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In pursuit of achieving Education‐For‐All goals of universal primary education and improving quality of education, the Indian Government has been providing substantial…
In pursuit of achieving Education‐For‐All goals of universal primary education and improving quality of education, the Indian Government has been providing substantial resources to Indian states. The responsibility of providing access and quality remains the states' responsibility. Assessment of educational development will therefore become a focal point of the Center for Education Policy & Guidelines Formulation. While educational development indices help in ranking states, they do not help in capturing best practices and assessing the efficient utilization of resources. Assessment of the Educational Development Efficiency can augment educational development indices in vogue. The purpose of this paper is to develop an Educational Development Efficiency (EDE) model to benchmark the Indian states.
This paper uses an input‐process‐output conceptual framework to identify the dimensions of educational development. This paper employs Data Envelopment Analysis (DEA) to compare relative efficiency of 28 states and seven Union territories in India and benchmark them. In order to strengthen the discriminatory power of DEA, cross‐efficiency model was used. Factor analysis was performed to determine the inter‐relationships between variables. The efficiency impacting variables were identified using multiple regression analysis.
This paper benchmarked Indian states on educational development based on their performance. Gross enrolment ratio, students' academic performance and infrastructural investments were identified as the three key variables impacting states' EDE. This paper has shown that the educational administrators can use the EDE model to identify the best practices from efficient states. Insights into utilization of input resources to enhance educational development and consequent improvement of state efficiencies are presented. Four components have been identified to analyze the states' educational development progress – namely, financial adequacy, school resource strength, educational quality and educational access.
Contributions of this paper pertain to evolving a decision support model for national education policy planners, besides providing analytic support to the administrators of the states to benchmark and emulate the efficient educational programs.
This paper is one of the few published studies concerning the evaluation of educational development programs launched in the Indian schools and providing a cross‐comparison of the Indian states for the purposes of performance benchmarking as well as exploring the influencing factors.
The purpose of this paper is to generate awareness of contributions made by benchmarking toward building performance of Indian service industries in globally market…
The purpose of this paper is to generate awareness of contributions made by benchmarking toward building performance of Indian service industries in globally market. Ranking of Benchmarking is done on the basis of their application which give confidence for the managers to adopt in their Industries so that they may become best in their field.
Methodology consists of three phase: define, phase include definitions, factors of benchmarking as literature outcomes, questionnaire survey and outcome of survey. In the second phase, analysis of collected data and applications of multi-criteria decision-making approaches [technique for order preference by similarity to ideal solution (TOPSIS) and analytical network process (ANP)] are used. The last phase includes comparison of results which gives validation in similarities of ranking obtained.
The study identifies seven different benchmarking techniques used for service industries. Using TOPSIS and ANP approaches shows similarity that external benchmarking, performance benchmarking and internal benchmarking are the first three ranks that give basis for several critical success factors s, namely, planning, reliability, standardization, time behavior, usability, etc., as part of benchmarking using in service industries.
The limitation is the assumptions made by multi-criteria decision-making approaches which may effect the analysis of the study as these are taken theoretically.
This study is a first attempt to find similarities in both techniques while comparing benchmarking in Indian service industries.