Do metro interruptions increase the demand for public rental bicycles? Evidence from Paris

Klingen, Joris

doi:10.1016/j.tra.2018.10.018

Cited by 6 publications

(4 citation statements)

References 19 publications

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“…In terms of spatial heterogeneity, Yang et al [72] and Jia et al [73] found the most signifcant increase in bike-sharing ridership in areas near disrupted rail lines. Klingen [75] and Saberi et al [76] observed that bike-sharing stations located near disrupted rail stations experience a signifcantly higher increase in ridership compared to other areas, and this increase decreases with distance from the disrupted rail stations. Tis implies that bike-sharing efectively supplements travel service capacity when public transit is out of service.…”

Section: Te Impact Of Sudden Public Transit Shutdown Onmentioning

confidence: 99%

“…Studies generally indicate that when urban rail transit shuts down for a full day or temporarily for a few hours, the use of shared bikes increases. Furthermore, the use of shared bikes shows signifcant spatial and temporal heterogeneity [72][73][74][75][76]. In terms of spatial heterogeneity, Yang et al [72] and Jia et al [73] found the most signifcant increase in bike-sharing ridership in areas near disrupted rail lines.…”

Section: Te Impact Of Sudden Public Transit Shutdown Onmentioning

confidence: 99%

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A Systematic Review of the Coopetition Relationship between Bike-Sharing and Public Transit

Ye,

Bai,

Hao

2024

Journal of Advanced Transportation

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The sharing economy, mobile Internet, and smartphones have been widely utilized in recent years to promote the development of bike-sharing services. Bike-sharing serves as a first/last mile travel mode to connect to public transit, which improves trip efficiency, alleviates traffic problems, improves environmental quality, and promotes public health. However, the substitution of public transit by bike-sharing and the decline in public transit ridership have raised concerns among city managers regarding the coopetition between shared mobility services and public transit. To understand the impact of bike-sharing on the decline in public transit and to formulate reasonable synergistic development policies, it is crucial to identify the coopetition relationships between the two. This paper uses a combination of database search and backward snowballing to review existing research. Three research themes were identified: macrolevel studies on bike-sharing and public transit interaction, studies on actual coopetition behaviors based on bike-sharing user surveys, and studies on potential coopetition relationships based on bike-sharing transaction data. The three categories of studies reveal the effect of bike-sharing usage on public transit ridership, the emergency function of bike-sharing in the event of unexpected transit shutdowns, and the substitution and connection relationships between bike-sharing and public transit and the factors influencing them. Finally, this study suggests many directions for future research. This review helps clarify the understanding of the coopetition relationships between bike-sharing and public transit, provides theoretical support to promote the synergistic development of both, and points out ways to deepen the research on the coopetition relationship between the two.

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Section: Te Impact Of Sudden Public Transit Shutdown Onmentioning

confidence: 99%

Section: Te Impact Of Sudden Public Transit Shutdown Onmentioning

confidence: 99%

A Systematic Review of the Coopetition Relationship between Bike-Sharing and Public Transit

Ye,

Bai,

Hao

2024

Journal of Advanced Transportation

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“…Characteristics of users and stations, influencing factors, and built environment are all main research contents. Users' gender [2][3][4][5][6][7], age [3,[6][7][8], income and education [2,5,6,9,10], weather conditions [11][12][13], infrastructure construction, population density, built environment [7,[12][13][14][15][16][17][18][19], and relationship with other means of transportation [20][21][22][23][24][25][26][27][28][29][30][31][32][33] have been confirmed to affect the usage of bike-sharing. On the other hand, 2 of 17 in order to solve the problem of rebalancing, optimization of BSSs has also become another hot issue [34][35][36][37][38][39]…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, 2 of 17 in order to solve the problem of rebalancing, optimization of BSSs has also become another hot issue [34][35][36][37][38][39][40][41][42][43]. As far as research methods are concerned, statistical methods such as correlation analysis, clustering analysis, and regression analysis are adopted to analyze characteristics and influencing factors [3,7,9,13,14,19,20,22,23,44], and optimization algorithms are used to solve rebalancing operations for BSSs [35,[38][39][40]42,43].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System

Yao

Han

et al. 2019

Sustainability

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To better understand the characteristics of a bike-sharing system, we applied complex network methods to analyze the relationship between stations within the bike-sharing system. Firstly, using Gephi software, we constructed the public bicycle networks of different urban areas based on the real-time data of the Nanjing public bicycle system. Secondly, we analyzed and compared degree, strength, radiation distance, and community structure of the networks to understand the internal relations of the public bicycle system. The results showed that there were many stations with low usage of public bicycles. Furthermore, there was a geographical division between high-demand and low-demand areas for public bicycles. The usage of public bicycles at a station was not only related to land use but also related to the usage of bicycles at stations nearby. Moreover, the average service coverage of the public bicycle system was consistent with the original intention of “the first and last mile”, and public bicycles could meet different travel needs.

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Spatiotemporal Analysis of Traffic Data: Correspondence Analysis with Fuzzified Variables vs. Principal Component Analysis Using Weather and Gas Price as Extra Data

Loslever

2024

Netw Spat Econ

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Do metro interruptions increase the demand for public rental bicycles? Evidence from Paris

Cited by 6 publications

References 19 publications

A Systematic Review of the Coopetition Relationship between Bike-Sharing and Public Transit

A Systematic Review of the Coopetition Relationship between Bike-Sharing and Public Transit

Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System

Spatiotemporal Analysis of Traffic Data: Correspondence Analysis with Fuzzified Variables vs. Principal Component Analysis Using Weather and Gas Price as Extra Data

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