Fuzzy-set Qualitative Comparative Analysis (fsQCA) for Causal
Relationship Validation of System Dynamics Model
Abstract
Modelers typically produce different system dynamics models for the same
problem, depending on each modeler’s perspective, leading to reduced
stakeholder confidence. Validation of system dynamics can increase
stakeholder confidence. This research proposes the use of Fuzzy-set
Qualitative Comparative Analysis (fsQCA), based on the set theory
method, as a method to validate causal relationships between entities in
Causal Loop Diagram (CLD) models. The problem of mobile network
operators in Indonesia with small sample data characteristics is used as
a case study to demonstrate the use of fsQCA. The fsQCA method is used
after the CLD model is built in the system dynamics methodology. The
fsQCA method is used to test causal relationships between entities in
the CLD that need to be validated. The results can be used to improve
the previously created CLD model. The Fuzzy-set Qualitative Comparative
Analysis (fsQCA) method, which combines QCA with fuzzy set theory that
allows partial membership, can be used to test whether or not there is a
causal relationship between entities in the CLD model. The fsQCA method
can be used to test causal relationships between entities in the CLD
model with small sample data and increase stakeholder confidence in the
CLD model.