A new model based on the extended COPRAS method for improving performance during the accreditation process of Indian Higher Educational Institutions

Abstract

AbstractThe standard of any country in the global world is dependent highly on the intellect content of the people. This intellect content is in turn dependent exclusively upon the quality of the higher education in the country. The aim of this research work is to perform an empirical evaluation to rank various quality parameters suggested by the National Board of Accreditation. This national board was established in India in 1994 by the All India Council for Technical Education with the main motive of assessing the quality of various Higher Educational Institutions. It provides marks to institutions out of 1000 on the basis of 10 parameters, which are further subdivided into 75 subparameters. This research work helps to guide educational institutions to access their weak points during and before applying for this accreditation to recover from them timely and in the most effective manner. An extended model of fuzzy COPRAS (COmplex PRoportional ASsessment) is proposed as an improved multicriteria decision‐making approach to first identify and then set preferences to help institutions improve their data related to accreditation key indicators. The work is divided into four steps. First, all the critical evaluation factors for the accreditation process are identified in consultation with senior, experienced and qualified academicians. They are then converted into fuzzy triangular numeric values and crisp weights. Lingual values and corresponding fuzzy weights of various preference key indicators are then identified and converted into crisp weights. Further critical factors are divided into price and profit values. Finally, key indicators are ranked using extended fuzzy COPRAS. A comparative ranking analysis is generated as end result through fuzzy COPRAS, TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and WASPAS (Weighted Aggregated Sum Product Assessment) approaches, which shows that the proposed model generates better ranking results. The proposed model is applicable to any accreditation process with a varied set of parameters and their subparameters.