Cross-ranking of Decision Making Units in Data Envelopment Analysis
By M. Z. Angiz, Adli Mustafa, M. Jalal Kamali. 2013
67 citations recorded by the source corpus.
Data Envelopment Analysis (DEA) is a mathematical model that evaluates the relative efficiency of Decision Making Units (DMUs) with multiple input and output. In some applications of DEA, ranking of the DMUs are important. For this purpose, a number of approaches have been introduced. Among them is the cross-efficiency method. The method utilizes the result of the cross-efficiency matrix and averages the cross-efficiency scores of each DMU. Ranking is then performed based on the average efficiency scores. In this paper, we proposed a new way of handling the information from the cross-efficiency matrix. Based on the notion that the ranking order is more important than individual efficiency score, the cross-efficiency matrix is converted to a cross-ranking matrix. A cross-ranking matrix is basically a cross-efficiency matrix with the efficiency score of each element being replaced with the ranking order of that efficiency score with respect to the other efficiency scores in a column. By so doing, each DMU assume the role of a decision maker and how they voted or ranked the other DMUs are reflected in their respective column of the cross-ranking matrix. These votes are then aggregated using a preference aggregation method to determine the overall ranking of the DMUs. Comparison with an existing cross-efficiency method indicates a relatively better result through usage of the proposed method.
Subfields: Control and Systems Engineering, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/888df730300615cda4ffd910b9b59b9b542484d5
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In Control and Systems Engineering
In Management Science and Operations Research
Citations in the corpus
- Review of efficiency ranking methods in data envelopment analysis (2017, background): “[22] developed another new approach that focuses on only ranking DMUs.”