Data Envelopment Analyses
Hosseinali Heydarzadeh; Fraydoon Rahnamay Roodposhti; Alireza Rashidi Komijan; esmaeil najafi
Abstract
Purpose:This research aims to construct a portfolio based on risk-adjusted performance and distribution-based returns and determine the efficiency using the data envelopment analysis (DEA) approach. In this study, the role of return distribution in the efficiency of risky assets is also examined to form ...
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Purpose:This research aims to construct a portfolio based on risk-adjusted performance and distribution-based returns and determine the efficiency using the data envelopment analysis (DEA) approach. In this study, the role of return distribution in the efficiency of risky assets is also examined to form a diversified portfolio consisting of assets with varying degrees of performance.Methodology:In this study, the diversified portfolio's performance based on the risk-adjusted value and conditional risk-adjusted value obtained from the probability distributions of returns was compared with the minimum-variance Markowitz portfolio performance in terms of the Sharpe ratio. After estimating the maximum likelihood parameters of the model, the risk values for each stock were calculated based on the empirical return distribution, the Cauchy distribution, and the normal distribution. These risk values were then used in the data envelopment analysis to calculate the efficiency scores of each company.Findings:The diversified portfolio with stock performance degrees outperforms the minimum-variance Markowitz portfolio in terms of risk-adjusted and conditional risk-adjusted values. The probability distribution of returns leads to different results in calculating stock risk-adjusted value/conditional value, with the empirical return distribution and normal distribution providing a more desirable performance (in terms of the Sharpe ratio) compared to the Cauchy distribution and sample ratios.Originality/Value:In the literature, an efficient portfolio is usually formed by calculating asset weights in the stock basket so that the Sharpe ratio reaches its maximum value. In the current study, this hypothesis is challenged in favor of the proposed method, which estimates portfolio weights based on the efficiency of risky assets.
Kasra Ghafori
Abstract
Purpose: In general, efficiency is a criterion for evaluating the performance of a decision unit from different dimensions. Data envelopment analysis is a mathematical programming method for evaluating the performance of decision-making units. The purpose of this study is to measure the financial efficiency ...
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Purpose: In general, efficiency is a criterion for evaluating the performance of a decision unit from different dimensions. Data envelopment analysis is a mathematical programming method for evaluating the performance of decision-making units. The purpose of this study is to measure the financial efficiency of firms by considering both incoming assets and financing.Methodology: In this research, a new method called the three-dimensional model of data envelopment analysis was introduced, and performance analysis was done on 10 active firms in Iran's steel industry for 5 years, from 2016 to 2021.Findings: The results showed that several firms have good performance in managing incoming assets but are inefficient in terms of financing. At the same time, some firms have poor management performance compared to inputs, but they are efficient in terms of financing. Therefore, when analyzing a firm's performance, an indicator that considers both inputs and financing at the same time is needed. According to this, we proposed a new measurement method and analyzed the current financial situation of each decision-making unit through the method of return to scale, and a path has been determined for financial improvement.Originality/Value: Attention to the effect of negative and destructive factors such as borrowings and debts of the decision-making unit in data envelopment analysis has been the key and different aspect of this study, compared to other previous studies. According to the literature review, using the redesigned DEA model has not been considered by Iranian researchers, and due to a new approach to data envelopment analysis, our approach has distinguished itself from the previous works.
Data Envelopment Analyses
Majid Yarahmadi; Saeedeh Sakiniya
Abstract
Purpose: This paper presents an intelligent method for applying Data Envelopment Analysis (DEA) to design a sustainable supply chain.Methodology: In the proposed method, for defuzzification of the ERM model, we used the -cutting technique. Then, to measure the productivity in the presence of environmental ...
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Purpose: This paper presents an intelligent method for applying Data Envelopment Analysis (DEA) to design a sustainable supply chain.Methodology: In the proposed method, for defuzzification of the ERM model, we used the -cutting technique. Then, to measure the productivity in the presence of environmental uncertainty via different -levels, a genetic algorithm is implemented to find an optimal -cutting. Finally, an intelligent DEA model for ranking the supplier companies via optimal value is designed.Findings: This paper presents a new fuzzy DEA model based on a Genetic Algorithm for evaluating the productivity of suppliers in a sustainable supply chain.Originality/Value: In the proposed method, since the -cut obtained from the Genetic Algorithm is optimal, there is no longer a need to calculate the efficiency for different α-cuts through trial and error. Therefore, the proposed method's advantage is that it offers a more sustainable ranking in addition to increasing productivity for each supplier. The example presented in this article demonstrates the method's superiority and advantages.
Data Envelopment Analyses
Seyedeh Masoumeh Mirsadeghpour Zoghi; Masoud Sanei; Ghasem Tohidi; Shokoofeh Banihashemi; Navideh Modarresi
Abstract
Purpose: Portfolio optimization is a selection of assets with the lowest risk and highest return. Asset performance evaluation is a useful way to choose assets and construct a profitable portfolio. For this purpose, the non-parametric Data Envelopment Analysis (DEA) method is used, which is a suitable ...
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Purpose: Portfolio optimization is a selection of assets with the lowest risk and highest return. Asset performance evaluation is a useful way to choose assets and construct a profitable portfolio. For this purpose, the non-parametric Data Envelopment Analysis (DEA) method is used, which is a suitable tool for measuring performance. By the fact that stock returns are not normally distributed and usually exhibit skewness, kurtosis and heavy-tails, which definitely affects the assets performance, we have to consider the characteristics of the returns distribution. In the proposed model, we apply the Variance Gamma (VG) process, which covers the skewness and kurtosis of returns. As a result, we construct a portfolio by selecting assets which their performance is more realistic.Methodology: In the introduced model, the only input of the model is Conditional Value at Risk (CVaR), and the mean return and Sharpe index are the model’s outputs. Since the outputs can be negative, the model is inspired by VRM in the output-oriented DEA model, which deals with negative values. As the returns on stock are VG distributed, its parameters are simulated by the method of moments estimation, and then the process factors are simulated by the Monte Carlo technique. Finally, the scenarios of returns are obtained, and the assets performance is evaluated.Findings: The correctness of the model is investigated by evaluating the relative efficiency of 7 companies from different industries in Iran Stock market. The results show that by considering the returns distribution characteristics, the input and outputs values of the model are estimated more realistically and more reliable results can be obtained; thus a profitable portfolio can be constructed.Originality/Value: Evaluation of the assets performance by taking into account the returns distribution characteristics leads to realistic results.
Data Envelopment Analyses
Hossein Azizi
Abstract
Purpose: The Analytic Hierarchy Process (AHP) is a multiple criteria decision-making method extensively used in various fields. Prioritization of decision criteria or alternatives from pairwise comparison matrices in AHP has been studied extensively. This article proposed the “Double-Frontier DEA” ...
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Purpose: The Analytic Hierarchy Process (AHP) is a multiple criteria decision-making method extensively used in various fields. Prioritization of decision criteria or alternatives from pairwise comparison matrices in AHP has been studied extensively. This article proposed the “Double-Frontier DEA” approach for prioritization in AHP. This new approach uses two optimistic and pessimistic DEA models to obtain the best local priorities from a pairwise comparison matrix, regardless of whether it is fully consistent or not.Methodology: One of these methods is Data Envelopment Analysis (DEA). The combination of DEA and AHP (DEAHP) is used to obtain and aggregate weights in AHP. Studies show that DEAHP fails in obtaining and aggregating weights in AHP and sometimes produces priority vectors contrary to evidence for inconsistent pairwise comparison matrices that limits its application.Findings: This new approach uses two optimistic and pessimistic DEA models to obtain the best local priorities from a pairwise comparison matrix, regardless of whether it is fully consistent or not. Some numerical examples, including a real application of AHP for selecting an innovation team for a university, are provided to specify the advantages of the proposed approach and its potential applications.Originality/Value: The double-frontier DEA approach generates true weights for fully consistent pairwise comparison matrices and best local priorities for inconsistent pairwise comparison matrices, that are logical and fit subjective judgments of decision-makers.
Data Envelopment Analyses
Azam Pourhabib Yekta; Mahnaz Maghbouli
Abstract
Purpose: Data Envelopment Analysis (DEA) is a technique used to assess performance and measure the relative efficiency of Decision Making Units (DMUs) through linear programming. In most cases, DEA models evaluate inefficient units on the boundary of the production possibility set using reference points ...
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Purpose: Data Envelopment Analysis (DEA) is a technique used to assess performance and measure the relative efficiency of Decision Making Units (DMUs) through linear programming. In most cases, DEA models evaluate inefficient units on the boundary of the production possibility set using reference points that are not Pareto efficient. Consequently, these models often yield zero weights for multipliers, failing to justify all sources of inefficiency. This paper aims to introduce a model that generates non-zero weights.Methodology: Weight restriction methods have primarily addressed the issue of non-realistic weights. We impose constraints on the weights in the proposed model to achieve our objectives.Findings: This paper presents a one-stage method based on the BCC model, incorporating weight restrictions, to evaluate the relative efficiency of decision-making units. The proposed model ensures non-zero weights and prevents dissimilarity between weights while maintaining feasibility. Notably, the proposed model does not require any prior information on weights or the classification of units, reducing the complexity of the problem.Originality/Value: To highlight the strength of the proposed method, the model is implemented on two case studies and compared with the results obtained from standard BCC models and those of Ramon and colleagues. The results indicate the superior performance of the proposed model.
Data Envelopment Analyses
Zeinab Tavassoli; Mohsen Rostami-MalKhalifeh; Farhad Hosseinzadeh Lotfi; Tofigh allahVieanloo
Abstract
Purpose: The current paper tries to determine the type of returns to scale in a decision-making unit under the condition that integer-valued inputs or outputs are present.Methodology: This paper introduces radial models for determining the value and type of Returns to Scale (RTS) in 4 scenarios, including ...
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Purpose: The current paper tries to determine the type of returns to scale in a decision-making unit under the condition that integer-valued inputs or outputs are present.Methodology: This paper introduces radial models for determining the value and type of Returns to Scale (RTS) in 4 scenarios, including single integer-valued input – single real output (scenario one), mixed inputs – exclusively real outputs (scenario two), exclusively integer-valued inputs – exclusively real outputs (scenario three), and exclusively integer-valued inputs – exclusively integer-valued outputs (scenario four); in each scenario, the values of the left RTS and right RTS are determined, and the RTS type is then determined on that basis. Finally, by presenting three examples based on two scenarios, namely single integer-valued input – single real output and single integer-valued input – single integer-valued output, the new method is compared with previous methods using GAMS software, and the conclusions are provided.Findings: The type of returns to scale differs when integer-valued inputs or outputs are present as compared with the case where the inputs and outputs are assumed to have real values.Originality/Value: This study focuses on the value and type of returns to scale for integer-valued data. For this purpose, returns to scale was modeled in 4 scenarios using input-oriented radial models, and in the fourth scenario (exclusively integer-valued inputs – exclusively integer-valued outputs), the modeling was carried out for output orientation as well. The existence of a difference between the results produced by our proposed model and those of the classical model was demonstrated through two examples, one using hypothetical data and the other real-world data.
Data Envelopment Analyses
Somayye Karimi Omshi; Sohrab Kordrostami; Alireza Amirteimoori; Armin Ghane Kanafi
Abstract
Purpose: In the most investigations of sustainability, including environmental, social and economic issues, in addition to the desirable outputs, undesirable outputs are also presented, which is an obstacle to sustainable development. In this regard, the purpose of this paper is providing an approach ...
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Purpose: In the most investigations of sustainability, including environmental, social and economic issues, in addition to the desirable outputs, undesirable outputs are also presented, which is an obstacle to sustainable development. In this regard, the purpose of this paper is providing an approach based on Data Envelopment Analysis (DEA) with different forms of weak disposability of undesirable outputs to move towards sustainability.Methodology: Presenting a DEA-based model, the sustainability and performance of each dimension of sustainability are calculated simultaneously, while undesirable outputs are present with different forms of weak disposability. The sustainability performance of provincial gas companies is examined using the proposed technique.Findings: The results show that the proposed method in the performance analysis of sustainability and its dimensions is efficient when undesirable outputs are presented.Originality/Value: DEA provides a variety of disposability to minimize undesirable outputs and moves to optimize. In this study, an integrated approach with different forms of weak disposability is presented to analyze sustainability.
Data Envelopment Analyses
Mohammad Khodabakhshi; Zahra Cheraghali
Abstract
Purpose: Due to the importance of productivity index in the economy, in this article we will discuss the different approaches that are used to measure partial and total factor productivity.Methodology: In all economic and social organizations and systems, the concept of productivity is very important ...
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Purpose: Due to the importance of productivity index in the economy, in this article we will discuss the different approaches that are used to measure partial and total factor productivity.Methodology: In all economic and social organizations and systems, the concept of productivity is very important and is examined using different approaches. Without the goal of productivity, no business will find a suitable direction, and without measuring productivity, there will be no control over business. Measurement is the first step towards control and ultimately improvement. Productivity can be divided into two categories, partial and total factor productivity. Total factor productivity in the economy has a significant impact on increasing GDP growth.Findings: According to the results obtained for the Malmquist index of the industrial sector in 2011, the productivity growth of total factor productivity has been desirable, but productivity in the mining sector has had the greatest decrease. The productivity growth of total factor productivity of the economy in 2011 is almost uniform.Originality/Value: By using the real data of Iran in 2011 calculate partial and total factor productivity with different approaches.
Data Envelopment Analyses
Gholamreza Panahandeh Khojin; Abbas Toloie Ashlaghi; Mohamad Ali Afshar Kazmi
Abstract
The purpose of this study is to combine two methods of data envelopment analysis and neural network in order to provide an optimal model for ranking inefficiency factors in the Iranian banking industry. First, through the study of theoretical foundations and interviews with banking experts, efficiency ...
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The purpose of this study is to combine two methods of data envelopment analysis and neural network in order to provide an optimal model for ranking inefficiency factors in the Iranian banking industry. First, through the study of theoretical foundations and interviews with banking experts, efficiency evaluation indicators in the banking industry were identified and finalized. In order to evaluate the efficiency of the units in the statistical population of the study, data envelopment analysis technique was used, especially the modified goal programming data envelopment analysis model, which was identified from 32 managements, 3 efficient managements and 29 inefficient managements. Then, the branches of inefficient management were evaluated and using the information of inefficient branches, the neural network matrix was prepared to identify the causes of inefficiency and the results were analyzed with different neural network models. The model with the lowest mean square error will be selected as the optimal model to determine the inefficiency factors. As a result, the self-organized mapping model with hyperbolic tangent transfer function and 0.9 momentum training rule was selected. By analyzing the sensitivity of this method, the indicators of provincial liquidity share, personnel distribution and operating costs were selected as the most important factors of inefficiency.
Data Envelopment Analyses
Zeynab Latifi; Neda Pouyan
Abstract
Purpose: Data Envelopment Analysis, one of the keys subfields in mathematical planning, has found a prominent role in evaluating the efficiency of decision making units in various fields. Methodology: In this research, after analysis and initial processing, based on studies, a parametric and efficient ...
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Purpose: Data Envelopment Analysis, one of the keys subfields in mathematical planning, has found a prominent role in evaluating the efficiency of decision making units in various fields. Methodology: In this research, after analysis and initial processing, based on studies, a parametric and efficient method for ranking intuitionistic fuzzy numbers is selected and proposed. The correctness of the performance of the selected method is obvious due to its formulation in linear structures. The developed model of data envelopment analysis, its mathematical formulation by CCR and IO-BCC methods are expressed in terms of governing the model structure and its implementation approach. A case study is presented to determine the factors affecting safety performance using the model. Based on previous theoretical studies and opinions of experts in the field of safety, the most important influencing factors (work pressure and perception of the supervisors' safety as inputs) and (the rate of physical and mental injuries and unsafe accidents as outputs) were selected. In addition to ranking the units, sensitivity analysis was performed in CCR and IO-BCC methods to rank the specified indicators in the inputs and outputs, and the results have been compared.Findings: The results of the data envelopment analysis model with intuitionistic fuzzy data showed that with increasing k, the number of efficient units increases. On the other hand, in CCR and IO-BCC methods, the lowest and highest efficiencies belong to the pessimistic view (k = 0) and the balanced view (k = 0.5), respectively. Sensitivity analysis also showed that, in CCR and IO-BCC methods, the work pressure is the most safety factor affecting the efficiency results.Originality/Value: Using a Data Envelopment Analysis model with intuitionistic fuzzy data to evaluate the performance of construction sites from a safety perspective can provide significantly better results. Because in the real world, there is uncertainty, and intuitionistic fuzzy data, due to the concept of belonging, non-belonging, and suspicion in the view of decision-makers simultaneously and in data reporting, is of particular importance.
Data Envelopment Analyses
mohammad reza mozaffari; Fatemeh Dadkhah; Mehdi Abbasi
Abstract
Purpose: The purpose of this paper is to present fully fuzzy value efficiency model and fully fuzzy value efficiency with ratio data model and determine DMU targets by solving them. It is considerable that to find targets of decision making units (DMUs) in data envelopment analysis, usually the required ...
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Purpose: The purpose of this paper is to present fully fuzzy value efficiency model and fully fuzzy value efficiency with ratio data model and determine DMU targets by solving them. It is considerable that to find targets of decision making units (DMUs) in data envelopment analysis, usually the required exact data and information are not available. In this situation using mathematical models with fuzzy parameters and decision making variables can be useful. Also, by using value efficiency analysis, the opinions of manager can be considered in determining DMU targets.Methodology: Here, the linear programming models which all parameters and decision variables are triangular fuzzy numbers are defined as fully fuzzy linear programming. Each proposed full fuzzy model is converted to a triple objective non-fuzzy linear programming model and solved by the lexicographic method.Findings: Research project targets in a university of Iran were determined by creating and solving proposed mathematical models.Originality/Value: To present and solve fully fuzzy value efficiency model and fully fuzzy value efficiency with ratio data model and determine DMU targets are the innovations of this research. It is considerable that presenting the results as fuzzy numbers can be applied to evaluate DMUs.
Data Envelopment Analyses
Elham Zaker Harofteh; Faranak Hosseinzadeh Saljooghi
Abstract
Purpose: In this paper, the combined model for determining capacity utilization by considering inputs and outputs based on efficiency is discussed and the loss due to the lack of suitable use of capacity utilization is also calculated.
Methodology: The current research is practical in terms of ...
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Purpose: In this paper, the combined model for determining capacity utilization by considering inputs and outputs based on efficiency is discussed and the loss due to the lack of suitable use of capacity utilization is also calculated.
Methodology: The current research is practical in terms of the type of purpose and fundamental in terms of the type of study. The capacity utilization evaluation method is based on data envelopment analysis model which is suitable for evaluating efficiency and function and it also has the ability to designate the capacity utilization. In the present models, the capacity utilization evaluation method is stated by assuming the possibility of changing all inputs/outputs with a multiplicative constant (Radial model) or assuming a distinct change in all factors affecting production. But in reality, some inputs/outputs might change radially and some of them non-radially in organizations and companies. In this article, a new model is submitted to designate the capacity utilization. It measures the capacity utilization simultaneously in the presence of radial and non-radial factors; furthermore, it has the ability to detect losses caused by any of the items such as the price of outputs/inputs or amount of output deficit and input surplus and it is a suitable model for evaluating the capacity utilization in practical and real issues.
Findings: The proposed approach in this article combines the points of the CCR radial model and the SBM non-radial model with the aim of determining capacity utilization and not just measuring efficiency, and with its help, we can evaluate the capacity utilization with the presence of non-radial data in addition to the radial data. In a case study of twelve hospitals with a fixed input of a doctor, and a variable input of a nurse and two outputs of outpatients and inpatients, it was observed that by eliminating the variable inputs in the presence of radial and non-radial outputs, there is no improvement in efficiency. On the other hand, the results show that some hospitals should improve the use of their capacity, and in some hospitals, by increasing the number of nurses, the number of outpatients or inpatients can be increased and the performance of hospitals can be improved. Then, using efficiency analysis, the inefficiency factor and its amount were determined. The combined model shows a lower number of inefficient units than the output-oriented BCC model.
Originality/Value: In this article, the combined model of capacity utilization in the presence of radial and non-radial indicators is presented, which can be an introduction to the presentation of DEA models of capacity utilization under different input and output conditions.
Data Envelopment Analyses
Parisa Nankali; Fatemeh Rakhshan; Mohammad Reza Alirezaee
Abstract
Purpose: Customer loyalty is significantly dependent on customer satisfaction with the services provided. Therefore, customer satisfaction in offline services such as e-banking, offline account opening, etc. can be considered as an effective competitive strategy, especially in the current situation due ...
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Purpose: Customer loyalty is significantly dependent on customer satisfaction with the services provided. Therefore, customer satisfaction in offline services such as e-banking, offline account opening, etc. can be considered as an effective competitive strategy, especially in the current situation due to the corona virus pandemic.Methodology: In this study, first, by considering the appropriate loyalty codes at the level of bank branches, we define the appropriate weight constraints of the type of confidence zone constraints of the first type and add them to the basic model of data envelopment analysis. The new size obtained from this mathematical model is due to the effect of loyalty constraints and will have more resolution than the basic model. The loyalty factor of each branch is then defined as the ratio of the size of the new model to the base model, which will be a number between zero and one. Then, the proposed model is implemented in a case study consisting of 195 branches of the Housing Bank and the results of the model are analyzed.Findings: The results show that the loyalty factor is directly related to the quality of in-person services and a new measure of efficiency is obtained to monitor customer loyalty.Originality/Value: The data envelopment analysis method can be a suitable technique to evaluate the role of non-personal bank services in the level of customer loyalty and can help banks to retain customers.
Data Envelopment Analyses
Fatemeh Gholami Golsefid; Behrooz Daneshian; Mohsen Rostamy-Malkhalifeh
Abstract
Purpose: The providing a proposed model pair for ranking interval data and their application to evaluate and improve the performance of a service system using results of simulation.Methodology: Mathematical techniques (data envelopment analysis) and computer simulation.Findings: By presenting proposed ...
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Purpose: The providing a proposed model pair for ranking interval data and their application to evaluate and improve the performance of a service system using results of simulation.Methodology: Mathematical techniques (data envelopment analysis) and computer simulation.Findings: By presenting proposed models pair, we were able to improve the performance of a service system by simulating different scenarios for that system. The results show that the introduced scenario could increase the efficiency of system by 22%.Originality/Value: Introducing new applied methods using mathematical models (Data Envelopment Analysis) and simulations to improve the performance of systems
Data Envelopment Analyses
Mohammad Izadikhah; Mohadeseh Shamsi; Abbas Sheikhsn; Fariba Ghafouri
Abstract
Purpose: Implementing a credit rating system considering banks' deferred claims is one of the most important means of controlling credit risk in banks and financial institutions. In the case of banking facilities, the possibility of non-repayment of facilities is one of the most important issues. By ...
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Purpose: Implementing a credit rating system considering banks' deferred claims is one of the most important means of controlling credit risk in banks and financial institutions. In the case of banking facilities, the possibility of non-repayment of facilities is one of the most important issues. By identifying various factors that affect the non-repayment of bank facilities, it is possible to provide a framework for reducing and controlling the credit risk of banks and improving the crediting process. The purpose of this paper is to examine the relationship between efficiency and risk in the banking system.Methodology: In this research, a sample of 24 companies from the most important legal customers of 11 branches of the Melli Bank of the city of Arak has been studied. 18 variables affecting credit risk were identified in this paper. Among the variables available, 6 variables were selected using the Factor Analysis Technique and Expert judgment (Delphi method), of which 3 were inputs and 3 were formed the outputsFindings: The efficiency and rank of legal firms were obtained with the help of Data Envelopment Analysis models, and then using the Fitch Institute's data and the efficiency of legal clients, the credit rating of each of the legal firms and their qualitative analysis was expressed.Originality/Value: Accordingly, using the method of data envelopment analysis and data provided by the Fitch Ratings Institute, the credit risk of Arak's Melli Bank's legal customers is assessed and ranked
Data Envelopment Analyses
nasrin bagheri mazraeh; Mohsen Rostami Mal Khalife; Meysam Varzi
Abstract
Purpose: Efficiency is an economic concept which shows the performance of a wide range of economic activities in different areas of an economic sector. Most of studies using frontier technique Data Envelopment Analysis (DEA) do not test for the relationship of efficiency estimation with key performance ...
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Purpose: Efficiency is an economic concept which shows the performance of a wide range of economic activities in different areas of an economic sector. Most of studies using frontier technique Data Envelopment Analysis (DEA) do not test for the relationship of efficiency estimation with key performance indicators. This is despite the fact that DEA is one of the most effective tools for measuring and evaluating efficiency. Nevertheless, identifying the relationship between efficiency estimates and commonly accepted financial measures of performance could guide benchmarking activities, pricing decisions, and regulatory monitoring.Methodology: In this paper, the DEA super-efficiency formula is tested in two profitability models. Four ratios of net interest income to total assets, post-tax profit to total assets, owner’s equity returns and impaired loans to total assets, were calculated with a developed profitability model; besides, the growth rate of assets was calculated with main profitability model and all the aforementioned ratios addressed a significant association with efficiency estimates.Findings: In this study, the DEA super-efficiency formula is tested in two profitability models for 15 banks for two years. The correlation obtained is generally low. However, the four ratios of net interest income to total assets, post-tax profit to total assets, owner’s equity returns and impaired loans to total assets, in the EPM model and asset growth rate in the CPM model have a significant relationship with performance estimates. Finally, the results indicate poor credit quality in Iranian banks in 1397-1397.Originality/Value: In this study, for the first time, the nature of the relationship between performance and key performance indicators has been estimated. DEA technique has been used to purposefully identify criteria for analyzing financial ratios.
Data Envelopment Analyses
Zohreh Moghaddas; Mohsen Vaez Ghasemi
Abstract
Purpose: Evaluating the cost efficiency of a network system using Data Envelopment Analysis (DEA) models can be improved from various aspects that exist in real applications. In this study, the aim is to consider a specific set of weights to evaluate cost efficiency in a two-stage network system.Methodology: ...
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Purpose: Evaluating the cost efficiency of a network system using Data Envelopment Analysis (DEA) models can be improved from various aspects that exist in real applications. In this study, the aim is to consider a specific set of weights to evaluate cost efficiency in a two-stage network system.Methodology: In this research, using data envelopment analysis method, an attempt is made to provide a model for evaluating the cost of the network system.Findings: The results showed that considering the relationships between different stages in a network system can directly affect the results. This issue has been investigated from cost optimization assessments. Considering the set of weights from different aspects can affect the scores obtained.Originality/Value: According to the models and methods in the literature, in this study, a model is presented that considers cost efficiency in a two-stage model.
Data Envelopment Analyses
Hengameh Mohamadinejadrashti; Alireza Amirteimoori; Sohrab Kordrostami; Farhad Hosseinzadeh Lotfi
Abstract
Purpose: In resource allocation and target setting problems, a central planner decision making from a managerial point of view has a pivotal role, especially in presence of undesirable outputs such as greenhouse gas emissions. In these situations, firms have to incorporate to each other to achieve the ...
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Purpose: In resource allocation and target setting problems, a central planner decision making from a managerial point of view has a pivotal role, especially in presence of undesirable outputs such as greenhouse gas emissions. In these situations, firms have to incorporate to each other to achieve the goals of the central planner. The existing DEA-based resource allocation models have not considered the influence of managerial effort and technology innovation. In this study, we will use the managerial disposability assumption to reflect the central planner managerial achievement and technology novelty perspective in the process of resource allocation and target setting.Methodology: Using a managerial disposability assumption in this paper offers a solution to a correct and acceptable resource allocation and target setting along with improving the performance of units. To analyze the method presented in this paper, the data of 29 famous international airlines representing the global aviation industry have been selected and studied.Findings: The results of this study show that in this model, decision-making units use managerial disposability assumption in the regulation of undesirable outputs based on the perspective of cooperation strategies to improve their environmental performance. In addition, in this approach increasing the inputs, fixing the amount of the desirable outputs, reducing the amount of undesirable outputs will be allowed. This model ensures that the adjusted decision-making units in the next period, will improve their efficiency after resource allocation and target setting, as well as improving the overall efficiency is observed in the results obtained by this method.Originality/Value: The paper presents a new approach of resource allocation and target setting based on data envelopment analysis which considers the impact of managerial effort and technology innovation on resource allocation and target setting problems.
Data Envelopment Analyses
Ahmad Reza Tahanian; Hasan Haleh; Farhad Etebari; Behnam Vahdani
Abstract
Purpose: The current study aims to provide a framework for evaluating the large projects based on the sustainability dimensions and with agility approach using data envelopment analysis.Methodology: To this end, sustainability indicators, agility indices in project management and project management critical ...
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Purpose: The current study aims to provide a framework for evaluating the large projects based on the sustainability dimensions and with agility approach using data envelopment analysis.Methodology: To this end, sustainability indicators, agility indices in project management and project management critical success factors are identified. By calculating the large projects efficiency numbers in each of attitudes include financial, social and environmental, three dimensions of sustainability and by drawing a regional graph based on the projects’ efficiency numbers in both attitudes of agiliy and project management critical success factors, the project performance is studied in both attitudes. Findings: Graphs and efficiency results in sustainability attutudes show that among 27 projects, just three projects are efficient in all three attitudes. In addidtion, to deliver product/service in the shortest time is the meaning of delivering value to the customer with extending the agility in project management. Also, to protect the resources for the next generation, project manager can dedicate the financial and social resources in order to control the environmental impacts of the projects in parallel with the sustainable development principles which which can be translated to be responding efficiently and effectively to the customers while meeting the requirements of the sustainable development. Originality/Value: The project as a temprory organization should be managed in such a way that while adapting to the changes and being agile in responsiveness, it also keeps the time range, cost and qulity for delivering the created product/service. Agility has been proposed as an approach to gain and keep the competitiveness in a changing and unpredictable environment and it focuses on meeting customers needs while sustainability attitude does focus on the reduction of the udesireable affects of the meeting customers demands. To integrate these two concepts in the field of project management leads to the efficiency and success of the project, comprehensively.
Data Envelopment Analyses
Rezvan Shaban; Bahman Banimahd; Farhad Hosseinzadeh Lotfi; Hashem Nikoumaram
Abstract
Data envelopment analysis is a suitable and useful technique for measuring and evaluating the efficiency of decision-making units. This technique is also an effective tool in evaluating the efficiency of units in auditing. Therefore, the purpose of this paper is to evaluate the efficiency of audit firms ...
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Data envelopment analysis is a suitable and useful technique for measuring and evaluating the efficiency of decision-making units. This technique is also an effective tool in evaluating the efficiency of units in auditing. Therefore, the purpose of this paper is to evaluate the efficiency of audit firms in terms of audit quality by using data envelopment analysis. Theoretical foundations and data of this study are based on library studies of the pharmaceutical industry of companies listed in the Tehran Stock Exchange. In this study, the output variable is audit quality and input variables include the number of partners of auditing firms, audit fees and auditing hours. The results, using the cross-functional method of data envelopment analysis, show that Behmand, Azmoodeh Karan and Arvin Argham Pars have the first to third ranks in terms of efficiency. Evidence from this study confirms that data envelopment analysis can be used as an appropriate method for analyzing the efficiency of audit firms in in order to assess the quality of auditors' work to support investors by financial analysts and capital market policymakers.
Data Envelopment Analyses
Hossein Azizi
Abstract
Research has revealed that Data Envelopment Analysis (DEA) is an excellent method of data-based performance analysis for comparing decision-making units with multiple inputs and outputs. Selecting inputs and outputs (performance measures) in DEA is a delicate task. In principle, including ...
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Research has revealed that Data Envelopment Analysis (DEA) is an excellent method of data-based performance analysis for comparing decision-making units with multiple inputs and outputs. Selecting inputs and outputs (performance measures) in DEA is a delicate task. In principle, including a large number of inputs and outputs is a positive advantage. However, the inclusion of multiple inputs and outputs might translate into a great deal more of additional data being included, and this may lead to some decision-making units being considered and designated as efficient simply because of their high performance in relation to a number of redundant and useless variables. Elsewhere, in some situations, some performance measures can play both an input and output role. These performance measures are called flexible measures or dual-role factors. Even though models have been developed for working with such dual-role factors, this paper proposes performance appraisal from both an optimistic and pessimistic perspective for selecting a third-party reverse logistics provider in the presence of multiple dual-role factors. A numerical example illustrates the application of the proposed approach.
Data Envelopment Analyses
Samira Maleki; Monavvar Karbalaei Alilou
Abstract
In recent literature, many studies have been performed on DEA performance evaluation of systems with two-stage network structure. One of the topics of interest to researchers is the study of the progress or regress of production over separate time periods in the two-stage network structure. The Luenberger ...
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In recent literature, many studies have been performed on DEA performance evaluation of systems with two-stage network structure. One of the topics of interest to researchers is the study of the progress or regress of production over separate time periods in the two-stage network structure. The Luenberger productivity index is one of the techniques introduced in this field. However, the calculation of output or progress in the two-step network in the presence of undesirable intermediate products and uncontrollable input data has received less attention. The main purpose of this paper is to investigate the impact of the presence of undesirable intermediate products and uncontrollable input data in evaluating the performance of two-stage series-structured network systems when discussing the progress or regress of production systems during different periods of activity. For this purpose, in this paper, we introduce a new directional distance function and propose a method to solve this model that is not problematic in the adjacent time periods. Then, we present a three-stage algorithm to calculate the Luenberger productivity index in a two-stage network with the presence of these data. Finally, with an example, we show the applicability of the proposed algorithm.
stochastic/Probabilistic/fuzzy/dynamic modeling
Alireza Hajihosseini; Ali Payan; Ali Salari
Abstract
One of the most important tasks of an organization manager is to evaluate the performance of the units within the organization because only the performance evaluation can inform the manager about the extent to which the organization has stepped toward the goals established to achieve it so that the manager ...
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One of the most important tasks of an organization manager is to evaluate the performance of the units within the organization because only the performance evaluation can inform the manager about the extent to which the organization has stepped toward the goals established to achieve it so that the manager can identify weaknesses, and poor performance of his organization take corrective action and improve the performance of his organization. In this regard, this study has evaluated accurately and inaccurately the relative performance of 11th-grade nongovernmental schools in Sistan and Baluchestan province. There are various methods for assessing the performance of organizations. One of the most important of these methods is data envelopment analysis technique which by comparing the efficiency of organization units with each other separates efficient units from inefficient units. Selection of inputs and outputs in this study was done according to similar research and interviews with experts. In this study, the relative efficiency of 55 of 11th grade nongovernmental Schools in Sistan and Baluchestan province was calculated by using data envelopment analysis for the academic year 1395-1396 and the efficient and inefficient units were identified, then the performance of these schools is presented by a fuzzy interval based on the technical efficiency and the subjective efficiency and finally ranked.
Data Envelopment Analyses
Reza Maddahi; Hamidreza Yazdani
Abstract
Data Envelopment Analysis (DEA) is a technique for evaluating homogeneous decision-making units. In this method, the efficiency score for each unit is obtained by comparing the performance of each Decision-Making Unit (DMU) with the performance of the other units. This performance score can be used as ...
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Data Envelopment Analysis (DEA) is a technique for evaluating homogeneous decision-making units. In this method, the efficiency score for each unit is obtained by comparing the performance of each Decision-Making Unit (DMU) with the performance of the other units. This performance score can be used as a criterion for ranking units. In many cases, a significant number of units are efficient, and therefore, the efficiency of the classic DEA models cannot be a good criterion for accurate ranking of DMUs. In this study, a method for ranking DMUs using their efficiency is presented in several time periods, so that three types of production possibility sets are introduced. In the first type, for each time period, an independent production possibility set is defined, in the second type, a combination production possibility set is used for all time periods, and in the third type, a community production possibility set is created, which considers all time periods. Then, corresponding to each type, one efficiency number is obtained for each DMU. Therefore, the three values of efficiency resulting from the three methods are combined using the Shannon entropy method and define a general performance criterion for each unit. This criterion is ultimately considered as the main indicator for ranking units.