## 4 Results
### Cluster Analysis of Small- and Medium-Sized Enterprises
#### 4.1.4 Comprehensive Description of the Clusters  
The next part describes the characteristics of clusters in details, based on the characteristics of the enterprises that make them up. It is mainly the relation of the clusters to VPi4 index, its levels, the technologies used by the enterprises, the existence of Industry 4.0 strategies, subjective perception of Industry 4.0 levels by the managers, composition in terms of size, and technological demands of the enterprises in the clusters and others. Based on the prevailing tendencies, the clusters are named as follows:  
Cluster 1--top I4 technological enterprises;  
Cluster 2--advances I4 enterprises;  
Cluster 3--I4 starting enterprises;  
Cluster 4--I4 noobs enterprises.  
First, the characteristics related to the VPi4 index are defined: It is clear from Figure 3a that the clusters differ in the level (0-100%) achieved by the VPi4 index values. Cluster 4 enterprises (\"noobs enterprises\") account for more than 80% of the very low 0-25% index. On the other hand, Cluster 1 (\"top technological enterprises\") and Cluster 2 (\"advances enterprises\") have the largest share of the 50-100% index. Both of these categories of the enterprises thus achieve a relatively significant index value. Cluster 3 (\"start enterprises\") contains mainly the enterprises with an index of 25-50%.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Factor** & **Cluster 1** & **Cluster 2** & **Cluster 3** & **Cluster 4** \\ \hline VPi4 Level 1 & 0.6123 & \(-\)0.2678 & 0.7175 & \(-\)1.3276 \\ VPi4 Level 2 & 1.3700 & \(-\)0.0685 & \(-\)0.7312 & 0.0931 \\ VPi4 Level 3 & \(-\)0.4001 & 1.5000 & \(-\)0.2943 & \(-\)0.7022 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Results of k-means clustering—cluster means (centroids).  
Figure 2: K-means and PCA analysis results: (**a**) clusters based on three factors (i.e., F1, F2, and F3) in 3D space; (**b**) biplot—PCA combined with cluster analysis (relations of the clusters and factors).  
Figure 3b shows a more detailed resolution of each index level. Cluster 4 has low VPi4 index value at all levels; Cluster 3 has low VPi4 index value at the first two levels, in particular; and Clusters 1 and 2 have a decent rating at all the levels of the index. The distinction between Cluster 1 and Cluster 2 is subjected to further analysis with regard to the similarity of the VPi4 index level.  
Other criteria in describing the characteristics of the clusters are related to a subjective evaluation of VPi4 level by the managers and the existence of Industry 4 strategy. Figure 4a summarizes the results of the subjective evaluation of Industry 4 level by the managers on a scale of 1 (low) to 5 (high). From the results, it is clear that, even in the case of Cluster 4, the managers perceived the level of Industry 4.0 at most companies at a low level. A relatively large proportion of managers reported their ranking to be low, similarly, in Cluster 3. The enterprises in Clusters 3 and 4 (mostly 80% of them) have no Industry 4.0 strategy (Figure 4b). The best subjective perception of the implementation of Industry 4.0 was in Clusters 1 and 2. The enterprises in these clusters (approximately 50% of them) also have an Industry 4.0 strategy. These characteristics divide the clusters into two groups (Figure 4b).