Performance evaluation of technical institutions: an application of data envelopment analysis
29 Apr 2008-Education, Knowledge and Economy (Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals)-Vol. 2, Iss: 1, pp 51-66
TL;DR: The method of data envelopment analysis (DEA) is employed to compare the relative efficiency of TIs in India and the results are insightful to the educational planner as it identifies priority areas for each technical institute, which can improve the performance.
Abstract: Technical institutions (TIs) are playing an important role in making India a knowledge hub of this century. There is still great diversity in their relative performance, which is a matter of concern to the education planner. This article employs the method of data envelopment analysis (DEA) to compare the relative efficiency of TIs in India. The identification of the strongest and the weakest parameters of various TIs could be very useful in improving their efficiency and performance. Mathematically, DEA determines the best weights for each input and output for a particular unit under study so as to maximize its relative efficiency. The results are insightful to the educational planner as it identifies priority areas for each technical institute, which can improve the performance. This article also identifies some generic insights from this study. This article is one of the few published studies that evaluate the performance of technical institutes in India.
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TL;DR: In this paper, the authors examined the relationship of service marketing mix (SMM) as service input and service output in terms of students' performance, satisfaction and referral act in context to higher and technical education (HTE) through the application of structural equation modeling.
Abstract: The purpose of this paper is to examine the relationships of service marketing mix (SMM) as service input and service output in terms of students’ performance, satisfaction and referral act in context to higher and technical education (HTE) through the application of structural equation modeling.,A quantitative research, conducted through a self-administered survey composed by a closed-ended structured questionnaire, was incorporated for the students who were enrolled in the technical educational institutions situated in the Khandesh region of India.,The findings of this study revealed that traditional SMM is statistically linked with the performance of students in terms of skill and knowledge enhancement, satisfaction and referral act of students, which are perceptible new emerging SMM; performance, pleasure and pointing out in terms of service output.,Integrating SMM as service input and service output are productive for HTE in enhancing growth (quantitatively) by the inclusivity of diversified students and development (qualitatively) by enhancing their performance for global standing, making them satisfied and motivating them for recommending their institution to others. This integration can be utilized as a yardstick by the institutions for staying ahead in students’ market with a distinctive competitive advantage.,Growth and development of HTE will raise a society’s quality of life and thereby increase a country’s socio-economic status.,The study has exhibited SMM as input and output of a service system that is useful for the growth and development of HTE. The measurement tool presented is effective in (re)framing policies on SMM as service input based on desired service output.
18 citations
TL;DR: In this article, data envelopment analysis (DEA) is used to measure the relative efficiency of 25 public universities in Saudi Arabia and results show that although most public universities are efficient, some fall behind in performance due to poor utilization of available resources.
Abstract: Saudi Arabia is one of the countries that allot substantial amount of government resources for education. Thus, it is important to measure how these resources are used to generate favorable academic outcomes for its nationals. In this study, data envelopment analysis (DEA) is used to measure the relative efficiency of 25 public universities in Saudi Arabia. Results show that although most public universities in the country are efficient, some fall behind in performance due to poor utilization of available resources. Implications of this are discussed and recommendations are provided.
17 citations
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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.
25,433 citations
"Performance evaluation of technical..." refers background in this paper
...Later on Charnes, Cooper and Rhodes ( 1978 ) generalized Farrell's framework and popularized the concept....
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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
"Performance evaluation of technical..." refers methods in this paper
...The two most frequently applied models used in DEA are the CCR model – after Charnes, Cooper and Rhodes ( 1978 ) – and the BCC model, after Banker, Charnes and Cooper ( 1984 )....
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Book•
30 Nov 1999TL;DR: In this article, the basic CCR model and DEA models with restricted multipliers are discussed. But they do not consider the effect of non-discretionary and categorical variables.
Abstract: List of Tables. List of Figures. Preface. 1. General Discussion. 2. The Basic CCR Model. 3. The CCR Model and Production Correspondence. 4. Alternative DEA Models. 5. Returns to Scale. 6. Models with Restricted Multipliers. 7. Discretionary, Non-Discretionary and Categorical Variables. 8. Allocation Models. 9. Data Variations. Appendices. Index.
4,395 citations
Posted Content•
TL;DR: In this article, the authors point out that public and professional interest in education is likely to be short-lived, doomed to dissipate as frustration over the inability of policy to improve school practice sets in.
Abstract: N RECENT YEARS, public and professional interest in schools has been heightened by a spate of reports, many of them critical of current school policy.' These policy documents have added to persistent and long-standing concerns about the cost, effectiveness, and fairness of the current school structure, and have made schooling once again a serious public issue. As in the past, however, any renewed interest in education is likely to be short-lived, doomed to dissipate as frustration over the inability of policy to improve school practice sets in. This frustration about school policy relates directly to knowledge about the educational production process and in turn to underlying research on schools. Although the educational process has been extensively researched, clear policy prescriptions flowing from this research have been difficult to derive.2 There exists, however, a consistency to the research findings that does have an immediate application to school policy: Schools differ dramatically in "quality,"
3,102 citations
"Performance evaluation of technical..." refers background in this paper
...Hanushek ( 1986 , 1989 ) has published influential reviews of literally hundreds of education production function studies and concluded that existing methods failed to show any systematic relationship between student outcomes and such things as per pupil expenditures, teacher/pupil ratios, teacher education, teacher experience and teacher salaries....
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2,617 citations
"Performance evaluation of technical..." refers methods in this paper
...The two most frequently applied models used in DEA are the CCR model – after Charnes, Cooper and Rhodes (1978) – and the BCC model, after Banker, Charnes and Cooper (1984). The basic difference between these two models is the returns-to-scale (RTS)....
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