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dc.contributor.authorSAINI, LAKSHYA-
dc.date.accessioned2024-08-05T08:54:22Z-
dc.date.available2024-08-05T08:54:22Z-
dc.date.issued2024-06-
dc.identifier.urihttp://dspace.dtu.ac.in:8080/jspui/handle/repository/20795-
dc.description.abstractThe main aim of this study is to re-examine the performance ranking processes of Higher Educational Institutions. National Institutional Ranking Framework (NIRF) is considered as the case ranking organization. The performance indicators used in NIRF are used to produce the different models of performance measurement using correlation and regression analysis. These models are used to measure the relative efficiency of the Higher Engineering Institutions (HEIs) using Data Envelopment Analysis (DEA). It is observed that the same criteria cannot be used to rank the performance of all the institutions. These institutions may be divided into different clusters based on their performance, specialties, constraints, locations, available resources, etc. A separate model of performance measurement should be developed for each cluster. The weights assigned to the different inputs and output variables should be optimal using DEA. The input variables must influence the outputs significantly and be concerned with the context of the analysis. This study may help the policymakers and the performance ranking organization in exploring the performance indicators and finding the performance considering the real situations of the educational institutions. The improved ranking system, with its well-defined outputs, empowers users to make informed decisions about higher education institutions. By providing specific and easy-to-understand information, this system allows users to compare HEIs more effectively. This newfound clarity empowers them to choose the institution that best aligns with their academic goals and career aspirations.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesTD-7313;-
dc.subjectPERFORMANCE RANKINGen_US
dc.subjectHIGHER ENGINEERING INSTITUTIONSen_US
dc.subjectDATA ENVELOPMENT ANALYSISen_US
dc.subjectCORRELATION AND REGRESSION ANALYSISen_US
dc.subjectNIRFen_US
dc.titleMICROANALYSIS OF NIRF RANKING OF TOP-FIFTY ENGINEERING INSTITUTIONS IN INDIA: AN INTEGRATED APPROACH OF DEA and STATISTICAL ANALYSISen_US
dc.typeThesisen_US
Appears in Collections:M.E./M.Tech. Mechanical Engineering

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