Statistical evaluation of research performance of young university scholars: A case study

Abstract

The research performance of a small group of 49 young scholars, such as doctoral students, postdoctoral and junior researchers,
working in different technical and scientific fields, was evaluated based on 11 types of research outputs. The scholars worked
at a technical university in the fields of Civil Engineering, Ecology, Economics, Informatics, Materials Engineering, Mechanical
Engineering, and Safety Engineering. Principal Component Analysis was used to statistically analyze the research outputs
and its results were compared with factor and cluster analysis. The metrics of research productivity describing the types of
research outputs included the number of papers, books and chapters published in books, the number of patents, utility models
and function samples, and the number of research projects conducted. The metrics of citation impact included the number
of citations and h-index. From these metrics – the variables – the principal component analysis extracted 4 main principal
components. The 1st principal component characterized the cited publications in high-impact journals indexed by the Web of
Science. The 2nd principal component represented the outputs of applied research and the 3rd and 4th principal components
represented other kinds of publications. The results of the principal component analysis were compared with the hierarchical
clustering using Ward’s method.