E-scooter and public transport are two different transportation modes, each one having its own audience. The latter is a very old means of transport, existing for decades, while the former is relatively new. In this thesis, an investigation is conducted between public transport and e-scooter ridership to understand if there is any relation in the demand or on the external factors that affect people’s preference on one of the two. The study area is Austin, Texas and the study period for e-scooter ridership is from April 2018 till August 2020. Time intervals are created for e-scooter trips depending on the actual demand. In addition, Automated Passenger Counting (APC) datasets are used for public transport for the years 2017 and 2019, from August till December in both years. The Iterative Proportional Fitting Procedure (IPFP) is applied on APC datasets to create origin-destination matrixes with passenger trips. Moreover, both public transport and e-scooter trips are used as count data and the Negative Binomial Model (NBM) is applied. In these models, the dependent variable is the total number of trips, while the independent variables are external factors, such as the built environment, weather and census data. Origin and destination trips are modelled separately, so in total 40 models are generated. Finally, a comparison in public transport trips between 2017 and 2019 is conducted in e-scooter hotspot areas, to identify if the arrival of e-scooters in 2018 had an impact in public transport travel behaviour.     «

E-scooter and public transport are two different transportation modes, each one having its own audience. The latter is a very old means of transport, existing for decades, while the former is relatively new. In this thesis, an investigation is conducted between public transport and e-scooter ridership to understand if there is any relation in the demand or on the external factors that affect people’s preference on one of the two. The study area is Austin, Texas and the study period for e-scooter...     »