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Recent Articles
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Open Access Article
1 - A technique for identifying congestion in Data Envelopment Analysis
Amin Jabbari Farhad Hosseinzadeh Lotfi Mohsen Rostamy MalkhalifehIssue 3 , Vol. 11 , Summer 2023Data Envelopment Analysis (DEA) is a non-parametric mathematical programming method used to assess performance and measure the efficiency of Decision-making Units (DMUs) that operate with multiple concurrent inputs and outputs. The performance of these units is influen MoreData Envelopment Analysis (DEA) is a non-parametric mathematical programming method used to assess performance and measure the efficiency of Decision-making Units (DMUs) that operate with multiple concurrent inputs and outputs. The performance of these units is influenced by the utilization of input resources. While an increase in input utilization typically leads to higher production levels, there are scenarios where increased input usage results in decreased outputs. This phenomenon is termed congestion. Given that alleviating congestion can reduce costs and enhance production, it holds significant importance in economics. This paper introduces a method for identifying congestion based on a defined modeling framework. A DMU is considered congested when reducing inputs in at least one component leads to increased outputs in at least one component, and increasing inputs in at least one component can be achieved by reducing outputs in at least one component, without improvement in other indicators. The paper explores congestion in DMUs with both increasing and decreasing inputs. Manuscript profile -
Open Access Article
2 - Low interest loans in micro businesses and its impact on social entrepreneurship using data envelopment analysis
Sajjad Tavakoli Mahnaz Ahadzadeh Namin Navid KhabiriIssue 3 , Vol. 11 , Summer 2023Evaluating the efficiency of low-fee loans in small businesses and comparing them with each other can be a support for strategic planning. Banks and escape from economic inflation. One of the methods of measuring efficiency is data coverage analysis. In this research, t MoreEvaluating the efficiency of low-fee loans in small businesses and comparing them with each other can be a support for strategic planning. Banks and escape from economic inflation. One of the methods of measuring efficiency is data coverage analysis. In this research, the indicators affecting the performance of low-fee loans have been researched and identified, and then the researched samples have been estimated. In three parts, the evaluation of the public institution of Resalat (Qarz Al-Hasna Resalat Bank) which is active in paying microloans has been done and in order to measure the impact of microloans on business creation, it has been compared with 9 other banks. In fact, the purpose of this research is to measure the efficiency of micro-bank facilities and its impact on the creation of micro- and home-based businesses and to identify indicators that affect micro-businesses. At the end, the steps of the research are described with a practical example Manuscript profile -
Open Access Article
3 - Data Envelopment Analysis-Discriminant Analysis by imprecise data for more than two groups: apply to the pharmaceutical stock companies
Sarah Navidi Mohsen Rostamy-MalkhalifehIssue 3 , Vol. 11 , Summer 2023One of the interesting subjects that amuse the mind of researchers is surmising the correct classification of a new sample by using available data. Data Envelopment Analysis (DEA) and Discriminant Analysis (DA) can classify data by each one alone. DEA classifies as effi MoreOne of the interesting subjects that amuse the mind of researchers is surmising the correct classification of a new sample by using available data. Data Envelopment Analysis (DEA) and Discriminant Analysis (DA) can classify data by each one alone. DEA classifies as efficient and inefficient groups and DA classify by historical data. Merge these two methods is a powerful tool for classifying the data. Since, in the real world, in many cases we do not have the exact data, so we use imprecise data (e.g. fuzzy and interval data) in these cases. So, in this paper, we represent our new DEA-DA method by using Mixed-Integer Nonlinear Programming (MINLP) to classify with imprecise data to more than two groups. Then we represent an empirical example of our purpose method on the Iranian pharmaceutical stock companies' data. In our research, we divided pharmaceutical stock companies into four groups with imprecise data (fuzzy and interval data). Since, most of the classical DA models used for two groups, the advantage of the proposed model is beheld. The result shows that the model can predict and classify more than two groups (as many as we want) with imprecise data so correct. Manuscript profile -
Open Access Article
4 - Fair distribution of weights for ranking decision making units using cross-efficiency method in DEA
Sarvar Kassaei Alireza Amirteimoori Bijan Rahmani ParchikolaeiIssue 3 , Vol. 11 , Summer 2023Cross-efficiency is a frequently used method for ranking decision-making units in Data Envelopment Analysis (DEA). A fundamental weakness of this method which has been quite problematic is the presence of multiple optimal weights along with selection of zero values by m MoreCross-efficiency is a frequently used method for ranking decision-making units in Data Envelopment Analysis (DEA). A fundamental weakness of this method which has been quite problematic is the presence of multiple optimal weights along with selection of zero values by many of these multiple weights in calculating cross-efficiency. In the current paper it is tried to provide a method which through utilizing fair distribution of weights resolve the mentioned problems and in this way give more validity to the cross-efficiency method in raking decision-making units. Manuscript profile
Most Viewed Articles
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Open Access Article
1 - Analysis of the performance of symbols of cement companies in the Tehran Stock Exchange, using data envelopment analysis based on integer indices
Mohhamad Reza ShahriariIssue 1 , Vol. 9 , Winter 2021Considering the important role of the construction industry in the form of one of the expandable industries for economic growth, increasing GDP and job creation, as well as the great relationship between construction and its required tools, such as machinery, materials MoreConsidering the important role of the construction industry in the form of one of the expandable industries for economic growth, increasing GDP and job creation, as well as the great relationship between construction and its required tools, such as machinery, materials Construction, tools, etc., scientific study of each of these sectors, provides the possibility of better development in the construction industry, the results of which can suggest solutions to boost national production. Since cement as an underlying commodity is a widely used material in construction and concreting, and investing in cement companies can play an important role in improving their process, so in this The paper examines the efficiency of symbols of cement companies in the Tehran Stock Exchange using data envelopment analysis. Due to the fact that some of the indicators extracted from the stock market are usually integers, in this study, a data envelopment analysis model in mixed integer programming class (MILP) has been used, which is capable of processing continuous data. And has the integer together. The results presented in this article can be effective on managers' decisions to increase capital or on how to invest in cement companies. Manuscript profile -
Open Access Article
2 - Enterprise Resource Planning Selection based on a Preference Voting and Data Envelopment Analysis
Mohhamad Reza ShahriariIssue 3 , Vol. 9 , Summer 2021Today, there are several reasons for the necessity of using an enterprise resource planning system (ERP) more than ever. In the competitive environment of companies, components such as flexibility, quality, management of the relationship with customers, and lower cost s MoreToday, there are several reasons for the necessity of using an enterprise resource planning system (ERP) more than ever. In the competitive environment of companies, components such as flexibility, quality, management of the relationship with customers, and lower cost show this necessity more colorfully. The necessity of integration in the processes of an organization and the need for ERP as one of the important and innovative decision-making and management tools increases the competitiveness of the organization. Since the application of ERP in the world has had many successes and failures, therefore, the efficient selection of one of the companies providing ERP can play a decisive role in the survival of organizations. In this article, considering standard KPIs, a method for selecting an ERP service provider based on Data Envelopment Analysis and Preference Voting is proposed. Manuscript profile -
Open Access Article
3 - Assessment of Cost Effectiveness of a Firm Using Multiple Cost Oriented DEA and Validation with MPSS based DEA
Subhadip SarkarIssue 1 , Vol. 3 , Winter 2015Data Envelopment Analysis (DEA) is a nonparametric tool for discriminating the best performers from a number of homogenous Decision Making Units (DMU). Cost oriented DEA models identify those best DMUs which run cost efficient process. This paper validates the outcome d MoreData Envelopment Analysis (DEA) is a nonparametric tool for discriminating the best performers from a number of homogenous Decision Making Units (DMU). Cost oriented DEA models identify those best DMUs which run cost efficient process. This paper validates the outcome derived from the Ideal Frontier (mentioned in Sarkar. S (2014)) derived from non-central Principal Component Analysis and a slack based optimization model to identify the cost efficient DMUs. Instead of offering real cost of each resource, the proposed model minimizes the projection of inputs along the direction of first Eigenvector of specific covariance matrix from each allocated outputs. These essential directions vectors represent various "combined consumption (cost)" for the production of outputs. A Multi-Objective Fuzzy Goal Programming model is applied here to solve this multi-objective problem. Superiority is judged on the basis of higher value of a cost oriented performance ratio. A case study of six schools is incorporated here to identify the superior cost efficient school and also to visualize gaps in their performances. Manuscript profile -
Open Access Article
4 - Presenting an efficiency analysis model of posts in social networks of digital marketing (Case Study: Facebook)
Mohhamad Reza ShahriariIssue 1 , Vol. 10 , Winter 2022Today, there are several reasons for the necessity of using an enterprise resource planning system (ERP) more than ever. In the competitive environment of companies, components such as flexibility, quality, management of relationships with customers, and lower cost show MoreToday, there are several reasons for the necessity of using an enterprise resource planning system (ERP) more than ever. In the competitive environment of companies, components such as flexibility, quality, management of relationships with customers, and lower cost show this necessity more colorfully. The necessity of integration in the processes of an organization and the need for ERP as one of the important and innovative decision-making and management tools increases the competitiveness of the organization. Since the application of ERP in the world has had many successes and failures, therefore, the efficient selection of one of the companies providing ERP can play a decisive role in the survival of organizations. In this article, considering standard KPIs, a method for selecting an ERP service provider based on Data Envelopment Analysis and Preference Voting is proposed. Manuscript profile -
Open Access Article
5 - Robust optimization for identifying the most efficient decision making unit in data envelopment analysis
Reza Akhlaghi Mohsen Rostamy-Malkhalifeh Alireza Amirteimoori Sohrab KordrostamiIssue 2 , Vol. 11 , Spring 2023Due to the nonlinear and discrete nature of BCC (Banker, Charnes, and Cooper, [11]) models for determining the most efficient decision-making unit, it is practically impossible to evaluate the models' dual and, consequently, optimistic case. Thus, in this paper, the lin MoreDue to the nonlinear and discrete nature of BCC (Banker, Charnes, and Cooper, [11]) models for determining the most efficient decision-making unit, it is practically impossible to evaluate the models' dual and, consequently, optimistic case. Thus, in this paper, the linear model with linear constraints proposed by Akhlaghi et al. [2] is used to investigate the dual equality of the model's robust problem and the optimistic case of the new model's dual under VRS uncertainty. The model proposed in this paper is novel in comparison to previous models because it solves the most efficient decision-making unit only once, without relying on uncertain data to determine its rank. The paper demonstrates how the proposed robust model can also ascertain the most efficient decision-making unit when uncertainty exists. Furthermore, the dual issues raised by robust counterparts in the new linear programming (LP) model are addressed to identify the most efficient decision-making unit. The robust counterpart is demonstrated to be equivalent to a linear program under interval uncertainty, and the dual of the robust counterpart is shown to be equal to the optimistic counterpart of the dual problem. Consequently, this study aims to demonstrate that the dual problem is equivalent to a decision-maker operating under optimal data, whereas the primal robust problem is equivalent to a decision-maker operating through the worst-case possible data scenario. Manuscript profile -
Open Access Article
6 - Target setting in the process of merging and restructuring of decision-making units using multiple objective linear programming
Javad GeramiIssue 3 , Vol. 7 , Summer 2019This paper presents a novel approach to achieving the goals of data envelopment analysis in the process of reconstruction and integration of decision-making units by using multiple objective linear programming. In this regard, first, we review inverse data envelopment a MoreThis paper presents a novel approach to achieving the goals of data envelopment analysis in the process of reconstruction and integration of decision-making units by using multiple objective linear programming. In this regard, first, we review inverse data envelopment analysis models for data reconstruction and integration. We present a model with multi-objective linear programming structure in inverse data envelopment analysis. The superiority of the model to prioritize inputs and outputs in the input and output data integration process. Finally, we used of bank data for showing the validity of proposed approach and we proposed results. Manuscript profile -
Open Access Article
7 - Data Envelopment Analysis Models In The Presence Of Ratio Data and Non-Discretionary Factors
Azam AhmadzadehIssue 4 , Vol. 4 , Autumn 2016The traditional data envelopment analysis (DEA) models for the observations containing ratio data as input or output may result incorrect efficiency scores. To overcome this shortcoming, a set of modified DEA models has been presented in this paper by taking into accoun MoreThe traditional data envelopment analysis (DEA) models for the observations containing ratio data as input or output may result incorrect efficiency scores. To overcome this shortcoming, a set of modified DEA models has been presented in this paper by taking into account the correct convexity of decision making units (DMUs) when a ratio variable is included in the assessment model. Manuscript profile -
Open Access Article
8 - Fair distribution of weights for ranking decision making units using cross-efficiency method in DEA
Sarvar Kassaei Alireza Amirteimoori Bijan Rahmani ParchikolaeiIssue 3 , Vol. 11 , Summer 2023Cross-efficiency is a frequently used method for ranking decision-making units in Data Envelopment Analysis (DEA). A fundamental weakness of this method which has been quite problematic is the presence of multiple optimal weights along with selection of zero values by m MoreCross-efficiency is a frequently used method for ranking decision-making units in Data Envelopment Analysis (DEA). A fundamental weakness of this method which has been quite problematic is the presence of multiple optimal weights along with selection of zero values by many of these multiple weights in calculating cross-efficiency. In the current paper it is tried to provide a method which through utilizing fair distribution of weights resolve the mentioned problems and in this way give more validity to the cross-efficiency method in raking decision-making units. Manuscript profile -
Open Access Article
9 - Data Envelopment Analysis-Discriminant Analysis by imprecise data for more than two groups: apply to the pharmaceutical stock companies
Sarah Navidi Mohsen Rostamy-MalkhalifehIssue 3 , Vol. 11 , Summer 2023One of the interesting subjects that amuse the mind of researchers is surmising the correct classification of a new sample by using available data. Data Envelopment Analysis (DEA) and Discriminant Analysis (DA) can classify data by each one alone. DEA classifies as effi MoreOne of the interesting subjects that amuse the mind of researchers is surmising the correct classification of a new sample by using available data. Data Envelopment Analysis (DEA) and Discriminant Analysis (DA) can classify data by each one alone. DEA classifies as efficient and inefficient groups and DA classify by historical data. Merge these two methods is a powerful tool for classifying the data. Since, in the real world, in many cases we do not have the exact data, so we use imprecise data (e.g. fuzzy and interval data) in these cases. So, in this paper, we represent our new DEA-DA method by using Mixed-Integer Nonlinear Programming (MINLP) to classify with imprecise data to more than two groups. Then we represent an empirical example of our purpose method on the Iranian pharmaceutical stock companies' data. In our research, we divided pharmaceutical stock companies into four groups with imprecise data (fuzzy and interval data). Since, most of the classical DA models used for two groups, the advantage of the proposed model is beheld. The result shows that the model can predict and classify more than two groups (as many as we want) with imprecise data so correct. Manuscript profile -
Open Access Article
10 - Effect of Relocation and Rotation on Radial Efficiency Scores for a Partially Negative Data Problem
S .SarkarIssue 4 , Vol. 2 , Autumn 2014Negative data handling has gained a remarkable importance in the literature of Data Envelopment Analysis (DEA) to address many real life problems. Various erstwhile applications, in this arena, referred relocation of the origin to a superior (RDM) or to an inferior (Tra MoreNegative data handling has gained a remarkable importance in the literature of Data Envelopment Analysis (DEA) to address many real life problems. Various erstwhile applications, in this arena, referred relocation of the origin to a superior (RDM) or to an inferior (Translated Input Oriented BCC) neighboring point. In this paper, the conditions for Rotation Invariance of various Data Envelopment Analysis models are discussed. Specifically, in presence of partially negative data, a rotation using the Cone Ratio model, beyond a threshold value of the oblique index does not alter the efficient frontier. So, a solution can be obtained without relocating the origin. In this context, two models, termed as Input Oriented BCC model with Relocated Origin (IOBCC-RO) and Input oriented BCC model with Rotated Axis (IOBCC-RA), are applied on a case of "the notional effluent processing system" (from Sharp et al (2006)) to observe their impact on the radial efficiency scores. Manuscript profile
