%0 Generic
%A Geržinič, Nejc
%A van Dalen, Maurizio
%A Donners, Barth
%A Cats, Oded
%D 2024
%T [Supporting Data and Software] The perception of COVID-19 infection risk in Long-distance travel
%U 
%R 10.4121/8a77dbc7-cde0-4c5d-9763-53823af947a4.v1
%K Long-distance travel
%K COVID-19
%K Risk perception
%K Hierarchical information integration
%K Latent Class Choice Model
%X <p>The files included below are part of a research on passengers' perception of infection risk with COVID-19 and its relation to long-distance (international) travel.</p><p>&nbsp;</p><p>Data was collected through a Hierarchical Information Integration (HII) approach, where respondents were first asked to rate their perceived risk of infection, based on various safety measures. This subjective risk was then included in a mode choice experiment for long-distance trips, where respondents could choose between car, train and aircraft.</p><p><br></p><p>Information on the data and model can be found in the README file and the python script below.</p>
%I 4TU.ResearchData