Analysis of Changes in Railway Passenger Mobility to the New Normal in the Post-COVID-19 Era

Abstract

The COVID-19 pandemic posed a great challenge in railway industry, as it changed passengers' behavior towards travelling, which affected their mobility choice in turn. This paper focuses on factors influencing railway passengers' behavior in the new normal, based on 3,318 valid responses collected through an online survey. Variance analysis and exploratory factor analysis were conducted to identify key determinants of passengers' mode choice. Building on these results, a structural equation model (SEM) was developed to describe the interrelationships among passengers' personal attributes, mode characteristics, and travel intentions. The whole modelling process involved selecting latent variables, designing the initial theoretical framework, developing the questionnaire, and estimating the model using maximum likelihood in AMOS, followed by calibration and modification until acceptable parameter significance and model fit were achieved. Considering the trends and uncertainties related to railway industry, 4 development scenarios were constructed based on political, economic, and social factors. The sample data from 4 scenarios were input into the modified SEM model separately. In the end, we could obtain 4 similar SEMs adapting to different scenarios by adjustment. This will provide a scientific basis for formulating railway development strategies in the future for the new normal of post-COVID-19 era.