Data Envelopment Analysis, DEA
Abbasali Monzeli; Behrouz Daneshian; Gasem Tohidi; Shabnam Razavian; Masud Sanei
Abstract
We extend the concept of returns to scale in Data Envelopment Analysis (DEA) to the weight restriction environments. By adding weight restrictions, the status of returns to scale, i.e. increasing, constant, and decreasing, may need a change. We first define "returns to scale" underweight restrictions ...
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We extend the concept of returns to scale in Data Envelopment Analysis (DEA) to the weight restriction environments. By adding weight restrictions, the status of returns to scale, i.e. increasing, constant, and decreasing, may need a change. We first define "returns to scale" underweight restrictions and propose a method for identifying the status of returns to scale. Then, we demonstrated that this addition would usually narrow the region of the most productive scale size (MPSS). Finally, for an inefficient decision-making unit (DMU), we will present a simple rule for determining the status of returns to the scale of its projected DMU. Here, we carry out an empirical study to compare the proposed method's results with the BCC model. In addition, we demonstrate the change in the MPSS for both models. We have presented different models of DEA to determine returns to scale. Here, we suggested a model that determines the whole status to scale in decision-making units.Different models of DEA to determine returns to scale are presented. Here, we suggested a model that determines the whole status to scale in decision-making units.
Data Envelopment Analysis, DEA
F. Z. Montazeri
Abstract
One of the best techniques for evaluating the performance of organizations is data envelopment analysis. Data Envelopment Analysis (DEA) is a non-parametric method for evaluating the performance of decision-making units (DMUs) that recognizes the relative performance of DMUs based on mathematical programming. ...
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One of the best techniques for evaluating the performance of organizations is data envelopment analysis. Data Envelopment Analysis (DEA) is a non-parametric method for evaluating the performance of decision-making units (DMUs) that recognizes the relative performance of DMUs based on mathematical programming. The classic DEA model was initially formulated for optimal inputs and outputs, But in real-world problems, the values observed from input and output data are often ambiguous and random. In fact, decision-makers may be faced with a specific hybrid environment where there are fuzziness and randomness in the problem. To overcome this problem, data envelopment analysis models in the random fuzzy environment have been proposed. Although the DEA has many advantages, one of the disadvantages of this method is that the classic DEA does not actually give us a definitive conclusion and does not allow random changes in input and output. In this research data envelopment analysis models in fuzzy random environments is reviewed.
Data Envelopment Analysis, DEA
M. V. Sebt; M. N. Juybari; V. R. Soleymanfar
Abstract
According to the increasing need of industry to financiers and investors in order to incorporate and encouraging them to invest in various fields of industry, the necessity of a method to help investors for making a decision has emphasized. We present a method which tries to omit to apply personally ...
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According to the increasing need of industry to financiers and investors in order to incorporate and encouraging them to invest in various fields of industry, the necessity of a method to help investors for making a decision has emphasized. We present a method which tries to omit to apply personally partial views in making a decision in order to make the results more reliable. This paper focuses on ranking investing opportunities. The strategy which has used is the Data Envelopment Analysis that the 4 main sub-models including Charnes, Cooper & Rhodes (CCR) model, Input Oriented Banker, Charnes & Cooper (BCC) model, Output Oriented BCC model, and Additive model have been utilized. The contribution of this research is using 4 DEA models for ranking projects in terms of feasibility whereas in the similar researches, as what found in the literature, the mentioned models have not been taken into account simultaneously. The developed model is applied in an Iranian investment company which has 15 investment opportunities that we have evaluated and ranked them based on 5 financial indices with DEA mechanism. Our approach can be performed by any investment company or financier to rank their investment projects considering feasibility study results of each investment opportunity.
Data Envelopment Analysis, DEA
Z. Taeb; F. Hosseinzadeh Lotfi; S. Abbasbandy
Abstract
In the last years, several techniques have been reported for managing a system and recognition of the related decision making units. One of them is based on mathematical modeling. Efficiency of any system is very important for all decision makings. Often applied data have time dependent inputs/ outputs. ...
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In the last years, several techniques have been reported for managing a system and recognition of the related decision making units. One of them is based on mathematical modeling. Efficiency of any system is very important for all decision makings. Often applied data have time dependent inputs/ outputs. To calculate the efficiency of time dependent data, a new calculation method has been developed and reported here. By this method, the efficiency has been calculated, with minimum errors and minimum mathematical solving model. The data are often time dependent, therefore Spline function has been estimated as a function of time, without using any particular time. Based on this developed function, the efficiency of time dependent data of a numerical example has been calculated and reported.
Fuzzy optimization
M. M. Tavakoli; B. Molavi; H. Shirouyehzad
Abstract
In recent years, researchers in their studies considered human capital as one of the most important capitals of every organization and even some of them placed it beyond this definition and introduced it as the unique factor of creating the competitive advantage in the organization. Due to the importance ...
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In recent years, researchers in their studies considered human capital as one of the most important capitals of every organization and even some of them placed it beyond this definition and introduced it as the unique factor of creating the competitive advantage in the organization. Due to the importance of human capital management, by evaluating the performance of human capital management system, managers can be aware of their organization’s status from the perspective of human capital management creation and perform corrective practices better. In this study, a method for the performance evaluation and ranking of organizational unit is presented using fuzzy DEA. Therefore in the beginning, the performance of organizational units was evaluated using fuzzy DEA and then with the use of sensitivity analysis, the most effective criteria on the efficiency of organizational units were determined. Then using the efficiency of organizational units in the best and the worst states, ranking of organizational units has been paid. Finally to examine the functionality of the proposed method, Foolad Technic Company has been chosen as a case study and the procedure has been implemented in this company.
Data Envelopment Analysis, DEA
M. Nayebi; F Hosseinzadeh Lotfi
Abstract
The science of Data Envelopment Analysis (DEA) evaluates the effectiveness of decision making units. But, one of the problems of Data Envelopment Analysis (DEA) is that, if the number of units with the same efficiency equal to one was more than one, then we couldn’t select the best between them. ...
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The science of Data Envelopment Analysis (DEA) evaluates the effectiveness of decision making units. But, one of the problems of Data Envelopment Analysis (DEA) is that, if the number of units with the same efficiency equal to one was more than one, then we couldn’t select the best between them. It means that, we can’t rank them. Therefore, the need for ranking these units is considered by the managers. Different methods were proposed in this context. Most of these methods are modeled by DEA models. Due to the variety of ranking methods in DEA, this paper will describe ranking methods which are based on super-efficiency. More precisely, we introduced methods that rank using elimination (removing) of decision making units under the evaluation of observations(set). These methods have some advantages and disadvantages such as, model feasibility or infeasibility, stability or instability, being linear or nonlinear, being radial or non-radial, existence or non- existence of bounded optimal solution in objective function, existence or non- existence of multiple optimal solution, non-extreme efficient units ranking, complexity or simplicity of computational processes, that in this paper, Super Efficiency methods are compared with these eight properties.
Data Envelopment Analysis, DEA
F Hosseinzadeh Lotfi; M. Jahanbakhsh
Abstract
By distinction between efficiency and effectiveness scales, the aim of this paper is to propose a model that can show the differents of efficiency and effectiveness. For this purpose, enveloping form of ICCR model ,has considered to calculate simultaneously the influences of efficiency and effectiveness. ...
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By distinction between efficiency and effectiveness scales, the aim of this paper is to propose a model that can show the differents of efficiency and effectiveness. For this purpose, enveloping form of ICCR model ,has considered to calculate simultaneously the influences of efficiency and effectiveness. this model, is a linear programming model based on Data envelopment analysis (DEA), that combine the input and output oriented CCR model to investigate the efficiency and effectiveness impressed each other ,in a three-stage process. By applying the model on data of 24 bank branches, the result clarify comprehensive view of the performance of the branches that have been substantially three-stage.
