Data envelopment analysis and multiple criteria decision making

Omega ◽  
1993 ◽  
Vol 21 (6) ◽  
pp. 713-715 ◽  
Author(s):  
J Doyle ◽  
R Green
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Data Envelopment

Classifying the Usage of Multiple Objective Decision Making Techniques in Data Envelopment Analysis

2017 ◽  
pp. 1-56
Author(s):  
A. Ghazi ◽  
F. Hosseinzadeh Lotfi ◽  
G. H. Jahanshahloo ◽  
M. Sanei
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Large Volume ◽  
Multiple Criteria Decision Making ◽  
Multiple Objective ◽  
Data Envelopment ◽  
Multiobjective Decision Making ◽  
Wide Range ◽  
Multiple Objective Decision Making

There exist a wide range of research studies that apply the Multiple Criteria Decision Making (MCDM) techniques in Data Envelopment Analysis (DEA) methodology and vice versa. Also, MCDM is divided into two subsets, Multiobjective Decision Making (MODM) and Multiattribute Decision Making (MADM). Early studies of DEA methodology utilized the MODM concepts and consequently, most studies in the relationships between MCDM and DEA have involved the usage of MODM techniques in DEA. There remains a large volume of papers in this field; yet, none of them classifies this relationship. Hence, in this research the authors focused on classification of this field that is divided into six groups. Then, some papers in each group are selected for consideration.

scholarly journals 2-Tuple Unbalanced Linguistic Multiple Criteria Group Decision Making using Prospect Theory Data Envelopment Analysis

2021 ◽  
Author(s):  
Imran Khan ◽  
Anjana Gupta ◽  
Aparna Mehra
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Prospect Theory ◽  
Group Decision Making ◽  
Group Decision ◽  
Programming Model ◽  
Multiple Criteria ◽  
Data Envelopment ◽  
Linguistic Term ◽  
Criteria Weights

Abstract The linguistic terms in a balanced linguistic term set describing qualitative data are symmetrical around the central linguistic word. With the growing complexity of the problems, the symmetric linguistic term set appears to be confined. This work examines the multiple criteria group decision-making problems where decision-makers employ a 2-tuple unbalanced linguistic term set to provide entries of alternative-criteria matrices.We adopt a data envelopment analysis (DEA) method and create a linear programming model to evaluate alternative-criteria weights for each decision-maker. The value function from prospect theory models the non-rational aspect of risk in criteria. The values of prospect gain and prospect loss on cost and benefit criteria are computed and used to create a DEA model that evaluates the weights of each criterion on each alternative. Finally, the entropy values of the cross-efficiency scores deliver a ranking of the alternatives. A numerical example illustrates the proposed methodology

Relative Efficiency of Decision Making Units Producing Both Desirable and Undesirable Outputs: A Case of Textile Processing Units in Pakistan.

2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Value Added ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Textile Processing ◽  
Decision Making Unit ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output

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