922 resultados para Data Envelopment Analysis (DEA), scale efficiency, technical efficiency


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Resumen tomado de la publicación

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Diante das atuais tendências de busca da eficiência, muitas vezes através de grandes investimentos em novas tecnologias, em infra-estrutura, em recursos humanos, entre outros, objetiva a presente pesquisa apresentar uma forma de mensurar a eficiência relativa que os diversos níveis de recursos utilizados possam, ou não, trazer às Escrivanias de Paz do Estado de Santa Catarina. Através da técnica “Data Envelopment Analisys” - DEA (Análise Envoltória de Dados), busca-se mostrar as relações que os diversos níveis de recursos possam ou não trazer na performance de cada empresa de forma relativa umas as outras. A pesquisa de campo busca levantar os diversos inputs, como instalações físicas, quantidade de funcionários, tempo médio de serviço dos funcionários, quantidade de linhas telefônicas, equipamentos de fax, copiadoras, computadores e software e os diversos outputs, como escrituras, procurações, autenticações, reconhecimentos de firmas, casamentos, nascimentos e óbitos existentes em cada uma das 266 Escrivanias de Paz do estado. Acredita-se que os procedimentos utilizados revelam-se como um instrumento de apoio decisório para essas empresas, além de mostrar as diferenças de desempenho organizacional com a utilização de diversos níveis de recursos. Os resultados obtidos através das analises, demonstram os principais pontos que devem sofrer alterações nas escrivanias não eficientes com relação ao conjunto. Estes pontos norteiam rumos de ações aos dirigentes para melhoria da eficiência destas empresas.

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This paper discusses the use of comparative performance measurement by means of Data Envelopment Analysis in the context of the regulation of English and Welsh water companies. Specifically, the use of Data Envelopment Analysis to estimate potential cost savings in sewerage is discussed as it fed into the price review of water companies carried out by the regulator of water companies in 1994. The application is used as a vehicle for highlighting generic issues in terms of assessing the impact of factors on the ranking of units on performance, the insights gained from using alternative methods to assess comparative performance, and the issue of assessing comparative performance when few in number but highly complex entities are involved. The paper should prove of interest to those interested in regulation and, more generally, in the use of methods of comparative performance measurement.

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This paper uses a Data Envelopment Analysis based approach to decompose pupil under-attainment into that attributable to the school the pupil attends and that attributable to the pupil. The approach measures pupil attainment in terms of value added. Data on over 6700 A-level pupils from 122 English schools have been analysed. The results suggest that at current levels of school effectiveness a pupil's own application accounts for the major part of any under-attainment, though schools also have scope to improve their effectiveness.The approach also makes it possible to identify target attainment levels a pupil could be set and the extent to which the attainment of those targets necessitates an improvement in the effectiveness of the school the pupil attends and in the pupil's own efforts.

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Practitioners assess performance of entities in increasingly large and complicated datasets. If non-parametric models, such as Data Envelopment Analysis, were ever considered as simple push-button technologies, this is impossible when many variables are available or when data have to be compiled from several sources. This paper introduces by the 'COOPER-framework' a comprehensive model for carrying out non-parametric projects. The framework consists of six interrelated phases: Concepts and objectives, On structuring data, Operational models, Performance comparison model, Evaluation, and Result and deployment. Each of the phases describes some necessary steps a researcher should examine for a well defined and repeatable analysis. The COOPER-framework provides for the novice analyst guidance, structure and advice for a sound non-parametric analysis. The more experienced analyst benefits from a check list such that important issues are not forgotten. In addition, by the use of a standardized framework non-parametric assessments will be more reliable, more repeatable, more manageable, faster and less costly. © 2010 Elsevier B.V. All rights reserved.

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Pantaneiro horses were submitted to a performance test.

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The purpose of this study is to provide a comparative analysis of the efficiency of Islamic and conventional banks in Gulf Cooperation Council (GCC) countries. In this study, we explain inefficiencies obtained by introducing firm-specific as well as macroeconomic variables. Our findings indicate that during the eight years of study, conventional banks largely outperform Islamic banks with an average technical efficiency score of 81% compared to 95.57%. However, it is clear that since 2008, efficiency of conventional banks was in a downward trend while the efficiency of their Islamic counterparts was in an upward trend since 2009. This indicates that Islamic banks have succeeded to maintain a level of efficiency during the subprime crisis period. Finally, for the whole sample, the analysis demonstrates the strong link of macroeconomic indicators with efficiency for GCC banks. Surprisingly, we have not found any significant relationship in the case of Islamic banks.

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Copyright © 2013 Springer Netherlands.

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In for-profit organizations efficiency measurement with reference to the potential for profit augmentation is particularly important as is its decomposition into technical, and allocative components. Different profit efficiency approaches can be found in the literature to measure and decompose overall profit efficiency. In this paper, we highlight some problems within existing approaches and propose a new measure of profit efficiency based on a geometric mean of input/output adjustments needed for maximizing profits. Overall profit efficiency is calculated through this efficiency measure and is decomposed into its technical and allocative components. Technical efficiency is calculated based on a non-oriented geometric distance function (GDF) that is able to incorporate all the sources of inefficiency, while allocative efficiency is retrieved residually. We also define a measure of profitability efficiency which complements profit efficiency in that it makes it possible to retrieve the scale efficiency of a unit as a component of its profitability efficiency. In addition, the measure of profitability efficiency allows for a dual profitability interpretation of the GDF measure of technical efficiency. The concepts introduced in the paper are illustrated using a numerical example.

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Applying programming techniques to detailed data for 406 rice farms in 21 villages, for 1997, produces inefficiency measures, which differ substantially from the results of simple yield and unit cost measures. For the Boro (dry) season, mean technical efficiency was efficiency was 56.2 per cent and 69.4 per cent, allocative efficiency was 81.3 per cent, cost efficiency was 56.2 per cent and scale efficiency 94.9 per cent. The Aman (wet) season results are similar, but a few points lower. Allocative inefficiency is due to overuse of labour, suggesting population pressure, and of fertiliser, where recommended rates may warrant revision. Second-stage regressions show that large families are more inefficient, whereas farmers with better access to input markets, and those who do less off-farm work, tend to be more efficient. The information on the sources of inter-farm performance differentials could be used by the extension agents to help inefficient farmers. There is little excuse for such sub-optimal use of survey data, which are often collected at substantial costs.

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The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

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The purpose of this paper is to analyse the relationship between the corporate governance system and technical efficiency in Italian manufacturing. We use a non-parametric frontier technique (DEA) to derive technical efficiency measures for a sample of Italian firms taken from nine manufacturing industries. These measures are then related to the characteristics of the corporate governance system. Two of these characteristics turn out to have a positive impact on technical efficiency: the percentage of the company shares owned by the largest shareholder and the fact that a firm belongs to a pyramidal group. Interestingly, a trade-off emerges between these influences, in the sense that one is stronger in industries where the other is weaker. Copyright © 2007 John Wiley & Sons, Ltd.

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We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright (C) 2003 John Wiley Sons, Ltd.