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This paper adopts a modified approach of data envelopment analysis (DEA) to measure the academic efficiency of university departments. In real-world case studies, conventional DEA models often identify too many decision-making units (DMUs) as efficient. This occurs when the number of DMUs under evaluation is not large enough compared to the total number of decision variables. To overcome this limitation and reduce the number of decision variables, multiobjective data envelopment analysisdoi:10.1007/s40092-018-0258-6 fatcat:asrzulpoc5cwxhdhd7jwkzgbuq