Impacts of COVID-19 Risk Perceptions on Train Travel Decisions: A Hierarchical Information Integration Analysis

Master thesis (2021)

Authors

T.W. van de Wiel Civil Engineering & Geosciences

Contributors

O. Cats Transport and Planning - CEG (supervisor 1)
S. Shelat Transport and Planning - CEG (supervisor 1)
E.J.E. Molin Transport and Logistics - TPM (supervisor 1)
J.W.C. van Lint Transport and Planning - CEG (supervisor 1)
Faculty
Civil Engineering & Geosciences
Copyright: © 2021 Thijs van de Wiel
COVID-19 Public transport Risk perception Hierarchical Information Integration Stated Choice Experiments
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Published Date

24-03-2021

Language

English

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Faculty

Civil Engineering & Geosciences

Abstract

The number of passengers using public transport has decreased drastically as a consequence of the global coronavirus pandemic in 2020. This study aimed to retrieve the importance of the perceived risk of getting infected with the coronavirus in choosing to go by train in the Netherlands. With a Hierarchical Information Integration approach it was possible to retrieve the perceived importance of different risk factors on the likelihood to get infected and evaluate this with respect to the taste for travel time and travel costs. After collecting 408 responses, a multiple linear regression revealed that on-board crowdedness was perceived as the most important risk factor. With discrete choice modelling we were able to calculate that an average traveller is willing to pay around 0,88 euros to reduce the seating occupancy with 10%. Furthermore, we were able to conclude that both the obligation to use face masks and extra cleansing of contact surfaces negatively influence the perceived risk and thereby increase the chances of going by train. Since extra cleansing is not extensively done yet in Dutch trains, it could, together with reducing crowding levels, be the key to nudge people back into the train.