Research, Teaching, Performance: An Analysis Using Frontiers and Meta-frontiers
TL;DR: In this paper, the authors estimate the research efficiency scores of higher education institutions in India and compare the efficiencies in research and teaching according to characteristics like ownership, specialisation of courses and age.
Abstract: The paper aims to: a) estimate the research efficiency scores of Higher Educational Institutions (HEIs) in India, b) compare efficiencies in research and teaching according to characteristics like ownership, specialisation of courses and age and c) estimate the group efficiencies of HEIs categorized according to their characteristics. We estimate efficiency scores using Data Envelopment Analysis and, for the first time, find out the Meta-technology ratio for each group to identify the group which represents the operations and processes of entire higher education. Research efficiencies are higher than teaching efficiencies. In terms of research efficiency, old HEIs perform better than young HEIs, Public HEIs perform better than Private HEIs and HEIs specialising in Non-professional courses perform better than HEIs specialising in Professional courses. The teaching-learning and research processes followed by public HEIs are closer to those followed by the entire higher education system. The association between teaching and research is low.
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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.
Abstract: In management contexts, mathematical programming is usually used to evaluate a collection of possible alternative courses of action en route to selecting one which is best. In this capacity, mathematical programming serves as a planning aid to management. Data Envelopment Analysis reverses this role and employs mathematical programming to obtain ex post facto evaluations of the relative efficiency of management accomplishments, however they may have been planned or executed. Mathematical programming is thereby extended for use as a tool for control and evaluation of past accomplishments as well as a tool to aid in planning future activities. 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. A separation into technical and scale efficiencies is accomplished by the methods developed in this paper without altering the latter conditions for use of DEA directly on observational data. Technical inefficiencies are identified with failures to achieve best possible output levels and/or usage of excessive amounts of inputs. Methods for identifying and correcting the magnitudes of these inefficiencies, as supplied in prior work, are illustrated. In the present paper, a new separate variable is introduced which makes it possible to determine whether operations were conducted in regions of increasing, constant or decreasing returns to scale in multiple input and multiple output situations. The results are discussed and related not only to classical single output economics but also to more modern versions of economics which are identified with "contestable market theories."
14,941 citations
TL;DR: In this article, non-parametric techniques are used to estimate technical and scale efficiency of individual Australian universities and the results show that regardless of the output-input mix, Australian universities as a whole recorded high levels of efficiency relative to each other.
703 citations
Abstract: The global expansion of access to higher education has increased demand for information on academic quality and has led to the development of university ranking systems or league tables in many countries of the world. A recent UNESCO/CEPES conference on higher education indicators concluded that cross-national research on these ranking systems could make an important contribution to improving the international market for higher education. The comparison and analysis of national university ranking systems can help address a number of important policy questions. First, is there an emerging international consensus on the measurement of academic quality as reflected in these ranking systems? Second, what impact are the different ranking systems having on university and academic behavior in their respective countries? Finally, are there important public interests that are thus far not reflected in these rankings? If so, is there a needed and appropriate role for public policy in the development and distribution of university ranking systems and what might that role be? This paper explores these questions through a comparative analysis of university rankings in Australia, Canada, the UK, and the US.
607 citations
TL;DR: 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.
574 citations
TL;DR: In this article, the problem of determining teaching and research efficiencies for university departments concerned with the same discipline is considered, and a non-linear approach based upon data envelopment analysis is presented.
Abstract: In this paper we consider the problem of determining teaching and research efficiencies for university departments concerned with the same discipline. Considering this problem highlights the issue of how to determine efficiencies when resources are shared between different activities, and a non-linear approach to this issue based upon data envelopment analysis is presented. Computational results are given for chemistry and physics departments in the United Kingdom.
421 citations