Preferences for Demand-Responsive Transit Services in Transit-Poor New Towns: An Integrated Choice and Latent Variable Approach
Dongjun Chu, Yumi Jeong, Myungsik Do, Doh Kyoum Shin, Wanhee Byun, Seheon KimNew towns often experience a structural transit gap in early stages, where transport supply lags behind population growth. Demand-responsive transit (DRT) has emerged as a promising complementary solution; however, most studies rely on MNL-based ICLV models that do not account for error covariance across alternatives. This study applies an ICLV model, integrating an Error Component Mixed Logit kernel with latent variables, to analyze mode choice behavior in transit-poor new towns. Based on an SP-off-RP survey of 644 residents in new towns, 2576 observations were analyzed. The model incorporates five latent variables, including Transit Dissatisfaction, Convenience, Safety, Travel Time, and Travel Companion Sensitivity, and captures unobserved correlations through a two-level nesting structure. Results show that DRT has a significantly positive alternative-specific constant, indicating latent acceptance beyond observable attributes. DRT adoption is more common among transit-poor new town residents and highly educated individuals, but less common among car owners. Users are more sensitive to access and waiting time than to in-vehicle time. Convenience, Safety, and Travel Time significantly influence DRT utility, while Travel Companion Sensitivity reveals heterogeneous effects across modes. These findings provide behavioral insights for designing effective DRT strategies in transit-poor new towns.