Number 1 Volume 2

Open Access Article

1 - Presenting a Hybrid Approach based on Two-stage Data Envelopment Analysis to Evaluating Organization Productivity
E. Najafi M. Fallah S. Hamed

Measuring the performance of a production system has been an important task in management for purposes of control, planning, etc. Lord Kelvin said :“When you can measure what you are speaking about, and express it in numbers, you know something about it; but when More

Measuring the performance of a production system has been an important task in management for purposes of control, planning, etc. Lord Kelvin said :“When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind.” Hence, management knowledge is measurable science and if we can’t measure each subject we can’t control it so management is impossible. We know, the major criteria performance is productivity and we should be able to measure it. Data Envelopment Analysis (DEA), as an evaluation method, can estimate the relative efficiency of organizations systematically. The efficiency of an organization can be benchmarked by using DEA. DEA presents a model for evaluating the performance of a set of comparable decision making units (DMUs). In this paper we developed a new model for calculating productivity with Two-stage data envelopment analysis. Manuscript profile

Open Access Article

2 - Prioritizing Potential Risks based on Failure Mode and Effects Analysis Using Data Envelopment Analysis: a case study
B. Nasr Esfahani H. Shirouyehzad F. Mokhatab Rafiei

The need to establish power plants to supply the required electricity of the country has been rising dueto increasing demand levels as well as the lack of governmental resources. Furthermore, the availabletraditional attitude in performing and conducting power plant pro More

The need to establish power plants to supply the required electricity of the country has been rising dueto increasing demand levels as well as the lack of governmental resources. Furthermore, the availabletraditional attitude in performing and conducting power plant projects has made government seek amodern attitude. This paper tries to use the topics that have been employed in automotive industry of thecompany for many years to detect and analyse failure reasons as well as the solutions that are suggestedto prevent and improve them. The present study has used Failure Mode & Effects Analysis along withData Envelopment Analysis to evaluate 17 failure modes of South Esfahan Power Plant. Severity,Occurrence and Detection are 3 failure factors considered in this study. Failure mode dealing with Scalingon rotor and diaphragms blades has the highest importance with the highest Risk Priority Number,Severity and its first grade. Manuscript profile

Open Access Article

3 - Malmquist Productivity Index for Multi Time Periods
Y. Jafari

The performance of a decision making unit (DMU) can be evaluated in either across-sectional or a time-series manner, and data envelopment analysis (DEA) is a useful method for both types of evaluation. The Malmquist productivity index (MPI) evaluates the change in effic More

The performance of a decision making unit (DMU) can be evaluated in either across-sectional or a time-series manner, and data envelopment analysis (DEA) is a useful method for both types of evaluation. The Malmquist productivity index (MPI) evaluates the change in efficiency of a DMU between two time periods. It is defined as the product of the Catch-up and Frontier-shift terms. In this paper, we study the Malmquist productivity index of a DMU between several time periods. Manuscript profile

Open Access Article

4 - A Russell Measure for Modeling Environmental Performance
H. Zare Haghighi M. Rostamy-Malkhalifeh

Data Envelopment Analysis (DEA) has been long employed as a popular methodology to evaluatethe performance of various production activities with multiple inputs and outputs. However, animportant issue is that the production process in the real world inevitably generates More

Data Envelopment Analysis (DEA) has been long employed as a popular methodology to evaluatethe performance of various production activities with multiple inputs and outputs. However, animportant issue is that the production process in the real world inevitably generates undesirableoutputs (like wastes and pollutants) along with desirable outputs. Therefore, the undesirable outputsshould be included into the environmental performance evaluation. This study surveys the twotechnologies which is available in the DEA literature for modelling environmental performance underweak disposability assumption of good and bad outputs. Then, it attempts to present a Russellmeasure that incorporates both desirable and undesirable outputs. To illustrate the use of the proposedmethod, an empirical application corresponding to 31 administrative regions of China is provided andinterpreted. Manuscript profile

Open Access Article

5 - The Calculation of Unit's Efficiency by Using the Interval
B. Babazadeh E. Najafi M. AhadzadehNamin Y. jafari Z. Ebrahimi

Data Envelopment Analysis )DEA( is a technique for measuring the efficiency of decision makingunits. In all models of the DEA, for each unit under assessment, the numerical efficiency which maybe less than or equal to one is obtained. Given the possible large number of More

Data Envelopment Analysis )DEA( is a technique for measuring the efficiency of decision makingunits. In all models of the DEA, for each unit under assessment, the numerical efficiency which maybe less than or equal to one is obtained. Given the possible large number of efficiency units forevaluating units, we use various methods of ranking. span style="font-family: Cambria Math;font-size:8pt;color:rgb(0,0,0);font-style:normal;font-variant:normal L1norm is one of the methods of ranking. Thismethod has been used for categorical data. In this paper, we assume data as interval and introducespan style="font-family: Cambria Math;font-size:8pt;color:rgb(0,0,0);font-style:normal;font-variant:normal L1norm andrun it on a single example. Manuscript profile

Open Access Article

6 - The Efficiency of MSBM Model with Imprecise Data (Interval)
F. seyed Esmaeili

Data Envelopment Analysis (DEA) is a mathematical programming-based approach for evaluates the relative efficiency of a set of DMUs (Decision Making Units). The relative efficiency of a DMU is the result of comparing the inputs and outputs of the DMU and those of other More

Data Envelopment Analysis (DEA) is a mathematical programming-based approach for evaluates the relative efficiency of a set of DMUs (Decision Making Units). The relative efficiency of a DMU is the result of comparing the inputs and outputs of the DMU and those of other DMUs in the PPS (Production Possibility Set). Also, in Data Envelopment Analysis various models have been developed in order to evaluate the performance of decision-making units with negative data. The Modified Slack Based Measure (MSBM) model is from collective models family. This modified model is based on slack-based measure (SBM). Also the early models of data envelope analysis considered inputs and outputs as precise data. However, in studies about the data envelope analysis, some methods presented for applying imprecise data. Based on this, data envelope analysis models with interval data have been developed. In this paper, the MSBM model is investigated in presence of interval negative data, and then the efficiency of the model with imprecise data (interval) is evaluated. The efficiency of ten decision-making units is evaluated. Manuscript profile

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