Research Performance and Hierarchical Staff-Mix by Rank in a Research-Oriented System: A Case Study

Virtue U. Ekhosuehi ()
Additional contact information
Virtue U. Ekhosuehi: Department of Statistics, University of Benin, P.M.B. 1154, Benin City, Nigeria

Journal of Information & Knowledge Management (JIKM), 2022, vol. 21, issue 04, 1-23

Abstract: 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.

Keywords: Nigerian university system; research performance; scientometric analysis; scientist; Scopus; staff-mix by rank (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219649222500551
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:jikmxx:v:21:y:2022:i:04:n:s0219649222500551

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219649222500551

Access Statistics for this article

Journal of Information & Knowledge Management (JIKM) is currently edited by Professor Suliman Hawamdeh

More articles in Journal of Information & Knowledge Management (JIKM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().