## 3 Results
### Descriptive Statistical Analysis
Table 6 reports the results of the demographic factors affecting individuals' criteria for choosing a specific pick-up point for courier services for the Greek case study. Males exhibit a stronger preference for time flexibility compared to females, which is statistically significant at the 1% level. Age plays a significant role, with older individuals showing a preference for time flexibility and lower cost, although this effect diminishes as age increases. University student status does not show significant effects across the criteria examined. Regarding income level, lower-income individuals prioritize proximity (distance from home), whereas higher-income individuals are less concerned with delivery speed. Overall, the findings highlight the importance of considering demographic characteristics in understanding consumer behaviors and preferences within the courier delivery service context. Table 7 reports the results of the demographic factors affecting individuals' criteria for choosing a specific pick-up point for courier services for the Italian case study. Males show a stronger preference for lower cost and a weaker preference for the time flexibility criterion compared to females. In addition, older individuals are more concerned about lower cost and delivery speed; however, the effect of age is, again, non-linear. Finally, both university students and higher-income individuals seem to be more concerned about the distance from home criterion, while lower-income individuals are less concerned about user-friendliness. \begin{table}
\begin{tabular}{l l l l l l} \hline \hline  & **(1)** & **(2)** & **(3)** & **(4)** & **(5)** \\ \hline \multicolumn{6}{l}{**Time Flexibility**} & **Distance from Home** & **Lower Cost** & **Delivery Speed** & **User Friendliness** \\ \hline Gender & \(0.174\)*** & \(0.116\) & \(-0.125\) & \(0.001\) & \(0.040\) \\  & (\(0.046\)) & (\(0.139\)) & (\(0.096\)) & (\(0.062\)) & (\(0.105\)) \\ Age & \(0.707\)*** & \(0.219\) & \(0.665\)** & \(0.411\) & \(0.108\) \\  & (\(0.244\)) & (\(0.702\)) & (\(0.304\)) & (\(0.295\)) & (\(0.179\)) \\ Age\({}^{2}\) & \(-0.132\)** & \(-0.070\) & \(-0.189\)*** & \(-0.109\)* & \(-0.015\) \\  & (\(0.056\)) & (\(0.131\)) & (\(0.071\)) & (\(0.063\)) & (\(0.029\)) \\ University student & \(-0.071\) & \(0.086\) & \(-0.108\) & \(0.079\) & \(0.172\) \\  & (\(0.106\)) & (\(0.215\)) & (\(0.116\)) & (\(0.129\)) & (\(0.112\)) \\ Low income class & \(0.053\) & \(0.386\)*** & \(0.074\) & \(0.048\) & \(-0.054\) \\  & (\(0.125\)) & (\(0.147\)) & (\(0.092\)) & (\(0.084\)) & (\(0.124\)) \\  & \(-0.118\) & \(0.434\) & \(-0.459\) & \(-0.405\)** & \(0.235\) \\  & (\(0.260\)) & (\(0.336\)) & (\(0.305\)) & (\(0.159\)) & (\(0.173\)) \\ \hline Observations & \(1054\) & \(1054\) & \(1054\) & \(1054\) & \(1054\) \\ Nagelkerke R\({}^{2}\) & \(0.013\) & \(0.011\) & \(0.032\) & \(0.014\) & \(0.004\) \\ \hline \hline \end{tabular} Notes: All regressions are estimated with robust-clustered standard errors at the municipality level. Standard errors are given in parentheses. *, **, and *** denote statistical significance at 10%, 5%, and 1%.  
\end{table} 
Table 6: Empirical results from logistic regression models: criteria for choosing a specific pick-up point (Greek case study). \begin{table}
\begin{tabular}{l l l l l l} \hline \hline  & **(1)** & **(2)** & **(3)** & **(4)** & **(5)** \\ \hline \multicolumn{6}{l}{**Time Flexibility**} & **Distance from Home** & **Lower Cost** & **Delivery Speed** & **User Friendliness** \\ \hline Gender & \(-0.613\)** & \(0.432\) & \(0.539\)* & \(-0.228\) & \(0.581\) \\  & (\(0.278\)) & (\(0.391\)) & (\(0.305\)) & (\(0.306\)) & (\(0.299\)) \\ Age & \(0.313\) & \(0.519\) & \(-1.013\)*** & \(-0.892\)** & \(0.079\) \\  & (\(0.323\)) & (\(0.425\)) & (\(0.341\)) & (\(0.355\)) & (\(0.328\)) \\ Age\({}^{2}\) & \(-0.111\) & \(-0.055\) & \(0.215\)*** & \(0.149\)* & \(0.047\)* \\  & (\(0.079\)) & (\(0.109\)) & (\(0.077\)) & (\(0.082\)) & (\(0.079\)) \\ \hline \hline \end{tabular}
\end{table}