Arash Method

DEA is a technique for measuring the efficiency and performance of decision-making units (DMUs) with multiple inputs and outputs. The term overload in the literature DEA refers to the overuse of the source, which reduces the output and thus the efficiency. This problem changes over time, and the progress and rate of decline of the units can be measured by these changes. In this paper, the Malmquist productivity index and congestion are used to measure the progress and regression of units over time. The proposed model can change the congestion changes in addition to calculating the efficiency and technology changes by changing the relative distances in the Mamquist productivity index. The criterion for congestion is the fraction \(({e}_{o}^{i}\)(j))/\({c}_{o\left(j\right)}^{i}\), and the lower it is, the lower the congestion to be evaluated, and if it is 1, there is no congestion. Thus, by applying this criterion to the structure of the Malmquist productivity index, two categories of...

Universities play a vital role in a country's growth and have the potential to stay in the field of higher education by determining their performance. Thereby, management will not know whether university performance is profitable if it is not measured. Therefore, this project was carried out to determine the efficiency of public universities in Malaysia using Data Envelopment Analysis (DEA) models such as the Charnes, Cooper, and Rhodes model (CCR) and Slack-Based Measure model (SBM). . Public higher education is under tremendous pressure worldwide to improve its performance and quality. This paper examines the efficiency scores of 20 public universities in Malaysia using the CCR and SBM. These 20 public universities state as Decision Making Unit (DMU) and DMU will be efficient if and only if the optimal value of efficiency is equal to 1; otherwise, it is inefficient. Three inputs and five outputs are determined to measure the performance of the university through the graduate student's marketability. The findings show that out of 20 public universities, 11 public universities are efficient with an efficiency score equal to 1. Meanwhile, the remaining nine public universities showed inefficient score results. Suggestions and improvements are identified to improve the efficiency of those universities in the future. To overcome inefficient universities, the use of the SBM model provides recommendations to consider in measuring efficiencies which are the number of postgraduate students enrolled, number of undergraduate students enrolled, and number of academic staff as the inputs and the number of postgraduates, number of undergraduates, number of graduates working, number of graduates who choose to further studies and number of graduates choose to develop skills as the outputs. All the criteria need to consider for the improvement for the universities to be more efficient.

The purpose of this research is to develop an evaluation tool to assess performance of Emergency Physicians according to such criteria as resource utilization, patient throughput and the quality of care. Evaluation is conducted using a mathematical programming model known as Data Envelopment Analysis (DEA). Use of this model does not require the subjective assignment of weights associated with each criterion - a feature typical of methodologies that rely on composite scores. The DEA model presented in this paper was developed using a hypothetical data set describing a representative set of profiles of Emergency Physicians. The solution to the model relates the performance of each Emergency Physician in relation to the others and to a benchmark. We discuss how such an evaluation tool can be used in practice.

Data Envelopment Analysis (DEA) is one of the most popular techniques for measuring the relative efficiencies of a set of decision making units (DMUs), which use different inputs producing various outputs. Ranking of efficient DMUs is one of the most interesting DEA perspectives. However, there are cases where we see some limitations on available resources and the proposed model of this paper is associated with Indicator with Limited Sources (ILS), which affects ranking methods. The ILS exists as fixed amount in a community and the DMUs can own it with their abilities. When a DMU loses the same amount of the indicator, the rest of the DMUs are able to own some without even changing their capacities of other indicators and or vice versa. If a DMU looks for more of the same amount of the indicator, the rest of the DMUs have to supply it without even changing their capacity of other indicators. This paper develops a ranking method based on the ILS for the efficient DMUs, when there is ...

Universities play a vital role in a country's growth and have the potential to stay in the field of higher education by determining their performance. Thereby, management will not know whether university performance is profitable if it is not measured. Therefore, this project was carried out to determine the efficiency of public universities in Malaysia using Data Envelopment Analysis (DEA) models such as the Charnes, Cooper, and Rhodes model (CCR) and Slack-Based Measure model (SBM).. Public higher education is under tremendous pressure worldwide to improve its performance and quality. This paper examines the efficiency scores of 20 public universities in Malaysia using the CCR and SBM. These 20 public universities state as Decision Making Unit (DMU) and DMU will be efficient if and only if the optimal value of efficiency is equal to 1; otherwise, it is inefficient. Three inputs and five outputs are determined to measure the performance of the university through the graduate student's marketability. The findings show that out of 20 public universities, 11 public universities are efficient with an efficiency score equal to 1. Meanwhile, the remaining nine public universities showed inefficient score results. Suggestions and improvements are identified to improve the efficiency of those universities in the future. To overcome inefficient universities, the use of the SBM model provides recommendations to consider in measuring efficiencies which are the number of postgraduate students enrolled, number of undergraduate students enrolled, and number of academic staff as the inputs and the number of postgraduates, number of undergraduates, number of graduates working, number of graduates who choose to further studies and number of graduates choose to develop skills as the outputs. All the criteria need to consider for the improvement for the universities to be more efficient.

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During the last two decades public sector activities at the regional or national level have been involved in a worldwide trend for improved performance. The concept of efficiency has also penetrated the legal and judicial systems at all levels, since courts around the world are in a state of crisis, dealing with backlogs and inefficiencies. Moreover, political authorities place emphasis on courts delay, which represents a widely observed phenomenon and undermines the functioning of court systems around the world. Hence, nowadays there is an increasing interest in determining whether courts and judicial systems operate efficiently. In this context, the aim of this study is to analyse the productive efficiency of the Italian Courts of Appeal for the year 2008 by using a non-parametric technique, Data Envelopment Analysis.

In this paper we assess the efficiency of units using data envelopment analysis (DEA). In first stage, a functional data is converted to a fuzzy bell shape number and then a benchmark point would be chosen for each input or output and using the preference ratio method, the equivalence multiplier of each data would be calculated. In order to simplification of functional data, functional data will be replaced bythe equivalence multiplier.

Department Chair, Assoc. Prof. Dr. Gökhan Izbirak for their various contributions throughout my study period in the department, also all the experts involved in the validation of this thesis. I would like to acknowledge Dr. Mustapha Ibrahim Daruwana, for his valuable contributions and ideas, my relatives and friends whom we struggle together through good and harsh times. You guys are wonderful. My special appreciation goes to my father, Alhaji Ibrahim Hassan for always being there for me, I am proud to have a dad who is worthy of being called a good father, I am greatly indebted to my uncle Alhaji Muhammad Hassan, for sponsoring my studies and tireless support. My entire family, particularly Muhammad Ibrahim Hassan and Rukayya Ibrahim Hassan for their support and encouragement.

This paper presents a method that allows managers and information technology professionals to better evaluate how efficiently risk is being managed within the confines of a portfolio of software projects. The method, which is based upon optimization and risk modeling, favors actions that increase the efficiency of risk management and, as a result, the likelihood of projects being delivered on time, within budget and in accordance with the requirements they were intended to be satisfied.

The capacity of 35 Brazilian domestic airports was analyzed with a view to determining which of them were ecient in terms of the number of passengers processed. Data Envelopment Analysis (DEA) methodology was employed to construct the ecient frontier for the sample, to re¯ect which of the airports used airport resources eciently and which oered surplus in these same facilities, and in what proportion. On the basis of passenger demand forecasts, it was possible to determine, for each airport, the periods when capacity expansions would become necessary to maintain services at standards currently perceived by passengers.

This paper covers some of the past accomplishments of DEA and its future prospects. It starts with the "engineering-science" definitions of efficiency and uses the duality theory of linear programming to show how, in DEA, they can be related to the Pareto-Koopmens definitions used in "welfare economics." Some of the models that have now been developed for implementing these concepts are then described and properties of these models are examined for weaknesses and strengths along with different measures of distance that may be used to determine their optimal values. Relations between the models are also demonstrated en route to delineating paths for future developments. These include extensions to different objectives such as "satisfactory" vs. "full" (or "strong") efficiency. They also include extensions from efficiency to effectiveness evaluations of performances as well as extensions to evaluate social-economic performances of countries and other entities where "inputs" and "outputs" give way to other categories in which increases and decreases are located in the numerator or denominator of the ratio (=engineering-science) definition of efficiency in a manner analogous to the way output (in the numerator) and input (in the denominator) are usually positioned in the fractional programming form of DEA. Beginnings in each of these extensions are cited and the role of applications in bringing further possibilities to the fore is highlighted.

Data Envelopment Analysis (DEA) is a non-parametric approach to operations research for assessing the relative efficiencies of a set of peer units, called Decision Making Units (DMUs), with multiple inputs and multiple outputs. DEA provides a fair benchmarking tool that includes a technical efficiency score for each DMU, a technical efficiency reference set with peer DMUs, a target for a technically inefficient DMU, and information detailing by how much inputs can be decreased or outputs can be increased to improve performance of DMUs. In this paper, we compare DEA models to benchmark technically inefficient DMUs, and prove that popular models like the Slack-Based Measure (SBM) and Charnes, Cooper and Rhodes (CCR) may not give the acceptable results for benchmarking technically inefficient DMUs as strong as the weighted additive (ADD) model. The study also warns against applying the conventional DEA models for most of applications and suggests using the Kourosh and Arash Method to (KAM) assess the performance evaluation of DMUs.

Data Envelopment Analysis (DEA) is a non-parametric approach to operations research for assessing the relative efficiencies of a set of peer units, called Decision Making Units (DMUs), with multiple inputs and multiple outputs. DEA provides a fair benchmarking tool that includes a technical efficiency score for each DMU, a technical efficiency reference set with peer DMUs, a target for a technically inefficient DMU, and information detailing by how much inputs can be decreased or outputs can be increased to improve performance of DMUs. In this paper, we compare DEA models to benchmark technically inefficient DMUs, and prove that popular models like the Slack-Based Measure (SBM) and Charnes, Cooper and Rhodes (CCR) may not give the acceptable results for benchmarking technically inefficient DMUs as strong as the weighted additive (ADD) model. The study also warns against applying the conventional DEA models for most of applications and suggests using the Kourosh and Arash Method to (KAM) assess the performance evaluation of DMUs.

The aim of this study is to analyse the productivity of airports, operated by the General Directorate of State Airports Authority (DHMI in Turkish acronym) in Turkey, for a period from 2014 to 2018 using a hybrid method called Weight Restricted EATWOS without Consideration of Satisficing Levels and to offer improvement suggestions. The productivity of the airports was also measured using both equally weighted EATWOS without consideration of satisficing levels and the model of input-oriented DEA based on the assumption of constant returns to scale to compare the results obtained using the proposed model with those obtained using traditional methods.

Conventional Data Envelopment Analysis (DEA) models are based on a production possibility set (PPS) that satisfies various postulates. Extension or modification of these axioms leads to different DEA models. In this paper, our focus concentrates on the convexity axiom, leaving the other axioms unmodified. Modifying or extending the convexity condition can lead to a different PPS. This adaptation is followed by a two-step procedure to evaluate the efficiency of a unit based on the resulting PPS. The proposed frontier is located between two standard, well-known DEA frontiers. The model presented can differentiate between units more finely than the standard variable return to scale (VRS) model. In order to illustrate the strengths of the proposed model, a real data set describing Iranian banks was employed. The results show that this alternative model outperforms the standard VRS model and increases the discrimination power of (VRS) models.

Conventional Data Envelopment Analysis (DEA) models are based on a production possibility set (PPS) that satisfies various postulates. Extension or modification of these axioms leads to different DEA models. In this paper, our focus concentrates on the convexity axiom, leaving the other axioms unmodified. Modifying or extending the convexity condition can lead to a different PPS. This adaptation is followed by a two-step procedure to evaluate the efficiency of a unit based on the resulting PPS. The proposed frontier is located between two standard, well-known DEA frontiers. The model presented can differentiate between units more finely than the standard variable return to scale (VRS) model. In order to illustrate the strengths of the proposed model, a real data set describing Iranian banks was employed. The results show that this alternative model outperforms the standard VRS model and increases the discrimination power of (VRS) models.

The technique of Data Envelopment Analysis originated with the publication of a seminal paper Measurement of efficiency of decision making units (Charnes et al, 1978). Since then several models and methods are devised over the years and the technique has been used in varied fields and different applications both in the private and the public sectors. This paper surveys the various literature published in the field in the areas of a) various models and methods and b) various application procedures in applying the technique in various fields.The paper demonstrates the use of the method with a practical example of service delivery of Veterinary Districts of Odisha using CCR Output oriented model. The results produced include average efficiencies and projections for achieving efficiency.

Data Envelopment Analysis (DEA) is a method for comparing the efficiency of decision making units when the output of these units is evaluated based on the amount of inputs used. A special application area of DEA is the evaluation of student groups participating in a production simulation game. This paper shows how DEA is used to compare the performance of student groups in the simulation game, and how their results can be evaluated using the efficiency scores. Different DEA models are used to capture the different characteristics of the operation. Basic models with radial efficiency measures are used to analyze the effect of input and output weights, and to separate the proportional decrease of inputs from the independent input reduction possibilities. Slack based measure models are applied to study the joint effect of proportional and independent input/output changes. Dynamic models are used to study the change of efficiency over time. The paper compares the results of the applied models and analyses the differences. The results show that the application of the assurance regain models is strongly recommended. The presence of negative outputs requires the application of models which can be adapted to negative data.

This paper presents a method that allows managers and information technology professionals to better evaluate how efficiently risk is being managed within the confines of a portfolio of software projects. The method, which is based upon optimization and risk modeling, favors actions that increase the efficiency of risk management and, as a result, the likelihood of projects being delivered on time, within budget and in accordance with the requirements they were intended to be satisfied.

Department Chair, Assoc. Prof. Dr. Gökhan Izbirak for their various contributions throughout my study period in the department, also all the experts involved in the validation of this thesis. I would like to acknowledge Dr. Mustapha Ibrahim Daruwana, for his valuable contributions and ideas, my relatives and friends whom we struggle together through good and harsh times. You guys are wonderful. My special appreciation goes to my father, Alhaji Ibrahim Hassan for always being there for me, I am proud to have a dad who is worthy of being called a good father, I am greatly indebted to my uncle Alhaji Muhammad Hassan, for sponsoring my studies and tireless support. My entire family, particularly Muhammad Ibrahim Hassan and Rukayya Ibrahim Hassan for their support and encouragement.

Data Envelopment Analysis (DEA) is a method for comparing the efficiency of decision making units when the output of these units is evaluated based on the amount of inputs used. A special application area of DEA is the evaluation of student groups participating in a production simulation game. This paper shows how DEA is used to compare the performance of student groups in the simulation game, and how their results can be evaluated using the efficiency scores. Different DEA models are used to capture the different characteristics of the operation. Basic models with radial efficiency measures are used to analyze the effect of input and output weights, and to separate the proportional decrease of inputs from the independent input reduction possibilities. Slack based measure models are applied to study the joint effect of proportional and independent input/output changes. Dynamic models are used to study the change of efficiency over time. The paper compares the results of the applied models and analyses the differences. The results show that the application of the assurance regain models is strongly recommended. The presence of negative outputs requires the application of models which can be adapted to negative data.

The transportation problem is a particular type of linear programming problem in which the main objective is to minimize the cost. In marked contrast to the classical real-world transportation model, shipping supplies from one source to a destination cause several costs and benefits, each of which is incomparable to another. The extended transportation problem was first introduced in a study conducted by Amirteimoori [1]. In contrast, many important questions regarding the production possibility set, the place of costs, the benefits, and the essence of these costs were not fully addressed yet. Therefore, this paper focuses on transportation models that do not provide explicit output. This method is helpful because it is designed for a specific purpose: to send goods and supply-demand at the lowest cost and decision-maker; does not suffer from the confusion of costs and the various consequences of placing them costs and outputs. Furthermore, this model improves the contradiction betw...

Purpose-The purpose of the study is the evaluation of the efficiencies of a group of small Italian airports and the comparison with a set of transport heliports to show the difference in the productivity of the two types of infrastructures. Design/methodology/approach-The methodology used for the evaluation is the data envelopment analysis (DEA). Findings-The better performance of the heliports compared to the small inefficient airports. Research limitations/implications-This research is limited by the field of application and the weaknesses of the DEA methodology. However, it could be the first step for further works that will include more accurate models. Practical implications-The study suggests the conversion of the small inefficient airports into heliports feeding traffic towards the major hubs. The use of helicopters to reach poor accessible areas represents an alternative mode of transport. Originality/value-This is the first case of application of the DEA methodology to a group of heliports.

The highest efficiency score 1 (100% efficiency) is regarded as a common benchmark for Decision Making Units (DMUs). This brings about the existence of more than one DMU with the highest score. Such a case normally occurs in all Data Envelopment Analysis (DEA) models and also in all the Common Set of Weights (CSWs) methods and it may lead to the lack of thorough ranking of DMUs. And ideal DMU based on its specific structure is a unit that no unit would do better than. Therefore, it can be utilized as a benchmark for other units. We are going to take advantage of this feature to introduce a linear programming problem that will produce CSWs. The proposed method assures that the efficiency of all the units is less than that of the benchmark unit. As a result, it provides a comprehensive ranking of DMUs. Moreover, the proposed method is also noteworthy regarding computation. A numerical example is suggested to clarify and explain the proposed method and compare it to two other CSWs methods. Finally, 33 universities in Iran were ranked and compared using the proposed method.

Railway transportation is one of the most commonly used to commute by citizen of Jabodetabek (Jakarta-Bogor-Depok-Tangerang-Bekasi). The train station is part of the railroad infrastructure, including the Jabodetabek area which also has a large number of stations. In this case, the station needs its own efficiency assessment. This is because efficiency can lead train transportation to a transportation system that is more efficient and effective. In addition, by knowing the value of efficiency, it also supports the objectives of the National Transportation System (also known as Sistranas) as stated in Minister of Transportation Regulation No. KM 49 in 2005. This study aims to analyze the efficiency of the railway station. with the results-based orientation of the Data Envelopment Analysis (DEA) method and solving the problem of inefficient stations by the projection method. This research was conducted at 15 stations in Jabodetabek (Tebet Station to Cilebut Station). The results showed that 60% (9 stations) were declared efficient, which was known by evaluating using the CRS (Constant Return to Scale) method and 87% (13 stations) were also declared efficient by using the VRS (Variable Return to Scale) method. Then priority handling was determined to help the operator handle inefficient variables.

One of the difficulties of Data Envelopment Analysis(DEA) is the problem of de_ciency discrimination among efficient Decision Making Units(DMUs) and hence, yielding large number of DMUs as efficient ones. The main purpose of this paper is to overcome this inability. One of the methods for ranking efficient DMUs is minimizing the Coefficient of Variation (CV) for inputs-outputs weights. In this paper, it is introduced a nonlinear model for ranking efficient DMUs based on the minimizing the mean absolute deviation of weights and then we convert the nonlinear model proposed into a linear programming form.

This paper evaluates the technical effi ciencies of non-life insurance companies, which are active in Turkey in 2007, using Data Envelopment Analysis (DEA). DEA, which is a nonparametric method, facilitates to examine different input-output components. DEA is a management evaluation tool that assists in identifying the most effi cient and ineffi cient decision making units (DMUs) in the best practice frontier. In this study, as inputs of 23 non-life insurance companies, the number of agents, the number of brokers, fi xed assets, shareholders' equity and as outputs the investment incomes, premiums received are used. Empirical results of BCC and CCR models, which are DEA models, show that the most effi cient insurance company is RAY.

The unique properties of solar energy have led to increase demands for such resources in various countries. In order to use solar energy as a natural resource, environmental circumstances and geographical location related to solar intensity must be considered. Different factors may affect the selection of a suitable location for solar plants and should concurrently be considered for identifying the optimum location of solar plants. This article pre sents an approach for the location of solar plants by Arash Me thod (AM) in Data Envelopment Analysis (DEA). DEA is a useful tool for assessing the performance evaluation Decision Making Units (DMUs) with multiple inputs and multiple outputs. AM is also one of the earlier technique in DEA to arrange DMUs strongly. In this paper, the effected factors are illustrated and AM is applied to select the suitable locations for solar plants in 40 cities in Turkey which have some uncontrollable data.

This study comments on the data envelopment analysis (DEA) approach which was presented to grade countries/territories by Yang et al. (2016) [Yang, G.-l., Ahlgren, P., Yang, L., Rousseau, R., & Ding, J. (2016). Using multi-level frontiers in DEA models to grade countries/territories. Journal of Informetrics, 10, 238–253]. We show the fundamental problem of their approach and propose a DEA approach to tackle this problem.

DEA (Data Envelopment Analysis) is the optimization method of mathematical programming to measure the relative efficiencies of decision making units (DMUs). Due to its wide applicability, the DEA has been studied extensively for the last 30 years to solve decision making problems. Since, there are a lot of selection decisions in manufacturing, DEA as an appropriate tool to be necessary-especially for engineers-to improve learning for decision making. In this paper, the DEA method is applied in decision making process through DEA Excel-Solver software and the required processes are explained step by step to help academics and practitioners to get appropriate results in making decision.

In many countries, bus operators are private companies whose service has been leased by government agencies. These agencies develop service compliance indices or measures to keep track of factors such as passenger satisfaction, frequency, and regularity but do not necessarily include the objectives of the operators in the assessment. In this paper, we used slack-based measure data envelopment analysis (SBM) to investigate whether it is possible for a bus operator to be efficient (from a private perspective) and match required standards of frequency and regularity. In doing so, data collected from two major bus operators in Santiago, Chile has been used comprising 99 services. The results show that when private objectives, namely revenues, are included in the analysis, bus operators do not necessarily seek to improve the regularity of their service. Moreover, it was found that some bus services are on the efficient frontier while keeping low performance measure standards. Using the s...

The technique of Data Envelopment Analysis originated with the publication of a seminal paper Measurement of efficiency of decision making units (Charnes et al, 1978). Since then several models and methods are devised over the years and the technique has been used in varied fields and different applications both in the private and the public sectors. This paper surveys the various literature published in the field in the areas of a) various models and methods and b) various application procedures in applying the technique in various fields.The paper demonstrates the use of the method with a practical example of service delivery of Veterinary Districts of Odisha using CCR Output oriented model. The results produced include average efficiencies and projections for achieving efficiency.

The capacity of 35 Brazilian domestic airports was analyzed with a view to determining which of them were ecient in terms of the number of passengers processed. Data Envelopment Analysis (DEA) methodology was employed to construct the ecient frontier for the sample, to re¯ect which of the airports used airport resources eciently and which oered surplus in these same facilities, and in what proportion. On the basis of passenger demand forecasts, it was possible to determine, for each airport, the periods when capacity expansions would become necessary to maintain services at standards currently perceived by passengers.

One of the key issues in projects management is improvement of projects' efficiency. Efficiency subject in project management has been discussed from different aspects and one of the problems which influence efficiency of projects is the high rate of accidents at the workplace. So, it is clear that safety issue as a vital dimension of each activity can decline organizations' efficiency. Various approaches and indicators have been proposed in this context. One of the practical approaches in the field of operation research which examine efficiency of decision making units is data envelopment analysis. Therefore, in this paper a DEA method is applied to measure efficiency of project organizations taking into account safety factors. The criteria considered in this model are safety costs, number of accidents and lost days. This approach may help safety managers to effectively evaluate safety performance of each project concerning safety performance of the best project. Results of DEA model can be used in order to calculate and determine benchmark values to compare with inefficient projects.

The post-hurricane restoration of electric power is attracting increasing scrutiny as customers' tolerance for even short power interruptions decreases. Currently there are no standards for what constitutes an acceptably fast restoration. This paper introduces the use of data envelopment analysis to help evaluate post-hurricane restorations through comparison with the experiences of other companies in similar storms. The method accounts for the variable severity of the hurricane themselves, so that companies are not penalized for outages that are long only because the hurricane that caused them was particularly severe. The analysis is illustrated through an application comparing 19 recent post-hurricane restoration experiences across 9 different electric power companies in the United States. The method could be applied to other types of infrastructure systems and other extreme events as well.

As aviation demand increased constantly along with the rapid economic growth in Japan and surrounding East Asian countries over the last several decades, Japanese government promoted airport construction since 1950s. However, the recent change in the economic ...

Data Envelopment Analysis (DEA) was originally developed to measure the relative efficiency of peer Decision Making Units (DMUs) in multiple input-multiple output settings. Standard DEA models such as the CCR, BCC, and other similar models were applicable only to technologies identified by positive inputs and outputs. However, in real-world situations, this assumption may not always be true. In this paper, we provide a non-radial model for measuring efficiency when the inputs and outputs can take both negative and positive values. The proposed model computes the Pareto-Koopmans efficiency of DMUs and their reference sets, whereas traditional DEA models have hitherto been restricted to non-negative data. Applicability of the proposed model is illustrated by using real-world data of the notional effluent processing system.

Data envelopment analysis (DEA) is a linear programming based non-parametric technique for evaluating the relative efficiency of homogeneous decision making units (DMUs) on the basis of multiple inputs and multiple outputs. There exist radial and non-radial models in DEA. Radial models only deal with proportional changes of inputs/outputs and neglect the input/output slacks. On the other hand, non-radial models directly deal with the input/output slacks. The slack-based measure (SBM) model is a non-radial model in which the SBM efficiency can be decomposed into radial, scale and mix-efficiency. The mixefficiency is a measure to estimate how well the set of inputs are used (or outputs are produced) together. The conventional mix-efficiency measure requires crisp data which may not always be available in real world applications. In real world problems, data may be imprecise or fuzzy. In this paper, we propose (i) a concept of fuzzy input mix-efficiency and evaluate the fuzzy input mix-efficiency using a-cut approach, (ii) a fuzzy correlation coefficient method using expected value approach which calculates the expected intervals and expected values of fuzzy correlation coefficients between fuzzy inputs and fuzzy outputs, and (iii) a new method for ranking the DMUs on the basis of fuzzy input mix-efficiency. The proposed approaches are then applied to the State Bank of Patiala in the Punjab state of India with districts as the DMUs.

Airport concessions to private management began in Brazil in 2011 to address infrastructure bottlenecks and the need for investments. Productivity improvements after privatization need to be measured and efficiency gains can help to identify strategic points where to intervene both in current and upcoming concessions. However, previous studies have applied neither the Slacks-Based Measure Data Analysis Envelopment models nor the second stage Tobit regression to evaluate airport efficiency, especially in the context of Brazilian airport privatization. The objective of this study is to verify if privatization contributes to improving Brazilian airports' productive efficiency compared with public airports, using variable slacks and identifying new socio-economic variables that may influence the productive efficiency index. A two-stage SBM-DEA approach found that only 40% of the sample among 28 airports are efficient, evidencing poor management overall, and the slacks show the secto...

In many countries, bus operators are private companies whose service has been leased by government agencies. These agencies develop service compliance indices or measures to keep track of factors such as passenger satisfaction, frequency, and regularity but do not necessarily include the objectives of the operators in the assessment. In this paper, we used slack-based measure data envelopment analysis (SBM) to investigate whether it is possible for a bus operator to be efficient (from a private perspective) and match required standards of frequency and regularity. In doing so, data collected from two major bus operators in Santiago, Chile has been used comprising 99 services. The results show that when private objectives, namely revenues, are included in the analysis, bus operators do not necessarily seek to improve the regularity of their service. Moreover, it was found that some bus services are on the efficient frontier while keeping low performance measure standards. Using the s...

The purpose of this study is to measure and assess the performance of 100 largest listed companies in Malaysia. A modified strictly output-oriented Data Envelopment Analysis (DEA) model is used to measure the relative performance of each company by utilizing a list of normalized performance indicators based on data published in the Malaysian Business (16th October, 2009). The DEA scores indicate that only 6 and 19% of the companies are operating on the best-practice frontier under the assumptions of constant return to scale (CRS) and variable return to scale (VRS) respectively. No company exhibits increasing return to scale (IRS). Most of the relatively large (revenue-top-ranked) companies show serious scale inefficiency and exhibit decreasing return to scale (DRS). Ranking based on the performance index reveals that top-ranked companies by revenue are not necessarily top-ranked performers. Although ten of the seventeen governments linked companies, GLCs are top-20 by revenue, only ...

Data envelopment analysis (DEA) is one of the most efficient tools for efficiency measurement which can be employed as a benchmarking method with multiple inputs and outputs. However, DEA does not provide any suggestions for improving efficient units, nor does it provide any benchmark or reference point for these efficient units. Impracticability of these benchmarks under environmental conditions is another challenge of benchmarking by DEA. The current study attempts to extend basic models for benchmarking of efficient units under practical conditions. To this end, we construct the practical production possibility set (PPPS) by employing the concept of artificial decision-making units and adding these decisionmaking units to the production possibility set (PPS) such that these artificial units satisfy all environmental constraints. Then, the theorems related to PPPS and their proofs are provided. Moreover, as a secondary result of this study, efficient units can be ranked according to their practical efficiency scores.

This paper presents a method that allows managers and information technology professionals to better evaluate how efficiently risk is being managed within the confines of a portfolio of software projects. The method, which is based upon optimization and risk modeling, favors actions that increase the efficiency of risk management and, as a result, the likelihood of projects being delivered on time, within budget and in accordance with the requirements they were intended to be satisfied.

In this paper we present an approach to automatic authorship attribution dealing with real-world (or unrestricted) text. Our method is based on the computational analysis of the input text using a text-processing tool. Besides the style markers relevant to the output of this tool we also use analysis-dependent style markers, that is, measures that represent the way in which the text has been processed. No word frequency counts, nor other lexically-based measures are taken into account. We show that the proposed set of style markers is able to distinguish texts of various authors of a weekly newspaper using multiple regression. All the experiments we present were performed using real-world text downloaded from the World Wide Web. Our approach is easily trainable and fully-automated requiring no manual text preprocessing nor sampling.

Brassica rapa L. is an important agricultural crop that requires a period of prolonged cold for flowering. This process is known as vernalization. Studies have shown that long noncoding RNAs (lncRNAs) play important roles in abiotic stress responses and several cold-responsive noncoding RNAs have been suggested to be involved in vernalization. We examined the transcriptome of the Chinese cabbage inbred line (B. rapa L. var. pekinensis) RJKB-T24, and identified 1,444 long intergenic noncoding RNAs (lincRNAs), 551 natural antisense transcripts (NATs), and 93 intronic noncoding RNAs (incRNAs); 549 of the 2,088 lncRNAs significantly altered their expression in response to four weeks of cold treatment. Most differentially expressed lncRNAs did not lead to a change of expression levels in mRNAs covering or near lncRNAs, suggesting that the transcriptional responses to four weeks of cold treatment in lncRNA and mRNA are independent. However, some differentially expressed mRNAs had NATs with expression altered in the same direction. These genes were categorized as having an abiotic stress response, suggesting that the paired-expression may play a role in the transcriptional response to vernalization or cold treatment. We also identified short-term cold treatment induced NATs in BrFLC and BrMAF genes, which are involved in vernalization. The lncRNAs we identified differed from those reported in Arabidopsis thaliana, suggesting the role of lncRNAs in vernalization differ between these two species.

Videoconference, using a mechanism is needed to support the quality of service of the application programs. Different models have been presented to guarantee the quality of service. Among these, the differentiated services can be mentioned which was presented by IETF. In the architecture of the differentiated services, no admission control mechanism is considered. To guarantee the quality of service, the differentiated services network should support the admission control mechanism. In order to have the best result of the admission control mechanism, the parameters of the network should be considered to decrease the rate of loss and delay as well as the increase of the network utilization. Therefore, due to the spontaneous evaluation of the efficiency of the different inputs and finding the best set of inputs which produce the best outputs, the Data Envelopment Analysis (DEA) is used. Data Envelopment Analysis is one of the scientific approaches which computes the efficiency using the strong mathematical basis. In this paper, first the parameter based admission control mechanism is added to the edge routers of the differentiated services network and implemented by NS-2 simulator. Then, the best set of inputs is using the DEA.