2016
4
1
13
58
Calculation of the Efficiency of TwoStage Network Structures with Additional Inputs to the Second Stage by SBM Approach: A Case Study on Credit Branches of an Iranian State Bank in Guilan Province
2
2
Many studies have been conducted to determine the efficiency of twostage network structures in the recent years. The twostage network with additional inputs to the second stage, in which the second stage is independent of the first stage are one of these structures. Thus, there is a need for a model capable of calculating the efficiency of twostage structures as well as efficiency of each stage which can then provide managers with recommendations to increase the efficiency of the entire system and its subprocesses. In this study, a noncooperative game adapted from game theory and SBM approach is used to calculate the efficiency of a twostage network structure to provide a unique analysis of the overall efficiency as the product of efficiency scores of the two stages. SBM approach is a nonradial DEA model capable of providing modification recommendations for inputs and outputs. The model then is implemented on 29 credit branches of an Iranian state bank in Guilan province and the results are analyzed.
1

881
892


Saeed
Jahangard Patavani
M.Sc, Department of Applied Mathematics, Islamic Azad University, Lahijan Branch, Lahijan, Assessor Keshavarzi Bank, Guilan, Iran.
M.Sc, Department of Applied Mathematics,
Iran
berjis.sj@gmail.com


Nasima
Mahboubi
M.Sc, Department of Applied Mathematics, Islamic Azad University, Lahijan Branch, Lahijan, Iran
M.Sc, Department of Applied Mathematics,
Iran
natali_mi2006@yahoo.com
DEA
Twostage Network
Stackelberg Game
SBM Model
Bank
An Additive Model for Estimation Return to Scale in Regulated Environment with QuasiFixed Inputs in Data Envelopment Analysis (DEA)
2
2
The measurement of RTS amounts measures a relationship between inputs and outputs in a production structure. There are many different ways to calculate RTS in primal or dual space. But in more realistic cases, governments usually intervene on DMU’s behavior as regulatory agency, this clearly represent a set of limitations and restrictions on behaviors of DMUs, So very few decisions in DMUs are made without intersecting some regulations. Therefore it is essential to be able to assess the impact of regulation on the behavior of the DMUs, and this would be ideally done by estimating returns to scale with and without the effect of the regulation.
In this paper we use additive model to provide an alternative approach for estimating returns to scale in regulated environments. The proposed model is developed to determining returns to scale in the presence of quasifixed inputs in Data Envelopment Analysis.
1

893
901


Farshid
Emami
Department of Mathematics, Shahid Rajaee Teacher Training University, Lavizan, Tehran, Iran
Department of Mathematics, Shahid Rajaee
Iran


Toktam
Nasirzade Tabrizi
Department of Mathematics, Science and Research Branch, Islamic Azad University
Department of Mathematics, Science and Research
Iran
Returns to scale
Regulation
Quasifixed inputs
Some Conditions for Characterizing Minimum Face in NonRadial DEA Models with Undesirable Outputs
2
2
The problem of utilizing undesirable (bad) outputs in DEA models often need replacing the assumption of free disposability of outputs by weak disposability of outputs. The Kuosmanen technology is the only correct representation of the fully convex technology exhibiting weak disposability of bad and good outputs. Also, there are some specific features of nonradial data envelopment analysis (DEA) models for obtaining all projections of a decision making unit (DMU) on the boundary of production possibility set (PPS) or efficient frontier. Production technologies in DEA are modeled by polyhedral sets that envelop the observed DMUs. Because the efficient frontiers of DEA technologies are generally nonsmooth and are characterized by different faces, thus, all projections of a DMU on efficient frontier can not belong to different faces that do not have common points. The rationale behind abovementioned statement is as follows: if all projections of a DMU belong to different faces then the interior points of PPS will become efficient that contradicts the principles of optimality conditions in linear programming models. Therefore all projections would belong to a unique face that is called minimum face. In this paper we propose a procedure to find minimum face and so all projections of a DMU on efficient frontiers in nonradial DEA models with undesirable outputs. This leads us to an interesting algorithm to obtain minimum face.
1

903
909


Sevan
Sohraiee
Department of Mathematics, Faculty of Sciences, Tehran North Branch, Islamic Azad University, Tehran, Iran
Department of Mathematics, Faculty of Sciences,
Iran
s_sohraiee@iautnb.ac.ir
Data Envelopment Analysis
Undesirable outputs
Nonradial Model
Minimum Face
Satisfaction Function in Present Undesirable Factors
2
2
Data Envelopment Analysis (DEA) is an efficient method to perform evaluation of units. In DEA we try to evaluate units with undesirable factors in input & outputs by satisfaction function, testing some models. On the other hand benefiting this concept, we can identify nonefficient units. Also we can recognize why these units are inefficient and calculate the reason of their inefficiency and how they turn efficient. In DEA we cannot know why some units are nonefficient and how these units can be efficient, but by this paper we can do this work.
1

911
915


Zohreh
Iravani
Department of Mathematics, Yadegar  e Imam Khomeini (rah), shahrerey Branch, Islamic Azad University, Tehran, Iran.
Department of Mathematics, Yadegar  e Imam
Iran
zohrehiravani@gmail.com


Mohammad
Mohseni Takaloo
Young Researchers and Elite club, YadegareImam Khomeini(rah), ShahreRey Branch, Islamic Azad University, Tehran, Iran.
Young Researchers and Elite club, YadegareImam
Iran
Data Envelopment Analysis with LINGO Modeling for Technical Educational Group of an Organization
2
2
Data Envelopment Analysis (DEA) was developed to help compare the relative performance of decisionmaking units. It is a nonparametric method for performing frontier analysis. It uses linear programming to estimate the efficiency of multiple decisionmaking units and it is commonly used in production, management and economics [3]. DEA generates an efficiency score between 0 and 1 for each unit, indicating how effectively they are managing their resources. A compelling feature of DEA is it develops a unique rating system for each unit designed to make them look their best. This should facilitate acceptance of DEA within an organization [2].
LINGO is a comprehensive tool designed to make building and solving mathematical optimization models easier and more efficient. In this paper, we have explained what DEA does? How DEA evaluates efficiency, how DEA identifies paths to improve efficiency using this LINGO software, and how to use DEA. We have considered a group of 3 technical colleges (campuses). We assume that each campus “converts” 2 inputs into 3 outputs. This will enable managers to explore and assess the value of using DEA in their service operations. This paper also shows that Lingo Model can offer more information than the standard LP approach with exclusion of Simulation modeling approach [4]. The advantages of this approach are modesty, flexibility and visualization. The results by comparison of educational campuses were helpful for organization management.
1

917
927


Mohd
Rizwanullah
Associate Professor, Department of Mathematics and Statistics, Manipal University Jaipur, Rajasthan, India
Associate Professor, Department of Mathematics
Iran
rizwansal@yahoo.co.in
Data envelopment analysis (DEA)
Efficiency
Performance, Reference Units, Weights
Estimating the Efficient Portfolio in NonRadial DEA and DEAR Models
2
2
The portfolio is a perfect combination of stock or assets, which an investor buys them. The objective of the portfolio is to divide the investment risk among several shares. Using nonparametric DEA and DEAR methods can be of great significance in estimating portfolio. In the present paper, the efficient portfolio is estimated by using nonradial DEA and DEAR models. By proposing nonradial models in DEAR when there is ratio data the efficient portfolio is determined. At the end of the study, an applicatory example based on article [2] with nonradial DEA and DEAR models has been conducted and results are presented.
1

929
938


Forod
Najafi
Department of Mathematics, Payame Noor University, Shiraz, Iran
Department of Mathematics, Payame Noor University,
Iran


Mohammad Reza
Mozaffari
Department of Mathematics, Shiraz Branch, Islamic Azad University, Shiraz, Iran
Department of Mathematics, Shiraz Branch,
Iran
DEA
DEAR
Efficient Portfolio