Non-commuting intentions during COVID-19 in Nanjing, China: A hybrid latent class modeling approach

Xinwei Ma; Shuai Zhang; Minqing Zhu; Tao Wu; Mingjia He; Hongjun Cui

doi:10.1016/j.cities.2023.104341

Non-commuting intentions during COVID-19 in Nanjing, China: A hybrid latent class modeling approach

Cities. 2023 Jun:137:104341. doi: 10.1016/j.cities.2023.104341. Epub 2023 Apr 24.

Authors

Xinwei Ma¹, Shuai Zhang¹, Minqing Zhu², Tao Wu³, Mingjia He^{1

4}, Hongjun Cui¹

Affiliations

¹ School of Civil and Transportation Engineering, Hebei University of Technology, Tianjin 300401, China.
² School of Architecture and Art Design, Hebei University of Technology, Tianjin 300401, China.
³ Mental Health Education Center, Hebei University of Technology, Tianjin 300401, China.
⁴ Department of Civil Engineering, Technology University of Delft, 2600 AA Delft, Netherlands.

Abstract

Non-commuting travel is essential for people to meet daily demands and regulate mental health, which is greatly disrupted due to the COVID-19 pandemic. To explore non-commuting intentions during COVID-19 across different groups of residents, this paper uses online survey data in Nanjing and constructs a hybrid latent class choice model that combines sociodemographic characteristics and psychological factors. Results showed that the respondents can be divided into two groups: the "cautious" group versus the "fearless" group. The "cautious" group with lower willingness to travel tend to be older, higher-income, higher-educated, female and full-time employees. Furthermore, the "cautious" group with higher perceived susceptibility is more obedient to government policies. In contrast, the "fearless" group is significantly affected by perceived severity and is more inclined to turn to personal protection against the pandemic. These results suggested that non-commuting trips were influenced not only by individual characteristics but also by psychological factors. Finally, the paper provides implications for the government to formulate COVID-19 management measures for the heterogeneity of different groups.

Keywords: COVID-19; Hybrid latent class choice models; Non-commuting; Psychological factors; Willingness to travel.