The impact of covid-19 on modal shift in long-distance travel

Nejc Geržinič*, Maurizio van Dalen, Barth Donners, Oded Cats

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

Abstract

This research aims to analyse the perception of covid-19 infection risk in long-distance travel in Europe and how it impacts mode choice and travel behaviour. We make use of an HII variant type experiment and model it by means of a latent class choice model, where we uncover four distinct user groups. For infection risk perception, we apply a novel approach in the field, utilising a weighted least squares regression, to obtain segment-specific regression functions, based on their respective probabilistic segment allocations. Some segments exhibit risk-aversion behaviour that is time-based (longer journeys perceived as more risky), whereas others see it as time-independent. With respect to modal preferences, the four segments either show a strong preference or aversion to one of the two land-based modes: car-loving, car-averse (using train or air), trainloving and train-averse (using car and air).
Original languageEnglish
Number of pages7
Publication statusPublished - 2023
EventhEART 2023: 11th Symposium of the European Association for Research in Transportation - HIT E51, Campus Hoenggerberg, ETH Zurich, Zurich, Switzerland
Duration: 6 Sept 20238 Sept 2023
Conference number: 11
https://heart2023.org/

Conference

ConferencehEART 2023
Country/TerritorySwitzerland
CityZurich
Period6/09/238/09/23
Internet address

Keywords

  • COVID-19
  • Discrete choice modelling
  • Hierarchical information integration
  • Risk perception
  • Travel behaviour

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