PCA integrated DEA for hostel assessment of a Higher Education Institution

Abstract

Data envelopment analysis (DEA) is a well-known multi-criteria decision-making technique which is used to measure the relative efficiency of decision-making units (DMUs). However, in the case of classical DEA, the discriminatory power is often weak particularly when the number of input and output variables are high. In the paper, combine analytic hierarchy process-principal component analysis, is applied to identify the most relevant criteria thereby reducing the number of criteria and increasing the discriminatory power of DEA. Further, in this study, super-efficiency-data envelopment analysis is applied to determine the efficiency of DMUs. The feasibility of the proposed process is illustrated for a real-world multi-criteria decision-making problem based on the hostel management system for the higher education institute and assesses the performance of the decision-making units.