## 4 Results  
### Linear and Logistic Regression Results  
The results of the linear regression analysis are presented in Table 3.  
In Figure 1, a graphical presentation of the linear regression analysis plot is presented. Figure 1: Graphical presentation of the linear regression model. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Independent Variables (Predictor Groups)** & **Dependent Variable** &
\begin{tabular}{c} **Standardized** \\ **Coefficients** \\ \end{tabular} & \(\boldsymbol{p}\) \\ \hline \hline \multicolumn{2}{c}{Website optimization (WOPT)} & 0.271 & 0.000 \\ \hline \multicolumn{2}{c}{Social media marketing (SMM)} & 0.214 & 0.214 \\ \hline \multicolumn{2}{c}{Email marketing (EMAIL)} & \(-\)0.062 & 0.000 \\ \hline \multicolumn{2}{c}{Content marketing (CMA)} & 0.366 & 0.000 \\ \hline \multicolumn{2}{c}{Customer relationship management (CRM)} & 0.219 & 0.621 \\ \hline \multicolumn{2}{c}{Online advertising (OA)} & 0.058 & 0.057 \\ \hline \multicolumn{2}{c}{Data management and analytics (DMA)} & 0.137 & 0.004 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results of the linear regression analysis. For the linear regression, website optimization (WOPT), social media marketing (SMM), email marketing (EMAIL), content marketing (CMA), customer relationship management (CRM), online advertising (OA), and data management and analytics (DMA) were observed as independent variables, while entrepreneur intentions (ENTIN) was observed as a dependent variable. The results indicate that several factors influence entrepreneurship intentions, with varying levels of significance. Website optimization (WOPT) showed a strong positive relationship with entrepreneurship intentions (ENTIN), reflected by a standardized coefficient of 0.271 and a highly significant \(p\)-value of 0.000. This suggests that optimizing websites is a key factor in supporting entrepreneural intentions among individuals. Social media marketing (SMM) also demonstrated a positive influence on entrepreneural intentions, with a standardized coefficient of 0.214. However, its \(p\)-value of 0.214 indicates that this relationship may not be statistically significant. In contrast, email marketing (EMAIL) presented a negative effect on entrepreneural intentions, with a coefficient of \(-0.062\) and a \(p\)-value of 0.000 showing a significant and negative association. This suggests that email marketing might deter entrepreneurship intentions or could be less effective in promoting entrepreneurial behaviors. Among all of the factors, content marketing (CMA) emerged as the most significant predictor, with a standardized coefficient of 0.366 and a \(p\)-value of 0.000. This strong positive relationship highlights the importance of content marketing in shaping and improving entrepreneural intentions. On the other hand, customer relationship management (CRM) showed a positive coefficient of 0.219, but its \(p\)-value of 0.621 indicates that this relationship was not statistically significant. Online advertising (OA), with a small positive coefficient of 0.058 and a \(p\)-value of 0.057, showed marginal significance, suggesting a weak association with entrepreneural intentions. Data management and analytics (DMA), however, exhibited a notable positive relationship, with a standardized coefficient of 0.137 and a \(p\)-value of 0.004, pointing to its significance in influencing entrepreneural intentions. Overall, content marketing and website optimization were important drivers, while email marketing may have a counterproductive impact on entrepreneural intentions. Next, a logistic regression was conducted. A stepwise regression was used to automatically select the significant predictor variables. The results are presented in Table 4.  
The results indicate that several key factors significantly influence the likelihood of achieving the desired outcome. Website optimization (WOPT) showed a strong positive effect, with a coefficient of 0.82 and a highly significant \(p\)-value of 0.000.