Modelling of pre and post Covid-19’s impact on employee’s mode choice behavior

Abstract

Public transportation is one of the most affected systems by the pandemic. The utilization of public transit during the pandemic made the people feel unsafe. So, the use of private transportation modes for daily mobility has increased. This study aims to understand the COVID-19 impact on the employee's mode choice. The survey methodology adopted in this study is a web-based survey in which questionnaires are distributed via various social media platforms and collected respondents' opinions. After collecting the responses, statistical analysis of socio-demographic characteristics, mode choice preferences, and factors affecting the mode choice were performed. From the results, it is observed that there is a mode shift from public transportation to private transportation to avoid the spread of COVID-19, and also there is a marginal increase in non-motorized transportation modes post COVID-19. The finding indicates the factors related to the spread of the infection, are the most important factors to consider when choosing a mode of transportation following COVID-19. Multinomial logistic regression and artificial neural network models were developed to analyze the mode choice of travelers pre and post COVID-19.