Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Datu apvalka analīze (CCR modelis) efektivitātes balstītai ranžēšanai× | Tīkla datu apvalka analīze (Network DEA)× | |
|---|---|---|
| Nozare≠ | Lēmumu pieņemšana | Efektivitātes analīze |
| Saime≠ | MCDM | Regression model |
| Izcelsmes gads≠ | 1978 | 2000 |
| Autors≠ | Charnes, A., Cooper, W. W., Rhodes, E. | Färe & Grosskopf |
| Tips≠ | Non-parametric efficiency frontier (CCR model) | Multi-stage nonparametric efficiency model |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi≠ | — | Network Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi |
| Saistītās≠ | 0 | 2 |
| Kopsavilkums≠ | 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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