convergence-scoring-matrix-construction

name	convergence-scoring-matrix-construction
description	Build a complete scoring matrix through criterion definition, weighting, scoring, normalization, and sensitivity testing.
execution	tactic
dependencies	{"sops":["alternative-scoring","criterion-definition","normalization","scoring-synthesis","weight-elicitation-sop"]}

Scoring Matrix Construction

Standard MCDA workflow of define criteria → assign weights → score → aggregate → sensitivity check, producing a complete scoring matrix and ranking results.

Stages

1. Criterion Definition — Extract evaluation criteria from research goals and candidates
2. Weight Elicitation — Compute criteria weights using specified method
3. Alternative Scoring — Score candidates against each criterion
4. Normalization — Normalize scores to make different scales comparable
5. Sensitivity Testing — Perturb weights to verify result robustness

Available SOPs

• criterion-definition — Extract evaluation criteria
• weight-elicitation-sop — Compute criteria weights
• alternative-scoring — Score alternatives
• normalization — Normalize scores
• scoring-synthesis — Aggregation and sensitivity (including perturbation analysis)

Execution Guidance

• Stages execute sequentially; each stage's output serves as input for the next
• Stage 2 method options: AHP, Swing, BWM, MACBETH, Simos
• Stage 4 normalization method must match the subsequent aggregation method (linear normalization for WSM, vector normalization for TOPSIS)
• Sensitivity testing must perturb at least 3 weight parameters by ±10%
• If any stage's output fails quality requirements, roll back and redo that stage

Minimum Yield

Complete scoring matrix + weight vector + ranking results

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOP	When to use
alternative-scoring	Score each candidate alternative against all criteria to produce a score matrix.
criterion-definition	Extract evaluation criteria from research goals and candidate alternatives.
normalization	Normalize a score matrix using a specified method to make scores comparable across criteria.
scoring-synthesis	Synthesize score matrix, rankings, and sensitivity analysis into a final recommendation.
weight-elicitation-sop	Compute criteria weights using a specified elicitation method (AHP, Swing, BWM, MACBETH, or Simos).