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Estimating Mode of Transport in Daily Mobility during the COVID-19 Pandemic Using a Multinomial Logistic Regression Model

Author

Listed:
  • Jaroslav Mazanec

    (Department of Quantitative Methods and Economic Informatics, Faculty of Operation and Economics of Transport and Communications, University of Zilina, 01026 Zilina, Slovakia)

  • Veronika Harantová

    (Department of Road and Urban Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, 01026 Zilina, Slovakia)

  • Vladimíra Štefancová

    (Department of Railway Transport, Faculty of Operation and Economics of Transport and Communications, University of Zilina, 01026 Zilina, Slovakia)

  • Hana Brůhová Foltýnová

    (Faculty of Social and Economic Studies, Jan Evangelista Purkyňe University in Ústí nad Labem, 40096 Ústí nad Labem, Czech Republic)

Abstract

At the beginning of 2020 there was a spinning point in the travel behavior of people around the world because of the pandemic and its consequences. This paper analyzes the specific behavior of travelers commuting to work or school during the COVID-19 pandemic based on a sample of 2000 respondents from two countries. We obtained data from an online survey, applying multinomial regression analysis. The results demonstrate the multinomial model with an accuracy of almost 70% that estimates the most used modes of transport (walking, public transport, car) based on independent variables. The respondents preferred the car as the most frequently used means of transport. However, commuters without car prefer public transport to walking. This prediction model could be a tool for planning and creating transport policy, especially in exceptional cases such as the limitation of public transport activities. Therefore, predicting travel behavior is essential for policymaking based on people’s travel needs.

Suggested Citation

  • Jaroslav Mazanec & Veronika Harantová & Vladimíra Štefancová & Hana Brůhová Foltýnová, 2023. "Estimating Mode of Transport in Daily Mobility during the COVID-19 Pandemic Using a Multinomial Logistic Regression Model," IJERPH, MDPI, vol. 20(5), pages 1-15, March.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:4600-:d:1088208
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    1. Damianos P. Sakas & Nikolaos T. Giannakopoulos & Nikos Kanellos & Christos Christopoulos & Kanellos S. Toudas, 2023. "Determining Factors for Supply Chain Services Provider Selection and Long-Term Relationship Maintenance: Evidence from Greece," Logistics, MDPI, vol. 7(4), pages 1-21, October.
    2. Riqing Liao & Wei Liu & Yuandao Yuan, 2023. "Resilience Improvement and Risk Management of Multimodal Transport Logistics in the Post–COVID-19 Era: The Case of TIR-Based Sea–Road Multimodal Transport Logistics," Sustainability, MDPI, vol. 15(7), pages 1-21, March.

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