M2: Multi-Dimensional Evaluation - Selection Logic

Overview

Evaluate options across dimensions; set weights based on your needs.

Theoretical basis

• A2 Conditional subjectivity: /en/wiki/axiom-2-conditional-subjectivity
• T1 Matching: /en/wiki/theorem-1-matching

The evaluation template

1. Choose dimensions (facts).
2. Define criteria per dimension (how to measure).
3. Collect evidence and note uncertainty.
4. Set weights from needs.
5. Compute a fit score and document assumptions.

Output artifacts (for validation)

• a scoring table,
• weight vector,
• evidence sources,
• uncertainty notes.

These enable M5 validation and future improvement.

References

1. Keeney, R. L., & Raiffa, H. (1993). Decisions with Multiple Objectives: Preferences and Value Tradeoffs. Cambridge University Press.[source]
2. Payne, J. W., Bettman, J. R., & Johnson, E. J. (1993). The Adaptive Decision Maker. Cambridge University Press.[source]

Further Reading

• Fit score
• General evaluation dimensions