# A Lifestyle-Based Perspective on the Mobility Choices and Preferences of Urban Travelers
## 4 Results
### Socioeconomic Characteristics of Attitudinal Clusters  
The socioeconomic characteristics of the clusters (gender, age, job status, access to car, education level, monthly budget, cost category of highest spending) were tested for significant differences using Chi-square tests with corrections by [PERSON]'s Exact tests when necessary (Table 2). Gender, age, job status, education level and monthly budget were found to differentiate significantly across the attitudinal clusters (\(p<0.05\)). This was not the case for car access, which was uniformly high (\(>\)90%) across the entire sample. \begin{table}
\begin{tabular}{c c c c c c c} \hline \multirow{2}{*}{**Characteristic**} & \multirow{2}{*}{**Value**} & **Cluster 1** & **Cluster 2** & **Cluster 3** & **Cluster 4** & **No. of** \\  & & **(Eco-Conscious** & **(Digitally Engaged** & **(Cautious Green** & **(Socially Driven** & **Replies** \\  & & **Social Adapters)** & **Conventionalists)** & **Conservatives)** & **Digital Enthusiasts)** & **Replies** \\ \hline \multirow{3}{*}{Gender *} & Female & 60.9\% & 50.0\% & 44.9\% & 35.4\% & \multirow{3}{*}{399} \\  & Male & 37.9\% & 49.2\% & 54.2\% & 64.6\% & \\  & Other & 1.1\% & 0.8\% & 0.9\% & 0.0\% & \\  & Cluster population & 87 & 126 & 107 & 79 & 399 \\ \hline \multirow{3}{*}{Age *} & \(\leq\)24 & 14.9\% & 14.3\% & 6.5\% & 20.3\% & \multirow{3}{*}{35.4\%} \\  & 25-34 & 23.0\% & 23.8\% & 27.1\% & 36.7\% & \\  & 35-44 & 16.1\% & 31.7\% & 28.0\% & 24.1\% & \\  & 45-54 & 17.2\% & 17.5\% & 22.4\% & 11.4\% & \\  & 55-64 & 17.2\% & 10.3\% & 12.1\% & 6.3\% & \\  & \(\geq\)65 & 11.5\% & 2.4\% & 3.7\% & 1.3\% & \\  & Cluster population & 87 & 126 & 107 & 79 & 399 \\ \hline \multirow{3}{*}{Access to car} & Yes & 90.8\% & 92.1\% & 96.3\% & 93.7\% & \multirow{3}{*}{399} \\  & No & 9.2\% & 7.9\% & 3.7\% & 6.3\% & \\  & Cluster population & 87 & 126 & 107 & 79 & 399 \\ \hline \multirow{3}{*}{Job status *} & Freelance & 44.8\% & 42.9\% & 39.3\% & 49.4\% & \multirow{3}{*}{399} \\  & Student & 9.2\% & 11.9\% & 7.5\% & 19.0\% & \\ \cline{1-1}  & Employee & 29.9\% & 42.9\% & 43.9\% & 27.8\% & \\ \cline{1-1}  & Householding/other & 4.6\% & 0.0\% & 2.8\% & 2.5\% & \\ \cline{1-1}  & Retired/unemployed & 11.5\% & 2.4\% & 6.5\% & 1.3\% & \\ \cline{1-1}  & Cluster population & 87 & 126 & 107 & 79 & 399 \\ \hline \multirow{3}{*}{Education level *} & High school & 14.9\% & 13.5\% & 9.3\% & 17.7\% & \multirow{3}{*}{399} \\  & education or less & & 25.4\% & 20.6\% & 21.5\% & \\ \cline{1-1}  & Some college & 29.9\% & 46.8\% & 54.2\% & 53.2\% & \\ \cline{1-1}  & Bachelor’s degree & 14.9\% & 14.3\% & 15.9\% & 7.6\% & \\ \cline{1-1}  & Cluster population & 87 & 126 & 107 & 79 & 399 \\ \hline \end{tabular}
\end{table} 
Table 2: Socioeconomic characteristics of attitudinal cluster analysis. Cautious Green Conservatives (cluster 3) and Socially Driven Digital Enthusiasts (cluster 4) consist predominantly of males, while Eco-Conscious Social Adapters (cluster 1) have the highest percentage of females across all clusters. Digitally Engaged Conventionalists (cluster 2) are evenly distributed between males and females. Socially Driven Digital Enthusiasts (cluster 4) have the highest percentage of younger individuals (aged below 24 and 25-34 years) among all clusters, while Eco-Conscious Social Adapters (cluster 1) include the highest percentage of older individuals (aged 55-64 or above 65 years). Digitally Engaged Conventionalists (cluster 2) predominantly consist of individuals aged 35-44 years, while the highest percentage of individuals aged 45-54 years can be found within Cautious Green Conservatives (cluster 3). However, cluster 3 also shows relatively balanced representation across the 25-34, 35-44 and 45-54 age groups. In terms of job status, freelancers are most prevalent within Eco-Conscious Social Adapters (cluster 1) and Socially Driven Digital Enthusiasts (cluster 4).