Exploring factors associated with commute mode choice: An application of city-level general social survey data

Developing sustainable transportation systems in a city can be substantially assisted by promoting environmentally friendly transportation modes such as walking, cycling, and public transit rather than private cars. Strategies for promoting these desirable transportation modes can be effectively identified based on a sound understanding of how citizens choose a travel mode. In this study, we sought to enhance this understanding by exploring factors associated with commute mode choice utilizing data from a general social survey in Seoul, South Korea. Based on the data, parametric and non-parametric statistical models based on classification tree and multilevel logistic regression approaches, respectively, were developed as a way to capture influential factors associated with the mode choice decision. The models illustrate that commuters' socio-demographic characteristics such as income, occupation, gender, and residence duration tend to significantly influence mode choice. In addition, they showed that respondents' attitudes and behaviors, including the amount of time spent on the internet and self-assessed social status, can be strongly associated with mode choice. This study is also meaningful in that it demonstrates the potential applicability of general social survey data for investigating travel behavior considering various factors that are rarely included in general transportation surveys.