4.3.5 MICMAC Analysis
MICMAC stands for matrix cross-impact matrix classification. The MICMAC
analysis examines the system’s key categories. Attri et al.
[55] say that the MICMAC
”analysis involves the development of a graph that classifies factors
based on driving power and dependence power.” ”MICMAC analysis is used
to classify the factors and validate the interpretive structural model
factors in the study to reach their results and conclusions” [54].
Enablers are divided into four groups based on their driving and
dependence power.
- Autonomous Cluster: This cluster contains a category with low
driving and dependency power. They are mostly disconnected due to weak
links. As a result, their influence on the system as a whole is
negligible [76].
- Linkage Cluster: This cluster has great driving and
dependency power and affects other enablers due to strong connectivity
[76].
- Dependent Cluster : This cluster’s enablers have a high degree
of dependence but a low level of driving power [76].
- Independent Cluster: The enablers in this cluster have weak,
dependent power but significant driving power; they are also known as
”key enablers” [76].