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Journal ArticleDOI

Investigating technical and scale efficiencies of australian universities through data envelopment analysis

Necmi K. Avkiran
- 01 Mar 2001 - 
- Vol. 35, Iss: 1, pp 57-80
TLDR
In this article, the authors used data envelopment analysis (DEA) to examine the relative efficiency of Australian universities and developed three performance models, namely, overall performance, performance on delivery of educational services, and performance on fee-paying enrolments.
Abstract
Performance indicators in the public sector have often been criticised for being inadequate and not conducive to analysing efficiency. The main objective of this study is to use data envelopment analysis (DEA) to examine the relative efficiency of Australian universities. Three performance models are developed, namely, overall performance, performance on delivery of educational services, and performance on fee-paying enrolments. The findings based on 1995 data show that the university sector was performing well on technical and scale efficiency but there was room for improving performance on fee-paying enrolments. There were also small slacks in input utilisation. More universities were operating at decreasing returns to scale, indicating a potential to downsize. DEA helps in identifying the reference sets for inefficient institutions and objectively determines productivity improvements. As such, it can be a valuable benchmarking tool for educational administrators and assist in more efficient allocation of scarce resources. In the absence of market mechanisms to price educational outputs, which renders traditional production or cost functions inappropriate, universities are particularly obliged to seek alternative efficiency analysis methods such as DEA.

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Book ChapterDOI

Data Envelopment Analysis: History, Models, and Interpretations

TL;DR: This chapter discusses the basic DEA models and some of their extensions, which have been successfully applied to a host of many different types of entities engaged in a wide variety of activities in many contexts worldwide.
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Data Envelopment Analysis and Its Application to the Measurement of Efficiency in Higher Education.

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Efficiency in education: a review of literature and a way forward

TL;DR: The authors provide an extensive overview of the literature on efficiency in education, summarizing the earlier applied inputs, outputs and contextual variables, as well as the used data sources of papers in the field of education.
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Measuring the research performance of Chinese higher education institutions using data envelopment analysis

TL;DR: In this article, the authors used data envelopment analysis (DEA) to examine the relative efficiency in the production of research of 109 Chinese regular universities in 2003 and 2004, and found that mean research efficiency is higher in comprehensive universities compared to specialist universities, and in universities located in the coastal region compared to those in the western region of China.
References
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Journal ArticleDOI

Measuring the efficiency of decision making units

TL;DR: A nonlinear (nonconvex) programming model provides a new definition of efficiency for use in evaluating activities of not-for-profit entities participating in public programs and methods for objectively determining weights by reference to the observational data for the multiple outputs and multiple inputs that characterize such programs.
Journal ArticleDOI

Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis

TL;DR: The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs as mentioned in this paper.
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TL;DR: In this article, the authors present DEA Software Packages for the U.S. Airline Industry and present a Spatial Efficiency Framework for the Support of Locational Decision (SELF).
Journal ArticleDOI

Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through

TL;DR: A model for measuring the efficiency of Decision Making Units =DMU's is presented, along with related methods of implementation and interpretation, and suggests the additional possibility of new approaches obtained from PFT-NFT combinations which may be superior to either of them alone.
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