## 4 Results and Analysis
### Structural Model Assessment  
The standard PLS-SEM bootstrapping procedure was applied for the assessment of path coefficients between the defined constructs. The results of the structural model assessment related to the direct relationships between the latent variables are shown in Table 4. The results of the statistical analysis confirmed that information and data literacy is positively related to digital transformation enablers (\(\beta\) = 0.318, \(p\) < 0.001) and that the relationship is statistically significant. Thus, hypothesis H1a is supported. The relationship between information security management and digital transformation enablers, as well as the relationship between digital piracy and digital transformation enablers, is not statistically significant. The conclusion is that hypotheses H1b and H1c are not supported. Regardless of that fact, it is worth stating that the obtained values for the path coefficient are negative but discrete. The remaining two constructs of digital citizenship, namely responsibility and collaboration, have a positive association with digital transformation enablers (\(\beta\) = 0.242, \(p\) < 0.001; \(\beta\) = 0.284, \(p\) < 0.001), and therefore the hypotheses H1d and H1e are supported. The results of the structural model assessment revealed that digital capability enablers are positively related to innovation (\(\beta\) = 0.463, \(p\) < 0.001). Also, the results obtained using the bootstrapping procedure confirmed the positive association between digital capability enablers and problem-solving capabilities (\(\beta\) = 0.482, \(p\) < 0.001). The results of the study supported both hypotheses H2a and H2b. The same bootstrapping procedure was applied to evaluate indirect effects and to detect the mediator effect. The results of the statistical analysis, representing the values of path coefficients for indirect effects, are shown in Table 5. A statistically significant indirect effect and a positive relationship between information and data literacy and innovation through digital transformation enablers was revealed (\(\beta\) = 0.147, t = 2.819, \(p\) < 0.01), as well as between information and data literacy and problem-solving capabilities through digital transformation enablers (\(\beta\) = 0.153, t = 3.039, \(p\) < 0.01). Information security management did not report a statistically significant indirect relationship with innovation and problem-solving capabilities through digital transformation enablers. Also, the indirect association between digital piracy and innovation as well as with problem-solving capabilities through digital transformation enablers is not statistically significant. Despite this, it is worth stating \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline
**Constructs** & **1** & **2** & **3** & **4** & **5** & **6** & **7** & **8** \\ \hline
1. COL: Collaboration & 0.834 & & & & & & & & \\
2. DIPI: Digital Piracy & 0.035 & 0.911 & & & & & & \\
3. DTE: Digital Transformation Enablers & 0.435 & 0.190 & 0.756 & & & & & \\
4. IDL: Information and Data Literacy & 0.403 & 0.382 & 0.543 & 0.817 & & & & \\
5. IN: Innovation & 0.397 & 0.180 & 0.459 & 0.648 & 0.788 & & & \\
6. ISM: Information Security Management & 0.232 & 0.460 & 0.387 & 0.703 & 0.477 & 0.854 & & \\
7. PS: Problem-Solving & 0.245 & 0.256 & 0.481 & 0.587 & 0.502 & 0.572 & 0.791 & \\
8. RES: Responsibility & 0.132 & 0.513 & 0.427 & 0.579 & 0.396 & 0.561 & 0.476 & 0.842 \\ \hline \hline \end{tabular} Source: Authors.  
\end{table} 
Table 2: Discriminant validity (Fornell–Lracker criterion).