| Autor: |
Guo-Qing Cheng, Liang Wang, Ying-Ming Wang |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
International Journal of Computational Intelligence Systems, Vol 14, Iss 1 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1875-6883 |
| DOI: |
10.2991/ijcis.d.201019.001 |
| Popis: |
The traditional three-stage data envelopment analysis (DEA) model only measures exact input–output indicator data, but cannot perform efficiency analysis on uncertain data. The interval DEA method does not exclude the influence of external environmental factors. Therefore, this paper combines the traditional three-stage DEA model with the interval DEA method, and proposes a three-stage interval DEA efficiency model, which eliminates the impact of external environmental factors and realizes the measurement of the efficiency for interval data. From the perspective of the impact of environmental factors, defining the degree of efficiency change vector, a clustering analysis technique based on the efficiency change degree vector is proposed to provide improvement benchmark for poorly performing decision-making units. Finally, an example is used to demonstrate the feasibility and validity of the proposed method in this paper. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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