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Data envelopment analysis (DEA) has proven to be very useful in evaluating relative efficiencies of decision-making units (DMUs) with multiple outputs and multiple inputs. The conventional form of data envelopment analysis evaluates performances of decision-making units only from the optimistic point of view. In other words, it chooses a set of the most favorable weights for each decision-making unit. There is another approach that measures the efficiency of a decision-making unit from the pessimistic point of view. This approach chooses a set of the most unfavorable weights for evaluation of each decision-making unit. In this paper, we propose to integrate both efficiencies in the form of an interval in order to measure the overall performance of a decision-making unit. The proposed Data Envelopment Analysis Models for evaluation of efficiencies are called bounded data envelopment analysis models. The proposed approach will be compared using a numerical example. Another example about assessment of burden-sharing among members of the North Atlantic Treaty Organization (NATO) will be presented to illustrate the advantages, simplicity, and utility of this approach in real-life situations.  

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There are several approaches for increasing the competitive power of an organization. However, in some cases, some of the approaches are contradictory. Improving efficiency and productivity is one of the best approaches to solve these conflicts. In this research, we have measured the efficiency of five active iron mines during 2008 - 2011, using Data Envelopment Analysis (DEA) method and the efficient and inefficient units were determined. Due to the limited number of studied mines compared with the total amount of inputs and outputs, the discrimination could happen. Thus, we have used Anderson-Peterson (AP) approaches as a complementary method for DEA classic models, in order to determine productive units' final ranking. Based on the results obtained, Mishduvan mine has the highest rank and the highest amount of efficiency during 2009 - 2011.

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Performance evaluation has always been considered as one of the critical issues in every and each organization. In order to identify, adjust and apply the changes in their short-term and long-term goals, every organization needs to evaluate its performance continuously. Considering the key role of banks as one of the most important financial and economic parts of any society, it is important to evaluate the performance of these financial institution. In this study, 100 third level branches of Keshavarzi Bank were evaluated with 36 sub-indicators (7 inputs and 29 outputs) and these 36 sub-indicators were clustered in 3 inputs and 7 outputs. In this research, CCR-O model is used as the main model and to reduce the number of sub-indicators and obtain main-indicators three scenarios were performed (simple average, weighted average by using weights from AHP and Principle Component Analysis (PCA)) and outputs of these three scenarios were used as CCR-O inputs. Finally, increasing of discrimination power in all three scenarios was examined using coefficient of variation and it was understood that discrimination power in PCA-DEA scenario increased more than the other two.

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Despite organizations become technological and are changed into a pile of hardware nowadays, the role of human as a vital and strategic factor for survival of organization is noticeable. Human resources are the most worth resource in modern organization. Because they form organizational decisions, solve the organizational problems and materialize productivity. As human resources are important and have a noticeable role in the organization, human resources allocation is important too. This research has been performed in 23Shiraz emergency centers. For practical use of models, important factors for optimal human resources allocation in Shiraz emergency centers were determined by interview and checklist. Then human resources allocation was done in 23 Shiraz emergency centers by using CDEA model. Number of missions, ambulances and requests were predicted for efficiency calculation after optimal allocation by regression method. Efficiency comparison after and before allocation showed efficiency average has increased in centers.

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Efficiency and productivity are conception that input and output proportions one economic system determine. Data envelopment analysis (DEA) is suitable instrument for calculation efficiency one establishment, but one of the difficulties this model is decision maker can not interment terms of risk and uncertainty in result, in one hand in searches in agricultural sector decision maker hardly with terms of risk and uncertainty confront. Interval data envelopment analysis method (IDEA) a useful instrument in efficiency of evaluation so much establishment take into terms of risk, uncertainty and inexact data. In this search with use of IDEA model provinces of country efficiency in basis animal husbandry in country with consider key input and output in this industry studied. Conclusion say Ardebil province most efficiency and Booshehr province lower most efficiency in basis milky cow-keepers and also Khozestan province most efficiency and Chahar Mahal Bakhtiyari province lower most efficiency in basis fattened cow-keepers in country. Statistics that used in this search it concern five years.

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Total Factor Productivity (TFP) index is the rate of transformation of total input into total output and Total Factor Productivity Growth (TFPG) is used to analyze productivity performance in multiple time periodso, Also, TFPG index is one of the major sources of economic development, thus understanding the factors affecting productivity is very important. The main purpose of productivity measurement during multiple periods is to identify areas of improvement in activities as well as to aid strategic decision making or continuous improvement. Therefore, information about effective factors on productivity changes is useful. This paper presents a general view to the productivity growth indexes and their qualities. Then, a new method for evaluating the productivity growth is proposed. This method will be constructing by the combination of DEA and Tornqvist productivity index to measure TFPG and its decompositions. This paper also evaluates productivity growth and finds out the factors affecting productivity which are critical for the National Iranian Oil Company (NIOC) on the years 1977-2000. The obtained results showed that growth in efficiency is dominant source of change in productivity at NIOC.

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In the present study an attempt has been made to use a non-parametric method Data Envelopment Analysis (DEA) for assessing source-wise and operation-wise the Technical Efficiency (TE) and Return-to-Scale (RTS) for paddy production in four zones of the state of Punjab, India. The results were then compared to corresponding ones already obtained from a parametric method (Cobb-Douglas production function). The data from farmers growing rice in four zones including labor-h, machine-h, power source, horse power and hours used, kind of machinery used, physical inputs such as seed, fertilizers and pesticides (as inputs) and the yield (as output) were transformed into energy terms (MJ ha-1). The results revealed that farmers in zone 2 with a source-wise TE of 0.91, have consumed energy from more efficient sources, followed by zone 4 (0.90) and then zones 3 and 5 (0.85). No significant correlation could be established between the parametric and non-parametric TE for source-wise energy inputs. According to the DEA results, it was observed that 55.6% and 64.1% of inefficient farmers had an increasing RTS for operation-wise and source-wise energy inputs, respectively. However, a constant RTS had been reported by the parametric frontier function.

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In this paper, with the priority of measuring and promoting productivity in energy sector, we presented a model for evaluating the technical efficiency of oil refineries, as huge producers of energy and different fuels. The basis of evaluation in this research was Math modeling by using new and advanced operational research techniques such as data envelopment analysis, goal programming, analytical hierarchy process and designing combined models. The formulating process was made under two different scenarios and assumptions: consumption-production and cost-income. The final results ranked the order and sort of each refinery as a decision making unit. In addition to calculation of each unit’s score, we also made a comparison between the units, their weaknesses and the favorite score of each unit in real situation. This research focuses on the optimized utilization of refining processes with less refining cost and ability to make more valuable products considering the present availabilities and capacities

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Efficiency of economical units especially banks is one of the success factors in developed countries. In this regard, managers of the banks are responsible for the efficiency of them, which is not possible without evaluation of efficiency of the bank branches under the supervision of the managers. Data Envelopment Analysis (DEA) is a method for calculating the efficiency of various organizations having multiple-inputs multiple-outputs. This method leads to ordering of efficient and inefficient branches and identifying reference unit (DMU) to attain efficiency frontier. Also, effectiveness of each variable in efficiency of each unit can be determined. In this research, an input-oriented BCC model with envelopment form has been employed. Thus, the statistical data from 17 branches of Refah Kargaran Bank in Lorestan Province was collected during 2010-2011. The results show that there are 11 efficient branches (65% of the branches) and 6 inefficient branches. Inefficient branches were ranked in terms of their efficiency, and AP model was used for ranking of the efficient branches. Finally, TOPSIS was applied for ranking of the branches in order to verify the results.

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This research has been done with the aim of identification of the effective factors that influence credit risk and designing a model for the credit rating of the legal clients of Tejarat Bank in 2003-2004 by using Data Envelopment Analysis. For this purpose, the necessary sample data on financial and nonfinancial information of 146 companies (as random simple) was selected. In this research, 27 explanatory variables (including financial and non-financial variables) were identified and examined. Finally, with the application of factor analysis and Delphi method, 8 variables, which had significant effect on credit risk, were selected and entered into the DEA model. Efficiency of the companies was calculated by using these variables. Then the model validity was measured by regression analysis. The DEA credibility scores represented the dependent variables while the 8 ratios used were considered as independent variables. The findings of the research showed that 25 companies stand on the border of efficiency. Also with one exception (owners equity/ total asset), ’all variables had the expected direction α = %5 . Research conclusions confirmed the hypothesis of DEA model’s efficiency on credit rating of the companies who have taken credit facilities from branches of Tejarat Bank in Tehran city.

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Due to increasing concerns on environmental problems in current era, this study assesses the eco-efficiency of oil refineries. The oil refineries play essential role in the national economy in one hand, and cause environmental pollution due to high fossil fuel consumption and Co2 emissions in the other hand. Eco-efficiency is calculated using Windeap software, DEA output-oriented method, and inclusion of undesirable outputs. The results suggest that Bandar Abbas Oil Refining Company is the most efficient refinery over the 2003-2009, and growth rates of refineries eco-efficiency are positive. The results of Tobit regression show that fuel oil and gasoil have negative effects on the eco-efficiency, however natural gas, refinery gases, and liquefied petroleum gas (LPG) have positive effects on the eco-efficiency. On the other hand, if a refinery refines crude oil slightly more than nominal capacity rate, refinery eco-efficiency will be further decreased. 

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In the present study, an attempt has been made to use Data Envelopment Analysis (DEA) for assessing the technical efficiency and return-to-scale for greenhouse cucumber production in Iran. For this purpose, the data from greenhouses in Esfahan province, during one period of plant cultivation in one year including spring plants were randomly collected. The results indicated that total input energy, total output energy and energy ratio were 436,824 MJ ha^-1, 128,532 MJ ha^-1 and 0.29, respectively. DEA can be used to optimize the performance of any cucumber greenhouse. Based on input-oriented CRS and VRS models of DEA, the average values of pure technical efficiency, technical efficiency and scale efficiency were found to be 0.95, 0.83 and 0.88, respectively. Also the results revealed that, on average, about 30.27% of the total input energy could be saved without reducing the cucumber yield from its present level by adopting the recommendations based on the present study.

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The need for designing and implementing performance assessment systems at ‎R&D centers is one of the urgent issues of all industries. Assessment of R&D ‎projects has become one of the most challenging decision making issues for ‎the managers of R&D centers. Multi-criteria decision making methods have so ‎far been used for the assessment of R&D projects in different stages of their ‎lifecycle. Our approach is to develop Data Envelopment Analysis by ‎combining Balanced Scorecard and Data Envelopment Analysis. Inputs and ‎outputs for the integrated DEA-BSC model have been extracted from ‎‎“Balanced Scorecard for R&D projects”. The major goals of the integrated ‎DEA-BSC approach are as follows: increasing the reliability of inputs and ‎outputs criteria, improving the calculated efficiency of all sections and striking ‎a balance between the efficiency and the effectiveness of different sections. ‎This model has been implemented in an industrial research laboratory for ‎R&D projects as a case study. The results showed that synergizing between ‎BSC and DEA in R&D projects causes the: achieving of the expected ‎objectives of each project and balancing and optimizing the usage of resources ‎to meet the desired outputs.‎ .‎

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The Assessment of Financial Distress in Tehran Stock Exchange: A Comparative Study Between Data Envelopment Analysis (DEA) and Logistic Regression (LR) Mohammad Reza Rostami1, Mirfeyz Fallahshams2, Farzaneh Eskandari3 1- Assistant Professor, Department of Management, Faculty of Social Sciences & Economics, Alzahra University, Tehran, Iran 2- Associate Professor, Department of Management, Faculty of Social Sciences & Economics, Alzahra University, Tehran, Iran 3- Msc., Department of Management, Faculty of Social Sciences & Economics, Alzahra University, Tehran, Iran Received: 5 /9/2010 Accept: 13/8/2011 Financial distress evaluation is important because firm failure imposes significant direct and indirect costs on a firm’s stakeholders. Hence, using financial ratios has been considered by bank loan officers, creditors, stockholders, financial analysts, and the general public in order to provide them with timely and accurate assessment. Timely evaluation can help decision makers to find the optimal way and predict bankruptcy. There are different models for financial distress evaluation, which are mainly applied in decision making by financial market players. It has been attempted to improve the accuracy of these models by more developed techniques. The main goal of this research is to examine the capability of the additive model of Data Envelopment Analysis (DEA) model in assessing corporate financial distress by comparing it with logistic regression (LR). The results showed that in within-sample evaluation, LR outperforms DEA (Additive model) in correctly identifying the default firms significantly.

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Identifying Inefficient Bank Branches Using DEA and Use of Integrated Strategies in Order to Increase Performance Branches Naser Hamidi1, Reza Akbari Shemirani2, Safar Fazli3 1. Assistant Professor, Department of Managemen and Accounting, Islamic Azad University Qazvin Branch, Qazvin, Iran 2. M. A , Department of Managemen and Accounting , Islamic Azad University Qazvin Branch, Qazvin, Iran 3. Assistant Professor, Department of Social Sciences, Imam Khomeini International University, Qazvin, Iran Received: 27 /10/2010 Accept: 9/3/2011 Among the various economic and financial organizations, banks are considered and discussed as one of the most important pillars of any economic system. Therefore, considering the important role of banks in the developed countries and their multiple branches, bank branch performance measurement is important. The main purpose of this work is measure branch performance and the use of integration strategy to obtain efficient branches. Accordingly, first the efficiency of bank branches conceptual system was defined. Then using the action plan were inputs and outputs determined. In the next stage, Tehran province branch efficiency was calculated through Data Envelopment Analysis model as non-radial (SBM) to determine the inefficient branches. Based on the bank merger policy, the clusters were determined and the branches in each cluster were merged in a binary form. The final stage of the integration of non-radial (SBM) to assess the performance of branches and compare it with their initial performance.

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Supplier selection is a complex but important decision that requires careful review of various performance criteria. Traditionally, models of supplier selection have been based on cardinal data, with less emphasis on ordinal data. However, with the widespread use of production methods, such as the just-in-time method, recently more emphasis is placed on considering imprecise data—i.e., mixtures of interval and ordinal data. This article proposes to use data envelopment analysis (DEA) with double frontiers for supplier selection, a methodology which considers not only the optimistic efficiency but also the pessimistic efficiency of each supplier. Compared with the traditional DEA, the DEA approach with double frontiers can identify the best supplier accurately and easily without having to impose any weight limitations. A numerical example will be examined using the DEA approach with double frontiers to illustrate its simplicity and convenience for supplier selection and justification.

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Managers in all organizations today called for optimum use of existing facilities and capacities in different sectors. So in order to provide feedback model to improve performance of various branches and agencies to achieve a tool to meet the needs of managers, and the essential logic seems. The purpose of this study provide a model compilation process fuzzy network analysis, balanced scorecard and fuzzy data envelopment analysis for performance evaluation of branch offices is Yazd Cooperative with the device can also identify efficient and inefficient branches, the appropriate strategies improve the performance of inefficient branches and more branches to strengthen whatever can be effectively developed. In this study of balanced scorecard model to extract parameters assessment, fuzzy analysis network process techniques to estimate fuzzy relative importance of each indicator under a single perspective and of fuzzy data envelopment analysis techniques to evaluate the performance of branches has been used. financial Perspective as the most important, and the Yazd and ardakan Branches were identified Assessment as the efficient performance of the branches.

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Data envelopment analysis (DEA) is an approach to measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs using mathematical programming. The traditional DEA, which is based on the concept of efficiency frontier (output frontier), determines the best efficiency score that can be assigned to each DMU. Based on these scores, DMUs are classified into DEA-efficient (optimistic efficient) or DEA-non-efficient (optimistic non-efficient) units, and the DEA-efficient DMUs determine the efficiency frontier. There is a comparable approach which uses the concept of inefficiency frontier (input frontier) for determining the worst relative efficiency score that can be assigned to each DMU. DMUs on the inefficiency frontier are specified as DEA-inefficient or pessimistic inefficient, and those that do not lie on the inefficient frontier, are declared to be DEA-non-inefficient or pessimistic non-inefficient. In this paper, we argue that both relative efficiencies should be considered simultaneously, and any approach that considers only one of them will be biased. For measuring the overall performance of the DMUs, we propose to integrate both efficiencies in the form of an interval, and we call the proposed DEA models for efficiency measurement the bounded DEA models. In this way, the efficiency interval provides the decision maker with all the possible values of efficiency, which reflect various perspectives. A numeric example about Iranian gas companies will be evaluated using the DEA approach with efficient and inefficient frontiers to show its convenience and usefulness.

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With the increasing pace of science and knowledge in today, s world, the company in order to comply with the condition environment variable to use communication technology and capital investment in this technology is growing rapidly. Performance evaluation is one of the main concerns for monitoring this agreement. Recently applied the theory of data envelopment analysis (DEA) and grey theory for performance evaluating has been highly regarded. Considering the importance of telecommunications as a leader in the field of communication technology and necessary to evaluate the performance of these two techniques have been used in this study. For this mining first set of criteria in evaluating the financial performance of telecommunication and the importance (weight) each was determined using the number of grey. Then, technique of using DEA model for evaluating and ranking the telecommunications companies were presented. The result indicates that the major telecommunication companies province in Markazi, Tehran and Khuzestan have the best financial performance.