Measuring the Efficiency of Knowledge Output at Saudi Public Universities: An Application of Data Envelopment Analysis

Abstract

The aim of this research was to measure the relative efficiency of knowledge output at Saudi public universities via data envelopment analysis. A performance assessment of 28 Saudi public universities was conducted using constant returns to scale (CRS) and variable returns to scale (VRS) models. The models were designed to include five variables: three input variables (enrolled students; faculty members; and administrators and technicians) and two knowledge output variables (research publications in journals with an impact factor and indexed in the Institute for Scientific Information (ISI) Web of Knowledge; and the number of graduates in the previous year). Data were analysed for the 2019/2020 academic year, a period significantly impacted by the COVID-19 pandemic. The results revealed that 82% of the studied universities were inefficient in using their resources. The CRS model produced an average score of 0.769, with 76% of the universities achieving efficiency at their output level during the selected academic year. The VRS model produced an average efficiency score of 0.888 under variable returns to scale. The results also indicated that some of the institutions had become so inefficient that they were not fit to serve as benchmarks for others. These findings highlight the need to examine how policy modifications and higher education governance affect the knowledge output efficiency of universities and how efficiently universities perform in general.

Keywords: Data Envelopment Analysis, Constant Returns to Scale, Variable Returns to Scale, Saudi Public Universities.

DOI: 10.7176/IKM/16-1-04

Publication date: March 31^st 2026