Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| By-Production Technology DEA× | Datu apvalka analīze (CCR modelis) efektivitātes balstītai ranžēšanai× | |
|---|---|---|
| Nozare | Lēmumu pieņemšana | Lēmumu pieņemšana |
| Saime | MCDM | MCDM |
| Izcelsmes gads≠ | 2005 | 1978 |
| Autors≠ | Färe, Grosskopf, Noh et al. | Charnes, A., Cooper, W. W., Rhodes, E. |
| Tips≠ | Non-parametric efficiency with undesirable outputs and by-products | Non-parametric efficiency frontier (CCR model) |
| Pirmavots≠ | Scheel, H. (2001). Undesirable outputs in efficiency valuations. European Journal of Operational Research, 132(2), 400-410. DOI ↗ | Charnes, A., Cooper, W. W., Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research DOI ↗ |
| Citi nosaukumi≠ | By-Production DEA, Joint Production DEA | — |
| Saistītās≠ | 2 | 0 |
| Kopsavilkums≠ | By-Production Technology DEA is a variant of Data Envelopment Analysis designed for production systems that generate both desirable outputs and undesirable by-products or emissions. Rather than ignoring or arbitrarily penalizing undesirable outputs, this method explicitly models them as joint products of the production process. It evaluates efficiency while accounting for the trade-off between desired production and environmental impact. | 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. |
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