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| CRITIC-M× | Methode basierend auf den Entfernungseffekten von Kriterien× | |
|---|---|---|
| Fachgebiet | Entscheidungsfindung | Entscheidungsfindung |
| Familie | MCDM | MCDM |
| Entstehungsjahr≠ | 1995 | 2021 |
| Urheber≠ | Based on Diakoulaki et al.'s CRITIC; modified variants developed later | Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. |
| Typ≠ | Objective weight derivation via correlation and variance | Removal-effect objective weighting (logarithmic utility) |
| Wegweisende Quelle≠ | Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The CRITIC method. Computers & Operations Research, 22(7), 763-770. DOI ↗ | Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. (2021). Determination of objective weights using a new method based on the removal effects of criteria (MEREC). Informatica DOI ↗ |
| Aliasnamen≠ | CRITIC-M, Modified CRITIC | — |
| Verwandt≠ | 3 | 8 |
| Zusammenfassung≠ | CRITIC-M (Criteria Importance Through Intercriteria Correlation - Modified) is an objective weight derivation method that extends the classical CRITIC approach. It assigns weights to criteria based on two intrinsic properties of the decision matrix: variance (how much a criterion differentiates alternatives) and correlation (how much a criterion conflicts with or supplements others). Modified variants adjust the formulation to improve robustness or interpretability. | MEREC (MEthod based on the Removal Effects of Criteria) is a weight objective multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Antucheviciene, J., Turskis, Z. in 2021. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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