方法对比
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| 窗口数据包络分析× | 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≠ | 1984 | 2000 |
| 提出者≠ | Charnes, Clark, Cooper & Golany | Färe & Grosskopf |
| 类型≠ | Non-parametric panel efficiency model | Multi-stage nonparametric efficiency model |
| 开创性文献≠ | Charnes, A., Clark, C. T., Cooper, W. W., & Golany, B. (1984). A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. Air Forces. Annals of Operations Research, 2(1), 95–112. DOI ↗ | Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49. DOI ↗ |
| 别名 | Sliding-Window DEA, Temporal DEA, Rolling-Period DEA, Pencere VZA | Network Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi |
| 相关 | 2 | 2 |
| 摘要≠ | Window Data Envelopment Analysis (Window DEA) is a non-parametric panel efficiency method that evaluates decision-making units (DMUs) over time by embedding each DMU's observations across a rolling temporal window into a single cross-sectional DEA problem. Introduced by Charnes, Clark, Cooper, and Golany in 1984, it enables longitudinal efficiency tracking without requiring a full panel, increasing discriminatory power by pooling observations across consecutive periods. | 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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