##  [Multi-Criteria Decision Analysis](/multi-criteria-decision-analysis-0) 

 Definition

A family of methods and practices for evaluating, comparing and ranking alternatives using multiple quantitative and qualitative criteria by making criterion-specific assessments, assigning weights or preferences, and aggregating those assessments according to a chosen rule to support transparent trade-offs.

 

 

 

 

 

 





## Principle

Principle

Decisions under multiple criteria require an explicit model that maps criterion-level evaluations and stakeholder preferences into an aggregated ordering; the chosen weighting and aggregation rules determine how trade-offs are resolved and therefore materially affect outcomes.

 

 

 

 

 





## Demonstration

Demonstration

Illustrative scenario: A municipal authority evaluates project bids using criteria (cost, environmental impact, social benefit). For each bid the team scores criteria, elicits stakeholder weights through a workshop, and applies a weighted-sum or an outranking method. The result ranks bids and shows sensitivity to different weight sets, informing deliberation.

 

 

 

 

## Misapplication

Misapplication

Treating method outputs as purely objective without documenting weighting choices, or aggregating incommensurate scales without appropriate normalization—errors that hide normative choices or produce spurious rankings.

 

 

 

 

 





## Consequence

Consequence

MCDA increases transparency about trade-offs and makes the influence of preferences explicit, supporting stakeholder dialogue and robust decisions; but it can legitimize contested value choices and produce different outcomes depending on method selection and weight elicitation.

 

 

 

 

## Reversal

Reversal

If criteria are fundamentally incommensurable for aggregation (e.g., rights vs. costs), or when stakeholder disagreement cannot be represented by a single weighting, non‑aggregative approaches (e.g., multi‑stakeholder deliberation, veto thresholds, or Pareto analysis) may be preferable to simple aggregation.

 

 

 

 

 





## Boundary

Boundary

Clearly within: decisions requiring explicit trade-offs among multiple, potentially conflicting criteria where stakeholders’ preferences can be expressed or elicited. Boundary case: problems with many uncertain, context‑dependent criteria where numerical scoring yields fragile results. Clearly outside: single‑metric optimization or decisions driven by legal rules that preclude trade‑offs.

 

 

 

 

 





## Semantic Tension

Semantic Tension

Methodological transparency and comparability (explicit weights and aggregation) ↔ the normative nature of weights and the subjectivity of preferences; MCDA makes value choices explicit but does not automatically resolve disputes about them.

 

 

 

 

 





## Synthesis

Synthesis

MCDA is a toolbox rather than a single algorithm: its usefulness depends on aligning method, scale treatment and stakeholder processes with the decision’s structure; selecting and documenting weighting and aggregation choices is as important as computing scores.