Description
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.
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.
Information on the data and model can be found in the README file and the python script below.
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.
Information on the data and model can be found in the README file and the python script below.
| Date made available | 2024 |
|---|---|
| Publisher | TU Delft - 4TU.ResearchData |
| Date of data production | 2024 |
| Geographical coverage | The Netherlands |
Research output
- 1 Article
-
COVID-19 risk-perception in long-distance travel
Geržinič, N., van Dalen, M. & Cats, O., 2024, In: European Transport Studies. 1, 17 p., 100003.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile32 Downloads (Pure)
Cite this
- DataSetCite