Showing papers on "Data envelopment analysis published in 1990"
TL;DR: In this paper, the authors discuss the mathematical programming approach to frontier estimation known as Data Envelopment Analysis (DEA) and examine the effect of model orientation on the efficient frontier.
1,873 citations
TL;DR: Polyhedral Cone-Ratio Data Envelopment Analysis Models generalizing the CCR Ratio Model are developed for situations with a finite number of DMUs and employing polyhedral cones of virtual multipliers as discussed by the authors.
722 citations
TL;DR: In this paper, the AR concept is defined for efficiency analysis of the linear production possibility set and applied here to 83 farms, using only the special case of AR consisting of separate linear homogeneous restrictions on the input and output multipliers.
706 citations
TL;DR: A method, based on the use of proportions, for restricting weight flexibility in data envelopment analysis when the decision-making units being evaluated have multiple inputs and outputs is presented.
Abstract: In this paper we present a method, based on the use of proportions, for restricting weight flexibility in data envelopment analysis. This method is applicable when the decision-making units being evaluated have multiple inputs and outputs.
511 citations
TL;DR: In this paper, the authors discuss the methodology of an empirical study that was employed to measure the operating efficiencies of a set of 20 bank branches of a major Turkish Commercial Bank offering relatively homogeneous products in a multi-market business environment.
392 citations
TL;DR: In this paper, conditions under which DEA models are translation invariant are established under which affine displacement does not alter the efficient frontier for models incorporating the convexity constraint, which affords a ready solution to the problems of scaling and the presence of zero values which arise in Data Envelopment Analysis.
379 citations
TL;DR: In this article, a quantitative model for comparing university departments concerned with the same discipline is presented, based upon ideas drawn from data envelopment analysis, for chemistry and physics departments in the United Kingdom.
Abstract: In this paper we present a quantitative model for comparing university departments concerned with the same discipline. This model is based upon ideas drawn from data envelopment analysis. Computational results are given for chemistry and physics departments in the United Kingdom.
320 citations
TL;DR: In this paper, the authors present a systematic application of data envelopment analysis (DEA) for identifying inefficient decision-making units in an organization, which is an accepted approach to identify inefficient decision making units.
Abstract: Data envelopment analysis (DEA) has become an accepted approach for identifying inefficient decision-making units in an organization. This paper presents a systematic application of DEA car...
314 citations
TL;DR: In this article, the authors present a new approach to measure the input productivity gains from information technology (it) in complex managerial environments, illustrated in the context of a study of a pilot deployment at Hardee's Inc. of a new cash register point-of-sale and order-coordination technology called "Positran".
Abstract: :This paper presents a new approach to measuring the input productivity gains from information technology (it) in complex managerial environments. The approach is illustrated in the context of a study of a pilot deployment at Hardee’s Inc. of a new cash register point-of-sale and order-coordination technology called “Positran.” The method employs data envelopment analysis (dea) and nonparametric production frontier hypothesis testing to determine whether the performance of restaurants that have deployed Positran is better, on average, than for those that have not. The design of the study is of special interest, because it approximates a controlled experiment Our results show that Positran helped to reduce input materials costs, since restaurants that deployed the technology were less likely to be inefficient It is further possible to characterize the class of restaurants for which the relationship holds. Operational efficiency measures such as the ones we have developed provide managers with the o...
194 citations
TL;DR: In this paper, an alternative DEA approach which does not invoke the assumption of a convex production possibility set is developed, which is implemented in two stages, one concerned with the spanning of isoquants and the other with an evaluation of the position of an observed input-output combination compared to the iso-quants.
Abstract: Data Envelopment Analysis is a procedure for evaluation of the relative efficiency of units in a production system. DEA involves construction of composite units as convex combinations of other units' inputs and outputs under various conditions related to returns to scale. The assumption of convexity is inconsistent with increasing returns to scale and not implied by constant or non-increasing returns to scale. An alternative DEA approach which does not invoke the assumption of a convex production possibility set is developed in this paper. It is implemented in two stages. Stage one is concerned with the spanning of isoquants and stage two with an evaluation of the position of an observed input-output combination compared to the isoquants. Both stages involve linear programming techniques solely.
177 citations
TL;DR: A pilot application of Data Envelopment Analysis (DEA) for the measurement of the efficiency of highway maintenance patrols is demonstrated and results are compared to those obtained from a conventional DEA model.
Abstract: A pilot application of Data Envelopment Analysis (DEA) for the measurement of the efficiency of highway maintenance patrols is demonstrated. Selection of pertinent factors is discussed and the potential benefits of the analysis listed. A bounded DEA model is constructed and results are compared to those obtained from a conventional DEA model. The effects of secondary factors on the relative efficiencies of patrols are examined by analyses of sub-groups of Decision Making Units (DMUs), differing in the intensities of the respective factors.
01 Jan 1990
TL;DR: In this paper, the authors used data envelopment analysis (DEA) to develop a single measure for the efficiency and a single metric for the effectiveness of a transit agency relative to other agencies within the same peer group.
Abstract: Transit managers, like managers of other public agencies, need to assess the performance of their system compared to peer agencies. This assessment must measure not only how efficient the agency is in producing transit service, but also how effective it is in having that service consumed. This paper uses data envelopment analysis (DEA) to develop a single measure for the efficiency and a single measure for the effectiveness of a transit agency relative to other agencies within the same peer group. By using a single measure for each of these criteria, this paper provides a more robust indicator of transit peformance than the widely used multiple ratio analysis performed in the Irvine Performance Evaluation Method (IPEM). The DEA model is applied to two transit agency peer groups--one serving large metropolitan areas and the other serving relatively small cities and large towns. These examples illustrate the importance of distinguishing between measures of efficiency and effectiveness as well as the sensitivity of the DEA model to the choice of input variables.
TL;DR: In this article, the authors extend the traditional ratio analysis to permit the incorporation of any number of dimensions of performance, using data envelopment analysis, which produces measures of corporate efficiency, together with a wealth of supporting information.
Abstract: Ratio analysis has been a tool of analysts for as long as financial statements have been prepared. Yet its limitation to considering only one numerator and one denominator severely limits its usefulness. This paper extends the traditional ratio analysis to permit the incorporation of any number of dimensions of performance, using data envelopment analysis. The method produces measures of corporate efficiency, together with a wealth of supporting information. The strengths and weaknesses of the method applied to financial statements are appraised.
TL;DR: In this paper, the sensitivity analysis of the additive model in data envelopment analysis is studied, and sufficient conditions for simultaneous change of all outputs and all inputs of an efficient decision making unit which preserves efficiency are established.
TL;DR: The notion of size efficiency is introduced to measure this potential for further input reductions, and the existence of a largest radially size-efficient output scale is established as a ray property of the production frontier.
TL;DR: In this paper, Lovell and Sickles adopt a pragmatic perspective and, while neither damning DEA nor offering it as a panacea for productivity analysis, seek to underscore some of its strengths as well as its weaknesses.
TL;DR: Generalized method of moments (GMM) estimation procedures are presented that enable various degrees of distributional flexibility that are typically difficult to attain in likelihood-based approaches to estimation of frontier models.
TL;DR: The utility of DEA is analyzed by comparing this technique with other methods used to measure efficiency, by discussing the application of DEA in the health care industry and by assessing the validity of results from DEA studies.
Abstract: The rising cost of health care has created great interest in developing methods to increase the efficiency of health care organizations. Despite this interest most analyses of prospective payment and other programs designed to control expenditures have examined costs and not efficiency. This article examines a new technique—data envelopment analysis (DEA)—that facilitates the conduct of efficiency studies. The utility of DEA is analyzed by comparing this technique with other methods used to measure efficiency, by discussing the application of DEA in the health care industry and by assessing the validity of results from DEA studies. The article concludes with an assessment of the strengths and weaknesses of DEA and suggestions for refining this technique.
TL;DR: In this article, a comparison between subjective judgements as reflected in an Analytic Hierarchy Process (AHP) of site selection, a comparison is made to an objective Data Envelopment Analysis (DEA) selection procedure.
TL;DR: An empirical application to educational production frontier data shows the usefulness of the canonical correlation test and how they can be statistically tested as a two-stage procedure to provide the bridge between the parametric and the nonparametric approaches to the estimation of production frontiers.
TL;DR: In this article, the authors discuss issues of accurate and robust computation for DEA focusing on three data envelopment analysis models: CCR, BCC, and ADDITIVE, and discuss the characteristics of the linear programs arising in DEA.
TL;DR: In this article, a data envelopment analysis (DEA) model for evaluating the efficiency of incremental siting decisions is formulated, which provides an intuitively attractive approach to measuring accessibility on the basis of multiple spatial criteria, and articulates a ratio-scale based understanding of the "noninferiority" of locational decisions.
TL;DR: In this article, the method of data envelopment analysis is used to show that participation in DEEP seems to increase the efficiency of some classes and decrease efficiency of the other classes.
Abstract: The method of data envelopment analysis is used to show that participation in DEEP seems to increase the efficiency of some classes and decrease the efficiency of the other classes.
TL;DR: A special algorithm is presented for the additive model in data envelopment analysis (DEA) that can efficiently deal with a large data set and outperformed available DEA codes in simulation studies.
Abstract: A special algorithm is presented for the additive model in data envelopment analysis (DEA). The special algorithm first classifies a data set into several subsets. Then the subset is solved by a different algorithmic framework. In simulation studies, the algorithm outperformed available DEA codes. The proposed algorithm can efficiently deal with a large data set.
TL;DR: This paper applies Data Envelopment Analysis (DEA) to the assessment of the performance of Florida general hospitals.
Abstract: Unlike conventional methods for evaluating the performance of a not-for-profit entity, a recently developed mathematical programming technique called Data Envelopment Analysis (DEA) is able to handle multiple inputs and outputs simultaneously without assigning arbitrary weights and does not require the use of homogeneous measurement units nor a prespecified functional relationship between inputs and outputs. This technique can generate a summary scalar efficiency ratio for each decision-making unit and identify the individual amount of inefficiency for each input and/or output. This paper applies DEA to the assessment of the performance of Florida general hospitals.
TL;DR: Data Envelopment Analysis (DEA) as discussed by the authors provides a brief survey of recent progress in DEA research and uses in the areas of education, health care, regional planning, and information systems.
TL;DR: Data envelopment Analysis is an eminently parallelizable process that needs not be solved in any particular order, and each LP can fit within a single “transputer.”
Dissertation•
01 Jan 1990
TL;DR: Data Envelopment Analysis (DEA) as discussed by the authors has been proposed as a methodology for combining project input and output factors into a single efficiency score which can be used to rank projects.
Abstract: Existing appraisal and evaluation methodologies provide for a
separate assessment of technical, financial, economic, institutional,
social and environmental aspects of projects without a unifying theory
to combine these aspects into a single measure of project performance.
Data Envelopment Analysis is proposed as a methodology for combining
project input and output factors into a single efficiency score which
could be used to rank projects. The efficacy of the methodology has
been demonstrated in an application to data from the water supply and
sanitation sector in Ghana.
This study involved the selection of ten projects in Ghana (six in
water supply and four in sanitation). Each project is a representative
of large urban or small urban or large rural or small rural systems in
operation in Ghana. Various technologies employed in the projects
include:
(a) For water supply:
Conventional Water Treatment Plant
Boreholes with Motorised Pumps
Package Water Treatment Plant
Drilled Wells with Handpumps (2 projects)
Hand Dug Well
(b) For sanitation:
Conventional Sewerage
Communal Ventilated Improved Pit Latrines for an Urban
Community
Communal Ventilated Improved Pit Latrines for Rural
Communities
Traditional Pit Latrine
Data on technical, financial, economic, institutional, social and
environmental factors were collected in a 30-month fieldwork in Ghana.
The fieldwork involved extensive travelling visiting urban and remote
rural communities operating various systems in the sector. The data collected were analysed to provide the basic information for Data
Envelopment Analysis (DEA). DEA requires input and output data for each
project to be used in formulating linear programming models which are
subsequently solved using a personal computer to provide an efficiency
score for each project. Four different formulations were investigated
and the results used to identify which projects could be classified as
efficient given the Ghanaian context in which they are operated.
Suggestions for the improvement of inefficient projects are made using
the efficient projects as models.
In conclusion DEA is recommended as a useful tool in appraisal and
evaluation of water supply and sanitation projects to be adopted in
developing countries, developing banks and other aid donor agencies.
Other specific recommendations are made for the water supply and
sanitation sector in Ghana.