Swing Weighting — importance weights derived from worst-to-best swing utility gains
SWING (Swing Weighting — importance weights derived from worst-to-best swing utility gains) is a weight subjective multi-criteria decision-making (MCDM) method introduced by von Winterfeldt, D., Edwards, W. in 1986. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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When to use it
Swing weighting asks the DM: 'Starting from a baseline where all attributes are at their worst level, how much would you gain by swinging each attribute from worst to best?' The attribute with the highest swing gain gets the highest weight. It is closely related to SMART but grounds the ratings in an explicit comparative context.
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.
Sources
- von Winterfeldt, D., Edwards, W. (1986). Decision Analysis and Behavioral Research. Cambridge University Press ISBN: 978-0521271073
How to cite this page
ScholarGate. (2026, June 2). Swing Weighting — importance weights derived from worst-to-best swing utility gains. ScholarGate. https://scholargate.app/en/decision-making/swing
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