Experimental comparison of results provided by ranking methods in Data Envelopment Analysis
Autor: | Miłosz Kadziński, Anna Labijak-Kowalska |
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Rok vydání: | 2021 |
Předmět: |
0209 industrial biotechnology
Multivariate statistics Computer science Monte Carlo method General Engineering 02 engineering and technology Benchmarking Computer Science Applications 020901 industrial engineering & automation Ranking Artificial Intelligence Robustness (computer science) Statistics 0202 electrical engineering electronic engineering information engineering Data envelopment analysis 020201 artificial intelligence & image processing Pairwise comparison Decision analysis |
Zdroj: | Expert Systems with Applications. 173:114739 |
ISSN: | 0957-4174 |
DOI: | 10.1016/j.eswa.2021.114739 |
Popis: | We consider the problem of ranking Decision Making Units (DMUs) in Data Envelopment Analysis. We illustrate the use of fifteen selected approaches on a numerical example. They represent different categories, including cross- and super-efficiency, multivariate statistics, decision analysis, benchmarking, virtual DMU, and social networks. Moreover, we formalize a new category of ranking methods based on the concept of Robustness Analysis. They exploit a space of feasible input/output weight vectors with the Monte Carlo simulation to derive the expected efficiencies or ranks, or to compute the priorities or net flow scores of DMUs based on the matrix of pairwise efficiency outranking indices. The rankings constructed by all methods are compared on both artificially generated and real-world datasets with different numbers units, inputs and outputs, and performance distributions. The considered datasets represent the most common application areas of the DEA methods, such as finances, education, transportation, healthcare, farming, and the energy industry. The results are quantified in terms of five measures. We indicate that the choice of a method has a significant impact on the ranking, revealing the procedures that offer similar results or differ vastly in terms of the recommended order or the most preferred DMU. |
Databáze: | OpenAIRE |
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