PERFORMANCE EVALUATION OF HIGHER EDUCATION INSTITUTIONS IN INDIA THROUGH ENHANCED DATA ENVELOPMENT ANALYSIS MODELS

Abstract

The primary focus of the thesis is to utilize various DEA models, including classical DEA and extended DEA models, along with proposed hybrid DEA models, to address the limitations of classical DEA models. The hybrid DEA models developed in this work are PCA-DEA, DEA-GA, DEA-weighted sum method, and integrated DEA-∈-constraint method. Sensitivity analysis is employed to validate the results, and the Analytic Hierarchy Process (AHP) method is used for qualitative data analysis. Problems considered in the thesis are assessment of teaching and research performance of various departments of the institute along with the residential and mess facilities provided to the students. The thesis is divided into six chapters. Chapter 1 serves as an introduction to the study. It provides an overview of DEA, discussing various DEA models, hybrid DEA models and their applications in different domains. Chapter 2 provides background information on DEA and discusses the DEA models and hybrid models developed during this research. In Chapter 3, the focus is on measuring the performance of hostels and mess facilities of a Higher Educational Institute using MCDM methods. The study treats performance analysis as a multi-criterion decision-making (MCDM) problem and conducts a survey to identify 13 criteria affecting the performance. Analytic Hierarchy Process (AHP) is used for qualitative analysis, while Data Envelopment Analysis (DEA) is used for quantitative analysis. Relevant performance factors are identified through AHP and DEA sensitivity analysis (DEA-SA). Chapter 4 presents hybrid MCDM method viz. Analytic Hierarchy Process-with Principal Component Analysis (AHP-PCA) to identify essential criteria, reduce the number of criteria, and increase the discriminatory power of DEA. Further, Super-efficiency Data Envelopment Analysis (SE-DEA) is applied to determine the efficiency of Decision Making Units (DMUs) for hostel management. In Chapter 5, the performance of different departments vis-à-vis research and teaching is explored. This chapter is divided into two sections. The first part uses an integrated technique, DEA with Genetic Algorithm (GA), to maximize the efficiency of DMUs. The second part employs two integrated techniques: DEA with the Weighted Sum method and DEA with the ∈-Constraint method, to overcome the drawbacks of classical DEA models. Chapter 6 summarizes the entire work and presents final conclusions. Future research directions are also discussed in this chapter.