Will transit recover? A retrospective study of nationwide ridership in the United States during the COVID-19 pandemic

Ziedan, Abubakr; Brakewood, Candace; Watkins, Kari

doi:10.1016/j.jpubtr.2023.100046

Cited by 12 publications

(3 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Potter et al [25] identified differences in the resilience of rail freight flows in response to exogenous disturbances in the infrastructure, market, and macroeconomy that occurred during a multiyear period. Ziedan et al [5] aggregated monthly transit ridership trajectories in the United States at the metropolitan level and compared trends among them using changepoint analysis to find that metropolitan areas where the return of ridership levels was most prominent were those that offered fare-free transit for extended periods. This paper exemplifies a comprehensive analysis, assessing the differential resilience to COVID-19 across sub-sections of a large city by comparing travel demand changes before, during, and after the event.…”

Section: Literature Review a The Covid-19 Pandemic And Differential R...mentioning

confidence: 99%

“…The density of hospitality venues is calculated by counting the number of relevant businesses including restaurants, cafes, bakeries, and bars within the catchment area of each station and dividing that figure by the area of the catchment area. The business location data 5 are provided by the Korean Ministry of the Interior and Safety. Table 3 displays the units and value ranges of each continuous variable included.…”

Section: Data Description a Functional Data: Seoul Metro Passenger Vo...mentioning

confidence: 99%

“…Persistent shifts in economic activity and transportation usage necessitates the examination of patterns over a longer period of time in order to achieve a comprehensive analysis of the new equilibria. Another strand of literature primarily explores the overall impact of the pandemic on transportation demand, specifically its drop and recovery at the system level [3]- [5]. The heterogeneity of such impacts by location requires further study to accurately measure and analyze the socioeconomic and policy implications of the pandemic.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Differential Dynamics of Transit Use Resilience During the COVID-19 Pandemic Using Multivariate Two-Dimensional Functional Data Analysis

Choi,

Ryu,

Jung

et al. 2024

IEEE Access

View full text Add to dashboard Cite

This study delves into the nuanced patterns of shock and recovery in transit ridership during and after the COVID-19 pandemic, aiming to illuminate the resilience exhibited by various geographic areas. This resilience is measured by the ability of transportation systems to withstand, adapt to, and bounce back from unforeseen shocks. In this research, smart card big data were exploited to track real-time mobility dynamics and economic activity within the city of Seoul, Korea. The approach employed multivariate twodimensional functional data analysis and a hierarchical clustering method to examine both boarding and alighting patterns, taking into account multi-scalar temporal units, monthly and hourly demand fluctuations. The findings present distinct varied shock-and-recovery patterns across areas in transit ridership based on the socioeconomic characteristics of specific areas. These characteristics encompass factors such as industry and land-use composition, income levels, population density, and proximity to points of interest. Additionally, this methodology proves effective in identifying abnormal surges in demand linked to local large-scale development projects.

show abstract

Section: Literature Review a The Covid-19 Pandemic And Differential R...mentioning

confidence: 99%

Section: Data Description a Functional Data: Seoul Metro Passenger Vo...mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Differential Dynamics of Transit Use Resilience During the COVID-19 Pandemic Using Multivariate Two-Dimensional Functional Data Analysis

Choi,

Ryu,

Jung

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

Everything has changed: the impacts of the COVID-19 pandemic on the transit market in Montréal, Canada

Carvalho,

El-Geneidy

2024

Transportation

View full text Add to dashboard Cite

The COVID-19 pandemic has significantly impacted the transit market leading to ridership loss and service cuts. Most of the post-pandemic transit market literature has focused on how to attract those who stopped using transit services, however little attention has been given to how rider profiles have changed. To address this gap, we examine 2019 and 2022 data regarding transit commuters from Montréal, Canada. We apply factor and k-means cluster analyses to derive market segments at both points in time considering satisfaction levels, telecommuting rates, and frequency of transit use. We build upon these analyses to report on overall and mode group-level changes in the transit market. Our market segmentation reveals that captive, captive-by-choice, and choice riders still exist in the current public transit market. However, the share of these groups in the market has changed. The proportion of captive and choice riders has increased while captive-by-choice riders have shrunk in size. Moreover, the post-pandemic market has become mostly composed of infrequent riders and higher rates of telecommuting. We further explore these trends by commute mode (i.e., bus only, metro only, and bus and metro users). The findings from this research can be of interest to practitioners and policymakers as they shed light on the evolution of the perceptions and behaviours of segments of transit riders from before to after pandemic.

show abstract

Multi-modal Machine Learning Investigation of Telework and Transit Connections

Edward,

Soria,

Stathopoulos

2024

Data Sci. Transp.

View full text Add to dashboard Cite

Will transit recover? A retrospective study of nationwide ridership in the United States during the COVID-19 pandemic

Cited by 12 publications

References 33 publications

Differential Dynamics of Transit Use Resilience During the COVID-19 Pandemic Using Multivariate Two-Dimensional Functional Data Analysis

Differential Dynamics of Transit Use Resilience During the COVID-19 Pandemic Using Multivariate Two-Dimensional Functional Data Analysis

Everything has changed: the impacts of the COVID-19 pandemic on the transit market in Montréal, Canada

Multi-modal Machine Learning Investigation of Telework and Transit Connections

Contact Info

Product

Resources

About