TY - DATA
T1 - Data underlying the master thesis: Tradable Mobility Credits for Long-Distance Travel in Europe – Impacts on the Modal Split between Air, Rail and Car
PY - 2023/03/03
AU - Sandro Tanner
AU - Jesper Provoost
UR - https://data.4tu.nl/articles/dataset/Data_underlying_the_master_thesis_Tradable_Mobility_Credits_for_Long-Distance_Travel_in_Europe_Impacts_on_the_Modal_Split_between_Air_Rail_and_Car/22202389/1
DO - 10.4121/22202389.v1
KW - long-distance travel
KW - Tradable Mobility Credits
KW - market-based pricing
KW - modal split
N2 - <p>Long-distance travels cause a large share of total greenhouse gas emissions. Environmental policy instruments aim to direct people’s travel behaviour, but at present, they are not sufficiently effective. As an alternative to existing policies, there is growing attention to market-based pricing instruments. Such an innovative policy instrument is the Tradable Mobility Credit Scheme (TMC). It allows for the direct internalisation of externalities into the price of mobility. This study specifies a TMC which shall be internationally implemented in Europe. The objective of the study is to estimate the impact of such a TMC on the modal split for long-distance leisure travel in Europe. Therefore, first, a mode choice model is created to estimate the current modal split of long-distance routes in Europe. Second, the TMC is incorporated into the mode choice model, and the modal split under TMC is estimated. A case study with 73 European cities and 2,998 OD-pair connections is conducted. Flight and train ticket prices are obtained by web scraping. The dataset includes the Python TMC mode choice model, raw data (flight and train ticket prices collected by web scraping) and output data. The output data includes both the output assuming inelastic demand and the output assuming elastic demand.</p>
ER -