729 resultados para Data envelopment analysis-DEA


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Background: Specific research tools and designs can assist in identifying the efficiency of physical activity in elderly women. Objectives: To identify the effects of physical activity on the physical condition of older women. Method: A one-year-long physical activity program (123 sessions) was implemented for women aged 60 years or older. Four physical assessments were conducted, in which weight, height, BMI, blood pressure, heart rate, absences, grip strength, flexibility, VO2max, and static and dynamic balance were assessed. The statistical analyses included a repeated measures analysis, both inferential (analysis of variance - ANOVA) and effect size (Cohen's d coefficient), as well as identification of the participants' efficiency (Data Envelopment Analysis - DEA). Results: Despite the observation of differences that depended on the analysis used, the results were successful in the sense that they showed that physical activity adapted to older women can effectively change the decline in physical ability associated with aging, depending on the purpose of the study. The 60-65 yrs group was the most capable of converting physical activity into health benefits in both the short and long term. The >65 yrs group took less advantage of physical activity. Conclusions: Adherence to the program and actual time spent on each type of exercise are the factors that determine which population can benefit from physical activity programs. The DEA allows the assessment of the results related to time spent on physical activity in terms of health concerns. Article registered in Clinicaltrials.gov under number NCT01558401.

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This dissertation develops and tests a comparative effectiveness methodology utilizing a novel approach to the application of Data Envelopment Analysis (DEA) in health studies. The concept of performance tiers (PerT) is introduced as terminology to express a relative risk class for individuals within a peer group and the PerT calculation is implemented with operations research (DEA) and spatial algorithms. The analysis results in the discrimination of the individual data observations into a relative risk classification by the DEA-PerT methodology. The performance of two distance measures, kNN (k-nearest neighbor) and Mahalanobis, was subsequently tested to classify new entrants into the appropriate tier. The methods were applied to subject data for the 14 year old cohort in the Project HeartBeat! study.^ The concepts presented herein represent a paradigm shift in the potential for public health applications to identify and respond to individual health status. The resultant classification scheme provides descriptive, and potentially prescriptive, guidance to assess and implement treatments and strategies to improve the delivery and performance of health systems. ^

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This paper analyses the productivity growth of the SUMA tax offices located in Spain evolved between 2004 and 2006 by using Malmquist Index based on Data Envelopment Analysis (DEA) models. It goes a step forward by smoothed bootstrap procedure which improves the quality of the results by generalising the samples, so that the conclusions obtained from them can be applied in order to increase productivity levels. Additionally, the productivity effect is divided into two different components, efficiency and technological change, with the objective of helping to clarify the role played by either the managers or the level of technology in the final performance figures.

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This study evaluates the technical efficiency of the learning-teaching process in higher education using a three-stage procedure that offers advances in comparison to previous studies and improves the quality of the results. First, it utilizes a multiple stage Data Envelopment Analysis (DEA) with contextual variables. Second, the levels of super efficiency are calculated in order to prioritize the efficiency units. And finally, through sensitivity analysis, the contribution of each key performance indicator (KPI) is established with respect to the efficiency levels without omission of variables. The analytical data was collected from a survey completed by 633 tourism students during the 2011/12, 2012/13 and 2013/14 academic course years. The results suggest that level of satisfaction with the course, diversity of materials and satisfaction with the teacher were the most important factors affecting teaching performance. Furthermore, the effect of the contextual variables was found to be significant.

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We develop foreign bank technical, cost and profit efficiency models for particular application with data envelopment analysis (DEA). Key motivations for the paper are (a) the often-observed practice of choosing inputs and outputs where the selection process is poorly explained and linkages to theory are unclear, and (b) foreign bank productivity analysis, which has been neglected in DEA banking literature. The main aim is to demonstrate a process grounded in finance and banking theories for developing bank efficiency models, which can bring comparability and direction to empirical productivity studies. We expect this paper to foster empirical bank productivity studies.

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In this paper we propose a range of dynamic data envelopment analysis (DEA) models which allow information on costs of adjustment to be incorporated into the DEA framework. We first specify a basic dynamic DEA model predicated on a number or simplifying assumptions. We then outline a number of extensions to this model to accommodate asymmetric adjustment costs, non-static output quantities, non-static input prices, and non-static costs of adjustment, technological change, quasi-fixed inputs and investment budget constraints. The new dynamic DEA models provide valuable extra information relative to the standard static DEA models-they identify an optimal path of adjustment for the input quantities, and provide a measure of the potential cost savings that result from recognising the costs of adjusting input quantities towards the optimal point. The new models are illustrated using data relating to a chain of 35 retail department stores in Chile. The empirical results illustrate the wealth of information that can be derived from these models, and clearly show that static models overstate potential cost savings when adjustment costs are non-zero.

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Data Envelopment Analysis (DEA) is 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 proposes a neural network back-propagation Data Envelopment Analysis to address this problem for the very large scale datasets now emerging in practice. Neural network requirements 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 large datasets. Finally, the back-propagation DEA algorithm is applied to five large datasets and compared with the results obtained by conventional DEA.

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This paper introduces a compact form for the maximum value of the non-Archimedean in Data Envelopment Analysis (DEA) models applied for the technology selection, without the need to solve a linear programming (LP). Using this method the computational performance the common weight multi-criteria decision-making (MCDM) DEA model proposed by Karsak and Ahiska (International Journal of Production Research, 2005, 43(8), 1537-1554) is improved. This improvement is significant when computational issues and complexity analysis are a concern.

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In data envelopment analysis (DEA), operating units are compared on their outputs relative to their inputs. The identification of an appropriate input-output set is of decisive significance if assessment of the relative performance of the units is not to be biased. This paper reports on a novel approach used for identifying a suitable input-output set for assessing central administrative services at universities. A computer-supported group support system was used with an advisory board to enable the analysts to extract information pertaining to the boundaries of the unit of assessment and the corresponding input-output variables. The approach provides for a more comprehensive and less inhibited discussion of input-output variables to inform the DEA model. © 2005 Operational Research Society Ltd. All rights reserved.

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Data envelopment analysis (DEA) is a popular non-parametric technique for determining the efficiency of a homogeneous set of decision-making units (DMUs). In many practical cases, there is some doubt if the all the DMUs form a single group with a common efficiency distribution. The Mann-Whitney rank statistic has been used in DEA both to test if two groups of DMUs come from a common efficiency distribution and also to test if the two groups have a common frontier, each of which are likely to have important but different policy implications for the management of the groups. In this paper it is demonstrated that where the Mann-Whitney rank statistic is used for the second of these it is likely to overestimate programmatic inefficiency, particularly of the smaller group. A new non-parametric statistic is proposed for the case of comparing the efficient frontiers of two groups, which overcomes the problems we identify in the use of the Mann-Whitney rank statistic for this purpose. © 2005 Operational Research Society Ltd. All rights reserved.

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Fare, Grosskopf, Norris and Zhang developed a non-parametric productivity index, Malmquist index, using data envelopment analysis (DEA). The Malmquist index is a measure of productivity progress (regress) and it can be decomposed to different components such as 'efficiency catch-up' and 'technology change'. However, Malmquist index and its components are based on two period of time which can capture only a part of the impact of investment in long-lived assets. The effects of lags in the investment process on the capital stock have been ignored in the current model of Malmquist index. This paper extends the recent dynamic DEA model introduced by Emrouznejad and Thanassoulis and Emrouznejad for dynamic Malmquist index. This paper shows that the dynamic productivity results for Organisation for Economic Cooperation and Development countries should reflect reality better than those based on conventional model.

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The advent of Internet banking and phone banking is changing the role of bank branches from a predominantly transaction-based one to a sales-oriented role. This paper reports on an assessment of the branches of a Portuguese bank in terms of their performance in their new roles in three different areas: Their efficiency in fostering the use of new transaction channels, their efficiency in increasing sales and their customer base, and their efficiency in generating profits. Service quality is also a major issue in service organisations like bank branches, and therefore we analyse the way this dimension of performance has been accounted for in the literature and take it into account in our empirical application. We have used data envelopment analysis (DEA) for the different performance assessments, but we depart from traditional DEA models in some cases. Performance comparisons on each dimension allowed us to identify benchmark bank branches and also problematic bank branches. In addition, we found positive links between operational and profit efficiency and also between transactional and operational efficiency. Service quality is positively related with operational and profit efficiency. © 2006 Elsevier B.V. All rights reserved.

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This paper draws attention for the fact that traditional Data Envelopment Analysis (DEA) models do not provide the closest possible targets (or peers) to inefficient units, and presents a procedure to obtain such targets. It focuses on non-oriented efficiency measures (which assume that production units are able to control, and thus change, inputs and outputs simultaneously) both measured in relation to a Free Disposal Hull (FDH) technology and in relation to a convex technology. The approaches developed for finding close targets are applied to a sample of Portuguese bank branches.

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The present bibliography includes most of the references published in the field of Data Envelopment Analysis (DEA) up to the year 2007. Some publications in 2007 are also listed, but not included in the statistics. To the best of the authors’ knowledge, this listing appears to be the most complete source of references on DEA and its applications in measuring the efficiency and productivity of decision making units (DMUs). The authors hope that this new updated bibliography will assist researchers and other scholars as they develop new frontiers in DEA. The most utilized/relevant journals, a keyword analysis, and selected statistics are also presented.

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This thesis presents a number of methodological developments that were raised by a real life application to measuring the efficiency of bank branches. The advent of internet banking and phone banking is changing the role of bank branches from a predominantly transaction-based one to a sales-oriented role. This fact requires the development of new forms of assessing and comparing branches of a bank. In addition, performance assessment models must also take into account the fact that bank branches are service and for-profit organisations to which providing adequate service quality as well as being profitable are crucial objectives. This study analyses bank branches performance in their new roles in three different areas: their effectiveness in fostering the use of new transaction channels such as the internet and the telephone (transactional efficiency); their effectiveness in increasing sales and their customer base (operational efficiency); and their effectiveness in generating profits without compromising the quality of service (profit efficiency). The chosen methodology for the overall analysis is Data Envelopment Analysis (DEA). The application attempted here required some adaptations to existing DEA models and indeed some new models so that some specialities of our data could be handled. These concern the development of models that can account for negative data, the development of models to measure profit efficiency, and the development of models that yield production units with targets that are nearer to their observed levels than targets yielded by traditional DEA models. The application of the developed models to a sample of Portuguese bank branches allowed their classification according to the three performance dimensions (transactional, operational and profit efficiency). It also provided useful insights to bank managers regarding how bank branches compare between themselves in terms of their performance, and how, in general, the three performance dimensions are connected between themselves.