方法对比
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| 超效率数据包络分析× | 网络数据包络分析 (Network DEA)× | |
|---|---|---|
| 领域 | 效率分析 | 效率分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1993 | 2000 |
| 提出者≠ | Andersen & Petersen | Färe & Grosskopf |
| 类型≠ | Nonparametric linear programming model | Multi-stage nonparametric efficiency model |
| 开创性文献≠ | Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261–1264. DOI ↗ | Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49. DOI ↗ |
| 别名 | Andersen-Petersen Model, Super-Radial DEA, Ranking DEA, Süper Etkinlik VZA | Network Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi |
| 相关 | 2 | 2 |
| 摘要≠ | Super-Efficiency DEA is a nonparametric linear programming extension of classical Data Envelopment Analysis (DEA) introduced by Andersen and Petersen (1993). While standard DEA assigns a maximum efficiency score of 1.0 to all units on the efficient frontier, Super-Efficiency DEA allows efficient units to receive scores greater than 1.0 by temporarily removing the evaluated unit from the reference set. This modification enables full ranking of all decision-making units (DMUs), including those previously indistinguishable at the frontier. | Network Data Envelopment Analysis (Network DEA) is a nonparametric efficiency measurement framework introduced by Färe and Grosskopf (2000) that extends classical DEA to multi-stage or multi-division production processes. Rather than treating a decision-making unit as a black box, it explicitly models the internal structure — the divisions and the intermediate products that flow between them — enabling stage-level and overall efficiency scores to be estimated simultaneously within a single coherent model. |
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