136 resultados para Data-driven analysis


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Purpose - The purpose of this paper is to measure the technical and scale efficiency of health centres; to evaluate changes in productivity; and to highlight possible policy implications of the results for policy makers. Design/methodology/approach - Data envelopment analysis (DEA) is employed to assess the technical and scale efficiency, and productivity change over a four-year period among 17 public health centres. Findings - During the period of study, the results suggest that the public health centres in Seychelles have exhibited mean overall or technical efficiency of above 93 per cent. It was also found that the overall productivity increased by 2.4 per cent over 2001-2004. Research limitations/implications - Further research can be undertaken to gather data on the prices of the various inputs to facilitate an estimation of the allocative efficiency of clinics. If such an exercise were to be undertaken, researchers may also consider collecting data on quantities and prices of paramedical, administrative and support staff to ensure that the analysis is more comprehensive than the study reported in this paper. Institutionalization of efficiency monitoring would help to enhance further the already good health sector stewardship and governance. Originality/value - This paper provides new empirical evidence on a four-year trend in the efficiency and productivity of health centres in Seychelles. © Emerald Group Publishing Limited.

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Purpose – The data used in this study is for the period 1980-2000. Almost midway through this period (in 1992), the Kenyan government liberalized the sugar industry and the role of the market increased, while the government's role with respect to control of prices, imports and other aspects in the sector declined. This exposed the local sugar manufacturers to external competition from other sugar producers, especially from the COMESA region. This study aims to find whether there were any changes in efficiency of production between the two periods (pre and post-liberalization). Design/methodology/approach – The study utilized two methodologies to efficiency estimation: data envelopment analysis (DEA) and the stochastic frontier. DEA uses mathematical programming techniques and does not impose any functional form on the data. However, it attributes all deviation from the mean function to inefficiencies. The stochastic frontier utilizes econometric techniques. Findings – The test for structural differences in the two periods does not show any statistically significant differences between the two periods. However, both methodologies show a decline in efficiency levels from 1992, with the lowest period experienced in 1998. From then on, efficiency levels began to increase. Originality/value – To the best of the authors' knowledge, this is the first paper to use both methodologies in the sugar industry in Kenya. It is shown that in industries where the noise (error) term is minimal (such as manufacturing), the DEA and stochastic frontier give similar results.

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Over 60% of the recurrent budget of the Ministry of Health (MoH) in Angola is spent on the operations of the fixed health care facilities (health centres plus hospitals). However, to date, no study has been attempted to investigate how efficiently those resources are used to produce health services. Therefore the objectives of this study were to assess the technical efficiency of public municipal hospitals in Angola; assess changes in productivity over time with a view to analyzing changes in efficiency and technology; and demonstrate how the results can be used in the pursuit of the public health objective of promoting efficiency in the use of health resources. The analysis was based on a 3-year panel data from all the 28 public municipal hospitals in Angola. Data Envelopment Analysis (DEA), a non-parametric linear programming approach, was employed to assess the technical and scale efficiency and productivity change over time using Malmquist index.The results show that on average, productivity of municipal hospitals in Angola increased by 4.5% over the period 2000-2002; that growth was due to improvements in efficiency rather than innovation. © 2008 Springer Science+Business Media, LLC.

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This study uses Data Envelopment Analysis (DEA) to estimate the degree of technical, allocative and cost efficiency in individual public and private health centres in Zambia; and to identify the relative inefficiencies in the use of various inputs among individual health centers. About 83% of the 40 health centres were technically inefficient; and 88% of them were both allocatively and cost inefficient. The privately owned health centers were found to be more efficient than public facilities. © 2006 Springer Science+Business Media, Inc.

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In May 2006, the Ministers of Health of all the countries on the African continent, at a special session of the African Union, undertook to institutionalise efficiency monitoring within their respective national health information management systems. The specific objectives of this study were: (i) to assess the technical efficiency of National Health Systems (NHSs) of African countries for measuring male and female life expectancies, and (ii) to assess changes in health productivity over time with a view to analysing changes in efficiency and changes in technology. The analysis was based on a five-year panel data (1999-2003) from all the 53 countries of continental Africa. Data Envelopment Analysis (DEA) - a non-parametric linear programming approach - was employed to assess the technical efficiency. Malmquist Total Factor Productivity (MTFP) was used to analyse efficiency and productivity change over time among the 53 countries' national health systems. The data consisted of two outputs (male and female life expectancies) and two inputs (per capital total health expenditure and adult literacy). The DEA revealed that 49 (92.5%) countries' NHSs were run inefficiently in 1999 and 2000; 50 (94.3%), 48 (90.6%) and 47 (88.7%) operated inefficiently in 2001, 2002, and 2003 respectively. All the 53 countries' national health systems registered improvements in total factor productivity attributable mainly to technical progress. Fifty-two countries did not experience any change in scale efficiency, while thirty (56.6%) countries' national health systems had a Pure Efficiency Change (PEFFCH) index of less than one, signifying that those countries' NHSs pure efficiency contributed negatively to productivity change. All the 53 countries' national health systems registered improvements in total factor productivity, attributable mainly to technical progress. Over half of the countries' national health systems had a pure efficiency index of less than one, signifying that those countries' NHSs pure efficiency contributed negatively to productivity change. African countries may need to critically evaluate the utility of institutionalising Malmquist TFP type of analyses to monitor changes in health systems economic efficiency and productivity over time. African national health systems, per capita total health expenditure, technical efficiency, scale efficiency, Malmquist indices of productivity change, 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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This paper explores the use of the optimisation procedures in SAS/OR software with application to the measurement of efficiency and productivity of decision-making units (DMUs) using data envelopment analysis (DEA) techniques. DEA was originally introduced by Charnes et al. [J. Oper. Res. 2 (1978) 429] is a linear programming method for assessing the efficiency and productivity of DMUs. Over the last two decades, DEA has gained considerable attention as a managerial tool for measuring performance of organisations and it has widely been used for assessing the efficiency of public and private sectors such as banks, airlines, hospitals, universities and manufactures. As a result, new applications with more variables and more complicated models are being introduced. Further to successive development of DEA a non-parametric productivity measure, Malmquist index, has been introduced by Fare et al. [J. Prod. Anal. 3 (1992) 85]. Employing Malmquist index, productivity growth can be decomposed into technical change and efficiency change. On the other hand, the SAS is a powerful software and it is capable of running various optimisation problems such as linear programming with all types of constraints. To facilitate the use of DEA and Malmquist index by SAS users, a SAS/MALM code was implemented in the SAS programming language. The SAS macro developed in this paper selects the chosen variables from a SAS data file and constructs sets of linear-programming models based on the selected DEA. An example is given to illustrate how one could use the code to measure the efficiency and productivity of organisations.

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Due to its wide applicability and ease of use, the analytic hierarchy process (AHP) has been studied extensively for the last 20 years. Recently, it is observed that the focus has been confined to the applications of the integrated AHPs rather than the stand-alone AHP. The five tools that commonly combined with the AHP include mathematical programming, quality function deployment (QFD), meta-heuristics, SWOT analysis, and data envelopment analysis (DEA). This paper reviews the literature of the applications of the integrated AHPs. Related articles appearing in the international journals from 1997 to 2006 are gathered and analyzed so that the following three questions can be answered: (i) which type of the integrated AHPs was paid most attention to? (ii) which area the integrated AHPs were prevalently applied to? (iii) is there any inadequacy of the approaches? Based on the inadequacy, if any, some improvements and possible future work are recommended. This research not only provides evidence that the integrated AHPs are better than the stand-alone AHP, but also aids the researchers and decision makers in applying the integrated AHPs effectively.

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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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Traditional approaches to calculate total factor productivity change through Malmquist indexes rely on distance functions. In this paper we show that the use of distance functions as a means to calculate total factor productivity change may introduce some bias in the analysis, and therefore we propose a procedure that calculates total factor productivity change through observed values only. Our total factor productivity change is then decomposed into efficiency change, technological change, and a residual effect. This decomposition makes use of a non-oriented measure in order to avoid problems associated with the traditional use of radial oriented measures, especially when variable returns to scale technologies are to be compared.

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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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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 re-assesses three independently developed approaches that are aimed at solving the problem of zero-weights or non-zero slacks in Data Envelopment Analysis (DEA). The methods are weights restricted, non-radial and extended facet DEA models. Weights restricted DEA models are dual to envelopment DEA models with restrictions on the dual variables (DEA weights) aimed at avoiding zero values for those weights; non-radial DEA models are envelopment models which avoid non-zero slacks in the input-output constraints. Finally, extended facet DEA models recognize that only projections on facets of full dimension correspond to well defined rates of substitution/transformation between all inputs/outputs which in turn correspond to non-zero weights in the multiplier version of the DEA model. We demonstrate how these methods are equivalent, not only in their aim but also in the solutions they yield. In addition, we show that the aforementioned methods modify the production frontier by extending existing facets or creating unobserved facets. Further we propose a new approach that uses weight restrictions to extend existing facets. This approach has some advantages in computational terms, because extended facet models normally make use of mixed integer programming models, which are computationally demanding.