3. All variables were standardised by z-scores to avoid any bias in the classification clusters

• 3. All variables were standardised by z-scores to avoid any bias in the classification clusters

• 4. Euclidean distance was chosen as measure of proximity used to compute clusters

• 5. Ward’s hierarchical clustering algorithm was used in the initial partition as it does not require definition of the number of clusters prior to the clustering procedure – a suitable number of clusters chosen from Ward’s algorithm output…