ROC — Rank Order Centroid weights (rank-based surrogate weights)
ROC-WEIGHT (ROC — Rank Order Centroid weights (rank-based surrogate weights)) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Barron, F. H., Barrett, B. E. in 1996. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
Key highlights
- Follows a transparent, reproducible computational procedure that can be audited step by step.
- Handles multiple criteria of differing scales and units within a single decision matrix.
Intuition
This section is available to Pro members. Upgrade to Pro
How it works
This section is available to Pro members. Upgrade to Pro
When to use it
ROC weights are surrogate weights derived purely from the rank order — no numeric importance judgements needed. They are the expected value of the weights given only their ordering. w_1>w_2>…>w_n always holds. Most weight is concentrated at rank 1.
Strengths & limitations
- Follows a transparent, reproducible computational procedure that can be audited step by step.
- Handles multiple criteria of differing scales and units within a single decision matrix.
- Results depend on the chosen normalisation, weights, and parameter settings.
Common pitfalls
This section is available to Pro members. Upgrade to Pro
Sources
- 1.Barron, F. H. (1992). Selecting a best multiattribute alternative with partial information about attribute weights. Acta Psychologica
You have read it. What now?
Cite this page
ScholarGate. (2026, June 2). ROC-WEIGHT. ScholarGate. https://scholargate.app/decision-making/roc-weight