Shared mobility services, which facilitate the access to different modes without the need to own them, is favouring increasingly multimodal mobility habits among urban travellers. Understanding how these new services are integrated into individuals’ mobility patterns together with conventional modes is essential to understand the role that they play in improving accessibility and promoting sustainable urban mobility. To address this topic, two sub-samples have been extracted from a macro-survey conducted in the Region of Madrid: (i) users who have adopted shared micromobility (kick-scooter and bike-sharing) and (ii) users who have adopted shared macromobility (i.e., car- and moped-sharing). Using a Latent Class Analysis, we compare the profiles of each type of shared mobility user. The results show that three out of four classes can be found in both sub-samples. Specifically, a car-oriented class who rarely uses shared mobility, an active & public transport traveler class who mostly uses public transport and occasionally shared mobility; and a multimodal class who uses shared mobility around 3 and 4 times a week. In both cases, the most intensive users are clustered into classes whose mobility patterns and socio-economic profiles differ substantially. Finally, the model provides robust results regarding the impact of teleworking and place of residence on individuals’ multimodal travel habits, factors for which the previous literature had provided limited conclusions. These results have been used to provide policy recommendations specific to the role that each type of service plays in individuals’ mobility habits.
Shared mobility services, which facilitate the access to different modes without the need to own them, is favouring increasingly multimodal mobility habits among urban travellers. Understanding how these new services are integrated into individuals’ mobility patterns together with conventional modes is essential to understand the role that they play in improving accessibility and promoting sustainable urban mobility. To address this topic, two sub-samples have been extracted from a macro-survey conducted in the Region of Madrid: (i) users who have adopted shared micromobility (kick-scooter and bike-sharing) and (ii) users who have adopted shared macromobility (i.e., car- and moped-sharing). Using a Latent Class Analysis, we compare the profiles of each type of shared mobility user. The results show that three out of four classes can be found in both sub-samples. Specifically, a car-oriented class who rarely uses shared mobility, an active & public transport traveler class who mostly uses public transport and occasionally shared mobility; and a multimodal class who uses shared mobility around 3 and 4 times a week. In both cases, the most intensive users are clustered into classes whose mobility patterns and socio-economic profiles differ substantially. Finally, the model provides robust results regarding the impact of teleworking and place of residence on individuals’ multimodal travel habits, factors for which the previous literature had provided limited conclusions. These results have been used to provide policy recommendations specific to the role that each type of service plays in individuals’ mobility habits. Read More
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