Benchmarking of academic departments using data envelopment analysis (DEA)

Purpose The main objective of the paper is to develop an investment model using data envelopment analysis (DEA) that provides a decision-making framework allocate resources efficiently, such relative efficiency improved within available budget. Design/methodology/approach Firstly, DEA models are used evaluate departments their peers and providing benchmarks for less efficient departments. Secondly, inefficiencies in identified. Finally, departments, decision-support system introduced optimizing resource allocation improve efficiency. Findings Five 18 academic were determined be inefficient, benchmark found those most prevalent causes inefficiency number undergraduate students per faculty graduate students. Results from department 12 suggest increasing by 2 units H-Index 0.5 units, thereby, improving 6.8% (88%–94%), $290,000 out $500,000 budget provided. Originality/value When available, no study has maximize