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Home›Decision-making›Decision Making Trial and Evaluation Laboratory
MCDMWeight Subjectivecrisp

Decision Making Trial and Evaluation Laboratory

DEMATEL (Decision Making Trial and Evaluation Laboratory) is a weight subjective multi-criteria decision-making (MCDM) method introduced by Gabus, A., Fontela, E. in 1972. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

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DEMATEL
AHPSORTAPLOCOARASAROMANARTASICOBRACOCOSOCODAS

When to use it

DEMATEL produces: (1) Weights from normalised prominence P_i; (2) Causal map — criteria with E_i > 0 belong to the cause group (drivers), those with E_i < 0 to the effect group (receivers). The causal map is the primary insight; weights are secondary.

Strengths & limitations

Strengths
  • 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.
Limitations
  • Results depend on the chosen normalisation, weights, and parameter settings.

Sources

  1. Gabus, A., Fontela, E. (1972). World problems, an invitation to further thought within the framework of DEMATEL. Battelle Geneva Research Centre, Geneva, Switzerland link ↗

How to cite this page

ScholarGate. (2026, June 2). Decision Making Trial and Evaluation Laboratory. ScholarGate. https://scholargate.app/en/decision-making/dematel

Related methods

AHPSORTAPLOCOARASAROMANARTASICOBRACOCOSOCODAS

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Similar methods

AHPDELPHICRITICFUZZY-DELPHIANPDANPFUZZY-AHPFMEA

Related reference concepts

Decision MakingDecision Support SystemsDelphi TechniqueEvaluation CriteriaDecision Making SkillsParticipative Decision Making

Spotted an issue on this page? Report or suggest a fix →

ScholarGate — DEMATEL (Decision Making Trial and Evaluation Laboratory). Retrieved 2026-07-20 from https://scholargate.app/en/decision-making/dematel · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Gabus, A., Fontela, E.
Subfamily
Weight Subjective
Year
1972
Type
Cause-effect influence network (total relation matrix) — produces prominence + relation for criteria weighting
Value Space
crisp
Uncertainty
None
Compensation
N/A
Rank Reversal
No
Related methods
AHPSORTAPLOCOARASAROMANARTASICOBRACOCOSOCODAS
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