Ranking Methods Within Data Envelopment Analysis

2019 ◽  
pp. 189-224
Author(s):  
Nicole Adler ◽  
Nicola Volta
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Ranking Methods

scholarly journals EVALUATING HOTEL ADVERTISEMENTS EFFICIENCY USING DATA ENVELOPMENT ANALYSIS

2004 ◽  
Vol 5 (3) ◽  
pp. 133-141 ◽  
Author(s):  
Yossi Hadad ◽  
Lea Friedman ◽  
Aviad A. Israeli
Keyword(s):  
Data Envelopment Analysis ◽  
Decision Maker ◽  
Ranking Method ◽  
New Method ◽  
Data Envelopment ◽  
Ranking Methods ◽  
Multiple Outputs ◽  
Highly Correlated ◽  
Using Data

This paper introduces popular methods for ranking alternatives with multiple inputs and multiple outputs in the DEA context. The ranking methods are based on different criteria. Consequently, the ranking of the alternatives are not always the same, particularly as regards the best alternative. The decision maker, however, must make an absolute decision as to the most favored alternative. This study proposes a new ranking method, which is based on the average of the highly correlated ranking method. The new method is applied on a case study of ranking hotels in Israel.

Review of ranking methods in the data envelopment analysis context

2002 ◽  
Vol 140 (2) ◽  
pp. 249-265 ◽  
Author(s):  
Nicole Adler ◽  
Lea Friedman ◽  
Zilla Sinuany-Stern
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Ranking Methods

Review of efficiency ranking methods in data envelopment analysis

Measurement ◽  
2017 ◽  
Vol 106 ◽  
pp. 161-172 ◽  
Author(s):  
Abdullah Aldamak ◽  
Saeed Zolfaghari
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Ranking Methods ◽  
Efficiency Ranking

scholarly journals A Review of Ranking Models in Data Envelopment Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-20 ◽  
Author(s):  
F. Hosseinzadeh Lotfi ◽  
G. R. Jahanshahloo ◽  
M. Khodabakhshi ◽  
M. Rostamy-Malkhlifeh ◽  
Z. Moghaddas ◽  
...  
Keyword(s):  
Data Envelopment Analysis ◽  
Real Data ◽  
Research Area ◽  
Theory And Practice ◽  
Data Envelopment ◽  
Ranking Methods ◽  
Multivariate Statistical ◽  
Data Set ◽  
Fourth Group ◽  
Dea Models

In the course of improving various abilities of data envelopment analysis (DEA) models, many investigations have been carried out for ranking decision-making units (DMUs). This is an important issue both in theory and practice. There exist a variety of papers which apply different ranking methods to a real data set. Here the ranking methods are divided into seven groups. As each of the existing methods can be viewed from different aspects, it is possible that somewhat these groups have an overlapping with the others. The first group conducts the evaluation by a cross-efficiency matrix where the units are self- and peer-evaluated. In the second one, the ranking units are based on the optimal weights obtained from multiplier model of DEA technique. In the third group, super-efficiency methods are dealt with which are based on the idea of excluding the unit under evaluation and analyzing the changes of frontier. The fourth group involves methods based on benchmarking, which adopts the idea of being a useful target for the inefficient units. The fourth group uses the multivariate statistical techniques, usually applied after conducting the DEA classification. The fifth research area ranks inefficient units through proportional measures of inefficiency. The sixth approach involves multiple-criteria decision methodologies with the DEA technique. In the last group, some different methods of ranking units are mentioned.

scholarly journals EVALUATING HOTEL ADVERTISEMENTS EFFICIENCY USING DATA ENVELOPMENT ANALYSIS

2005 ◽  
Vol 6 (3) ◽  
pp. 145-153 ◽  
Author(s):  
Yossi Hadad ◽  
Lea Friedman ◽  
Aviad A. Israeli
Keyword(s):  
Data Envelopment Analysis ◽  
Decision Maker ◽  
Ranking Method ◽  
New Method ◽  
Data Envelopment ◽  
Ranking Methods ◽  
Multiple Outputs ◽  
Highly Correlated ◽  
Using Data

This paper introduces popular methods for ranking alternatives with multiple inputs and multiple outputs in the DEA context. The ranking methods are based on different criteria. Consequently, the ranking of the alternatives are not always the same, particularly as regards the best alternative. The decision maker, however, must make an absolute decision as to the most favored alternative. This study proposes a new ranking method, which is based on the average of the highly correlated ranking method. The new method is applied on a case study of ranking hotels in Israel.

Determining rates of change in data envelopment analysis

1997 ◽  
Vol 48 (6) ◽  
pp. 591-593
Author(s):  
Z Huang ◽  
S X Li ◽  
J J Rousseau
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Rates Of Change

Data Envelopment Analysis Theory, Methodology and Applications

1997 ◽  
Vol 48 (3) ◽  
pp. 332-333 ◽  
Author(s):  
A Charnes ◽  
W Cooper ◽  
A Y Lewin ◽  
L M Seiford
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Analysis Theory
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