Although the coronavirus disease (COVID-19) has been under control in Taiwan, the accumulated number of confirmed patients has reached up to 14,853, where 661 cases were fatal with a fatality rate of 4.45% (since the virus outbreak until July 1, 2021). Globally, the toll of confirmed cases has reached 182,641,391 people, where 3,955,679 cases were fatal with a fatality rate of 2.17% (from the virus outbreak until July 1, 2021). Considering the disease has not been under control yet and IT still significantly influences people’s daily travel behavior worldwide, it is urgent to investigate as to what extent it changes people’s travel habits. Therefore, we conducted a survey from April 24 to May 2, 2020, to obtain data on Taiwanese people’s travel behavior before and after the outbreak of COVID-19. Two models, logistic regression and ordered logit models, were used. As for the models’ performance, the estimated thresholds of the ordered logit model are significantly positive, and its coefficient is smaller than that of the logistic model, indicating that the estimated coefficients would be overestimated if the dependent variable is dichotomous. Hence, this study suggests that the influence of COVID-19 on travel behaviors in Taiwan can be explained by the ordered logit models. Several important conclusions are described as follows. First, people might significantly reduce travel activities related to social entertainment during the pandemic outbreak. Second, the total travel activities by private vehicles are significantly reduced, while there is no significant decrease in the use of transit. Finally, the important explanatory variables included the importance of the time to promote government policies (such as implementing the real-name registration system for mask purchases, publishing confirmed cases, and establishing the transit disinfection system), types and number of weekly activities, and storage of various types of consumer goods. The results of our study can serve as an important reference for accommodating similar scales of pandemics occurring in the future.
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