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.
  1. 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].
  2. Linkage Cluster: This cluster has great driving and dependency power and affects other enablers due to strong connectivity [76].
  3. Dependent Cluster : This cluster’s enablers have a high degree of dependence but a low level of driving power [76].
  4. Independent Cluster: The enablers in this cluster have weak, dependent power but significant driving power; they are also known as ”key enablers” [76].