Showing papers on "Data envelopment analysis published in 1993"
TL;DR: In this paper, a modified version of DEA based upon comparison of efficient DMUs relative to a reference technology spanned by all other units is developed, which provides a framework for ranking efficient units and facilitates comparison with rankings based on parametric methods.
Abstract: Data Envelopment Analysis DEA evaluates the relative efficiency of decision-making units DMUs but does not allow for a ranking of the efficient units themselves. A modified version of DEA based upon comparison of efficient DMUs relative to a reference technology spanned by all other units is developed. The procedure provides a framework for ranking efficient units and facilitates comparison with rankings based on parametric methods.
3,320 citations
TL;DR: In this article, the authors provided a formal statistical basis for the efficiency evaluation techniques of data envelopment analysis (DEA) and showed that DEA estimators of the best practice monotone increasing and concave production function are also maximum likelihood estimators if the deviation of actual output from the efficient output is regarded as a stochastic variable with a monotonically decreasing probability density function.
Abstract: This paper provides a formal statistical basis for the efficiency evaluation techniques of data envelopment analysis (DEA). DEA estimators of the best practice monotone increasing and concave production function are shown to be also maximum likelihood estimators if the deviation of actual output from the efficient output is regarded as a stochastic variable with a monotone decreasing probability density function. While the best practice frontier estimator is biased below the theoretical frontier for a finite sample size, the bias approaches zero for large samples. The DEA estimators exhibit the desirable asymptotic property of consistency, and the asymptotic distribution of the DEA estimators of inefficiency deviations is identical to the true distribution of these deviations. This result is then employed to suggest possible statistical tests of hypotheses based on asymptotic distributions.
908 citations
TL;DR: In this article, the methodology of free disposal hull (FDH) measure of productive efficiency is defined and put in perspectivevis-a-vis other nonparametric techniques, in terms of the postulates on which they respectively rest.
Abstract: The methodology of free disposal hull (FDH) measure of productive efficiency is defined and put in perspectivevis-a-vis other nonparametric techniques, in terms of the postulates on which they respectively rest. Computational issues are also considered, in relation to the linear programming techniques used in DEA. The first application bears on a comparison between a private and a public bank, in terms of the relative efficiency of their branches. Important characteristics of the data are revealed by FDH that are not by DEA, due to a better data fit. Next, efficiency estimates of judicial activities are used to evaluate what part of the existing backlog could be reduced by efficiency increases. Finally, with monthly data of an urban transit firm over 12 years, the FDH methodology is extended to a sequential treatment of time series, that supplements efficiency estimation with a measure of technical progress.
696 citations
TL;DR: The DEA efficiency ratings can be useful tool for port managers and for researchers, providing a deeper insight into port performance, and does not require the development of ‘standards’ against which efficiency is measured, although such standards can be incorporated in the DEA analysis.
Abstract: The large variety of factors that influence port performance complicates the determination of port efficiency. This paper presents a new approach to the measurement of efficiency. Data envelopment analysis (DEA), as a it is called, has particular applicability in the service sector. Applying mathematical programming techniques. DEA enables relative efficiency ratings ti be derived within a set of analysed units. Thus it does not require the developmentof ‘standards’ against which efficiency is measured, although such standards can be incorporated in the DEA analysis. The efficiency of units is compared with an ‘efficiency envelope’ that contains the most efficient units in the group. The DEA approach will be demonstrated by a hypothetical numerical example where the performance of 20 ports are compared. The DEA efficiency ratings can be useful tool for port managers and for researchers, providing a deeper insight into port performance. Weaknesses can be detected, leadungs the way to potential improvements.
420 citations
TL;DR: In this paper, the relative competitiveness of the banking industries in three Nordic countries is provided, by applying Data Envelopment Analysis of productivity on the national and the pooled data sets, which produces a detailed account of how well banks from different countries and different sizes may be prepared to meet the more intense competition of a common European banking market.
Abstract: Evidence of the relative competitiveness of the banking industries in three Nordic countries is provided, by applying Data Envelopment Analysis of productivity on the national and the pooled data sets. The analysis produces a detailed account of how well banks from different countries and different sizes may be prepared to meet the more intense competition of a common European banking market.
418 citations
TL;DR: The pioneering 1981 study of Program Follow Through is re-examine, with an empirical illustration, of the chance-constrained frontier envelops a given set of observations ‘most of the time’.
Abstract: Data envelopment analysis (DEA) is extended to the case of stochastic inputs and outputs through the use of chance-constrained programming. The chance-constrained frontier envelops a given set of observations ‘most of the time’. As an empirical illustration, we re-examine the pioneering 1981 study of Program Follow Through by Charnes, Cooper and Rhodes.
367 citations
01 Apr 1993
TL;DR: In this paper, the research output of economics departments in U.K. universities is assessed using data envelopment analysis and the results obtained are sensitive to the inclusion or absence of external funding as an input into the research process.
Abstract: The research output of economics departments in U.K. universities is assessed using data envelopment analysis. Results are compared with those obtained in the recent Universities Funding Council exercise. The results obtained are sensitive to the inclusion or otherwise of external funding as an input into the research process. A new method for assessing the relative performance of a number of data envelopment analyses is proposed. Copyright 1993 by Royal Economic Society.
306 citations
01 Jan 1993
TL;DR: Information is central to all applied studies in economics and other sciences and provides the basis for testing an economic model or theory and is intimately connected with decision making under conditions of risk and uncertainty.
Abstract: Information is central to all applied studies in economics and other sciences. It has many facets. As empirical data it provides the basis for testing an economic model or theory. It is also intimately connected with decision making under conditions of risk and uncertainty. Hence the choice of optimal policy under an uncertain environment depends on the type of information structures e.g., is it partial or total, incomplete or complete and imprecise or precise?
299 citations
TL;DR: In this paper, a conceptual framework for the treatment of factor weights in DEA is proposed, where general guidelines for setting bounds on factor weights are proposed and alternative methods to limit the range within which these factors are allowed to vary.
Abstract: Provisions for controlling factor weights constitute a significant extension of the data envelopment analysis (DEA) methodology, as an effective tool for measuring efficiency. This paper suggests a conceptual framework for the treatment of factor weights in DEA. First, the paper proposes general guidelines for setting bounds on factor weights. Then, it develops and presents alternative methods to limit the range within which these factor weights are allowed to vary. All of these methods involve additional information which is entered into the analysis in the form of constraints, bounds or different objective functions. Finally, the implications of the various approaches is discussed.
246 citations
TL;DR: It is found that, in general, data envelopment analysis outperforms regression analysis on accuracy of estimates but regression analysis offers greater stability of accuracy.
Abstract: This paper compares regression analysis and data envelopment analysis as two alternative methods for assessing the comparative performance of homogeneous organizational units such as bank branches or schools The comparison is restricted to units using a single resource or securing a single output It focuses on the estimates of relative efficiency, marginal input-output values and target input-output levels that the two methods offer A set of hypothetical hospitals is used to illustrate the performance of the two methods It is found that, in general, data envelopment analysis outperforms regression analysis on accuracy of estimates but regression analysis offers greater stability of accuracy
222 citations
TL;DR: The results of an experiment with simulated data that compares the estimation accuracy of two simple and very different production frontier methods: corrected ordinary least squares and data envelopment analysis are reported in this article.
TL;DR: In this article, the authors used parametric and nonparametric approaches to construct a frontier to be used as a yardstick of productive efficiency for both life and non-life insurance companies.
Abstract: The purpose of this paper is to provide for both life and non-life insurance an assessment of the relative productive performance of French companies. We use parametric and nonparametric approaches to construct a frontier to be used as a yardstick of productive efficiency. Our data basis covers 84 life and 243 non-life companies for the period 1984–1989. The main findings show a high correlation between parametric and nonparametric results and a wide dispersion in the rates of inefficiency across companies. This dispersion can be reduced when controlling for variations in scale, ownership, distribution, reinsurance, and claims ratios.
TL;DR: This paper describes an approach derived from the integration of data envelopment analysis and a multi-attribute value function that overcomes some of the limitations of the original DEA approach and increases users' understanding of DEA.
Abstract: Both Data Envelopment Analysis (DEA) and Multiple Criteria Analysis (MCA) can be used to assess the efficiency with which units perform similar tasks. This paper describes an approach derived from the integration of data envelopment analysis and a multi-attribute value function. This approach is implemented as a visual interactive decision support system, the use of which is illustrated by a practical application. The authors feel that this approach overcomes some of the limitations of the original DEA approach and, in particular, increases users' understanding of DEA. The approach is particularly well suited to the analysis of the efficiency of a small number of units.
TL;DR: The study has been applied to a set of branches of one of the largest commercial banks in Saudi Arabia in an attempt to evaluate the relative efficiency of these branches in order to improve the quality of services and utilize the available resources more efficiently.
Abstract: Details a data envelopment analysis (DEA) study of bank branches, where the bank branches are considered as the decision‐making units (DMUs). The Charnes, Cooper and Rhodes (CCR) ratio is used to evaluate the relative efficiency of each branch. The relative efficiency is computed utilizing specific input and output factors. The study has been applied to a set of branches of one of the largest commercial banks in Saudi Arabia in an attempt to evaluate the relative efficiency of these branches in order to improve the quality of services and utilize the available resources more efficiently.
TL;DR: A procedure is presented for incorporating an ordinal factor into the DEA structure, with the resulting formulation being a particular form of cone ratio model, which is then applied to the technology installation efficiency problem.
Abstract: In many problems involving efficiency analysis using DEA, certain factors may be measurable only on an ordinal scale. Specifically, it may be possible only to rank order the DMUs according to a factor, rather than being able to assign a specific numerical value of that factor to each DMU. To illustrate this, we examine a problem involving the evaluation of new technology installations. The presence of qualitative factors in such an environment motivates the need to investigate how such factors can be incorporated into existing efficiency measurement models. In particular, a procedure is presented for incorporating an ordinal factor into the DEA structure, with the resulting formulation being a particular form of cone ratio model. The model is then applied to the technology installation efficiency problem.
TL;DR: The model is extended to allow for the simultaneous presence of ND factors in both the input and the output sets and a generalization is offered which, for the first time, enables a quantitative evaluation of partially controlled factors.
Abstract: Data Envelopment Analysis (DEA) assumes, in most cases, that all inputs and outputs are controlled by the Decision Making Unit (DMU). Inputs and/or outputs that do not conform to this assumption are denoted in DEA asnon-discretionary (ND) factors. Banker and Morey [1986] formulated several variants of DEA models which incorporated ND with ordinary factors. This article extends the Banker and Morey approach for treating nondiscretionary factors in two ways. First, the model is extended to allow for thesimultaneous presence of ND factors in both the input and the output sets. Second, a generalization is offered which, for the first time, enables a quantitative evaluation ofpartially controlled factors. A numerical example is given to illustrate the different models.
TL;DR: In this article, the authors present three families of models for achieving this and describe the managerial situations in which they are useful, including the management of an existing Decision Making Unit (DMU) and die second attempts to identify the desired “location” for a new DMU.
Abstract: Following the characterization via Data Envelopment Analysis (DEA) of managerial units as efficient or inefficient, management will wish to increase profitability and/or control costs while becoming (or remaining) technically efficient in the DEA sense. This paper presents three families of models for achieving this and describes the managerial situations in which they are useful. The first addresses the management of an existing Decision Making Unit (DMU) and die second attempts to identify the desired “location” for a new DMU. The third addresses the aggregate of all DMUs, reallocating scarce resources among them for maximum overall organizational profitability and technical efficiency.
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.
TL;DR: In this paper, the state of society, which is measured by multiple social indicators, using data envelopment analysis (DEA), is discussed and compared with the standard DEA efficiency analysis, and the results using eight social indicators identify 26 DEA desirable prefectures out of the 47.
Abstract: This paper presents an approach for discussing the state of society, which is measured by multiple social indicators, using data envelopment analysis (DEA). Replacing inputs and outputs in DEA with negative and positive social indicators respectively, we analyze the desirability of living in the 47 prefectures of Japan. This is also a proposal for the potential use of DEA in multi-dimensional evaluation analysis other than the standard DEA efficiency analysis. The results using eight social indicators identify 26 DEA desirable prefectures out of the 47 and present other useful knowledge and information. It is concluded that DEA, which can avoid uniform evaluation by an a priori weighting system, provides availability as a comprehensive evaluation tool different from traditional ones.
TL;DR: In this paper, an approach entitled data envelopment analysis (DEA), which is widely used in management science, is introduced to measure the efficiency of forest management.
TL;DR: In this paper, data envelopment analysis was applied to performance and salary data for 433 professional baseball players and showed promise for generating objective estimates of pay equity, using a set of data envelopes.
Abstract: Data envelopment analysis shows promise for generating objective estimates of pay equity. Applied to performance and salary data for 433 professional baseball players, data envelopment analysis ide...
TL;DR: In this article, data envelopment analysis is used to estimate technical efficiency in for-profit independent and for-for-profit chain nursing homes and the empirical findings suggest that significant multiuser multiboxes are needed to achieve significant technical efficiency.
Abstract: Data envelopment analysis is used to estimate technical efficiency in for-profit independent and for-profit chain nursing homes. The empirical findings suggestceteris paribus, that significant mult...
TL;DR: It is concluded that simple cost-based ratios appear to be the most suitable for situations where pricing structures for resources and services are uniform and known, such as for company internal benchmarking.
TL;DR: In this article, a new linear programming formulation for handling categorical outputs in DEA is presented, which eliminates the difficulties of interpretation and computation that accompanied earlier mixed integer models and eliminates the need to use a linear programming language.
Abstract: A new linear programming formulation for handling categorical outputs in DEA is presented which eliminates the difficulties of interpretation and computation that accompanied earlier mixed integer models.
TL;DR: In this paper, the Stochastic Allocative Data Envelopment Analysis (SADEA) model is used to measure relative efficiency for a group of similar operating units with known input prices.
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TL;DR: Evidence is provided in favor of the proposition, that single-output techniques, like stochastic production function estimation, yield upwardly biased most efficient scales.
Abstract: Robustness of DEA scale efficiency scores is investigared in the context of non-radial efficency measures. Most efficient scales are identified with DEA's refernce firms instead of traditional clustering techniques.The systematic difference between single- and multi-output technologies as concerns most efficient scales is then examined by comparing applied DEA results. These provide evidence in favor of my proposition, that single-output techniques, like stochastic production function estimation, yield upwardly biased most efficient scales.
TL;DR: This study illustrates the hey concepts, identifies the decisions required to use the technique for medical care decision making, and presents an application to a system of nine hospitals that offer obstetric services.
Abstract: Data Envelopment Analysis (DEA) identifies price and technical inefficiencies among decision-making units. With controls for differences in case-mix and standardized outcomes, DEA's "best practice" frontier can be interpreted as a "cost-effectiveness" frontier. This study illustrates the key concepts, identifies the decisions required to use the technique for medical care decision making, and presents an application to a system of nine hospitals that offer obstetric services.
01 Jan 1993
TL;DR: Data envelopment analysis (DEA) and free disposal hull (FDH) analysis are alternative nonparametric techniques for constructing production and related frontiers, and for measuring the performance of production units relative to those frontiers as discussed by the authors.
Abstract: Data envelopment analysis (DEA) and free disposal hull (FDH) analysis are alternative nonparametric techniques for constructing production and related frontiers, and for measuring the performance of production units relative to those frontiers. We compare DEA and FDH on several criteria, including their implications for the structure of production technology, the way they measure producer performance relative to the technology, the way they treat input and output slacks, and on computational considerations.
01 Jan 1993
TL;DR: In this article, the authors deal with the measurement of efficiency and productivity growth in micro units of the Norwegian road sector using nonparametric Data Envelopment Analysis (DEA), Malmquist productivity index and a comparison of DEA methodology to a deterministic parametric frontier.
Abstract: This dissertation deals with the measurement of efficiency and productivity growth in micro units of the Norwegian road sector. The study comprises four studies within the context of nonparametric Data Envelopment Analysis (DEA), Malmquist productivity index and a comparison of DEA methodology to a deterministic parametric frontier. In the first study, the productive effciency of the Norwegian Motor Vehicle Inspectorate branches is examined. The second study focuses on the performance of trucks involved in road construction and maintenance, and operated by the regional agencies of the Norwegian Public Roads Administration. In the third study, the productivity growth within the Vehicle Inspectorate of Norway for the period 1989-91 is investigated using a decomposed Malmquist productivity index based on the Data Envelopment Analysis (DEA) framework. The fourth study examines the productive efficiency of rock blasting in Norwegian road constructions.(A)