943 resultados para Data envelopment analysis (DEA).
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Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF's efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of decision making units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-ropagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of a large set of MFs. Copyright © 2014 Inderscience Enterprises Ltd.
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Data envelopment analysis (DEA) is the most widely used methods for measuring the efficiency and productivity of decision-making units (DMUs). The need for huge computer resources in terms of memory and CPU time in DEA is inevitable for a large-scale data set, especially with negative measures. In recent years, wide ranges of studies have been conducted in the area of artificial neural network and DEA combined methods. In this study, a supervised feed-forward neural network is proposed to evaluate the efficiency and productivity of large-scale data sets with negative values in contrast to the corresponding DEA method. Results indicate that the proposed network has some computational advantages over the corresponding DEA models; therefore, it can be considered as a useful tool for measuring the efficiency of DMUs with (large-scale) negative data.
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This chapter provides information on the use of Performance Improvement Management Software (PIMDEA). This advanced DEA software enables users to make the best possible analysis of the data, using the latest theoretical developments in Data Envelopment Analysis (DEA). PIM-DEA software gives full capacity to assess efficiency and productivity, set targets, identify benchmarks, and much more, allowing users to truly manage the performance of organizational units. PIM-DEA is easy to use and powerful, and it has an extensive range of the most up-to-date DEA models and which can handle large sets of data.
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Two-stage data envelopment analysis (DEA) efficiency models identify the efficient frontier of a two-stage production process. In some two-stage processes, the inputs to the first stage are shared by the second stage, known as shared inputs. This paper proposes a new relational linear DEA model for dealing with measuring the efficiency score of two-stage processes with shared inputs under constant returns-to-scale assumption. Two case studies of banking industry and university operations are taken as two examples to illustrate the potential applications of the proposed approach.
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Data Envelopment Analysis (DEA) is a powerful analytical technique for measuring the relative efficiency of alternatives based on their inputs and outputs. The alternatives can be in the form of countries who attempt to enhance their productivity and environmental efficiencies concurrently. However, when desirable outputs such as productivity increases, undesirable outputs increase as well (e.g. carbon emissions), thus making the performance evaluation questionable. In addition, traditional environmental efficiency has been typically measured by crisp input and output (desirable and undesirable). However, the input and output data, such as CO2 emissions, in real-world evaluation problems are often imprecise or ambiguous. This paper proposes a DEA-based framework where the input and output data are characterized by symmetrical and asymmetrical fuzzy numbers. The proposed method allows the environmental evaluation to be assessed at different levels of certainty. The validity of the proposed model has been tested and its usefulness is illustrated using two numerical examples. An application of energy efficiency among 23 European Union (EU) member countries is further presented to show the applicability and efficacy of the proposed approach under asymmetric fuzzy numbers.
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Chronic obstructive pulmonary disease (COPD) is characterized by a largely irreversible obstruction of the airways, and is one of the leading causes of chronic morbidity and mortality worldwide. This paper illustrates the use of Data Envelopment Analysis (DEA) to assess the potential for cost savings at COPD inpatient episode level. The analysis uses the length of stay of each episode as a surrogate for expenditure on that episode while allowing for the medical condition of the patient and the quality of care received. We find substantial possible reductions in length of stay which would translate to cost savings. The paper also explores differences both between hospitals and between care teams within hospitals so that cost efficient protocols of treatment can be identified and disseminated.
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Formal education, understood by the gradual process that occurs at school, aims at learning and systematic knowledge is of great interest to society as it benefits its individuals and leads to many positive effects, such as increased productivity and welfare (Johnes, Johnes, 2007). Understanding what influences the educational outcome is as important as the result itself, because lets you manage these variables in order to obtain a better student performance. This work uses the data envelopment analysis (DEA) to compare the efficiency of Rio Grande do Norte schools. In this nonparametric method, an efficiency frontier was construct from the best schools that use the inputs set to generate educational products. Therefore, the data used were obtain by Test Brazil and year 2011 School Census to state and municipal schools of Rio Grande do Norte. Some of the variables considered as inputs and outputs have been obtain directly these bases - the other two were prepared, using the Item Response Theory (IRT) - they are the socioeconomic and school infrastructure indices. As a first step, we compared several DEA models, with changes of input variables. Then was chose the non-discretionary model for which was deep the analysis of results. The results showed that only seven schools were efficient in the 5th and 9th grades simultaneously; there were no significant differences between the efficiency of municipal and state schools; and there were no differences between large and small schools. Analyzing the municipalities, Mossoró excelled in both years with the highest proportion of efficient schools. Finally, the study suggests that using the projections provided by the DEA method, the most inefficient schools would be able to achieve the goal IDEB in 2011, in other words, it is possible to improve the education of significant state taking the efficient schools as a basis for too much.
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Mestrado em Controlo de Gestão e dos Negócios
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This paper demonstrates a connection between data envelopment analysis (DEA) and a non-interactive elicitation method to estimate the weights of objectives for decision-makers in a multiple attribute approach. This connection gives rise to a modified DEA model that allows us to estimate not only efficiency measures but also preference weights by radially projecting each unit onto a linear combination of the elements of the payoff matrix (which is obtained by standard multicriteria methods). For users of multiple attribute decision analysis the basic contribution of this paper is a new interpretation in terms of efficiency of the non-interactive methodology employed to estimate weights in a multicriteria approach. We also propose a modified procedure to calculate an efficient payoff matrix and a procedure to estimate weights through a radial projection rather than a distance minimization. For DEA users, we provide a modified DEA procedure to calculate preference weights and efficiency measures that does not depend on any observations in the dataset. This methodology has been applied to an agricultural case study in Spain.
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This paper presents the results of a research that aimed at identifying optimal performance standards of Brazilian public and philanthropic hospitals. In order to carry out the analysis, a model based on Data Envelopment Analysis (DEA) was developed. We collected financial data from hospitals’ financial statements available on the internet, as well as operational data from the Information Technology Department of the Brazilian Public Health Care System – SUS (DATASUS). Data from 18 hospitals from 2007 to 2011 were analyzed. Our DEA model used both operational and financial indicators (variables). In order to develop this model, two indicators were considered inputs: Values (in Brazilian Reais) of Fixed Assets and Planned Capacity. On the other hand, the following indicators were considered outputs: Net Margin, Return on Assets and Institutional Mortality Rate. As regards the proposed model, there were five hospitals with optimal performance and four hospitals were considered inefficient, upon the analysis of the variables, considering the analyzed period. Analysis of the weights indicated the most relevant variables for determining efficiency and scale variable values, which is an important tool to aid the decision-making by hospital managers. Finally, the scale variables determined the returns on production, indicating that 14 hospitals work with scale diseconomies. This may indicate inefficiency in the resource management of the Brazilian public health-care system, by analyzing this set of proposed variables.
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In multi-unit organisations such as a bank and its branches or a national body delivering publicly funded health or education services through local operating units, the need arises to incentivize the units to operate efficiently. In such instances, it is generally accepted that units found to be inefficient can be encouraged to make efficiency savings. However, units which are found to be efficient need to be incentivized in a different manner. It has been suggested that efficient units could be incentivized by some reward compatible with the level to which their attainment exceeds that of the best of the rest, normally referred to as “super-efficiency”. A recent approach to this issue (Varmaz et. al. 2013) has used Data Envelopment Analysis (DEA) models to measure the super-efficiency of the whole system of operating units with and without the involvement of each unit in turn in order to provide incentives. We identify shortcomings in this approach and use it as a starting point to develop a new DEA-based system for incentivizing operating units to operate efficiently for the benefit of the aggregate system of units. Data from a small German retail bank is used to illustrate our method.
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In this study we use region-level panel data on rice production in Vietnam to investigate total factor productivity (TFP) growth in the period since reunification in 1975. Two significant reforms were introduced during this period, one in 1981 allowing farmers to keep part of their produce, and another in 1987 providing improved land tenure. We measure TFP growth using two modified forms of the standard Malmquist data envelopment analysis (DEA) method, which we have named the Three-year-window (TYW) and the Full Cumulative (FC) methods. We have developed these methods to deal with degrees of freedom limitations. Our empirical results indicate strong average TFP growth of between 3.3 and 3.5 per cent per annum, with the fastest growth observed in the period following the first reform. Our results support the assertion that incentive related issues have played a large role in the decline and subsequent resurgence of Vietnamese agriculture.
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The reasons for the spectacular collapse of so many centrally-planned economies are a source of ongoing debate. In this paper, we use detailed farm-level data to measure total factor productivity (TFP) changes in Mongolian grain and potato farming during the 14-year period immediately preceding the 1990 economic reforms. We measure TFP growth using stochastic frontier analysis (SFA) and data envelopment analysis (DEA) methods. Our results indicate quite poor overall performance, with an average annual TFP change of - 1.7% in grain and 0.8% in potatoes, over the 14-year period. However, the pattern of TFP growth changed substantially during this period, with TFP growth exceeding 7% per year in the latter half of this period. This suggests that the new policies of improved education, greater management autonomy, and improved incentives, which were introduced in final two planning periods in the 1980s, were beginning to have a significant influence upon the performance of Mongolian crop farming. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.
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O objetivo deste artigo ?? apresentar um modelo alternativo de an??lise da efici??ncia dos programas de p??s-gradua????o acad??micos em Administra????o, Contabilidade e Turismo, vinculados ??s institui????es de ensino superior p??blicas e privadas. O estudo tem como base te??rica a efici??ncia e a otimiza????o de recursos, tomando como refer??ncia a maximiza????o do retorno, sujeito ??s limita????es de recursos. Como modelo anal??tico foi utilizada a An??lise Envolt??ria de Dados (DEA), enquanto t??cnica n??o param??trica de an??lise da efici??ncia relativa. Os resultados apontaram que os programas de p??s-gradua????o foram mais eficientes em 2006, seguido por 2004 e 2005, respectivamente. Notou- se ainda que, em m??dia, os programas vinculados ??s institui????es privadas de ensino foram mais eficientes que os da rede p??blica no tri??nio 2004/2006. Os gestores desses programas podem utilizar a an??lise da efici??ncia relativa como estrat??gia de benchmarking, adotando as melhores pr??ticas observadas nos programas eficientes, visando ?? maximiza????o da efici??ncia em sua gest??o.
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Este trabalho tem por objetivo identificar a eficiência técnica e as mudanças quanto à produtividade dos Institutos Federais de Educação, Ciência e Tecnologia (IF) no período de 2012 e 2013, perfazendo uma amostra formada por 19 unidades. Paralelamente a isso, procedeu-se a uma análise sobre a expansão da Rede Federal e os gastos correntes por aluno envolvido no processo de interiorização do ensino profissional e tecnológico. Como vertente teórica, discutiu-se a teoria do capital humano (SCHULTZ, 1960, 1961, 1962; BECKER, 1960; MINCER, 1958) junto às formas de investimentos em educação no Brasil e a sua política de prestação de contas. Para operacionalizar a pesquisa, verificou-se a eficiência técnica por meio da metodologia Análise Envoltória de Dados (DEA) utilizando os indicadores elaborados pela Secretaria de Educação Profissional e Tecnológica (SETEC) instituídos pelo Tribunal de Contas da União (TCU) e apresentados anualmente no Relatório de Prestação de Contas Anual. O resultado referente à eficiência demonstra que apenas 31% dos institutos federais analisados atingiram o escore de eficiência em 2012 e também em 2013. Porém, quando analisada a produtividade através do tempo com o Índice de Malmquist, é possível notar que 63% dos institutos federais estão se deslocando para a fronteira de eficiência demonstrando aumento do produto educação dentro das unidades. Adicionalmente, com o teste de diferença de médias (teste t), ocorreram evidências de que os institutos federais considerados eficientes apresentaram melhores resultados médios de concluintes e menores gastos correntes por aluno matriculado indicando que a obtenção do resultado pode não estar condicionada a maiores dispêndios financeiros.