ORIGINAL_ARTICLE
The Most Revenue Efficiency with Price Uncertainty
In this paper, a new revenue efficiency data envelopment analysis (RE-DEA) approach is considered for finding the most revenue efficient unit with price uncertainty in both optimistic and pessimistic perspectives. The optimistic and pessimistic perspectives use efficient frontier and inefficient frontier, respectively. An integrated model is introduced to find decision making units (DMUs) that can be a candidate for most revenue efficient unit, in both optimistic and pessimistic points. Consequently, the revenue efficiency of all DMUs is calculated with by solving one model. Then a mix integer programming (MIP) model is proposed for finding the most revenue efficient DMU with common set of weights. The proposed model ensures that just one unit has been revenue efficiency. To illustrate the applicability of the new approach, the model is utilized for data from 21 medical centers in Taiwan.
http://ijdea.srbiau.ac.ir/article_8100_f3d9498300e0b98e87703299ea5c69f7.pdf
2015-01-17T11:23:20
2020-05-27T11:23:20
575
592
Revenue efficiency
Price Uncertainty
Decision Making Unit
Common set of weights
Samira
Salehpour
true
1
Department of Mathematics, Ardabil Science and Research Branch, Islamic Azad University, Ardabil, Iran.
Department of Mathematics, Ardabil Branch, Islamic Azad University, Ardabil, Iran.
Department of Mathematics, Ardabil Science and Research Branch, Islamic Azad University, Ardabil, Iran.
Department of Mathematics, Ardabil Branch, Islamic Azad University, Ardabil, Iran.
Department of Mathematics, Ardabil Science and Research Branch, Islamic Azad University, Ardabil, Iran.
Department of Mathematics, Ardabil Branch, Islamic Azad University, Ardabil, Iran.
AUTHOR
Nazila
Aghayi
true
2
Department of Mathematics, Ardabil Science and Research Branch, Islamic Azad University, Ardabil, Iran.
Department of Mathematics, Ardabil Branch, Islamic Azad University, Ardabil, Iran.
Department of Mathematics, Ardabil Science and Research Branch, Islamic Azad University, Ardabil, Iran.
Department of Mathematics, Ardabil Branch, Islamic Azad University, Ardabil, Iran.
Department of Mathematics, Ardabil Science and Research Branch, Islamic Azad University, Ardabil, Iran.
Department of Mathematics, Ardabil Branch, Islamic Azad University, Ardabil, Iran.
LEAD_AUTHOR
ORIGINAL_ARTICLE
Assessment of Cost Effectiveness of a Firm Using Multiple Cost Oriented DEA and Validation with MPSS based DEA
Data 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.
http://ijdea.srbiau.ac.ir/article_8101_cefb55a0dee2719df1c9ba5080bd5814.pdf
2015-02-27T11:23:20
2020-05-27T11:23:20
593
607
Data Envelopment Analysis
non-central Principal Component Analysis
Non-Stochastic DEA
Frontier Function
Subhadip
Sarkar
true
1
(a) Department of Management Studies, NIT Durgapur, West Bengal, India
(a) Department of Management Studies, NIT Durgapur, West Bengal, India
(a) Department of Management Studies, NIT Durgapur, West Bengal, India
LEAD_AUTHOR
ORIGINAL_ARTICLE
Capacity utilization in data envelopment analysis with integer data
In the process of production, some of the inputs are fixed and cannot easily be changed, such as work hours of workers and hours of administrative or work, these types of inputs are fixed and others are variables. In this paper, by considering some inputs or outputs which are limited, their amounts must be integrated; this concept for integer data is extended. We show the importance of subject by bringing a real example of 25 branches of a bank.
http://ijdea.srbiau.ac.ir/article_8102_375b128f9e27d95ab6ecb1b3448c6f84.pdf
2015-03-17T11:23:20
2020-05-27T11:23:20
609
616
Data Envelopment Analysis
integer data
Capacity Utilization
Balal
karimi
true
1
(a) Department of Mathematics, Karaj Branch, Islamic Azad University, Karaj, Iran
(a) Department of Mathematics, Karaj Branch, Islamic Azad University, Karaj, Iran
(a) Department of Mathematics, Karaj Branch, Islamic Azad University, Karaj, Iran
AUTHOR
Esmaeil
Khorram
true
2
Department of Mathematics and Computer Science, Amirkabir University of Technology, Hafez Ave.; Tehran, Iran.
Department of Mathematics and Computer Science, Amirkabir University of Technology, Hafez Ave.; Tehran, Iran.
Department of Mathematics and Computer Science, Amirkabir University of Technology, Hafez Ave.; Tehran, Iran.
LEAD_AUTHOR
ORIGINAL_ARTICLE
Efficiency Evaluation and Ranking DMUs in the Presence of Interval Data with Stochastic Bounds
On account of the existence of uncertainty, DEA occasionally faces the situation of imprecise data, especially when a set of DMUs include missing data, ordinal data, interval data, stochastic data, or fuzzy data. Therefore, how to evaluate the efficiency of a set of DMUs in interval environments is a problem worth studying. In this paper, we discussed the new method for evaluation and ranking interval data with stochastic bounds. The approach is exemplified by numerical examples.
http://ijdea.srbiau.ac.ir/article_8103_d000f50e63e539093817219ef69e1678.pdf
2015-01-17T11:23:20
2020-05-27T11:23:20
617
626
Data envelopment analysis (DEA)
Decision making unit (DMU)
Efficiency
Ranking
Interval data
stochastic bounds
Hamid
Sharafi
true
1
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
LEAD_AUTHOR
Mohsen
Rostamy-Malkhalifeh
mohsen_rostamy@yahoo.com
true
2
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
AUTHOR
Alireza
Salehi
true
3
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
AUTHOR
Mohammad
Izadikhah
m-izadikhah@iau-arak.ac.ir
true
4
Department of Mathematics, Islamic Azad University, Arak Branch, Arak, Iran.
Department of Mathematics, Islamic Azad University, Arak Branch, Arak, Iran.
Department of Mathematics, Islamic Azad University, Arak Branch, Arak, Iran.
AUTHOR
ORIGINAL_ARTICLE
Revise Approach to Measuring Congestion Based on the Comparison of Inputs
the method for measuring the congestion of Noura et al. [A.A. Noura, F. Hosseinzadeh Lotfi, G.R. Jahanshahloo, S. Fanati Rashidi, R.P. Barnett, A new method for measuring congestion in data envelopment analysis, Socio-Economic Planning Sciences, 44 (2010) 240-246] ,there is no problem for congestion detection In the case of one input and one output but in higher space is not able to detect congestion of some units. we offer modification of the method of measuring the congestion of Noura et al. The proposed method ability congestion units go up and this method detect all congestion units.
http://ijdea.srbiau.ac.ir/article_8105_3d4f8e3b889f585fa57dd6f3b2610fa0.pdf
2015-02-07T11:23:20
2020-05-27T11:23:20
627
632
Data Envelopment Analysis
Congestion
Efficiency
Decision Making Unit
A.A.
Nouraa
true
1
(a) Faculty Of Mathematics, Sistan and baluchestan University, Danshgah street, Zahedan, IRAN
(a) Faculty Of Mathematics, Sistan and baluchestan University, Danshgah street, Zahedan, IRAN
(a) Faculty Of Mathematics, Sistan and baluchestan University, Danshgah street, Zahedan, IRAN
AUTHOR
E.
Hosseini
true
2
Faculty Of Mathematics, Sistan and baluchestan University, Danshgah street, Zahedan, IRAN
Faculty Of Mathematics, Sistan and baluchestan University, Danshgah street, Zahedan, IRAN
Faculty Of Mathematics, Sistan and baluchestan University, Danshgah street, Zahedan, IRAN
LEAD_AUTHOR
ORIGINAL_ARTICLE
Cross Efficiency Evaluation with Negative Data in Selecting the Best of Portfolio Using OWA Operator Weights
The present study is an attempt toward evaluating the performance of portfolios and asset selectionusing cross-efficiency evaluation. Cross-efficiency evaluation is an effective way of ranking decisionmaking units (DMUs) in data envelopment analysis (DEA). Conventional DEA models assume nonnegativevalues for inputs and outputs. However, we know that unlike return and skewness, varianceis the only variable in the model that takes non-negative values. This paper focuses on the evaluationprocess of the efficiencies in the cross-efficiency matrix with negative data and proposes the use ofordered weighted averaging (OWA) operator weights for cross-efficiency evaluation. The problemconsists of choosing an optimal set of assets in order to minimize the risk and maximize return. Thismethod is illustrated by application in Iranian stock companies and extremely weights are obtainedvia OWA operator in cross efficiency for making the best portfolio. The finding could be used forconstructing the best portfolio in stock companies, in various finance organization and public andprivate sector companies.
http://ijdea.srbiau.ac.ir/article_8175_cab1170cbbefbe266b402592cb61e54e.pdf
2015-02-27T11:23:20
2020-05-27T11:23:20
633
651
portfolio
Data envelopment analysis (DEA)
Cross-efficiency evaluation
Negative data
Ordered Weighted Averaging (OWA) Operator
Sh.
Banihashemi
true
1
Department of Mathematics, Department of Mathematics and Computer Science, Faculty of Econimics Allameh Tabataba’i University, Dr. Beheshti and Bokharest Ave.
Department of Mathematics, Department of Mathematics and Computer Science, Faculty of Econimics Allameh Tabataba’i University, Dr. Beheshti and Bokharest Ave.
Department of Mathematics, Department of Mathematics and Computer Science, Faculty of Econimics Allameh Tabataba’i University, Dr. Beheshti and Bokharest Ave.
LEAD_AUTHOR
M.
Sanei
true
2
Department of Applied Mathematics, Islamic Azad University, Central Tehran Branch, Tehran,Iran.
Department of Applied Mathematics, Islamic Azad University, Central Tehran Branch, Tehran,Iran.
Department of Applied Mathematics, Islamic Azad University, Central Tehran Branch, Tehran,Iran.
AUTHOR