Using DEA to estimate potential savings at GP units at medical specialty level

The aim of this paper is to identify benchmark cost-efficient General Practitioner (GP) units at delivering health care in the Geriatric and General Medicine (GMG) specialty and estimate potential cost savings. The use of a single medical specialty makes it possible to reflect more accurately the medical condition of the List population of the Practice so as to contextualize its expenditure on care for patients. We use Data Envelopment Analysis (DEA) to estimate the potential for cost savings at GP units and to decompose these savings into those attributable to the reduction of resource use, to altering the mix of resources used and to those attributable to securing better resource 'prices'. The results reveal a considerable potential for savings of varying composition across GP units. © 2013 Elsevier Ltd.

Neural network DEA for measuring the efficiency of mutual funds

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.

Technical efficiency determinants within a dual banking system:a DEA-bootstrap approach

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.

A spatiotemporal Data Envelopment Analysis (S-T DEA) approach:the need to assess evolving units

One of the major challenges in measuring efficiency in terms of resources and outcomes is the assessment of the evolution of units over time. Although Data Envelopment Analysis (DEA) has been applied for time series datasets, DEA models, by construction, form the reference set for inefficient units (lambda values) based on their distance from the efficient frontier, that is, in a spatial manner. However, when dealing with temporal datasets, the proximity in time between units should also be taken into account, since it reflects the structural resemblance among time periods of a unit that evolves. In this paper, we propose a two-stage spatiotemporal DEA approach, which captures both the spatial and temporal dimension through a multi-objective programming model. In the first stage, DEA is solved iteratively extracting for each unit only previous DMUs as peers in its reference set. In the second stage, the lambda values derived from the first stage are fed to a Multiobjective Mixed Integer Linear Programming model, which filters peers in the reference set based on weights assigned to the spatial and temporal dimension. The approach is demonstrated on a real-world example drawn from software development.

Introduction to performance improvement management software (PIM-DEA)

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.

Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping:a case of Mozambican banks

Performance analysis has become a vital part of the management practices in the banking industry. There are numerous applications using DEA models to estimate efficiency in banking, and most of them assume that inputs and outputs are known with absolute precision. Here, we propose new Fuzzy-DEA α-level models to assess underlying uncertainty. Further, bootstrap truncated regressions with fixed factors are used to measure the impact of each model on the efficiency scores and to identify the most relevant contextual variables on efficiency. The proposed models have been demonstrated using an application in Mozambican banks to handle the underlying uncertainty. Findings reveal that fuzziness is predominant over randomness in interpreting the results. In addition, fuzziness can be used by decision-makers to identify missing variables to help in interpreting the results. Price of labor, price of capital, and market-share were found to be the significant factors in measuring bank efficiency. Managerial implications are addressed.

A linear relational DEA model to evaluate two-stage processes with shared inputs

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.

Carbon efficiency evaluation:an analytical framework using fuzzy DEA

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.

A new inverse DEA method for merging banks

This study suggests a novel application of Inverse Data Envelopment Analysis (InvDEA) in strategic decision making about mergers and acquisitions in banking. The conventional DEA assesses the efficiency of banks based on the information gathered about the quantities of inputs used to realize the observed level of outputs produced. The decision maker of a banking unit willing to merge/acquire another banking unit needs to decide about the inputs and/or outputs level if an efficiency target for the new banking unit is set. In this paper, a new InvDEA-based approach is developed to suggest the required level of the inputs and outputs for the merged bank to reach a predetermined efficiency target. This study illustrates the novelty of the proposed approach through the case of a bank considering merging with or acquiring one of its competitors to synergize and realize higher level of efficiency. A real data set of 42 banking units in Gulf Corporation Council countries is used to show the practicality of the proposed approach.

Identifying the scope for savings at inpatient episode level:an illustration applying DEA to chronic obstructive pulmonary disease

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.

Fenntarthatósági szempontok beépítése a beszállító értékelésébe a DEA/CI összetett indikátorok módszere alkalmazásával (Integrating sustainability criteria in supplier evaluation with application of the method of of DEA/CI complex indicators)

A környezeti hatások rendszerint túlmutatnak egy vállalat határain, éppen ezért az ellátási lánc kontextusban a környezeti szempontok érvényesítése során fontos szerep jut a beszerzési döntéseknek is. Számos olyan példát lehetne említeni, amikor egy adott szempont szerint egy alternatíva környezetileg előnyös, de az ellátási lánc egészét nézve már környezetterhelő. A környezeti hatások ellátási lánc szinten való mérése azonban komoly kihívásokat jelent. Ezzel jelentős kutatásokat és fejlesztéseket inspirált a téma. Az egyik olyan terület, amelyben komoly kutatási eredmények születtek, az a környezeti szempontok beszállítói értékelésbe való beépítése. A kutatások ezen irányához csatlakozva a szerzők tanulmányunkban azt keresik, hogyan lehet meghatározni az egyik legáltalánosabban használt szállítóértékelési módszerben, a súlyozott pontrendszerben egy adott szemponthoz azt a súlyt, amely mellett az adott szempont már döntésbefolyásoló tényezővé válik. Ehhez a DEA (Data Envelopment Analysis) összetett indikátorok (Composite Indicators, CI) módszerét alkalmazzák. A szempontok közös súlyának fontossága megállapításához a lineáris programozás elméletét használják. _____ Management decisions often have an environmental effect not just within the company, but outside as well, this is why supply chain context is highlighted in literature. Measuring environmental issues of supply decisions raise a lot of problems from methodological and practical point of view. This inspires a rapidly growing literature as a lot of studies were published focusing on how to incorporate environmental issues into supplier evaluation. This paper contributes to this stream of research as it develops a method to help weight selection. In the authors’ paper the method of Data Envelope Analysis (DEA) is used to study the extension of traditional supplier selection methods with environmental factors. The selection of the weight system can control the result of the selection process.

Avaliando as escolas pelas suas competências: aplicação do DEA não discricionário para o ensino fundamental do Rio Grande do Norte

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.

Medición de la eficiencia técnica relativa de los proyectos de cimentación profunda de geofundaciones S.A. durante el año 2012 para la ciudad de Bogotá aplicando el análisis envolvente de datos-DEA

Tesis (Maestria en Administración de Empresas ).--Universidad de La Salle. Facultad de Ciencas Administrativas y Contables. Maestria en Administración de Empresas, 2014

Papel do PCT na diferenciação pedagógica e curricular de alunos com DEA/Dislexia

O presente estudo partiu de preocupações da prática relacionadas com o papel do PCT no desenvolvimento pedagógico e curricular sobretudo de alunos com dislexia. No sentido de se responder à pergunta de partida: “de que forma a diferenciação pedagógica e curricular dos alunos com DEA/Dislexia, é contemplada no PCT?” elaborou-se um quadro teórico onde se começou por discutir o papel da escola recorrendo inclusivamente à sua perspectivação histórica. Esta permitiu perceber a escola actual nomeadamente nas tensões entre os processos de massificação escolar conducentes a uma hegemonia do currículo e os processos de flexibilização curricular. O nosso interesse principal situou-se nestes últimos pela sua importância para a diferenciação curricular e pedagógica na sala de aula necessária para os alunos com dislexia. A formação dos professores desempenha neste contexto uma grande relevância, pelo que lhe atribuímos elevada importância. Utilizando como instrumentos de recolha inquéritos por questionário articulados com a análise dos PCTs inquirimos uma amostra de vinte e oito professores de um agrupamento de escolas do distrito de Santarém sobre a sua percepção face à dislexia e à importância dada à utilização do PCT. Os dados recolhidos e tratados permitiram verificar que nem os PCT são encarados como um instrumento de diferenciação curricular e pedagógica, resultando em algumas contradições entre o que se diz fazer e o que se faz efectivamente, nem a DEA/Dislexia é encarada como um problema, que apesar de real não se vê contemplada, de forma explícita nos PCT. Desta forma, consideramos que o estudo realizado (embora limitado no tempo e espaço) permite desvendar algumas das suas representações mostrando uma forte relação entre a ausência de formação e o impacto que esta lacuna tem nas práticas docentes.

La metodología «Análisis Envolvente de Datos» (DEA): una aplicación a la producción de arroz en Uruguay

El objetivo de este trabajo es comprender cuáles son las prácticas que llevan a una chacra a estar en la frontera de producción de arroz e identificar las fuentes de ineficiencia productiva.La frontera se determinó utilizando la metodología «Análisis Envolvente de Datos» (DEA, por su sigla en inglés).Se determinaron cuatro tipos de eficiencia: técnica, de escala, de asignación y económica. En un segundo paso se estimó el efecto de las variables de manejo y ambientales sobre los resultados de eficiencia. La estimación se realizó mediante una regresión truncada debido a la naturaleza del proceso generador de datos. Los datos corresponden a 573 chacras de arroz de 26 productores diferentes y corresponden a las zafras entre 2004/05 y 2008/09. Son 10 las que chacras definen la frontera de producción considerando rendimientos constantes a escala (eficientes) y que el promedio de eficiencia técnica es de 0,6. Con rendimientos variables a escala el número de chacras eficientes aumenta a 25 y el promedio de eficiencia técnica aumenta a 0,74. Al considerar los precios de insumos y productos el número de chacras económicamente eficientes es tres y el promedio de eficiencia es 0,53. Los resultados de la regresión truncada sobre los distintos indicadores de eficiencia indican que los determinantes más importantes son la elección de variedades y el tipo de suelo. Tipo de siembra, tipo de laboreo y época de laboreo también tienen efectos significativos sobre algunos tipos de eficiencia.