# The Evaluation of Industry 5.0 Concepts: Social Network Analysis Approach
## 4 Results and Discussion  
### Social Network Analysis  
Tables 3-5 show the results of the centrality between firms. The results are shown through degree, closeness, betweenness, and eigenvector. Degree gives information about the importance of an actor in the network--the higher the degree, the greater the importance. Closeness represents the position of the actor in the network when compared with other actors. Betweenness measures if a certain actor lies on some of the nodes created in the network. Finally, eigenvector shows how the most important actors of the network are interconnected. Additionally, Figures 1-3 show the networks for the aforementioned Industry 5.0 approaches. In these figures, the red dots represent the firms that took part in the research, while the blue squares represent the parameters corresponding to the approach. \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Parameter** & **Degree** & **Closeness** & **Betweenness** & **Eigenvector** \\ \hline S1 & 0.397 & 0.432 & 0.180 & \(-\)0.405 \\ S2 & 0.110 & 0.353 & 0.009 & \(-\)0.113 \\ S3 & 0.500 & 0.469 & 0.250 & \(-\)0.513 \\ S4 & 0.459 & 0.453 & 0.174 & \(-\)0.512 \\ S5 & 0.233 & 0.383 & 0.035 & \(-\)0.287 \\ S6 & 0.137 & 0.360 & 0.022 & \(-\)0.155 \\ S7 & 0.144 & 0.361 & 0.017 & \(-\)0.157 \\ S8 & 0.356 & 0.418 & 0.151 & \(-\)0.351 \\ S9 & 0.185 & 0.371 & 0.060 & \(-\)0.163 \\ S10 & 0.130 & 0.358 & 0.027 & \(-\)0.133 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Results of centrality for the sustainability approach. \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Parameter** & **Degree** & **Closeness** & **Betweenness** & **Eigenvector** \\ \hline HC1 & 0.014 & 0.308 & 0.012 & 0.006 \\ HC2 & 0.260 & 0.383 & 0.079 & 0.168 \\ HC3 & 0.315 & 0.394 & 0.044 & 0.238 \\ HC4 & 0.527 & 0.469 & 0.120 & 0.392 \\ HC5 & 0.568 & 0.485 & 0.162 & 0.405 \\ HC6 & 0.753 & 0.569 & 0.334 & 0.485 \\ HC7 & 0.356 & 0.410 & 0.041 & 0.292 \\ HC8 & 0.404 & 0.425 & 0.051 & 0.327 \\ HC9 & 0.397 & 0.423 & 0.048 & 0.322 \\ HC10 & 0.301 & 0.394 & 0.024 & 0.257 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results of centrality for the human-centric approach. \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Parameter** & **Degree** & **Closeness** & **Betweenness** & **Eigenvector** \\ \hline R1 & 0.260 & 0.371 & 0.075 & \(-\)0.214 \\ R2 & 0.637 & 0.498 & 0.308 & \(-\)0.545 \\ R3 & 0.007 & 0.311 & 0.000 & \(-\)0.009 \\ R4 & 0.034 & 0.321 & 0.001 & \(-\)0.031 \\ R5 & 0.610 & 0.486 & 0.263 & \(-\)0.545 \\ R6 & 0.432 & 0.421 & 0.1 Table 3 gives information about the human-centric approach. As shown in Table 3, 10 human-centric parameters were analyzed. The most important factor for achieving human-centricity was HC6 (training and competence development of production employees with a task-specific focus). HC6 is also the closest to other actors in the network; it lies on several network nodes, and it is the most connected with other important actors of the network. HC6 was followed by HC5 (employee bonus systems for outstanding performances in production and/or innovation), which is the second most important actor in the network, meaning that it is usually found in Serbian manufacturing firms as a way to achieve human-centricity. This parameter is significantly connected to other parameters, but it is found on a minority of network nodes. Also, its eigenvector score is significant, because this parameter is connected to other important parameters, such as the previously mentioned HC6. The third most significant actor was HC4 (employee involvement in innovation development), which also had a good connection to the other  
Figure 1: Social network for the human-centric approach. Figure 2: Social network for the sustainability approach. actors, resulting in a relatively good eigenvector score; however, HC4\({}^{\prime}\)s betweenness had a low score, which means that fulfilling this parameter does not affect the fulfilment of other actors of the same network.