方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| Data Envelopment Analysis (Productivity)× | 数据包络分析（BCC / VRS 模型）× | |
|---|---|---|
| 领域≠ | 经济学 | 决策 |
| 方法族≠ | Process / pipeline | MCDM |
| 起源年份≠ | 1978 | 1984 |
| 提出者≠ | Charnes, Cooper & Rhodes (building on Farrell 1957) | Banker, R. D., Charnes, A., Cooper, W. W. |
| 类型≠ | Nonparametric linear-programming efficiency frontier | Non-parametric efficiency frontier — Variable Returns to Scale (BCC model) |
| 开创性文献≠ | Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444. DOI ↗ | Banker, R. D., Charnes, A., Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science DOI ↗ |
| 别名≠ | DEA Efficiency Analysis, Nonparametric Frontier Efficiency, CCR/BCC Efficiency Measurement, Production Frontier DEA | — |
| 相关≠ | 5 | 0 |
| 摘要≠ | Data envelopment analysis (DEA) is a nonparametric, linear-programming technique for measuring the relative productive efficiency of comparable units — firms, plants, hospitals, schools, bank branches — that convert multiple inputs into multiple outputs. Introduced by Charnes, Cooper, and Rhodes in 1978 and rooted in Farrell's 1957 work on efficiency measurement, it constructs a best-practice frontier that envelops the observed data and scores each unit by its distance to that frontier, requiring no assumed functional form for the production technology. | DEA-BCC (Data Envelopment Analysis (BCC / VRS model)) is a dea multi-criteria decision-making (MCDM) method introduced by Banker, R. D., Charnes, A., Cooper, W. W. in 1984. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGate数据集 ↗ |
|
|