2022
Chen, Chao; Feng, Tao; Gu, Xiaoning; Yao, Baozhen
Investigating the effectiveness of COVID-19 pandemic countermeasures on the use of public transport: A case study of The Netherlands Journal Article
In: Transport Policy, vol. 117, pp. 98–107, 2022, ISSN: 0967-070X.
Abstract | Links | BibTeX | Tags: COVID-19 pandemic, Error component latent class choice model, Public transport, Taste variation, Travel behavior
@article{cd8c66995497429ba47116d41341c4f0,
title = {Investigating the effectiveness of COVID-19 pandemic countermeasures on the use of public transport: A case study of The Netherlands},
author = {Chao Chen and Tao Feng and Xiaoning Gu and Baozhen Yao},
url = {https://www.sciencedirect.com/science/article/pii/S0967070X22000051},
doi = {10.1016/j.tranpol.2022.01.005},
issn = {0967-070X},
year = {2022},
date = {2022-03-01},
urldate = {2022-03-01},
journal = {Transport Policy},
volume = {117},
pages = {98--107},
publisher = {Elsevier},
abstract = {During the COVID-19 pandemic, public transport in many cities faces dramatic reduction of passenger demand. Various countermeasures such as social distancing and in-vehicle disinfection have been implemented to reduce the potential risks concerning infection, the effectiveness in promoting the use of public transport however remains unclear. Unlike the usual situation where time and cost are the main factors affecting travel decisions, the uncertainty hiding behind the behavior change of public transport users in a pandemic might be greatly affected by the control measures and the perception of people. This paper therefore aims to examine the effects of COVID-19 related countermeasures implemented in public transport on individuals' travel decisions. We explore the extent to which do policy countermeasures influence different groups of people on the use of public transport. An error component latent class choice model was estimated using the data collected in the Netherlands. Results show that the restrictions policy lifted by the Dutch central government have significant effect on individuals' transportation mode choice decision during the pandemic. The related measures adopted by the public transport sector, by contrast, present different effects on different people. The older and highly educated people are more susceptible to enforcement measures, whereas young and single Dutch citizens are more accessible to non-compulsory measures. Moreover, compared with other private modes, public transport is generally identified as a riskier option, and the average willingness to travel descends. Findings of this study are helpful for the authorities in designing and promoting effective policies in the context of pandemics.},
keywords = {COVID-19 pandemic, Error component latent class choice model, Public transport, Taste variation, Travel behavior},
pubstate = {published},
tppubtype = {article}
}
During the COVID-19 pandemic, public transport in many cities faces dramatic reduction of passenger demand. Various countermeasures such as social distancing and in-vehicle disinfection have been implemented to reduce the potential risks concerning infection, the effectiveness in promoting the use of public transport however remains unclear. Unlike the usual situation where time and cost are the main factors affecting travel decisions, the uncertainty hiding behind the behavior change of public transport users in a pandemic might be greatly affected by the control measures and the perception of people. This paper therefore aims to examine the effects of COVID-19 related countermeasures implemented in public transport on individuals’ travel decisions. We explore the extent to which do policy countermeasures influence different groups of people on the use of public transport. An error component latent class choice model was estimated using the data collected in the Netherlands. Results show that the restrictions policy lifted by the Dutch central government have significant effect on individuals’ transportation mode choice decision during the pandemic. The related measures adopted by the public transport sector, by contrast, present different effects on different people. The older and highly educated people are more susceptible to enforcement measures, whereas young and single Dutch citizens are more accessible to non-compulsory measures. Moreover, compared with other private modes, public transport is generally identified as a riskier option, and the average willingness to travel descends. Findings of this study are helpful for the authorities in designing and promoting effective policies in the context of pandemics.
Chen, Chao; Feng, Tao; Gu, Xiaoning
Role of latent factors and public policies in travel decisions under COVID-19 pandemic: Findings of a hybrid choice model Journal Article
In: Sustainable Cities and Society, vol. 78, 2022, ISSN: 2210-6707.
Abstract | Links | BibTeX | Tags: COVID-19 pandemic, Latent factors, Public transport
@article{40c9feae3bd0408b805b8e9538654c6e,
title = {Role of latent factors and public policies in travel decisions under COVID-19 pandemic: Findings of a hybrid choice model},
author = {Chao Chen and Tao Feng and Xiaoning Gu},
url = {https://www.sciencedirect.com/science/article/pii/S2210670721008660},
doi = {10.1016/j.scs.2021.103601},
issn = {2210-6707},
year = {2022},
date = {2022-03-01},
urldate = {2022-03-01},
journal = {Sustainable Cities and Society},
volume = {78},
publisher = {Elsevier},
abstract = {Policy measures to control the spread of COVID-19 imposed by different countries have a devastating impact on people's travel behaviors. Differing from the normal situation where general concerns on travel time and cost determine the travel choices, the uncertainty underlying behavior change in the case of a pandemic might be largely attributed to the latent aspects, i.e., social responsibility, risk perception, attitudes, which could diminish the effects of main attributes on travel decisions. Therefore, this paper examines the effects of COVID-19 related policies on individuals' travel choices influenced by the latent aspects. A stated choice experiment was designed to collect people's responses under policy measures to various transportation modes. Results of a hybrid choice model show that COVID-19 related policies significantly affect individuals' transportation mode choice decisions during pandemic situations. The attributes, like travel time and travel cost, which significantly impact travel behavior in normal situations, become less relevant. Moreover, the travel preferences during the pandemic are significantly associated with latent factors of social responsibility, fear of infection, perceived risk, and travel anxiety. In general, public transportation is identified as an insecure alternative compared with other private modes, and people who are more socially responsible tend to travel less during the pandemic. Outcomes of this study could be of value to policymakers and public health emergencies, e.g., government authorities to utilize such knowledge in providing social support for these COVID-19 countermeasures and designing customized policies for specific population groups.},
keywords = {COVID-19 pandemic, Latent factors, Public transport},
pubstate = {published},
tppubtype = {article}
}
Policy measures to control the spread of COVID-19 imposed by different countries have a devastating impact on people’s travel behaviors. Differing from the normal situation where general concerns on travel time and cost determine the travel choices, the uncertainty underlying behavior change in the case of a pandemic might be largely attributed to the latent aspects, i.e., social responsibility, risk perception, attitudes, which could diminish the effects of main attributes on travel decisions. Therefore, this paper examines the effects of COVID-19 related policies on individuals’ travel choices influenced by the latent aspects. A stated choice experiment was designed to collect people’s responses under policy measures to various transportation modes. Results of a hybrid choice model show that COVID-19 related policies significantly affect individuals’ transportation mode choice decisions during pandemic situations. The attributes, like travel time and travel cost, which significantly impact travel behavior in normal situations, become less relevant. Moreover, the travel preferences during the pandemic are significantly associated with latent factors of social responsibility, fear of infection, perceived risk, and travel anxiety. In general, public transportation is identified as an insecure alternative compared with other private modes, and people who are more socially responsible tend to travel less during the pandemic. Outcomes of this study could be of value to policymakers and public health emergencies, e.g., government authorities to utilize such knowledge in providing social support for these COVID-19 countermeasures and designing customized policies for specific population groups.
2021
Zhang, Junyi; Feng, Tao; Kang, Jing; Li, Shuangjin; Liu, Rui; Ma, Shuang; Zhai, Baoxin; Zhang, Runsen; Ding, Hongxiang; Zhu, Taoxing
“What should be computed” for supporting post-pandemic recovery policy making? A life-oriented perspective Journal Article
In: Computational Urban Science , vol. 1, no. 24, pp. 1-16, 2021.
Abstract | Links | BibTeX | Tags: Computation, COVID-19 pandemic
@article{@ZHANG2021URBANCOMPUTATION,
title = {“What should be computed” for supporting post-pandemic recovery policy making? A life-oriented perspective},
author = {Junyi Zhang and Tao Feng and Jing Kang and Shuangjin Li and Rui Liu and Shuang Ma and Baoxin Zhai and Runsen Zhang and Hongxiang Ding and Taoxing Zhu },
url = {https://link.springer.com/content/pdf/10.1007/s43762-021-00025-8.pdf},
doi = {doi.org/10.1007/s43762-021-00025-8},
year = {2021},
date = {2021-11-19},
urldate = {2021-11-19},
journal = {Computational Urban Science },
volume = {1},
number = {24},
pages = {1-16},
abstract = {The COVID-19 pandemic has caused various impacts on people’s lives, while changes in people’s lives have shown mixed effects on mitigating the spread of the SARS-CoV-2 virus. Understanding how to capture such two-way interactions is crucial, not only to control the pandemic but also to support post-pandemic urban recovery policies. As suggested by the life-oriented approach, the above interactions exist with respect to a variety of life domains, which form a complex behavior system. Through a review of the literature, this paper first points out inconsistent evidence about behavioral factors affecting the spread of COVID-19, and then argues that existing studies on the impacts of COVID-19 on people’s lives have ignored behavioral co-changes in multiple life domains. Furthermore, selected uncertain trends of people’s lives for the post-pandemic recovery are described. Finally, this paper concludes with a summary about “what should be computed?” in Computational Urban Science with respect to how to catch up with delays in the SDGs caused by the COVID-19 pandemic, how to address digital divides and dilemmas of e-society, how to capture behavioral co-changes during the post-pandemic recovery process, and how to better manage post-pandemic recovery policymaking processes.},
keywords = {Computation, COVID-19 pandemic},
pubstate = {published},
tppubtype = {article}
}
The COVID-19 pandemic has caused various impacts on people’s lives, while changes in people’s lives have shown mixed effects on mitigating the spread of the SARS-CoV-2 virus. Understanding how to capture such two-way interactions is crucial, not only to control the pandemic but also to support post-pandemic urban recovery policies. As suggested by the life-oriented approach, the above interactions exist with respect to a variety of life domains, which form a complex behavior system. Through a review of the literature, this paper first points out inconsistent evidence about behavioral factors affecting the spread of COVID-19, and then argues that existing studies on the impacts of COVID-19 on people’s lives have ignored behavioral co-changes in multiple life domains. Furthermore, selected uncertain trends of people’s lives for the post-pandemic recovery are described. Finally, this paper concludes with a summary about “what should be computed?” in Computational Urban Science with respect to how to catch up with delays in the SDGs caused by the COVID-19 pandemic, how to address digital divides and dilemmas of e-society, how to capture behavioral co-changes during the post-pandemic recovery process, and how to better manage post-pandemic recovery policymaking processes.
Liu, Jiayi; Peng, Zhikai; Cai, Xiaoxi; Peng, You; Li, Jiang; Feng, Tao
Students’ Intention of Visiting Urban Green Spaces after the COVID-19 Lockdown in China Journal Article
In: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, vol. 18, no. 16, 2021.
Abstract | Links | BibTeX | Tags: COVID-19 pandemic, Green space, Student
@article{WOS:000690513900001,
title = {Students' Intention of Visiting Urban Green Spaces after the COVID-19 Lockdown in China},
author = {Jiayi Liu and Zhikai Peng and Xiaoxi Cai and You Peng and Jiang Li and Tao Feng},
url = {https://www.mdpi.com/1229054},
doi = {10.3390/ijerph18168601},
year = {2021},
date = {2021-08-01},
urldate = {2021-08-01},
journal = {INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH},
volume = {18},
number = {16},
abstract = {This study addresses students' perceptions of using urban green spaces
(UGSs) after the easing of COVID-19 lockdown in China. We questioned
whether they are still mindful of the risks from the outdoor gathering,
or conversely, starting to learn the restoration benefits from the green
spaces. Online self-reported surveys were distributed to the Chinese
students aging from 14 to 30 who study in Hunan and Jiangsu Provinces,
China. We finally obtained 608 complete and valid questionnaire forms
from all participants. Their intentions of visiting UGSs were
investigated based on the extended theory of planned behavior model.
Structural equation modeling was employed to test the hypothesized
psychological model. The results have shown good estimation performance
on risk perception and perceived knowledge to explain the variances in
their attitudes, social norms, and perceived behavior control. Among
these three endogenous variables, the perceived behavior control owns
the greatest and positive influence on the behavioral intention,
inferring that controllability is crucial for students to make decisions
of visiting green spaces in a post-pandemic context.},
keywords = {COVID-19 pandemic, Green space, Student},
pubstate = {published},
tppubtype = {article}
}
This study addresses students’ perceptions of using urban green spaces
(UGSs) after the easing of COVID-19 lockdown in China. We questioned
whether they are still mindful of the risks from the outdoor gathering,
or conversely, starting to learn the restoration benefits from the green
spaces. Online self-reported surveys were distributed to the Chinese
students aging from 14 to 30 who study in Hunan and Jiangsu Provinces,
China. We finally obtained 608 complete and valid questionnaire forms
from all participants. Their intentions of visiting UGSs were
investigated based on the extended theory of planned behavior model.
Structural equation modeling was employed to test the hypothesized
psychological model. The results have shown good estimation performance
on risk perception and perceived knowledge to explain the variances in
their attitudes, social norms, and perceived behavior control. Among
these three endogenous variables, the perceived behavior control owns
the greatest and positive influence on the behavioral intention,
inferring that controllability is crucial for students to make decisions
of visiting green spaces in a post-pandemic context.
(UGSs) after the easing of COVID-19 lockdown in China. We questioned
whether they are still mindful of the risks from the outdoor gathering,
or conversely, starting to learn the restoration benefits from the green
spaces. Online self-reported surveys were distributed to the Chinese
students aging from 14 to 30 who study in Hunan and Jiangsu Provinces,
China. We finally obtained 608 complete and valid questionnaire forms
from all participants. Their intentions of visiting UGSs were
investigated based on the extended theory of planned behavior model.
Structural equation modeling was employed to test the hypothesized
psychological model. The results have shown good estimation performance
on risk perception and perceived knowledge to explain the variances in
their attitudes, social norms, and perceived behavior control. Among
these three endogenous variables, the perceived behavior control owns
the greatest and positive influence on the behavioral intention,
inferring that controllability is crucial for students to make decisions
of visiting green spaces in a post-pandemic context.