| dc.description.abstract | The COVID-19 pandemic changed people's daily activity patterns, which can be reflected by travel purposes, but there is only limited research focused on this area. Besides, literature has revealed that the disadvantaged group had suffered more than the majority of the society, so it is also interesting to find out whether such social disparity existed in the Netherlands. Therefore, the main research question is proposed:
Did the COVID-19 pandemic significantly influenced people's travel activities and did the impacts varied with income and urban-rural settings of residence?
Four major types of travel purposes were studied: work-related, leisure, shopping, and visit/stay. By descriptive analysis, it is observed that the reduction of mobility was full-scale across all travel purposes and that the activity diversity shrank, from 1.18 travel purposes engaged per person per day to only 1.01 per day.
The thesis defines 'travel probability' as the ratio of number of people travelled for the given purpose to the total number of respondents in the sample (fraction). Changes of average distance, time travelled, and travel probability were plotted in several line graphs by every travel purpose and the variation with income and urbanization levels were examined. Overall, work travel was the most negatively impacted, shopping travel stayed stable to a large extent, and visit travel, the least frequent activity, was also strongly impacted. Among people who travelled outdoors, leisure travel distance decreased in two waves of the pandemic outbreak compared to last year, but its average travel time was longer in all month-groups of 2020, suggesting people probably switched recreational travel to within neighbourhood's scope. The varied impact of pandemic in income was most noticeable in work travel, but for other travel purposes the patterns were not as clear; variations with urbanization levels were even smaller. Some assumptions were derived from this section.
Binary regression models denied the assumptions partly. The urbanization classes explained shopping travel probability best, and partly explained work and visit travel probability. Income level was not as a good predictor as expected. Level of education was a much better parameter predicting travel probability for all travel purposes that could also reveal disparity in social status. Yet, the model showed perfect goodness of fit when interpreting work travel patterns.
By adding interaction terms between disparity indices of interest (income, education, and urbanity levels) and month-groups (pandemic stages) to regression models, significant improvements from basic models were found for work and shopping. Respondents living in the most strongly urbanized cities (U1) and with higher level of education (EDU3) were two factors that their influence on work travel probability depended significantly on the pandemic's effects. The effects of middle- and high-level of education on shopping travel probability also showed significant dependency on the first wave of the outbreak. No significant improvements were found in leisure or visit travel models. The impacts socio-demographic factors on leisure and visit travel probability were independent from the pandemic.
This thesis has several limitations with regard to sample weighting, survey designs, model goodness of fit, and choice of variables and models. But it also contributes to the understanding to the change of travel activities under the pandemic's conditions in Dutch context. The thesis also revealed potential supressed travel demand among low-income people as well as their limited accessibility to good-quality shopping malls and attached importance to built environment of neighbourhoods. Future research can further investigate the impact of different stages of pandemic by adding data of 2021&2022. | |
