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| Adatburkoló Elemzés (CCR modell) hatékonyság-alapú rangsoroláshoz× | Hálózat-adat-burkoló analízis (Network DEA)× | |
|---|---|---|
| Tudományterület≠ | Döntéshozatal | Hatékonyságelemzés |
| Módszercsalád≠ | MCDM | Regression model |
| Keletkezés éve≠ | 1978 | 2000 |
| Megalkotó≠ | Charnes, A., Cooper, W. W., Rhodes, E. | Färe & Grosskopf |
| Típus≠ | Non-parametric efficiency frontier (CCR model) | Multi-stage nonparametric efficiency model |
| Alapmű≠ | Charnes, A., Cooper, W. W., Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research DOI ↗ | Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49. DOI ↗ |
| Alternatív nevek≠ | — | Network Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi |
| Kapcsolódó≠ | 0 | 2 |
| Összefoglaló≠ | DEA (Data Envelopment Analysis (CCR model) for efficiency-based ranking) is a dea multi-criteria decision-making (MCDM) method introduced by Charnes, A., Cooper, W. W., Rhodes, E. in 1978. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | 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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