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Search Results: 1 - 10 of 52082 matches for " Data Envelopment Analysis "
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A Ranking Method of Extreme Efficient DMUs Using Super-Efficiency Model  [PDF]
Dariush Akbarian
Journal of Applied Mathematics and Physics (JAMP) , 2013, DOI: 10.4236/jamp.2013.11001
Abstract: In this paper, we present a method for ranking extreme efficient decision making units (DMUs) in data envelopment analysis (DEA) models based on measuring distance between them and new PPS (after omission extreme efficient DMUs) along the input-axis or output axis.
A Hierarchical Methodology for Performance Evaluation Based on Data Envelopment Analysis: The Case of Companies’ Competitiveness in an Economy  [PDF]
Mohamed Dia, Fouad Ben Abdelaziz
American Journal of Operations Research (AJOR) , 2011, DOI: 10.4236/ajor.2011.13015
Abstract: In this research, we present a hierarchical Data Envelopment Analysis (DEA) methodology for competitiveness analysis. This methodology takes into account the heterogeneity of the decision making units (DMUs) as well as the diversity of the comparison criteria. We propose to homogenize the DMUs by grouping them hierarchically, which permits a better identification and definition of the criteria in each specific grouping. The methodology proceeds first by the determination of the performances or relative efficiencies, which are in turn aggregated into competitiveness indices in each grouping by the superiority index of [1]; then, the overall competitiveness indices are determined additively along the hierarchical levels. We illustrate the methodology by a competitiveness analysis of several companies belonging to different sectors of activity in an economy, where are suggested ways of improvement for the non-competitive companies within their sectors and within the economy.
Evaluate the Investment Efficiency by Using Data Envelopment Analysis: The Case of China  [PDF]
Hualun Zhang, Wei Song, Xiaobao Peng, Xiaoyan Song
American Journal of Operations Research (AJOR) , 2012, DOI: 10.4236/ajor.2012.22020
Abstract: Although investment is regarded as a key force of China’s economic growth, little study has been done to measure China’s investment efficiency. The present paper applies the data envelopment analysis (DEA) to Chinese provincial panel data from the year 2003 to 2008 for measuring the investment efficiencies and identifying their trends of Chinese 30 provinces and autonomous regions. A cross-efficient DEA model with considering benevolent formulation is used for providing accurate efficiency scores and completely ranking. The empirical results suggest that the differences of investment efficiency in different regions are distinct but tending to diminish year by year, and the investment efficiencies in some provinces are significantly correlated to their investment rates to the national total investment.
Balanced Scorecard and Efficiency: Design and Empirical Validation of a Strategic Map in the University by Means of DEA  [PDF]
Teresa García Valderrama, Vanesa Rodríguez Cornejo, Daniel Revuelta Bordoy
American Journal of Operations Research (AJOR) , 2013, DOI: 10.4236/ajor.2013.31003

The principal objective of the research reported in this article is to validate a Balanced Scorecard (BSC) model and a Strategic Map for the University by studying the relationships of efficiency between its dimensions. Subsequently, the validation is completed by establishing hypotheses of efficiency relationships between the perspectives proposed, employing Data Envelopment Analysis (DEA). Empirical evidence has been obtained on the validity of the proposed BSC for a unit of academic management in the university. The first contribution of this work is the establishment of a framework of analysis of the hypothetical cause-effect relationships in the BSC in university institutions. The second contribution is to obtain the determining factors of the performance in this type of institution and, therefore, the Strategic Map. Specifically, these factors are: the participation of teaching staff in innovation activities; the number of doctorate-level staff; the academic subjects and credits in the Virtual Campus; and the scores in the surveys of student satisfaction. With respect to research, the determining factors of the performance are: the research sexennials; the funding obtained from contracts with companies; the number of research projects obtained; their financing; and the participation of teachers in these projects.

Technical Efficiency in the Container Terminals in Mexico, 1982-2010: Through Data Envelopment Analysis (DEA)  [PDF]
Odette V. Delfín-Ortega, César L. Navarro-Chávez
iBusiness (IB) , 2013, DOI: 10.4236/ib.2013.54019

The paper shows an analysis of the global technical efficiency of container terminals of the main ports of Mexico in the period 1982-2010, through Data Envelopment Analysis (DEA). This methodology allows us to measure each decision unit evaluated in relation to other homogeneous units. The aim of the study is to determine the importance of global technical efficiency, pure technical efficiency and scale efficiency in the ports of México. For this purpose, quay length and number of employees are used as input and as output of the number of containers. The results show that the Mexican ports in general have a low technical global efficiency and only the ports showed that technical global efficiency, technical pure efficiency and scale efficiency were Veracruz and Tuxpan in the year 1982, and Manzanillo and Lazaro Cárdenas in the year 2010. For that reason, it requires better operability which means greater mobility of TEUs.

Assessing the Relative Efficiency of Health Systems in Sub-Saharan Africa Using Data Envelopment Analysis  [PDF]
Samuel Ambapour
American Journal of Operations Research (AJOR) , 2015, DOI: 10.4236/ajor.2015.51003
Abstract: We assess the relative efficiency of health systems of 35 countries in sub-Saharan Africa using Data Envelopment Analysis. This method allows us to evaluate the ability of each country to transform its sanitary “inputs” into health “outputs”. Our results show that, on average, the health systems of these countries have an efficiency score between 72% and 84% of their maximum level. We also note that education and density of population are factors that affect the efficiency of the health system in these countries.
Determining the Technical Efficiency of Specialty Ophthalmology Hospital Using SFA and DEA: 2009-2011  [PDF]
Majid Heydari, Azadeh Ahmadzadeh Ghasab, Haleh Mousavi Isfahani, Mehdi Raadabadi, Mohsen Barouni
Health (Health) , 2014, DOI: 10.4236/health.2014.69102
Abstract: Introduction: During the last decade, the health sector of many countries in general has been faced significantly with the increase of health care costs and in particular with the growth in hospital costs, that a significant part of it is due to the inefficient use of resources. The present study has been calculated the technical efficiency of the Specialty Ophthalmology Hospital of Tehran University of Medical Sciences by the comprehensive data analysis methods and stochastic frontier analysis. Methods: In this article, the technical efficiency of the Specialty Ophthalmology Hospital of Tehran University of Medical Sciences has been calculated by the years of 2009 to 2011, by the comprehensive data analysis methods and stochastic frontier analysis. For this purpose, the form of input-oriented data envelopment analysis approach was used by assuming the variable Productivity to scale and stochastic frontier analysis method and from the five output, the occupied bed days, outpatient admissions, inpatient admissions, inpatient days and bed occupancy factor, and from the six output, it means active beds, number of doctors, nurses, and other personnel, budget and equipment costs were used for the study. For data analyzing, Deap software, edit 1/2 and Frontier edit 1/4, was used. Result: The results of a comprehensive data analysis method showed: 1) The capacity of improving technical efficiency in the studied sector is 34% (average technical efficiency is 0.663 parts); and 2) some of the sectors are met the excess inputs (factors of production). Technical efficiency using stochastic frontier analysis was equal to 0.937. In fact, the stochastic frontier analysis showed the inefficiency is less than the actual value. Conclusion: Reducing excess capacity factors (factors of production) should be conducted in the form of a comprehensive plan and by considering all regarded aspects, that this reduction plays a major role in the hospital and health sector costs reduction.
Using DEA and AHP for Ratio Analysis  [PDF]
Mohammad Sadegh Pakkar
American Journal of Operations Research (AJOR) , 2014, DOI: 10.4236/ajor.2014.44026

This research proposes an integrated approach to the Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP) methodologies for ratio analysis. According to this, we compute two sets of weights of ratios in the DEA framework. All ratios are treated as outputs without explicit inputs. The first set of weights represents the most attainable efficiency level for each Decision Making Unit (DMU) in comparison to the other DMUs. The second set of weights represents the relative priority of output-ratios using AHP. We assess the performance of each DMU in terms of the relative closeness to the priority weights of output-ratios. For this purpose, we develop a parametric goal programming model to measure the deviations between the two sets of weights. Increasing the value of a parameter in a defined range of efficiency loss, we explore how much the deviations can be improved to achieve the desired goals of the decision maker.This may result in various ranking positions for each DMU in comparison to the other DMUs. An illustrated example of eight listed companies in the steel industry of China is used to highlight the usefulness of the proposed approach.

An Expert System Approach to Medical Region Selection for a New Hospital Using Data Envelopment Analysis  [PDF]
Chin-Tsai Lin, Chuan Lee, Zhi-Jun Chen
iBusiness (IB) , 2010, DOI: 10.4236/ib.2010.22016
Abstract: An appropriate medical region must be selected before establishing a new hospital. Once established, a hospital may bring many medical doctors and facilities to the area. Not only can the distribution of medical resources in that area be influenced, but also competition among different hospitals can be enhanced. The government needs to consider the issue of medical resource distribution; therefore, medical region selection has important policy implications. This study uses data envelopment analysis (DEA) to establish the effective indicators, and also uses an expert system on the equality of medical resource distribution to identify medical areas lacking medical resources and where there is relatively less competition. As a result, this study can provide the necessary information to facilitate the choice of region for a new hospital. This method not only avoids assigning a hospital to a medical region where there are surplus resources, but it can also reduce the risk of excessive competition.
Efficiency in the Further Education Sector in England  [PDF]
Jill Johnes, Steve Bradley, Allan Little
Open Journal of Statistics (OJS) , 2012, DOI: 10.4236/ojs.2012.21015
Abstract: Further education in England is a diverse sector which typically provides education for the 16 - 19 age group. This study investigates efficiency levels by subject of study within further education (FE) colleges. Mean overall technical efficiency is found to vary from 75% to 86% in the worst- and best-performing subject areas, respectively. Statistical analysis of efficiency reveals that, while student and teacher composition and regional characteristics affect efficiency in each subject, the strength of these effects can vary by subject. This has the clear policy implication that strategies to improve efficiency in English FE must be devised and operated at subject rather than provider level.
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