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Journal ArticleDOI

Output–input ratio analysis and DEA frontier

01 Nov 2002-European Journal of Operational Research (North-Holland)-Vol. 142, Iss: 3, pp 476-479
TL;DR: It is shown that top-ranked performance by ratio analysis is a DEA frontier point, which allows identification of membership of frontier DMUs without solving a DEA program.
About: This article is published in European Journal of Operational Research.The article was published on 2002-11-01. It has received 63 citations till now. The article focuses on the topics: Data envelopment analysis.
Citations
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Journal ArticleDOI
TL;DR: The development of a model to handle unrestricted data in a DEA framework is reported on and the use of this model on data from the bank concerned is illustrated.
Abstract: This paper is drawn from the use of data envelopment analysis (DEA) in helping a Portuguese bank to manage the performance of its branches. The bank wanted to set targets for the branches on such variables as growth in number of clients, growth in funds deposited and so on. Such variables can take positive and negative values but apart from some exceptions, traditional DEA models have hitherto been restricted to non-negative data. We report on the development of a model to handle unrestricted data in a DEA framework and illustrate the use of this model on data from the bank concerned.

351 citations

Journal ArticleDOI
TL;DR: In this article, the authors investigate to what extent bank DEA super-efficiency estimates are associated with key financial ratios and find that a low correlation may present an opportunity to address inefficiencies that were not obvious in financial ratio analysis, thus enabling an update of inferences drawn from ratios.
Abstract: The great majority of applications of the popular frontier technique data envelopment analysis (DEA) do not test for the association of efficiency estimates with key performance indicators used by industry observers. Nevertheless, identifying efficiency estimates’ associations with commonly accepted financial measures of performance could guide benchmarking activities, pricing decisions, and regulatory monitoring. Thus, the current paper investigates to what extent bank DEA super-efficiency estimates are associated with key financial ratios. A low correlation may present an opportunity to address inefficiencies that were not obvious in financial ratio analysis, thus enabling an update of inferences drawn from ratios. Regressing ratios on efficiency estimates may also help predict financial ratios. Where an input–output specification is comprised of key financial ratios, DEA can also be used to objectively identify benchmarks for ratio analysis based on actual observed data collected from peers. Nine super-efficiency DEA formulations across two profitability models are systematically tested. The slacks-based measure of DEA with a parsimonious profitability efficiency model emerges as the most significant combination explaining the variation in the two industry ratios, post-tax profit/average total assets and return on average equity .

218 citations

Journal ArticleDOI
TL;DR: This paper presents a study on building DEA models without explicit inputs, so-called DEA-WEI models, which are applicable to the evaluation applications where inputs are not directly considered.
Abstract: In performance evaluations, data without explicit inputs (such as index data, pure output data) are widely used. To directly use such data, this paper presents a study on building DEA models without explicit inputs, so-called DEA-WEI models, which are applicable to the evaluation applications where inputs are not directly considered. We provide an axiom foundation of these kinds of models, and further discuss how to incorporate value judgments of decision makers into these DEA-WEI models. Several such models are derived. Finally, applications of the DEA-WEI models are presented.

129 citations


Cites background from "Output–input ratio analysis and DEA..."

  • ...In [34], some inherent relationship between DEA frontier DMUs and output–input ratios was discussed so that one sometimes can find DEA frontiers directly from ratios analysis....

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Journal ArticleDOI
TL;DR: In this paper, the authors used the data envelopment analysis (DEA) approach with the classical radial measure, A&P efficiency measure and efficiency achievement measure, respectively, combining multiple outputs and inputs to measure the magnitude of performance differences between leading global telecom carriers.

105 citations

Journal ArticleDOI
TL;DR: In this paper, a new mathematical model for efficiency analysis, called DEA-R, was proposed, which combines DEA methodology with an old idea-ratio analysis, treating all possible ratios "output" as outputs within the standard DEA model.
Abstract: We propose a new mathematical model for efficiency analysis, which combines DEA methodology with an old idea-Ratio Analysis. Our model, called DEA-R, treats all possible ratios "output/input" as outputs within the standard DEA model. Although DEA and DEA-R generate different summary measures for efficiency, the two measures are comparable. Our mathematical and empirical comparisons establish the validity of DEA-R model in its own right. The key advantage of DEA-R over DEA is that it allows effective integration of the model with experts' opinions via flexible restrictive conditions on individual "output/input" pairs. © 2007 Springer Science+Business Media, LLC.

68 citations


Cites background from "Output–input ratio analysis and DEA..."

  • ...(1996), Chen and Ali (2002) and Chen and McGinnis (2005)....

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  • ...5 This property was also proved in Chen and Ali (2002)....

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References
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Journal ArticleDOI
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

Journal ArticleDOI
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

Book
31 Jul 1995
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).
Abstract: Preface G. Kozmetsky. Part I: Concepts, Models & Computation. 1. Introduction. 2. Basic DEA Models. 3. Extensions to DEA Models. 4. Computational Aspects of DEA A. Iqbal Ali. 5. DEA Software Packages. Part II: Novel Applications. 6. Evaluating the Impacts of Operating Strategies on Efficiency in the U.S. Airline Industry R.D. Banker, H.H. Johnston. 7. Analyzing Technical and Allocative Efficiency of Hospitals P. Byrnes, V. Valdmanis. 8. A Multi Period Analysis of Market Segments and Brand Efficiency in the Competitive Carbonated Beverage Industry A. Charnes, W.w. Cooper, B. Golanyi, F.Y. Phillips, J.J. Rousseau. 9. Exploring why Some Physicians' Hospital Practices are More Efficient: Taking DEA Inside the Hospital J. Chilingerian. 10. On the Measurement and Monitoring of Relative Efficiency of Highway Maintenance Patrols W.D. Cook, A. Kazakov, Y. Roll. 11. Strategic Leaders in the U.S. Brewing Industry: a Longitudinal Analysis of Outliers D. Day, A.Y. Lewin, R. Salazar, Hongyu Li. 12. A Spatial Efficiency Framework for the Support of Locational Decision A. Desai, K. Haynes, J. Storbeck. 13. Productivity Developments in Swedish Hospitals: a Malmquist Output Index Approach R. Fare, S. Grosskopf, B. Lindgren, P. Roos. 14. Ownership Type, Property Rights and Relative Efficiency G. Ferrier. 15. A Comparative Analysis of Ferry Transport in Norway F.R. Forsund, E. Hernaes. 16. Incorporating Standards via Data Envelopment Analysis B. Golany, Y. Roll. 17.Stratified Models of Education Production Using Modified DEA and Regression Analysis C.A. Knox Lovell, L.C. Walters, L.L. Woods. 18. The Problems of New and Disappearing Commodities in the Construction of Price Indexes C.A. Knox Lovell, K.D. Zieschang. 19. Evaluating the Relative Efficiency of Baseball Players? M.J. Mazur. 20. Sensitivity Analysis of Efficiency Measures with Applications to Kansas Farming and Illinois Coal Mining R. Thompson, P.S. Dharmapala, R.M. Thrall. Part III: Epilogue: Process and Bibliography. 21. The DEA Process, Usages and Interpretations. 22. DEA Bibliography L.M. Seiford. References. Index.

2,773 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examine three essential components which comprise efficiency evaluation in data envelopment analysis and determine the implicit evaluation scheme associated with the model and provide a framework for classifying the various DEA models with respect to (i) the form of envelopment surface, (ii) the orientation, and (iii) the pricing mechanism implicit in the multiplier lower bounds.

111 citations

Journal ArticleDOI
TL;DR: Computational testing with real-world data sets with up to 533 decision making units indicates that employing constructs that facilitate efficiency of computation in solving a sequence of as many linear programs as there are decisionMaking units reduces computation time significantly.

99 citations