The impact of size and specialisation on universities' department performance: A DEA analysis applied to Austrian universities

This paper explores the performance efficiency of natural and technical science departments at Austrian universities using Data Envelopment Analysis (DEA). We present DEA as an alternative tool for benchmarking and ranking the assignment of decision-making units (organisations and organisational units). The method applies a multiple input and output variables approach, which is a clear advantage to other approaches using simple performance ratios. To deliver reasonable results, suitable input and output variables have been determined in a previous step using correlation analyses and OLS regression. The results validate the methods applied, and reveal performance differences and scale effects. The use of multiple output variables enables the revealing of detailed improvement or reduction amounts of each input and output of the evaluated units and furthermore for identifying the specialisation of teaching, research, and industrial cooperation. We find significant evidence that the size of a department influences its overall and specialisation performance; both small and large departments perform above average, which proves that simple linear scale effects do not exist.