco 5 (2nd ed.). Cambridge University Press.
Stack, M. (2021). Global university rankings and the politics of knowledge. University of Toronto Press.
Stephan, P., & Levin, S. (1992). Striking the mother lode in science. Oxford University Press.
Consiliul Național Pentru Finanțarea Învățământului Superior. (2019). Raport Public 2019. CNFIS. http://www.cnfis.ro/wp-content/uploads/2020/12/raport_public_CNFIS_2019.pdf
Sursock, A. (2014). Ten priorities for Romanian Higher Education. UEFISCDI. Institutional Evaluation Programme, Performance in Research, Performance in Teaching: Quality, Diversity, and Innovation in Romanian Universities Project. Retrieved December 14, 2020, from https://www.iep-qaa.org/downloads/publications/romaniasystemreviewreport.pdf
Teodorescu, D. (2000). Correlates of faculty publication productivity: A cross-national analysis. Higher Education, 39, 201–222. https://doi.org/10.1023/A:1003901018634
Ter Braak, C. J. F., & Šmilauer, P. (2018). Canoco reference manual and user’s guide: Software for ordination (version 5.10). Wageningen University & Research.
Thelwall, M., & Fairclough, R. (2017). The research production of nations and departments: A statistical model for the share of publications. Journal of Infometrics, 11(4), 1142–1157.
Therneau, T., Atkinson, B., (2019). rpart: Recursive Partitioning and Regression Trees. R package version 4.1–15. https://CRAN.R-project.org/package=rpart
Thompson, R. (2018). Indicators handbook. InCites.
Vancea, D. P., Bobe, A., & Gîrțu, M. A. (2016). Challenges and trends in financing Romanian higher education Will the reform be driven by the report of the Romanian Court of Accounts? Revista De Politica Ştiintei Si Scientometrie, 5(3), 214–237.
Vîiu, G., Păunescu, M., & Miroiu, A. (2016). Research-driven classification and ranking in higher education: An empirical appraisal of a Romanian policy experience. Scientometrics, 107, 785–805. https://doi.org/10.1007/s11192-016-1860-2
Waltman, L. (2016). A review of the literature on citation impact indicators. Journal of Informetrics, 10(2), 365–391. https://doi.org/10.1016/j.joi.2016.02.007
Zhang, L., Bao, W., & Sun, L. (2016). Resources and research production in higher education: A longitudinal analysis of Chinese universities, 2000–2010. Research in Higher Education, 57(7), 869–891. https://doi.org/10.1007/s11162-016-9410-6
Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A., & Smith, G. M. (2009). Mixed effects models and extensions in ecology with R. Springer Science+Business Media.
Funding
This work was supported by a Hasso Plattner Excellence Research Grant (LBUS-HPI-ERG-2020-02), financed by the Knowledge Transfer Center of the Lucian Blaga University of Sibiu.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interests
The authors declare no competing interests.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Annex 1: University categories and codes
Annex 1: University categories and codes
Research intensive universities
BP = Polytechnic University of Bucharest, B = University of Bucharest, BES = Bucharest University of Economic Studies, BCD = Carol Davila University of Medicine and Pharmacy Bucharest, CT = Technical University of Cluj Napoca, CAV = University of Agricultural Sciences and Veterinary Medicine of Cluj Napoca, CBB = Babes Bolyai University of Cluj Napoca, CIU = Iuliu Hatieganu University of Medicine and Pharmacy Cluj Napoca, IGA = Gheorghe Asachi Technical University of Iasi, IAC = Alexandru Ioan Cuza University of Iasi, IGP = Grigore T. Popa University of Medicine and Pharmacy Iasi, TP = Polytechnic University of Timisoara,
Teaching and research universities
BTE = Technical University of Civil Engineering Bucharest, BAV = University of Agronomic Sciences and Veterinary Medicine of Bucharest, NPP = National University of Political Studies & Public Administration, BVT = Transilvania University of Brasov, CTO = Ovidius University of Constanta, CRO = University of Craiova, CRM = University Medicine and Pharmacy of Craiova, GDJ = Dunarea de Jos University of Galati, IAV = University of Agricultural Sciences and Veterinary Medicine of Iasi, O = University of Oradea, SLB = Lucian Blaga University of Sibiu, TMP = G.Emil Palade University of Medicine and Pharmacy Science and Technology of Tg. Mures, TAV = Banat University of Agricultural Sciences and Veterinary Medicine of Timisoara, TW = West University of Timisoara, TVB = Victor Babes University of Medicine and Pharmacy of Timisoara,
Teaching universities
AI1 = 1 Decembrie 1918 University of Alba Iulia, AAV = Aurel Vlaicu University of Arad, BCV = Vasile Alecsandri University of Bacau, CTM = Constanta Maritime University, PET = University of Petrosani, PIT = University of Pitesti, PLO = Oil&Gas University of Ploiesti, SSM = Stefan Cel Mare University of Suceava, TV = Valahia University of Targoviste, JCB = Constantin Brancusi University of Targu Jiu.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Kifor, C.V., Benedek, A.M., Sîrbu, I. et al. Institutional drivers of research productivity: a canonical multivariate analysis of Romanian public universities. Scientometrics 128, 2233–2258 (2023). https://doi.org/10.1007/s11192-023-04655-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11192-023-04655-z