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This study leverages a city-scale GPS dataset of 14,029 e-scooter trips recorded over a three-month period in 2021 within the Mannheim\/Ludwigshafen metropolitan area in Germany. For the first time, our analysis integrates the discrete choice modelling framework with space syntax theory using such large-scale revealed preference data, uncovering new insights into the impact of spatial configuration on routing behaviour. The results highlight the significant role of spatial configuration in e-scooter routing, with space syntax metrics consistently improving model performance and suggesting that riders avoid both places that are not well-integrated on a regional and highly accessible on a local level. Results also reveal that dedicated bicycle infrastructure, including bike lanes and tracks, reduces perceived travel distance by over 51% for e-scooter riders. 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