Examining usage patterns of a bike-sharing scheme in a medium sized city

Caulfield, Brian; O’Mahony, Margaret; Brazil, William; Weldon, Peter

doi:10.1016/j.tra.2017.04.023

Cited by 115 publications

(91 citation statements)

References 22 publications

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“…Shared bicycles are one of the fastest growing modes of shared mobility and have been increasing in popularity worldwide in recent years. By the end of 2017, more than 23 million shared bicycles were available around the globe and 304 cities in more than 20 countries had implemented bicycle-sharing systems [19]. In 2017, there were more than 20 million shared bicycles in China and 22.1 Journal of Advanced Transportation 3 million subscribers [20].…”

Section: Literature Reviewmentioning

confidence: 99%

How Have Travelers Changed Mode Choices for First/Last Mile Trips after the Introduction of Bicycle-Sharing Systems: An Empirical Study in Beijing, China

Fan

Chen

Wan

2019

Journal of Advanced Transportation

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In recent years, there has been rapid development in bicycle-sharing systems (BSS) in China. Moreover, such schemes are considered promising solutions to the first/last mile problem. This study investigates the mode choice behaviors of travelers for first/last mile trips before and after the introduction of bicycle-sharing systems. Travel choice models for first/last mile trips are determined using a multinomial logit model. It also analyzes the differences in choice behavior between the young and other age groups. The findings show that shared bicycles become the preferred mode, while travelers preferred walking before bicycle-sharing systems were implemented. Gender, bicycle availability, and travel frequency were the most significant factors before the implementation of bicycle-sharing systems. However, after implementation, access distance dramatically affects mode choices for first/last mile trips. When shared bicycles are available, the mode choices of middle-aged group depend mainly on gender and access distance. All factors are not significant for the young and aged groups. More than 80% of public transport travelers take walking and shared bicycles as feeder modes. The proposed models and findings contribute to a better understanding of travelers' choice behaviors and to the development of solutions for the first/last mile problem.

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Section: Literature Reviewmentioning

confidence: 99%

How Have Travelers Changed Mode Choices for First/Last Mile Trips after the Introduction of Bicycle-Sharing Systems: An Empirical Study in Beijing, China

Fan

Chen

Wan

2019

Journal of Advanced Transportation

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“…Subsequently, Faghih-Imani and Eluru found that users' destination preferences significantly affected cycling choices [26]. De Chardon et al found that station-based systems encountered constraints in relation to the maximization of profits and service levels [27], although these constraints could be relaxed in medium-sized cities [28]. Moreover, Faghih-Imani et al concluded that bike-sharing systems were likely to be favoured where urban congestion was serious [29].…”

Section: Station-based Systemsmentioning

confidence: 99%

“…One of the largest bike-sharing companies was Yonganxing. In 2014, it provided services in over 200 mainly small and medium sized cities, proving that station-based systems could be successful in cities of these sizes [28]. In these cities, a finite number of stations could meet cycling demand.…”

Section: Launch Of Bike-sharing Systemsmentioning

confidence: 99%

Rethinking the Utility of Public Bicycles: The Development and Challenges of Station-Less Bike Sharing in China

2019

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Cycling is known to be environmentally friendly and beneficial to public health and sustainable urban development. Cycling has recently increased in Chinese cities as a result of the emergence of station-less bike-sharing systems. This study examines the emergence, rapid growth and consolidation of station-less bike-sharing systems and the role of suppliers, users and government regulators. It shows that these systems developed unevenly, growing most in large cities in eastern and south-eastern China, and explores the relationship between this spatial distribution and the nature of the service and the socio-economic characteristics of cities. To investigate patterns of, and reasons for, the use of these systems, this research also reports the results of a survey of users and non-users, identifying their gender, age, income characteristics and attitudes to station-less systems.

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“…In general, compared with SC data, bicycle trip data lacks card ID and thus cannot be used to model users' travel behavior. By far, public bicycle SC data has been used to investigate public bicycle users' travel patterns [22] as well as bicycle trip chains for men and women [14,23]. Public bicycle SC data could also help to classify different types of behaviors and compare the trip disparity [24].…”

Section: Smart Card Data For Trip Chainmentioning

confidence: 99%

An Association Rule Based Method to Integrate Metro-Public Bicycle Smart Card Data for Trip Chain Analysis

Zhao

Wang

Ong

et al. 2018

Journal of Advanced Transportation

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Smart card data provide valuable insights and massive samples for enhancing the understanding of transfer behavior between metro and public bicycle. However, smart cards for metro and public bicycle are often issued and managed by independent companies and this results in the same commuter having different identity tags in the metro and public bicycle smart card systems. The primary objective of this study is to develop a data fusion methodology for matching metro and public bicycle smart cards for the same commuter using historical smart card data. A novel method with association rules to match the data derived from the two systems is proposed and validation was performed. The results showed that our proposed method successfully matched 573 pairs of smart cards with an accuracy of 100%. We also validated the association rules method through visualization of individual metro and public bicycle trips. Based on the matched cards, interesting findings of metro-bicycle transfer have been derived, including the spatial pattern of the public bicycle as first/last mile solution as well as the duration of a metro trip chain.

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Examining usage patterns of a bike-sharing scheme in a medium sized city

Cited by 115 publications

References 22 publications

How Have Travelers Changed Mode Choices for First/Last Mile Trips after the Introduction of Bicycle-Sharing Systems: An Empirical Study in Beijing, China

How Have Travelers Changed Mode Choices for First/Last Mile Trips after the Introduction of Bicycle-Sharing Systems: An Empirical Study in Beijing, China

Rethinking the Utility of Public Bicycles: The Development and Challenges of Station-Less Bike Sharing in China

An Association Rule Based Method to Integrate Metro-Public Bicycle Smart Card Data for Trip Chain Analysis

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