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中国南京新冠疫情期间的非通勤出行意愿:一种混合潜在类别建模方法

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

作者信息

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

机构信息

School of Civil and Transportation Engineering, Hebei University of Technology, Tianjin 300401, China.

School of Architecture and Art Design, Hebei University of Technology, Tianjin 300401, China.

出版信息

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


DOI:10.1016/j.cities.2023.104341
PMID:37132012
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10140732/
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.

摘要

非通勤出行对于人们满足日常需求和调节心理健康至关重要,但由于新冠疫情,这一出行活动受到了极大干扰。为探究新冠疫情期间不同居民群体的非通勤意愿,本文利用南京的在线调查数据,构建了一个结合社会人口特征和心理因素的混合潜在类别选择模型。结果显示,受访者可分为两组:“谨慎”组和“无畏”组。出行意愿较低的“谨慎”组往往年龄较大、收入较高、受教育程度较高、为女性且是全职员工。此外,感知易感性较高的“谨慎”组更服从政府政策。相比之下,“无畏”组受感知严重性的影响显著,更倾向于采取个人防护措施应对疫情。这些结果表明,非通勤出行不仅受到个体特征的影响,还受到心理因素的影响。最后,本文为政府针对不同群体的异质性制定新冠疫情管理措施提供了启示。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7193/10140732/a9e1601e6b3d/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7193/10140732/a801ab948cf7/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7193/10140732/8ec58d75279c/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7193/10140732/1117d88d7e5f/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7193/10140732/a9e1601e6b3d/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7193/10140732/a801ab948cf7/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7193/10140732/8ec58d75279c/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7193/10140732/1117d88d7e5f/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7193/10140732/a9e1601e6b3d/gr4_lrg.jpg

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

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[6]
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[7]
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[10]
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本文引用的文献

[1]
Mapping travel behavior changes during the COVID-19 lock-down: a socioeconomic analysis in Greece.

Eur Transp Res Rev. 2021

[2]
When the impossible becomes possible: COVID-19's impact on work and travel patterns in Swedish public agencies.

Eur Transp Res Rev. 2021

[3]
COVID-19 lockdown measures and travel behavior: The case of Thessaloniki, Greece.

Transp Res Interdiscip Perspect. 2021-6

[4]
Understanding individual-level travel behavior changes due to COVID-19: Trip frequency, trip regularity, and trip distance.

Cities. 2023-4

[5]
Who is returning to public transport for non-work trips after COVID-19? Evidence from older citizens' smart cards in the UK's second largest city region.

J Transp Geogr. 2023-2

[6]
Studying the Interrelationship between Telecommuting during COVID-19, residential local accessibility, and active travel: a panel study in Montréal, Canada.

Transportation (Amst). 2023-1-6

[7]
Exploring how worthwhile the things that you do in life are during COVID-19 and links to well-being and working from home.

Transp Res Part A Policy Pract. 2023-2

[8]
Impact of COVID-19: A radical modal shift from public to private transport mode.

Transp Policy (Oxf). 2021-8

[9]
Measuring changes in travel behavior pattern due to COVID-19 in a developing country: A case study of Pakistan.

Transp Policy (Oxf). 2021-7

[10]
Quantifying COVID-19 recovery process from a human mobility perspective: An intra-city study in Wuhan.

Cities. 2023-1

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