Research Productivity in Terms of Output, Impact, and Collaboration for University Researchers in Saudi Arabia: SciVal Analytics and t-Tests Statistical Based Approach

Abstract

Analysis of the research productivity for any university is so important in order to raise its international ranking. Rankings offer universities evidence that the education they deliver is of high quality and top standard. A student’s level of dedication to their studies directly affects the outcome of their academic career. Sitting in on a lecture at a top-five rated institution is far less significant than actively contributing (engaging with classmates, doing research, etc.) at a top-50 ranked university. Using a SciVal dataset of 13 university entities across the Kingdom of Saudi Arabia over a span of 5 years (2017–2021), we conducted a scientometric study for three categories, namely Output (O), Impact (I), and Collaboration (C), incorporating a total of 18 features. The methodology for selecting universities in this research depended on selecting the best universities in the Kingdom of Saudi Arabia in terms of the number of published research papers and the number of citations. This article aims to forecast the pattern of development and shortcomings faced by researchers from around the country from 2017 to 2021. The dataset is evaluated at the university level with homogenized features termed as “Scholar Plot” (SP), a popular approach to maintain and encourage development at the individual level. It is concluded that variances in efficiency within each knowledge field are the major drivers of heterogeneity in scientific output. Disparities in quality and specialization play a lesser impact in influencing productivity differences. The measure of such disparities using the mean of the group’s significance is illustrated using a t-tests statistical approach.