What drives the changes in public transport use in the context of the COVID‐19 pandemic? Highlights from Lyon metropolitan area

Zein, Ali El; Béziat, Adrien; Pochet, Pascal; Klein, Olivier; Vincent, Stéphanie

doi:10.1111/rsp3.12519

Cited by 7 publications

(4 citation statements)

References 32 publications

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“…A transition to teleworking caused a decrease in public transport. Active transport recorded an increase due to the transfer of passengers from public transport [63]. Travel mode choice was reflected in another study.…”

Section: Discussionmentioning

confidence: 85%

Estimating Mode of Transport in Daily Mobility during the COVID-19 Pandemic Using a Multinomial Logistic Regression Model

Mazanec

Harantová

Štefancová

et al. 2023

IJERPH

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At the beginning of 2020 there was a spinning point in the travel behavior of people around the world because of the pandemic and its consequences. This paper analyzes the specific behavior of travelers commuting to work or school during the COVID-19 pandemic based on a sample of 2000 respondents from two countries. We obtained data from an online survey, applying multinomial regression analysis. The results demonstrate the multinomial model with an accuracy of almost 70% that estimates the most used modes of transport (walking, public transport, car) based on independent variables. The respondents preferred the car as the most frequently used means of transport. However, commuters without car prefer public transport to walking. This prediction model could be a tool for planning and creating transport policy, especially in exceptional cases such as the limitation of public transport activities. Therefore, predicting travel behavior is essential for policymaking based on people’s travel needs.

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Section: Discussionmentioning

confidence: 85%

Estimating Mode of Transport in Daily Mobility during the COVID-19 Pandemic Using a Multinomial Logistic Regression Model

Mazanec

Harantová

Štefancová

et al. 2023

IJERPH

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“…As evidence of spatial segregation has already been shown in terms of socioeconomic profiles in Lyon (Bouzouina et al, 2021), further analysis should investigate the link between spatially varying impact, land use (space function), and sociodemographic data. El Zein et al (2022) demonstrated the correlation between the drop in PT use in Lyon and the possibility to work from home or choosing an alternative mode in Lyon.…”

Section: Discussionmentioning

confidence: 99%

“…The impacts of COVID‐19 on travel behavior have been abundantly studied in different spatial contexts, at different levels, and using different data sources and methodologies (Bouzouina et al, 2022). PT data are largely used at aggregated levels, such as regional (Jenelius & Cebecauer, 2020; Manout et al, 2023), or municipal (Aloi et al, 2020; El Zein et al, 2022; Gramsch et al, 2022) levels. These levels are often suitable for sociodemographic analysis, which combines activity or demographic data available for the same level of aggregation.…”

Section: Introductionmentioning

confidence: 99%

Spatio‐temporal patterns of the impact of COVID‐19 on public transit: An exploratory analysis from Lyon, France

Cottreau,

Adraoui,

Manout

et al. 2023

Regional Science Policy & Practice

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Public transit has been highly impacted by COVID‐19, as well as transport demand in general. Using high resolution data from smart card systems, this research investigates spatial and temporal variability of pandemic impact on public transit in Lyon, France. The study was conducted with a sample of 95,779 daily records, distributed over years (2019, 2020 and 2021) and public transit stops (520 bus rapid transit stops, 88 tramways stops and 40 subway stops). Clustering and statistical methods are used to assess changes observed in the data. Findings highlight variability between modes in terms of intensity of impacts, recovery patterns and stability of the shock over time. Results show that central areas recover worse than peripheral areas and west stops recover worse than east stops. Globally, effects of COVID‐19 clear up over time, but not totally, with a faster recovery for subway. Local analysis on specific stops also suggests that public transit associated to medical facilities endures less COVID‐19 impacts than employment zones or universities.

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“…Since the beginning of the pandemic, several studies have been undertaken to assess its impacts on PT use at different spatial levels (Al Zein et al 2022;Bouzouina et al 2022;Eisenmann et al 2021;Jenelius et al 2020;Jiang et al 2022;Melo 2022;Rasca et al 2021;Séjournet et al 2022;Wielechowski et al 2020). These studies report various findings: decline in PT use in favor of the car, the impact of policy stringency on PT, fear of contamination in PT, and the wide adoption of remote activities, particularly during the first months of the pandemic (Gkiotsalitis et al 2021).…”

Section: Introductionmentioning

confidence: 99%

On the bumpy road to recovery: resilience of transit ridership during COVID-19 in 15 European cities

Manout

Bouzouina²,

Kourtit

et al. 2023

Preprint

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COVID-19 had a dramatic impact on the use of transit. Most European cities report a decline in transit use during 2020 and 2021. Nevertheless, not all cities report similar decline patterns or comparable resilience paths. We investigate the resilience patterns of transit use during 2020 and 2021 in 15 European cities from 11 different countries using clustering and regression analysis of data from Google Mobility Reports. Results highlight the variety of resilience patterns of transit use in these 15 cities. These patterns vary in time and space. Transit use in some cities recovered faster and more significantly than in others. Findings also suggest that changes in retail and recreational routines have the highest impact on the resilience of transit use in most cities. Changes in workplace routines are also important, but to a lesser degree. The impact of policy stringency on transit use is significant, but less consistent between the 15 cities. JEL classification: 40, 41, 48

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What drives the changes in public transport use in the context of the COVID‐19 pandemic? Highlights from Lyon metropolitan area

Cited by 7 publications

References 32 publications

Estimating Mode of Transport in Daily Mobility during the COVID-19 Pandemic Using a Multinomial Logistic Regression Model

Estimating Mode of Transport in Daily Mobility during the COVID-19 Pandemic Using a Multinomial Logistic Regression Model

Spatio‐temporal patterns of the impact of COVID‐19 on public transit: An exploratory analysis from Lyon, France

On the bumpy road to recovery: resilience of transit ridership during COVID-19 in 15 European cities

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