Local WLC: neighbourhood-adaptive weighted linear combination

Strengths

• •Automatically adjusts criterion importance to reflect local data variability (range-sensitivity principle)
• •No additional subjective input required beyond global weights and neighbourhood definition
• •Interpretable: the range-ratio table explains why local weights differ from global weights
• •Reduces to standard WLC when criterion variability is spatially homogeneous

Limitations

• •Neighbourhood definition choice is critical and subjective
• •Zero local range is a degenerate case requiring special handling
• •Requires at least 2 alternatives per neighbourhood
• •Cross-neighbourhood score comparisons rely on global normalisation being sensible

Assumptions to verify

• •Neighbourhood partition is meaningful and justified (not arbitrary zone boundaries)
• •Each neighbourhood contains at least 2 alternatives
• •Range-sensitivity principle holds: criteria with wider local spread should receive higher local weight
• •Global normalisation is appropriate (all alternatives in same measurement context)

When not to use

• •Non-spatial problem: no neighbourhood structure → use SAW
• •Only one alternative per neighbourhood → local range undefined
• •All neighbourhoods have equal criterion spreads → standard WLC is sufficient

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