System Upgrade on Tue, May 28th, 2024 at 2am (EDT)
Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours. For online purchase, please visit us again. Contact us at customercare@wspc.com for any enquiries.
No Access
Research Performance and Hierarchical Staff-Mix by Rank in a Research-Oriented System: A Case Study
This study examines the relationship between the research performance and the hierarchical staff-mix by rank (or staff-mix categories) for academics in a research-oriented system. A supervised learning approach is employed to classify academics on the basis of their research performance and the association between this classification and the staff-mix categories is measured using the Somer’s D coefficient. Although there have been other studies on research performance for such a system based on the volume-based indicators of research performance, this is the first study that assesses the researchers’ position in the academic reward structure on the basis of research performance. The Scopus database is used as a collection of individual productivity in research. A case-study is presented on a cross-section of academics in the mathematics discipline from different federal universities in Nigeria. The results show that there is a dearth of outstanding scientists in the system and that there is a weak association between research performance and the staff-mix categories. The need for scientific collaboration by way of a continuous collegial interaction between the outstanding scientists and the emerging scholars in the system is suggested.
Aboagye, E, I Jensen, G Bergstrom, EB Bramberg, OJ Pico-Espinosa and C Bjorklund (2021). Investigating the association between publication performance and the work environment of university research academics: A systematic review. Scientometrics, 126, 3283–3301. https://doi.org/10.1007/s11192-020-03820-yCrossref, Web of Science, Google Scholar
Afolabi, IC, SI Popoola, AU Adoghe, AA Atayero and OO Fayomi (2019). Research trends in Nigerian universities: Analysis of number of publications in Scopus (2008–2017). International Journal of Civil Engineering and Technology, 10(3), 148–157. Google Scholar
Anninos, LN (2014). Research performance evaluation: Some critical thoughts on standard bibliometric indicators. Studies in Higher Education, 39(9), 1542–1561. Crossref, Web of Science, Google Scholar
Bi, Y and DR Jeske (2010). The efficiency of logistic regression compared to normal discriminant analysis under class-conditional classification noise. Journal of Multivariate Analysis, 101, 1622–1637. Crossref, Web of Science, Google Scholar
Ebadi, A and A Schiffauerova (2013). Impact of funding on scientific output and collaboration. A survey of literature. Journal of Information & Knowledge Management, 12(4), 1350037. https://doi.org/10.1142/S0219649213500378. Link, Google Scholar
Edgar, F and A Geare (2013). Factors influencing university research performance. Studies in Higher Education, 38(5), 774–792. Crossref, Web of Science, Google Scholar
Ekhosuehi, VU and SE Omosigho (2018). The use of certain staffing requirements as a means of benchmarking academic staff structure. Mathematica Applicanda [Matematyka Stosowana], 46(2), 259–272. https://doi.org/10.14708/ma.v46i2.5175. Google Scholar
Faculty of Physical Sciences (2020). Prospectus of undergraduate and diploma programmes 2019/2020 session. University of Benin, Benin City. Google Scholar
Harris, G and G Kaine (1994). The determinant of research performance: A study of Australian university economists. Higher Education, 27, 191–201. Crossref, Web of Science, Google Scholar
Jacob, BA and L Lefgren (2011). The impact of research grant funding on scientific productivity. Journal of Public Economics, 95, 1168–1177. Crossref, Web of Science, Google Scholar
Jensen, I, C Bjorklund, J Hagberg, E Aboagye and L Bodin (2020). An overlooked key to excellence in research: A longitudinal cohort study on the association between the psycho-social work environment and research performance. Studies in Higher Education, 46(12), 2610–2628. https://doi.org/10.1080/03075079.2020.1744127Crossref, Web of Science, Google Scholar
Kusakunniran, W, AS Dahal and W Viriyasitavat (2018). Journal co-citation analysis for identifying trends of inter-disciplinary research: An exploratory case study in a university. Journal of Information & Knowledge Management, 17(4), 1850040. https://doi.org/10.1142/S0219649218500405. Link, Web of Science, Google Scholar
Mathies, C, J Kivisto and M Birnbaum (2020). Following the money? Performance-based funding and the changing publication patterns of Finnish academics. Higher Education, 79, 21–37. Crossref, Web of Science, Google Scholar
Minka, TP (2004). A comparison of numerical optimizers for logistic regression. Technical Report 758, Carnegie Mellon University, https://www.semanticscholar.org. Google Scholar
Ortega, JL, E Lopez-Romero and I Fernandez (2011). Multivariate approach to classify research institutes according to their outputs: The case of the CSIC’s institutes. Journal of Informetrics, 5, 323–332. Web of Science, Google Scholar
Sarrico, CS, PN Teixeira, MJ Rosa and MF Cardoso (2009). Subject mix and productivity in Portuguese universities. European Journal of Operational Research, 197, 287–295. Crossref, Web of Science, Google Scholar
Shin, JC (2008). Classifying higher education institutions in Korea: A performance-based approach. Higher Education, 57, 247–266. Crossref, Web of Science, Google Scholar
Sile, L and R Vanderstraeten (2018). Measuring changes in publication patterns in a context of performance-based research funding systems: The case of educational research in the University of Gothenburg (2005–2014). Scientometrics, 118, 71–91. https://doi.org/10.1007/s11192-018-2963-8Crossref, Web of Science, Google Scholar
Tanimoto, J and H Fujii (2003). A study on research performance in Japanese universities: Which is more efficient – A professor who is leading his research group or one who is working alone? The multi-agent simulation knows. Advances in Complex Systems, 6(3), 375–391. Link, Web of Science, Google Scholar
Turki, H, MB Aouicha and MAH Taieb (2019). Discussing Arab spring’s effect on scientific productivity and research performance in Arab countries. Scientometrics, 120, 337–339. Crossref, Web of Science, Google Scholar