Abstract:

This study collects, reveals preference data, and estimates a comprehensive mode choice model between several shared and personal micro-mobility modes (e-bikes, e-scooters) and more established transport modes (public transport, car, bike, walk). The authors contribute by collecting a large dataset with matching GPS tracks, booking data and survey data for more than 500 travellers, and by estimating a first choice model between eight transport modes, including shared e-scooters, shared e-bikes, personal e-scooters, and personal e-bikes. The authors find that trip distance, precipitation, and access distance are fundamental to micro-mobility mode choice. Substitution patterns reveal that personal e-scooters and e-bikes emit less CO2 than the transport modes they replace, while shared e-scooters and e-bikes emit more CO2 than the transport modes they replace. The results enable researchers and planners to test the effectiveness of policy interventions through transport simulations. Service providers can use our findings on access distances to optimize vehicle repositioning. City administrations can use these insights to justify public subsidies for personal e-bike/e-scooter sales and investments in bike lanes to increase their mode share.