Efficiency Analysis of Higher Education Institutions: Use of Categorical Variables

This paper focuses on the Data Envelopment Analysis (DEA) based efficiency evaluation to find the impact of two-step categorical impact on the enrollment efficiency of colleges in Bihar, one of the largest states of India. The objective of the study is to find the impact of factors, other than colle...

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Autores principales:	Prabhat Ranjan, Sanjeet Singh
Formato:	article
Lenguaje:	EN
Publicado:	International Journal of Mathematical, Engineering and Management Sciences 2021
Materias:	dea efficiency categorical variables higher education Technology T Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/42081a0a73be465e910c8651599ec9d0
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spelling	oai:doaj.org-article:42081a0a73be465e910c8651599ec9d02021-12-03T17:17:01ZEfficiency Analysis of Higher Education Institutions: Use of Categorical Variables10.33889/IJMEMS.2021.6.6.0902455-7749https://doaj.org/article/42081a0a73be465e910c8651599ec9d02021-12-01T00:00:00Zhttps://ijmems.in/cms/storage/app/public/uploads/volumes/90-IJMEMS-21-0247-6-6-1518-1532-2021.pdfhttps://doaj.org/toc/2455-7749This paper focuses on the Data Envelopment Analysis (DEA) based efficiency evaluation to find the impact of two-step categorical impact on the enrollment efficiency of colleges in Bihar, one of the largest states of India. The objective of the study is to find the impact of factors, other than college-specific, on the efficiency of the colleges. The proposed research includes colleges funded and managed through seven state public universities. To follow the homogeneity condition of DEA, colleges providing courses of Arts (languages and humanities only), Science, and Commerce only, have been selected. The numbers of students enrolled in undergraduate and postgraduate courses are considered as two outputs. Numbers of teaching and non-teaching staff are considered as inputs. Colleges have been classified into two categories based on their presence in the rural or urban areas. The efficiency of a college due to any categorical value is calculated as the ratio of overall efficiency and efficiency calculated with similar categorical Decision-Making Units (DMUs) only. The impact of both the categorical variables, affiliation to university and geographical presence, has been analyzed through the hypothesis testing with the null hypothesis that there is no impact of category on the efficiency of DMUs due to a categorical variable.Prabhat RanjanSanjeet SinghInternational Journal of Mathematical, Engineering and Management Sciencesarticledeaefficiencycategorical variableshigher educationTechnologyTMathematicsQA1-939ENInternational Journal of Mathematical, Engineering and Management Sciences, Vol 6, Iss 6, Pp 1518-1532 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	dea efficiency categorical variables higher education Technology T Mathematics QA1-939
spellingShingle	dea efficiency categorical variables higher education Technology T Mathematics QA1-939 Prabhat Ranjan Sanjeet Singh Efficiency Analysis of Higher Education Institutions: Use of Categorical Variables
description	This paper focuses on the Data Envelopment Analysis (DEA) based efficiency evaluation to find the impact of two-step categorical impact on the enrollment efficiency of colleges in Bihar, one of the largest states of India. The objective of the study is to find the impact of factors, other than college-specific, on the efficiency of the colleges. The proposed research includes colleges funded and managed through seven state public universities. To follow the homogeneity condition of DEA, colleges providing courses of Arts (languages and humanities only), Science, and Commerce only, have been selected. The numbers of students enrolled in undergraduate and postgraduate courses are considered as two outputs. Numbers of teaching and non-teaching staff are considered as inputs. Colleges have been classified into two categories based on their presence in the rural or urban areas. The efficiency of a college due to any categorical value is calculated as the ratio of overall efficiency and efficiency calculated with similar categorical Decision-Making Units (DMUs) only. The impact of both the categorical variables, affiliation to university and geographical presence, has been analyzed through the hypothesis testing with the null hypothesis that there is no impact of category on the efficiency of DMUs due to a categorical variable.
format	article
author	Prabhat Ranjan Sanjeet Singh
author_facet	Prabhat Ranjan Sanjeet Singh
author_sort	Prabhat Ranjan
title	Efficiency Analysis of Higher Education Institutions: Use of Categorical Variables
title_short	Efficiency Analysis of Higher Education Institutions: Use of Categorical Variables
title_full	Efficiency Analysis of Higher Education Institutions: Use of Categorical Variables
title_fullStr	Efficiency Analysis of Higher Education Institutions: Use of Categorical Variables
title_full_unstemmed	Efficiency Analysis of Higher Education Institutions: Use of Categorical Variables
title_sort	efficiency analysis of higher education institutions: use of categorical variables
publisher	International Journal of Mathematical, Engineering and Management Sciences
publishDate	2021
url	https://doaj.org/article/42081a0a73be465e910c8651599ec9d0
work_keys_str_mv	AT prabhatranjan efficiencyanalysisofhighereducationinstitutionsuseofcategoricalvariables AT sanjeetsingh efficiencyanalysisofhighereducationinstitutionsuseofcategoricalvariables
_version_	1718373142004498432

Efficiency Analysis of Higher Education Institutions: Use of Categorical Variables

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