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Showing papers on "Data envelopment analysis published in 1994"


Journal ArticleDOI
TL;DR: A neglected aspect of Data Envelopment Analysis: cross-efficiency is examined, and an intuitive understanding of cross- efficiency is ground in the concept of peer-appraisal, as opposed to self-appRAisal implied by simple efficiency.
Abstract: In this paper we examine a neglected aspect of Data Envelopment Analysis: cross-efficiency. We develop the concept of cross-efficiency in a number of new directions. We ground an intuitive understanding of cross-efficiency in the concept of peer-appraisal, as opposed to self-appraisal implied by simple efficiency, and discuss the relative merits of each. We also present mathematical formulations of, and intuitive meanings for three possible implementations of aggressive and benevolent cross-efficiency. We have implemented two of these formulations in computer programs; their performance is compared empirically on a real data set. Finally, we suggest practical uses for cross-efficiency, illustrated with reference to the same data set.

1,127 citations


Journal ArticleDOI
TL;DR: In this paper, the authors proposed a hybrid of a stochastic frontier regression and a truncated regression to estimate the production frontier with non-neutral shifting of the average production function.
Abstract: This article proposed a hybrid of a stochastic frontier regression The proposed model and estimation differ from the conventional model of Aigner, Lovell, and Schmidt The model combines a stochastic frontier regression and a truncated regression to estimate the production frontier with non-neutral shifting of the average production function The truncated regression identifies the sources of efficiency The article presents empirical evidence of non-neutral effects of the firm's characteristics—the age of the firms, the export ratio, and the R&D expenditure—on the frontier production function and production efficiency in the Taiwan's electronics industry

645 citations


Journal ArticleDOI
TL;DR: A case study where academic departments at Ben-Gurion University were evaluated via the Data Envelopment Analysis using the CCR model and the model was compared to the pure economic approach—the cost per student ratio.

310 citations


Journal ArticleDOI
TL;DR: Three papers that apply frontier estimation techniques to hospitals and nursing homes, together with an exchange over the usefulness of those techniques in the health care context are published, representing the current state-of-the-art with respect to applications of frontier estimation in health care.

285 citations


Journal ArticleDOI
TL;DR: In this paper, the authors used data envelopment analysis to compute a cumulative Malmquist input-based productivity index for coal-burning plants in the U.S. electric generating industry in the 1980s and found that productivity decreased from 1985 to each of their first three target years but grew in the 1985-89 comparison.
Abstract: Data envelopment analysis is used to compute a cumulative Malmquist input-based productivity index for coal-burning plants in the U.S. electric generating industry in the 1980s. The authors account for inputs used to control sulfur emissions as well as emissions outputs, and decompose the index into changes in technical efficiency, changes in technology, and changes in scale efficiency. They find that productivity decreased from 1985 to each of their first three target years but grew in the 1985-89 comparison, and that 18.5 percent of their plants, and 27 percent of net generation, lie in the decreasing returns region of the production set. Copyright 1994 by MIT Press.

185 citations


Journal ArticleDOI
TL;DR: This paper analyzes the technical efficiency of Dutch nursing homes with respect to the use of labor inputs by means of Data Envelopment Analysis (DEA) and the determinants of the efficiency scores are investigated using censored regression analysis.

174 citations


Journal ArticleDOI
01 Dec 1994-Top
TL;DR: The purpose of this paper is to provide a selective overview of some of the most useful DEA models, and to inform practitioners in the fields of management science, economics and public administration who want to learn and use these models.
Abstract: An important and rapidly growing empirical application of operations research techniques involves the measurement and analysis of the efficiency with which goods are produced and services are provided. The production activities whose efficiency has been the subject of investigation have varied widely, from profit-oriented industrial manufacturing enterprises all the way to public and private service providers operating in a not-for-profit environment. A similarly wide variety of operations research techniques has been utilized in the measurement and analysis of productive efficiency, ranging from stochastic parametric regressionbased methods to nonstochastic nonparametric mathematical programming methods. Foremost among the latter is a family of linear programming models collectively referred to as Data Envelopment Analysis (DEA). The purpose of this paper is to provide a selective overview of some of the most useful DEA models. I analyze these models in terms of their ability to accurately reflect the structure of the underlying production technology, their ability to accurately measure the productive efficiency of the producers being analyzed, and their data requirements and their sensivity to shortcomings in the data that form the basis of the analysis. The selectivity of the overview reflects my talents and my interests. Thus the orientation of the overview is toward the user of existing DEA models, not toward the developer of new models. In particular, the review is intended to inform practitioners in the fields of management science, economics and public administration who want to learn and

164 citations


Book ChapterDOI
01 Jan 1994
TL;DR: The empirical results suggest that a two-stage approach that augments MDEA with regression analysis provides a fruitful way of determining effectiveness outcomes and relating them to features of organizational design and the operating environment.
Abstract: In their agenda for research into the determinants of organizational effectiveness, Lewin and Minton (1986, p. 531) called for studies illustrating the “feasibility of using DEA (perhaps in combination with other analytical methods) as a mathematic for relating effectiveness outcomes to features of organization design.” In this chapter, we report the initial results of just such a study. The purpose of the study is to investigate the performance of secondary education in the U.S. Performance is defined as the ability of secondary schools to convert human, physical, and financial resources into educational opportunities, and then to combine these opportunities with student input to produce both intermediate and long-term educational outcomes. At each stage, performance is measured using a modified form of data envelopment analysis (MDEA). The three sets of calculated MDEA scores are then regressed against groups of environmental variables that reflect features of the organizational design and characteristics of the student body of each secondary school in the sample. The modification to DEA and the second- stage regression analysis are structured to take into account the special distributional features of unmodified DEA scores. The empirical results suggest that a two-stage approach that augments MDEA with regression analysis provides a fruitful way of determining effectiveness outcomes and relating them to features of organizational design and the operating environment. Furthermore, regression analysis provides useful information for policymakers interested in how changes in organizational characteristics can improve school performance.

163 citations


Journal ArticleDOI
TL;DR: In this article, the relative efficiency of a UK clearing bank's branches using non-parametric programming methodology is investigated, and a measure of technical efficiency is dichotomized into its constituent components, scale efficiency and pure technical efficiency.
Abstract: This paper investigates the relative efficiency of a UK clearing bank's branches using the non-parametric programming methodology. In addition to calculating indices of technical (productive) efficiency for all branches in the sample, this measure of technical efficiency is dichotomized into its constituent components, scale efficiency and pure technical efficiency. Finally, the non-parametric technique is utilized to investigate the causes of observed inefficiency in the case of one illustrative branch example in detail.

159 citations


Journal ArticleDOI
TL;DR: Results of this analysis support the hypothesis of significant non-linearities, and the existence of both economies and diseconomies of scale in software development.
Abstract: Researchers and practitioners have found it useful for cost estimation and productivity evaluation purposes to think of software development as an economic production process, whereby inputs, most notably the effort of systems development professionals, are converted into outputs (systems deliverables), often measured as the size of the delivered system. One central issue in developing such models is how to describe the production relationship between the inputs and outputs. In particular, there has been much discussion about the existence of either increasing or decreasing returns to scale. The presence or absence of scale economies at a given size are important to commercial practice in that they influence productivity. A project manager can use this knowledge to scale future projects so as to maximize the productivity of software development effort. The question of whether the software development production process should be modelled with a non-linear model is the subject of some recent controversy. This paper examines the issue of non-linearities through the analysis of 11 datasets using, in addition to standard parametric tests, new statistical tests with the non-parametric Data Envelopment Analysis (DEA) methodology. Results of this analysis support the hypothesis of significant non-linearities, and the existence of both economies and diseconomies of scale in software development.

140 citations


Journal ArticleDOI
TL;DR: In this article, the authors consider a series of Data Envelopment Analysis DEA frontiers, and show when these may be incentive efficient in the sense that they contain all the information that are relevant for optimal incentive provision.
Abstract: In this paper, we examine how empirical production frontiers may contribute to the incentives of production units. We consider a series of Data Envelopment Analysis DEA frontiers, and we show when these may be incentive efficient in the sense that they contain all the information that are relevant for optimal incentive provision. The frontiers considered include the so-called constant, decreasing and varying return to scale models, the free disposability and the free replicability models, as well as the increasing and decreasing return to scale models based on a relaxed set of assumptions. Also, we illustrate how to design optimal incentive schemes based on such frontiers. Contents: 1. Introduction, 2. The Incentive Problem, 3. Production Frontiers and Productivity Measures, 4. Incentive Efficient Production Frontiers, 5. Extensions, 6. An Example, 7. Final Remarks, Mathematical Appendix, References.

Journal ArticleDOI
TL;DR: In this article, an application of data envelopment analysis (DEA) for measuring and evaluating the operating efficiency of power plants in the Israeli Electric Corporation (IEC) is presented.
Abstract: An application of data envelopment analysis (DEA) for measuring and evaluating the operating efficiency of power plants in the Israeli Electric Corporation (IEC) is presented. Emphasis is placed on the process of screening the list of potential input and output factors and determining the most relevant ones. Special attention is given to the qualitative factor concerning air pollution, which is treated as a categorical variable. The incorporation of 'standard data' is examined and the results are analyzed. >

Journal ArticleDOI
TL;DR: In this paper, data envelopment analysis (DEA) is used to guide secondary schools to improved performance through role-model identification and target setting in a way which recognises the multi-outcome nature of the education process and reflects the relative desirability of improving individual outcomes.
Abstract: The educational process is characterised by multiple outcomes such as the achievement of academic results of various standards and non-academic achievements. This paper shows how data envelopment analysis (DEA) can be used to guide secondary schools to improved performance through role-model identification and target setting in a way which recognises the multi-outcome nature of the education process and reflects the relative desirability of improving individual outcomes. The approach presented in the paper draws from a DEA-based assessment of the schools of a local education authority carried out by the authors. Data from that assessment are used to illustrate the approach presented in the paper. (Key words: Data envelopment analysis, education, target setting.)

Journal ArticleDOI
TL;DR: In this paper, data envelopment analysis (DEA) is used to measure the relative efficiency of the best 25 U.S. News and World Report-ranked universities using performance indicators.
Abstract: Data envelopment analysis (DEA) is used to measure the relative efficiency of the “best” 25 U.S. News and World Report-ranked universities. Our results indicate how DEA may be used to measure relative efficiency of these higher education institutions from commonly available “performance indicators.” It is apparent that the quality ranking of U.S. News bears an inverse relationship to a ranking implied by the narrow production efficiency criterion of DEA. Improvements in technical efficiency of a “demonstration” university are examined by readjusting the particular input indicators.

Journal ArticleDOI
TL;DR: In this paper, data envelopment analysis is employed to estimate the intertemporal productive efficiency of U.S. computer manufactures, using financial data brought from earnings statements and balance sheets.
Abstract: DEA (data envelopment analysis) is a technique for determining the efficiencyfrontier (the envelope) to the inputs and outputs of a collection of individual corporations or other productive units. DEA is here employed to estimate the intertemporal productive efficiency of U.S. computer manufactures, using financial data brought from earnings statements and balance sheets. The results indicate that a few corporations, including Apple Computer Inc., Compaq Computer Corp., and Seagate Technology were able to stay at the productivity efficiency frontier throughout the time period investigated. But not all successful corporations did; sometimes subefficiency (=disequilibrium) actually goes together with very rapid growth. A new Malmquist type productivity index is calculated for each corporation, measuring shifts of the estimated intertemporal efficiency frontier.

Journal ArticleDOI
TL;DR: In this paper, the authors considered the semiparametric stochastic frontier model with panel data that arises in the problem of measuring technical inefficiency in production processes and provided a predictor of the individual effects that can be directly translated to firm-specific technical inefficiencies.
Abstract: This article considers the semiparametric stochastic frontier model with panel data that arises in the problem of measuring technical inefficiency in production processes. We assume a parametric form for the frontier function, which is linear in production inputs. The density of the individual firm-specific effects is considered to be unknown. We construct an efficient estimator of the slope parameters in the frontier function. We also give an estimator of the level of the frontier function and investigate its asymptotic properties. Furthermore, we provide a predictor of the individual effects that can be directly translated to firm-specific technical inefficiencies. Finally, we illustrate our methods through a real data example.

Journal ArticleDOI
TL;DR: Banker and Thrall as mentioned in this paper introduced the idea that the sum of the intensity variables in the DEA (Activity Analysis) model can be used to identify returns to scale and showed that Banker's method may fail.

Journal ArticleDOI
TL;DR: A measurement model for assessing the validity and reliability of performance measures is developed and Data Envelopment Analysis based on the performance measures allows the creation of a performance frontier which inherently recognizes the tradeoffs.

Journal ArticleDOI
TL;DR: In this paper, the authors estimate profit inefficiency of farms in the North-west Frontier Province of Pakistan using stochastic frontier and the behavioural profit functions. But, the behavioural approach satisfies most of the assumptions of the dual profit function and the likelihood ratio test rejects the market efficiency hypothesis.
Abstract: The objectives of this study are to estimate profit inefficiency of farms in the North-west Frontier Province of Pakistan using stochastic frontier and the behavioural profit functions. The derived measure of inefficiency, based on a half-normal distribution of the stochastic error term, is related to socio-economic variables; and of these, the size of holding, fragmentation of land,subsistence needs the higher age of farmers contribute positively to inefficiency. The behavioural approach satisfies most of the assumptions of the dual profit function and the likelihood ratio test rejects the market efficiency hypothesis. It is also shown that use of manures, labour and fertilizers is below the optimum. Small farms seem to have higher productive efficiency than large farms and, therefore small farm ownership needs to be encouraged.

Journal ArticleDOI
TL;DR: This article extended the DEA methodology to nonhomogeneous units by integrating DEA with a regression model that adjusts the DEA output to account for variations in site characteristics and to ensure that the final funding allocations were fair.
Abstract: North Carolina uses data envelopment analysis (DEA) to produce a pupil transportation funding process that encourages operational efficiency and reduces expenditures. To do so, we extended the DEA methodology to nonhomogeneous units by integrating DEA with a regression model that adjusts the DEA output to account for variations in site characteristics and to ensure that the final funding allocations were fair. The new process has led to changes in bus routes and schedules, adjustments in school start and stop times, and reductions in the inventory of buses. Between 1990 and 1993, the state saved $25.2 million in capital costs and $27.9 million in operating costs, and it expects savings to increase.

Book ChapterDOI
01 Jan 1994
TL;DR: The author's intention in maintaining a bibliography of DEA-related articles is to provide a single source referencing the wide range of articles appearing in the literature and facilitate comprehensive growth in the field.
Abstract: Since the original DEA study by Charnes, Cooper, and Rhodes (1978), there has been rapid growth in the field. Due to the interdisciplinary nature of much of the research, there is a need for a single source referencing the wide range of articles appearing in the literature. The author’s intention in maintaining a bibliography of DEA-related articles is to provide such a single source and thus facilitate comprehensive growth in the field.

Book ChapterDOI
01 Jan 1994
TL;DR: This chapter introduces elements of the computational characteristics of DEA in the context of the basic DEA models that were presented in chapter 2.
Abstract: The increased application of data envelopment analysis (DEA) over the past decade has been accompanied by a growing awareness of computational subtleties of the mathematical models that compose the methodology. In this chapter, we introduce elements of the computational characteristics of DEA in the context of the basic DEA models that were presented in chapter 2.

Journal ArticleDOI
TL;DR: In this paper, a non-parametric model of corporate performance is presented, which obviates the need for specification of statistical distributions or functional form, instead it seeks to identify outstanding performance in a number of dimensions, and to measure the performance of less efficient firms in relation to their efficient peers.
Abstract: Many problems arise in applying conventional statistical methods to accounting ratios, often relating to assumptions about the statistical distribution of ratios. This paper presents a non-parametric model of corporate performance which obviates the need for specification of statistical distributions or functional form. Instead it seeks to identify outstanding performance in a number of dimensions, and to measure the performance of less efficient firms in relation to their efficient peers. The method is illustrated with data relating to 27 failed UK companies and their peers. The strengths and weaknesses of the model are discussed, and it is concluded that, although the model is not a panacea for the problems of interpreting corporate performance, it does offer a useful addition to the armoury of the financial statement analyst. In particular, it offers a technology which is intermediate between the crudity of simple ratio analysis and the complexity of regression analysis.

Book ChapterDOI
01 Jan 1994
TL;DR: In view of the possibility of erroneous or misleading data, some critics of DEA have questioned the validity and stability of measures of DEA efficiency as mentioned in this paper, which is a data-based approach.
Abstract: Data envelopment analysis (DEA), as its name indicates, is data based. In view of the possibility of erroneous or misleading data, some critics of DEA have questioned the validity and stability of measures of DEA efficiency.

Journal ArticleDOI
TL;DR: In this article, the authors employ the techniques of chance-constrained data envelopment analysis to conduct a comparison of the productive efficiency of a set of West European market economies and East European planned economies and find the market economies to have been much more efficient in their allocation of resources.

Journal ArticleDOI
TL;DR: In this article, a new use of least absolute value (LAV) estimation for obtaining parameter estimates of a stochastic frontier production function is presented, which is combined with data envelopment analysis (DEA) and the resulting DEA/LAV estimates are examined by several statistical tests.

Journal ArticleDOI
TL;DR: In this article, the performance of the regulated school system in Norway is investigated by analyzing the relationship between resource use and student achievement in 34 Norwegian high schools, and the output of the schools is described by the number of graduates and the school effect.

Posted Content
TL;DR: In this article, the authors tried to address potential econometric problems of previous efficiency studies and suggest a new technique for measuring efficiency, which is applied to data on U.S. commercial banks from 1984 through 1989.
Abstract: Questions of whether the evolution of the financial services industry results in more efficient intermediaries, better prices and service quality for consumers, and greater bank safety and soundness cannot be answered without addressing the cost and revenue efficiencies of the industry. Most studies of the efficiency of financial institutions have used an econometric approach to measure efficiency. This paper tries to address potential econometric problems of previous efficiency studies and suggests a new technique for measuring efficiency. This method is applied to data on U.S. commercial banks from 1984 through 1989. Previous studies used one of four different approaches for estimating X-efficiencies - the econometric frontier approach, the thick frontier approach, data envelopment analysis, and the distribution free approaches. In all four cases, the econometric problem of estimating X-efficiencies is defined simply as one of distinguishing between two components of a random error term added to a cost or profit function. The authors suggest that it is possible that the actual econometric problem of estimating X-inefficiencies is not as simple as the problem of distinguishing between two random components because of the following three reasons: ( i ) the true functional forms of the cost or profit functions of the firms are usually unknown; ( ii ) explanatory variables excluded from the cost or profit function are likely to be correlated with the explanatory variables included in the function; and (iii) inconsistencies may arise if arbitrary error terms are added to a cost or profit function and their corresponding share equations. The authors use a fixed-coefficients model that allows them to address the econometric problems mentioned above. This methodology also allows for the estimation of a separate frontier for each firm as opposed to previous studies that estimate one frontier which is common to all firms. The results of the paper show that the residual which the previous studies attributed to technical inefficiency potentially included the effects of excluded variables, of inaccuracies in the specified functional forms, and of inconsistent parameter estimates. They further show that once these effects are subtracted from the residual, the measured inefficiencies are substantially reduced. The results do support some of the previous studies' conclusions - in general measured technical inefficiencies dominate allocative inefficiencies and that on average large banks are more efficient from both the technical and allocative perspectives than small and medium sized banks.

Journal ArticleDOI
TL;DR: A quantitative method based on the concept of Pareto-optimal organization which is much easier to conduct is proposed, and is a simpler version of the data envelopment analysis (DEA) technique for measuring relative efficiency.