2017
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4
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An extended of multiple criteria data envelopment analysis models for ratio data
2
2
One of the problems of the data envelopment analysis traditional models in the multiple form that is the weights corresponding to certain inputs and outputs are considered zero in the calculation of efficiency and this means that not all input and output components are utilized for the evaluation of efficiency, as some are ignored. The above issue causes the efficiency score of the under evaluation unit not to be calculated correctly. One of the ways to deal with the pseudoinefficiency is to use data envelopment analysis models with multicriteria structure. In this regard, we first investigate the models of data envelopment analysis with multicriteria structure and further, with regard to the ability of the ratiobased data envelopment analysis models, we develop data envelopment analysis models with a multicriteria structure for ratio data and the feasibility and the bounded condition of the above models and their efficiency intervals are described. By presenting a numerical example, we compare the efficiency scores obtained from the models presented with the previous models and we show that the proposed models can be used to deal with the pseudoinefficiency and efficiency underestimation. Finally, we present the results.
1

1361
1386


Javad
Gerami
Department of mathematics, Shiraz Branch, Islamic Azad University, Shiraz, Iran
Department of mathematics, Shiraz Branch,
Iran
geramijavad@gmail.com
Multicriteria data envelopment analysis
Discrimination power
Weight dispersion
DEAR
Pseudoinefficiency
Efficiency Evaluation of Football Teams in English Premier League: Application of Data Envelopment Analysis
2
2
In this paper, the financial efficiency of football clubs in English Premier League during 201617 season is determined. From a methodological perspective, we use Data Envelopment Analysis (DEA), a deterministic nonparametric frontier method. In particular, variable returns to scale and slack based measure are employed to assess whether teams are spending more resources than they need to achieve efficiency. DEA allows for inclusion of multiple inputs and outputs in assessing the efficiency and provides benchmarks for inefficient clubs. The input parameters selected are total expenses which include the salaries of players, coaches, managers and supporting staff. The output variables being revenue generated, profit gained and points scored at the end of the season.
1

1387
1398


Zahoor
Ul Haq Bhat
Department of Physical Education &amp; Sports
Pondicherry University605014
Department of Physical Education &amp;
Iran
zahoorpu@yahoo.com


D
Sultana
Department of Physical Education & Sports
Pondicherry University605014
Department of Physical Education &
Iran
d_sbegum@yahoo.co.in


Showkat
Bashir
Department of Physical Education & Sports
Pondicherry University605014
Department of Physical Education &
Iran
showkatbashirlone@gmail.com
Data Envelopment Analysis
Slack Based Measure
Football
Efficiency
Estimating Most Productive Scale Size of the provinces of Iran in the Employment sector using Interval data in Imprecise Data Envelopment Analysis(IDEA)
2
2
Unemployment is one of the most important economic problems in Iran, so that many of its managers plan to increase employment rates. Increasing the employment rate needs to increase economic productivity which DEA is one of the most appropriate evaluation methods for estimating the productivity of similar organizations. Employment in the amount of data input and output can be just interval. In this study by solving two models, using one of which the upper bound for efficiency and using the other, the lower bound for decision making units efficiency is acquired, we provide a new model for Most productive scale size with interval data. The main purpose of this study is to determine the productivity of Iran and sensitive indicators to provide a fundamental solution to exit from unemployment. The economic sector managers can do more exact planning for economic growth.
1

1399
1410


Mohammad
Khodabakhshi
Department of Mathematics, Faculty of Science, shahied Beheshti University,Tehran,Iran
Department of Mathematics, Faculty of Science,
Iran
moh_khodabakhshi@sbu.ac.ir


saeed
papi
Department of Mathematics, Faculty of Science, Lorestan University, Khorramabad,Iran
Department of Mathematics, Faculty of Science,
Iran
am_1380@yahoo.com


reza
fallahnejad
Department of mathematics, Khorramabad branch, Islamic Azad university, Iran
Department of mathematics, Khorramabad branch,
Iran
r.fallahnejad@gmail.com


Masoume
Yazdanpanah Maryaki
Department of Mathematics, Lahijan
Branch, Islamic Azad University, Lahijan, Iran.
Department of Mathematics, Lahijan
Branch,
Iran
m_yazdan_64@yahoo.com
: Employment
Data Envelopment Analysis
Efficiency
Interval data
Most productive scale size (MPSS)
An algorithm for the anchor points of the PPS of the CCR model
2
2
Anchor DMUs are a new class in the general classification of Decision Making Units (DMUs) in Data Envelopment Analysis (DEA). An anchor DMU in DEA is an extremeefficient DMU that defines the transition from the efficient frontier to the freedisposability part of the boundary of the Production Possibility Set (PPS). In this paper, the anchor points of the PPS of the CCR model are investigated. A basic definition of anchor point based on the supporting hyperplanes of the PPS of CCR model is provided. Then, by using a variant of superefficiency models, the necessary and sufficient conditions for a DMU to be an anchor DMU are provided via some theorems. To illustrate the applicability of the proposed model, some numerical examples are finally given.
1

1411
1424


Dariush
Akbarian
Department of Mathematics, Arak Branch, Islamic Azad University, Arak, Iran.
Department of Mathematics, Arak Branch, Islamic
Iran
d_akbarian@yahoo.com
Data envelopment analysis (DEA)
Production Possibility Set (PPS), Efficient and inefficient frontier
Entropy based Malmquist Productivity Index in Data Envelopment Analysis
2
2
Malmquist Productivity Index (MPI) is one of the most famous indices, which is used for estimating the productivity change of a Decision Making Unit (DMU) during the time. Virtually any empirical study that uses MPI, reports average of the productivity indices they estimate to represent the overall tendency in productivity changes. In such a case, productivity indices of a DMU are considered with equal value. In this paper, we propose using the entropy of productivity indices of all DMUs at a specific part of time as the weight of indices of that in aggregating the indices during the under study time section. Then, we use the proposed method for an empirical study of 18 Iranian companies manufacturing automobiles and automobile parts, which have been accepted in Tehran Stock Exchange.
1

1425
1434


reza
fallahnejad
Departeman of math,Islamic Azad university KhorramAbad , Iran
Departeman of math,Islamic Azad university
Iran
r.fallahnejad@gmail.com
Data Envelopment Analysis
Entropy
Malmquist Productivity Index
Finding Common Weights in TwoStage Network DEA
2
2
In data envelopment analysis (DEA), multiplier and envelopment CCR models evaluate the decisionmaking units (DMUs) under optimal conditions. Therefore, the best prices are allocated to the inputs and outputs. Thus, if a given DMU was not efficient under optimal conditions, it would not be considered efficient by any other models. In the current study, using common weights in DEA, a number of decisionmaking units are evaluated under the same conditions, and a number of twostage network DEA models are proposed within the framework of multiobjective linear programming (MOLP) for finding common weights. Furthermore, using the infinity norm, common weight sets are determined in twostage network models with MOLP structures.
1

1435
1451


Mohammad Reza
Mozaffari
Department of Mathematics, Shiraz Branch, Islamic Azad University, Shiraz, Iran
Department of Mathematics, Shiraz Branch,
Iran
mozaffari854@yahoo.com


mehrnoosh
khazraei
Department of mathematic, Shiraz branch, Islamic Azad university, Shiraz, Iran.
Department of mathematic, Shiraz branch,
Iran
mehrnooshkhazraei@gmail.com
Data Envelopment Analysis
Common weights
Ranking
Twostage Network
Decisionmaking unit