Estimation of Returns to Scale in the Presence of Undesirable (bad) Outputs in DEA when the Firm is Regulated
F
.Emami
Department of Mathematics, Shahid Rajaee Teacher University, Lavizan, Tehran, Iran. P.O.Box 16785-163
author
M
.Rostamy malkhalifeh
Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
author
H
.Safdari
Department of Mathematics, Shahid Rajaee Teacher University, Lavizan, Tehran, Iran. P.O.Box 16785-163
author
text
article
2014
eng
The calculation of RTS amounts to measuring a relationship between inputs and outputs in a production structure. There are many methods to measure RTS in the primal space or the dual space. One of the main approaches is using the multiplier on the convexity constraint. But returns to scale measurements in DEA models are affected by the presence of regulatory constraints. These additional constraints change the role played by the convexity constraint. In this paper discusses methods for determining returns to scale in the presence of undesirable (bad) outputs in the regulated environments.
International Journal of Data Envelopment Analysis
2345-458X
2
v.
4
no.
2014
487
495
http://ijdea.srbiau.ac.ir/article_7843_de297de7b4d8871abcadd4d910204f98.pdf
Deriving Common Set of Weights in the Presence of the Undesirable Inputs: A DEA based Approach
M
.Eyni
Department of Mathematics, University of Payam Noor, Tehran, Iran.
author
M
.Maghbouli
Departement of Mathematics, Islamic Azad University, Hadishahr Branch, Hadishahr, Iran.
author
text
article
2014
eng
Data Envelopment Analysis (DEA) as a non-parametric method for efficiency measurement allows decision making units (DMUs) to select the most advantageous weight factors in order to maximize their efficiency scores. In most practical applications of DEA presented in the literature, the presented models assume that all inputs are fully desirable. However, in many real situations undesirable inputs are part of the production process. In order to deal with undesirable inputs, this paper changes the undesirable inputs to be desirable ones by reversing, then a compromise solution approach is proposed to generate a common set of weights under DEA framework. The DEA efficiencies obtained with the most favorable weights to each DMU are treated as the target efficiencies of DMUs. Based on the generalized measure of distance, three types of DEA-based efficiency score programming can be derived. The proposed approach is then applied to real-world data set that characterize the performance of seven types of chemical activities.
International Journal of Data Envelopment Analysis
2345-458X
2
v.
4
no.
2014
497
508
http://ijdea.srbiau.ac.ir/article_7844_f26f3d61a24cd9fb54b9625c8556fb7c.pdf
Presenting a New Model for Bank’s Supply Chain Performance Evaluating with DEA Solution Approach
R
.Shahverdi
Department of mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran.
author
text
article
2014
eng
Data Envelopment Analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs) with multiple inputs and outputs. The traditional DEA treats decision making units under evaluation as black boxes and calculates their efficiencies with first inputs and last outputs. This carries the notion of missing some intermediate measures in the process of changing the inputs to outputs of DMU and as a result the effect of these measures in the process of performance evaluation is not considered. Recently, some models are created in DEA which can evaluate the system in multi stages and consider the relations between the systems. The objective of this paper is to investigate efficiency decomposition in a three-stage process that has a two independent parallel stages linking with a one final stage. This three stage processes calculate the efficiency of organization with considering intermediate constraints. Finally, we illustrate the proposed method with numerical example
International Journal of Data Envelopment Analysis
2345-458X
2
v.
4
no.
2014
509
526
http://ijdea.srbiau.ac.ir/article_7845_d90db554804512154121ebd4ffae8c91.pdf
Effect of Relocation and Rotation on Radial Efficiency Scores for a Partially Negative Data Problem
S
.Sarkar
Department of Management Studies, NIT Durgapur, West Bengal, India.
author
text
article
2014
eng
Negative 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.
International Journal of Data Envelopment Analysis
2345-458X
2
v.
4
no.
2014
527
550
http://ijdea.srbiau.ac.ir/article_7846_8e2be07fdda2f262b326dd6bb3b9e986.pdf
DEA Models with Interval Scale Inputs and Outputs
M
.Mohammadpour
Department of Mathematics, Boukan Branch, Islamic Azad University, Boukan, Iran.
author
text
article
2014
eng
This paper proposes an alternative approach for efficiency analysis when a set of DMUs uses interval scale variables in the productive process. To test the influence of these variables, we present a general approach of deriving DEA models to deal with the variables. We investigate a number of performance measures with unrestricted-in-sign interval and/or interval scale variables.
International Journal of Data Envelopment Analysis
2345-458X
2
v.
4
no.
2014
553
557
http://ijdea.srbiau.ac.ir/article_7847_c77279b10a0612df197010161883eaaa.pdf
A note on “Supplier selection by the pair of nondiscretionary factors-imprecise data envelopment analysis models”
A
.Amirteimoori
Department of Applied Mathematics, Rasht Branch, Islamic Azad University, Rasht, Iran.
author
R
.Farzipoor Saen
Department of Industrial Management, Faculty of Management and Accounting, Islamic Azad University – Karaj Branch, Karaj, PO Box 31485-313, Iran.
author
H
.Azizi
Department of Applied Mathematics, Parsabad Moghan Branch, Islamic Azad University, Parsabad Moghan, Iran.
author
text
article
2014
eng
Recently, Farzipoor Saen [Journal of the Operational Research Society, 60(11), 1575–1582 (2009)] proposed a method based on data envelopment analysis to identify optimistic efficient suppliers in the presence of nondiscretionary factors-imprecise data. This short communication aims at showing a computational error in computing the value of preference intensity parameter in Farzipoor Saen’s [1] article. Then, a ranking method is used to identify the suppliers with the best performance.
International Journal of Data Envelopment Analysis
2345-458X
2
v.
4
no.
2014
559
568
http://ijdea.srbiau.ac.ir/article_7848_3fda686e0deedce9db67846dcd638c41.pdf