## 4 Survey Results and Analysis
### Agreement Analysis  
To determine whether there were different opinions (any significant differences in their perception) regarding online training between participants with different positions in the organization (manufacturing team leader, TESA and production worker), as well as to test Hypothesis 1 (H1), the Kruskal-Wallis \(H\)-test was applied.  
Hypothesis 1 (H1). Employee satisfaction associated with online training on the SSM.ro platform varies depending on their role in the organization.  
The Kruskal-Wallis \(H\)-test (sometimes also called the \"one-way ANOVA on ranks\") is a nonparametric test based on ranks that can be used to determine whether there are statistically significant differences between two or more groups of an independent variable (consisting of different subjects) on a continuous or ordinal dependent variable [28; 46; 58; 59; 60; 61; 62; 63; 64]. The results of the Kruskal-Wallis \(H\)-test are shown in Table 4. Table 4 shows that within the items presented above, there are significant results after applying the Kruskal-Wallis \(H\)-test (\(p<0.05\)); there are different opinions between the participants in the online training with different functions in the organization, a fact noted for items I.01 \(\div\) I.08, I.10 and I.14. After applying the Kruskal-Wallis \(H\)-test, to perform the Pairwise Comparisons and to identify possible differences between the independent variables (team leader, TESA and production worker), a post hoc [PERSON]'s multiple comparison test was performed [46; 62]. The results for post hoc [PERSON]'s multiple comparison test are shown in Table 5.  
Therefore, in conformity with the [PERSON] test results, Table 5 highlights the presence of the following statistical differences between the production worker and manufacturing team leader in I.02, I.03, I.05 and I.14. Additionally, it identified statistical differences between the production worker and TESA in I.01, I.02, I.03, I.04, I.05, I.06, I.08 and I.14. In addition, it indicated statistical differences between the manufacturing team leader and TESA in I.01, I.02 and I.07.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Cod** & \multicolumn{3}{c}{**Percentage of Respondents Scoring (\%) for Likert Scale Priority**} & **RII** & **Rank** & **Kruskal-Wallis \(p\)-Value** \\ \cline{2-7}
**Items** & **1** & **2** & **3** & **4** & **5** & **Score** & **Rank** & **Kruskal-Wallis \(p\)-Value** \\ \hline I.01 & 0 & 10 & 21 & 160 & 740 & 0.931 & 1 & \textless{}0.001 * \\ I.02 & 0 & 2 & 48 & 324 & 510 & 0.884 & 2 & \textless{}0.001 * \\ I.03 & 0 & 6 & 60 & 344 & 455 & 0.865 & 3 & \textless{}0.001 * \\ I.04 & 0 & 6 & 96 & 424 & 295 & 0.821 & 10 & 0.002 * \\ I.05 & 0 & 10 & 93 & 324 & 415 & 0.842 & 5 & \textless{}0.001 * \\ I.06 & 0 & 4 & 129 & 388 & 290 & 0.811 & 12 & \textless{}0.001 * \\ I.07 & 25 & 146 & 192 & 136 & 20 & 0.519 & 14 & 0.007 * \\ I.08 & 1 & 16 & 132 & 408 & 225 & 0.782 & 13 & 0.001 * \\ I.09 & 0 & 0 & 78 & 508 & 235 & 0.821 & 11 & 0.108 \\ I.10 & 0 & 2 & 72 & 464 & 295 & 0.833 & 6 & 0.042 * \\ I.11 & 0 & 2 & 87 & 464 & 270 & 0.823 & 8 & 0.432 \\ I.12 & 0 & 0 & 81 & 492 & 250 & 0.823 & 9 & 0.329 \\ I.13 & 0 & 2 & 75 & 464 & 290 & 0.831 & 7 & 0.117 \\ I.14 & 0 & 0 & 87 & 384 & 375 & 0.846 & 4 & \textless{}0.001 * \\ \hline \hline \end{tabular}  
* The Kruskal–Wallis \(H\)-test result is significant at the significance level at \(p\)-value < 0.05.  
\end{table}
Table 4: Results for Relative Importance Index (RII), and Kruskal–Wallis \(H\)-test.