Journal ArticleDOI
Olympics ranking and benchmarking based on cross efficiency evaluation method and cluster analysis: the case of Sydney 2000
TLDR
In this paper, an extended tool of DEA, namely cross efficiency evaluation method, was used to measure the performance of the nations in the Summer Olympic Games of Sydney 2000, and the average cross efficiencies were calculated and were compared to those originated from the radial efficiency method and other previous works.Abstract:
In this paper, an extended tool of DEA, namely cross efficiency evaluation method, was used to measure the performance of the nations in the Summer Olympic Games of Sydney 2000. The model in the paper considered two inputs (GNP per capita and population) and a single output (the weighted sum of amounts of medals won). The advantages of the proposed model rest on the fact that it provides for a unique ranking of the participants and eliminates the unrealistic weight schemes without requiring the elicitation of extra weight restrictions. The average cross efficiencies were calculated and were compared to those originated from the radial efficiency method and other previous works. Also, cluster analysis technique was used to select the more appropriate targets for poorly performing countries to use as benchmarks.read more
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Journal ArticleDOI
A neutral DEA model for cross-efficiency evaluation and its extension
Ying-Ming Wang,Kwai-Sang Chin +1 more
TL;DR: A neutral DEA model is proposed for cross-efficiency evaluation, which determines one set of input and output weights for each DMU from its own point of view without being aggressive or benevolent to the other DMUs.
Journal ArticleDOI
The use of OWA operator weights for cross-efficiency aggregation
Ying-Ming Wang,Kwai-Sang Chin +1 more
TL;DR: In this paper, the authors proposed the use of ordered weighted averaging (OWA) operator weights for cross-efficiency aggregation, which allows the decision maker (DM)s optimism level towards the best relative efficiencies, characterized by an orness degree, to be taken into consideration in the final overall efficiency assessment and particularly in the selection of the best DMU.
Journal ArticleDOI
Cross efficiency evaluation method based on weight-balanced data envelopment analysis model
Jie Wu,Jiasen Sun,Liang Liang +2 more
TL;DR: A weight-balanced DEA model is proposed to lessen large differences in weighted data (weighted inputs and weighted outputs) and to effectively reduce the number of zero weights for inputs and outputs.
Journal ArticleDOI
Cross-efficiency evaluation based on ideal and anti-ideal decision making units
TL;DR: The new DEA models determine input and output weights from the point of view of distance from IDMU or ADMU without the need to be aggressive or benevolent to any DMUs, resulting in cross-efficiencies that are neutral and more logical.
Journal ArticleDOI
DEA models for minimizing weight disparity in cross-efficiency evaluation
TL;DR: The proposed DEA models determine the input and output weights of each DMU in a neutral way without being aggressive or benevolent to the other DMUs, to minimize the virtual disparity in the cross-efficiency evaluation.