Commuting Behavior Changes at Different Stages of Localized COVID-19 Outbreak: Evidence from Nanjing, China DOI Creative Commons
Pei‐Yu Chen, Tom Wu,

Yurui Yin

et al.

Systems, Journal Year: 2024, Volume and Issue: 12(8), P. 271 - 271

Published: July 28, 2024

Commuting behaviors have been changed by the COVID-19 pandemic. To investigate impacts at different stages of sudden and localized outbreak, this paper carries out an online survey to obtain data, targeting residents in Nanjing China, where there had outbreaks proposes a sequential analysis method calculate complexity commuting behavior changes. The Tobit model is used explore factors that influence Results show commuters using public transportation drop significantly when occur, with 43.5% them switching private cars or working from home. number home increases 14 times. While outbreak gradually subsides, modes tend recover, but does not immediately return state before outbreak. Regression results indicate aged 40–60 maintain their habits, while younger workers are more flexible on options. Middle-income commuters, those living low-risk areas near subway within 800 m prefer change modes, opting for what they perceive be safer ways commute. For medium- high-risk who people non-green health codes, adjust real time based color codes risk level live. research findings contribute our understanding targeted management needs during local outbreaks, can help government formulate comprehensive effective pandemic prevention policy.

Language: Английский

Evaluating consumer shopping, delivery demands, and last-mile preferences: An integrated MDCEV-HCM approach DOI
Ali Riahi Samani, Ahmadreza Talebian, Sabyasachee Mishra

et al.

Transportation Research Part E Logistics and Transportation Review, Journal Year: 2025, Volume and Issue: 197, P. 104067 - 104067

Published: March 16, 2025

Language: Английский

Citations

1
Resident Preferences for Urban Green Spaces in Response to Pandemic Public Health Emergency: A Case Study of Shanghai DOI Open Access

Yonggeng Xiong,

Min Xu,

Yan Zhao

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(9), P. 3738 - 3738

Published: April 29, 2024

The COVID-19 pandemic represents a quintessential public health crisis, profoundly impacting the utilization patterns of urban green spaces through stringent quarantine and lockdown measures. However, existing research inadequately addresses specific concerns regarding future tends to oversimplify population divisions. This study delves into needs preferences Shanghai residents affected by measures, focusing on various aspects such as types spaces, facilities, landscape elements, spatial types. Multifactorial clustering was also performed. delineates following conclusions: (1) It is imperative afford access at least once week, even during periods. (2) Residents exhibited preference for accessible equipped with essential amenities, favoring unobstructed vistas plant-centric ecological landscapes pandemic. Additionally, there notable private among residents. (3) Post-pandemic, “affluent” group displays heightened overall demand “middle-class” shows conspicuous inclination towards space while “low-income” consistently exhibits low after underscores necessity developing human-centric promote equity resilience in face emergencies, rooted residents’ amidst crises.

Language: Английский

Citations

4
Temporal Stability of Factors Affecting Residents’ Non-Commuting Travel Behavior across Different Stages of a Sudden and Localized Outbreak of COVID-19 DOI
Xinwei Ma,

Ying Shen,

Zhenhao Liu

et al.

Transportation Research Record Journal of the Transportation Research Board, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 27, 2025

People’s attitudinal shifts toward an epidemic at different stages of the affect their travel behavior. Non-commuting behavior is more variable than commuting, as non-commuters have options. However, few studies explored changes in non-commuting and its influencing factors across sudden localized COVID-19 outbreaks. Using survey data collected Nanjing, China, where there was a outbreak COVID-19, this research adopted random parameter ordered logit model with heterogeneity means variances (HMV) to explore early, middle, late stages. The results revealed that considering HMV would improve fitness. In addition, temporal stability investigated via likelihood ratio test, which confirms traveler behavioral differences showed “e-bike ownership” “the number PCR (polymerase chain reaction) tests” positively correlated trips over three variables “people who live together red health code,”“mask replacement frequency,” “risk-free areas” are significant early-stage middle-stage models. green code all time” only become late-stage model. Research findings contribute understanding behaviors targeted management needs during local outbreaks, can help government address issues under future major events.

Language: Английский

Citations

0
The battery-swapping revolution: Exploring user preferences in electric micro-mobility sector DOI
Fan Zhang,

Huitao Lv,

Chenchen Kuai

et al.

Transportation Research Part A Policy and Practice, Journal Year: 2025, Volume and Issue: 194, P. 104416 - 104416

Published: Feb. 17, 2025

Language: Английский

Citations

0
How does Bike Absence Influence Mode Shifts Among Dockless Bike-Sharing Users? Evidence From Nanjing, China DOI
Hongjun Cui,

Zhixiao Ren,

Xinwei Ma

et al.

Transportation Research Record Journal of the Transportation Research Board, Journal Year: 2025, Volume and Issue: unknown

Published: April 24, 2025

Dockless bike-sharing users often encounter difficulties in finding available bikes at their preferred times and locations. This study examines the determinants of users’ mode shifts context bike absence, using survey data from Nanjing, China. An integrated choice latent variable model based on multinomial logit was employed to investigate impact socio-demographic characteristics, trip attributes, psychological factors travel choices. Mode models were estimated with seven alternatives, including bike-sharing-related choices (i.e., waiting place, picking up way, a detour), bus, taxi, riding hailing, walking. The findings showed that under shared-bike unavailability, pick way rather than take detours, buses walking as favored alternatives shared bikes. Lower-educated tended wait showing greater concern for time compared time. Lower-income users, commuters, females whereas noncommuters males opted detours. insights gained this could provide ideas solving problems demand estimation, parking area siting, developing multimodal synergies sharing enhance utilization user satisfaction.

Language: Английский

Citations

0
Modeling Real Demand in Dockless Bike-Sharing Systems: Integrating User Preferences and Behavioral Insights DOI

Zhixiao Ren,

Hongjun Cui, Xinwei Ma

et al.

Journal of Transportation Engineering Part A Systems, Journal Year: 2025, Volume and Issue: 151(7)

Published: April 29, 2025

Language: Английский

Citations

0
Incorporating mobile phone data-based travel mobility analysis of metro ridership in aboveground and underground layers DOI Creative Commons
Jiping Xing, Xiaohong Jiang,

Yu Yuan

et al.

Electronic Research Archive, Journal Year: 2024, Volume and Issue: 32(7), P. 4472 - 4494

Published: Jan. 1, 2024

<p>Metro transit is the core of urban transportation, and mobility analysis metro ridership can contribute to enhance overall service level transit. Researchers studying are focused on spatiotemporal distribution characteristics in underground system station by smart card data. However, limited lack travel chain integrity, their activity patterns cannot be used identify heterogeneity ridership's origin transfer mode. In our research, we applied full coverage mobile phone data complete perspective ground First, boarding alighting stations was extracted order then extracted. Second, relying flow identification method, aboveground destination outside were extracted, transferred traffic mode identified. The empirical results have shown that proposed framework accurately analyze an area station.</p>

Language: Английский

Citations

2
The Effects of the COVID-19 Pandemic on the Modal Shifting Utilising a Latent Class Choice Model with Covariates DOI Creative Commons
Mahmut Esad Ergin

PROMET - Traffic&Transportation, Journal Year: 2024, Volume and Issue: 36(3), P. 399 - 414

Published: June 20, 2024

The COVID-19 pandemic has posed significant challenges to global public health organisations and governments, leading countermeasures like hand sanitizer availability, social distancing, mandatory face mask wearing, which have disrupted the transportation sector impacted virus spread. Anticipating effects of circumstances a on mobility is essential for operators managers systems effectively safely manage system. In this study, measures taken during pandemic, such as those mentioned above, were considered indicators in latent class model (LCM) modal shifting. incorporates sociodemographic variables covariates understand their impact shifting from transport private cars. An online survey with 53,973 valid responses was conducted Istanbul, Turkiye. As result LCM covariates, two-latent-class model, best fit among models ranging two six classes, emerged. Class-1 participants show increased sensitivity mode, while Class-2 are less concerned tend maintain existing mode. suggests using estimate shift cars any given situation.

Language: Английский

Citations

0
Commuting Behavior Changes at Different Stages of Localized COVID-19 Outbreak: Evidence from Nanjing, China DOI Creative Commons
Pei‐Yu Chen, Tom Wu,

Yurui Yin

et al.

Systems, Journal Year: 2024, Volume and Issue: 12(8), P. 271 - 271

Published: July 28, 2024

Commuting behaviors have been changed by the COVID-19 pandemic. To investigate impacts at different stages of sudden and localized outbreak, this paper carries out an online survey to obtain data, targeting residents in Nanjing China, where there had outbreaks proposes a sequential analysis method calculate complexity commuting behavior changes. The Tobit model is used explore factors that influence Results show commuters using public transportation drop significantly when occur, with 43.5% them switching private cars or working from home. number home increases 14 times. While outbreak gradually subsides, modes tend recover, but does not immediately return state before outbreak. Regression results indicate aged 40–60 maintain their habits, while younger workers are more flexible on options. Middle-income commuters, those living low-risk areas near subway within 800 m prefer change modes, opting for what they perceive be safer ways commute. For medium- high-risk who people non-green health codes, adjust real time based color codes risk level live. research findings contribute our understanding targeted management needs during local outbreaks, can help government formulate comprehensive effective pandemic prevention policy.

Language: Английский

Citations

0