AK
A. Kalapouti
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Mobility Hubs in Low-Car Neighborhoods
A Stated Preference Study on Safety, Comfort and Intended Use
As car dependency generates increasing environmental, spatial and public health externalities, low-car urban development has emerged as a sustainable alternative, with neighbourhood mobility hubs serving as its central instrument. Their effectiveness, however, depends not only on the transport modes they offer but on whether users choose to engage with them, with safety and comfort acting as decisive conditions that shape perceived user experience and thereby influence intended hub use. To address this gap, a Systematic Literature Review and a Discrete Choice Experiment were conducted, analysed using a dummy-coded Multinomial Logit Model and a Latent Class Choice Model. All five evaluated attributes positively and significantly influenced intended hub use, with real-time information emerging as the most influential attribute and surveillance consistently the weakest, contextually explained by the low-car neighbourhood framing and sample composition. Preference heterogeneity was identified across five covariates, with female respondents and households with children showing stronger safety orientations and hub-familiar respondents prioritising information provision. Three latent preference classes were identified, only partially explained by observed characteristics. Findings align with the node-place-experience framework, indicating that successful hubs should prioritise real-time information and comfort amenities, complemented by learning-by-doing initiatives to support long-term adoption.
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As car dependency generates increasing environmental, spatial and public health externalities, low-car urban development has emerged as a sustainable alternative, with neighbourhood mobility hubs serving as its central instrument. Their effectiveness, however, depends not only on the transport modes they offer but on whether users choose to engage with them, with safety and comfort acting as decisive conditions that shape perceived user experience and thereby influence intended hub use. To address this gap, a Systematic Literature Review and a Discrete Choice Experiment were conducted, analysed using a dummy-coded Multinomial Logit Model and a Latent Class Choice Model. All five evaluated attributes positively and significantly influenced intended hub use, with real-time information emerging as the most influential attribute and surveillance consistently the weakest, contextually explained by the low-car neighbourhood framing and sample composition. Preference heterogeneity was identified across five covariates, with female respondents and households with children showing stronger safety orientations and hub-familiar respondents prioritising information provision. Three latent preference classes were identified, only partially explained by observed characteristics. Findings align with the node-place-experience framework, indicating that successful hubs should prioritise real-time information and comfort amenities, complemented by learning-by-doing initiatives to support long-term adoption.