Analysis on bike-share ridership for origin-destination pairs: Effects of public transit route characteristics and land-use patterns

Kim, Minjun; Cho, Gi-Hyoug

doi:10.1016/j.jtrangeo.2021.103047

Cited by 38 publications

(19 citation statements)

References 50 publications

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“…The total number of BSS stations was 1,093, and out of the total 285 subway stations, more than 70% of subway stations were analyzed to be linked to one or more BSS stations. The total bike capacity was 13,985, and the average bike capacity per station was about 12.8 bike docks, which is higher than in other cities (Kim and Cho, 2021).…”

Section: Data Descriptionmentioning

confidence: 67%

“…Researchers have demonstrated the first-and last-mile travel mode for the integrated transport system consisting of access and egress travels. Some studies have mentioned the trip mode for the first-and last-mile trips to the BSS (Noland et al, 2016;Kim and Cho, 2021), and a study has analyzed the access and egress trips to subways by employing a negative binomial regression model (Guo and He, 2020). A study has demonstrated the competitiveness of bike-sharing compared to bus use for access and egress travels connected to subway use (Kapuku et al, 2020).…”

Section: First-and Last-mile Trips In Maasmentioning

confidence: 99%

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Estimation of Route Choice Behaviors of Bike-Sharing Users as First- and Last-mile Trips for Introduction of Mobility-as-a-Service (MaaS)

Cho

Shin

2022

KSCE J Civ Eng

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Bicycling has been considered the sustainable alternatives of first-and last-mile trips for Mobility-as-a-Service (MaaS) in integrated transport systems. This study aims to analyze the route choice behaviors of bike-sharing users for the first-and last-mile trips in MaaS, incorporating the connectivity to the subway stations. The observed GPS data is employed to generate the route travels of bike-sharing users, and the choice set generation algorithm, i.e., the k-medoids clustering method, is applied to extract the representative alternatives in route choice models. This study analyzes the path-size logit model to compare the route choice behaviors incorporating peak periods, and access and egress trips. The bike-sharing use at the evening-peak period is more frequent than the other periods. Also, the bike-sharing users are found to be positively associated with the ratio of bike lanes for the access and egress trips to the subway stations, whereas they are reluctant to detour for their trips. The finding of this research is that the extension of bike facilities on access and egress to the subway stations is necessary to improve the bike-sharing use for the first-and last-mile trips in MaaS. Bike-sharing system Global positioning system (GPS) data Mobility-as-a-Service (MaaS) First-and last-mile Route choice behavior Access and egress trip CORRESPONDENCE Shin-Hyung Cho

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Section: Data Descriptionmentioning

confidence: 67%

Section: First-and Last-mile Trips In Maasmentioning

confidence: 99%

Estimation of Route Choice Behaviors of Bike-Sharing Users as First- and Last-mile Trips for Introduction of Mobility-as-a-Service (MaaS)

Cho

Shin

2022

KSCE J Civ Eng

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“…The results of this study found that the presence of public transit stations, areas with good street connectivity, and places with more compact land use patterns related to an increase in e-scooter usage. Analysis on bike-share ridership for origin-destination pairs to find effects of public transit route characteristics and land-use patterns showed that bike-share ridership has a complementary relationship with the metro, and it has a competitive relationship with bus transit in non-residential areas ( Kim & Cho, 2021 ). Survey-based research on the relationship between perceived built environment and active travel, before and after the COVID-19 in Shiraz city, Iran showed that a people-friendly environment with mixed, diverse, dense and accessible land uses, as well as the presence of bike riding infrastructure had major effects on the mobility in the pandemic.…”

Section: Literature Reviewmentioning

confidence: 99%

Impacts of COVID-19 on bike-sharing usages in Seoul, South Korea

Jiao

Lee²,

Choi³

2022

Cities

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“…The ridership depends on coverage area, parking spots, ease of use, and wearing helmets [ 38 ]. Transfer times and travel time when using public transport also influence bike sharing [ 39 ]. Moreover, avoiding congestion has a stronger effect than economic and environmental benefits [ 29 ].…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of COVID-19 on Travel Mode Choice Behavior in Terms of Shared Mobility: A Case Study in Beijing, China

Zhang

Shao

Wang

et al. 2022

IJERPH

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Shared mobility is growing rapidly and changing the mobility landscape. The COVID-19 pandemic has complicated travel mode choice behavior in terms of shared mobility, but the evidence on this impact is limited. To fill this gap, this paper first designs a stated preference survey to collect mode choice data before and during the pandemic. Different shared mobility services are considered, including ride hailing, ride sharing, car sharing, and bike sharing. Then, latent class analysis is used to divide the population in terms of their attitudes toward shared mobility. Nested logit models are applied to compare travel mode choice behavior during the two periods. The results suggest that shared mobility has the potential to avoid the high transmission risk of public transport and alleviate the intensity of private car use in the COVID-19 context, but this is limited by anxiety about shared spaces. As the perceived severity of the pandemic increases, preference for ride hailing and ride sharing decreases, and a price discount for ride hailing is more effective than that for ride sharing at maintaining the ridership despite the impact of COVID-19. These findings contribute to understanding the change in travel demand and developing appropriate strategies for shared mobility services to adapt to the pandemic.

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Analysis on bike-share ridership for origin-destination pairs: Effects of public transit route characteristics and land-use patterns

Cited by 38 publications

References 50 publications

Estimation of Route Choice Behaviors of Bike-Sharing Users as First- and Last-mile Trips for Introduction of Mobility-as-a-Service (MaaS)

Estimation of Route Choice Behaviors of Bike-Sharing Users as First- and Last-mile Trips for Introduction of Mobility-as-a-Service (MaaS)

Impacts of COVID-19 on bike-sharing usages in Seoul, South Korea

The Impact of COVID-19 on Travel Mode Choice Behavior in Terms of Shared Mobility: A Case Study in Beijing, China

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