Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| DEA de la technologie de production conjointe× | DEA× | |
|---|---|---|
| Domaine | Prise de décision | Prise de décision |
| Famille | MCDM | MCDM |
| Année d'origine≠ | 2005 | 1978 |
| Auteur d'origine≠ | Färe, Grosskopf, Noh et al. | Charnes, A., Cooper, W. W., Rhodes, E. |
| Type≠ | Non-parametric efficiency with undesirable outputs and by-products | Non-parametric efficiency frontier (CCR model) |
| Source fondatrice≠ | 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 ↗ |
| Alias≠ | By-Production DEA, Joint Production DEA | — |
| Apparentées≠ | 2 | 0 |
| Résumé≠ | 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. |
| ScholarGateJeu de données ↗ |
|
|