Gini Coefficient Weighting — inequality-of-discrimination objective weighting
GINI-WEIGHT (Gini Coefficient Weighting — inequality-of-discrimination objective weighting) is a weight objective multi-criteria decision-making (MCDM) method introduced by Gini, C. in 1912. 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
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How it works
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When to use it
Gini weight is proportional to the inequality of performance values across alternatives (after normalisation). A criterion where all alternatives perform identically gets G_j=0 → w_j=0. Higher inequality → higher weight. Unlike ENTROPY and SD, uses the Gini coefficient (mean absolute difference) instead of variance or entropy.
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
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Sources
- 1.Gini, C. (1912). Variabilità e mutabilità. Studi economico-giuridici della R. Università di Cagliari
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ScholarGate. (2026, June 2). GINI-WEIGHT. ScholarGate. https://scholargate.app/decision-making/gini-weight