Bikeshare Users Research Articles

Does bike-share enhance transport equity? Evidence from the Sacramento, California region

As bike-share systems proliferate across the US, their potential as a way of expanding opportunities for those most underserved by the transportation system merits a deeper understanding of its current users. In this study, we examine the rate of bike-share adoption by individuals from different socio-demographic groups and living in different bicycling contexts. We explore how individuals incorporate bike-share service into their travel patterns for different travel purposes and change their use of other modes. Data are from a two-wave survey of bike-share users and a parallel household survey of residents in the Sacramento region. Our modeling results for bike-share adoption and use frequency show that low-income individuals are less likely to adopt bike-share but use the service more frequently than other income groups when they do adopt. Low-income users, people of color, and non-auto owners are more likely than other groups to use bike-share frequently for many trip purposes. Individuals living in areas with a stronger biking culture and surrounded by bike infrastructure are less likely to adopt the service and less likely to use it for purposes other than commuting. All users change their use of other modes when they incorporate bike-share into their travel patterns, but low-income individuals, people of color, and non-auto owners would be more severely impacted if the service were to stop. Our results add new insights into the use of bike-share, a service that can enhance social equity while also addressing sustainability.

A Comparison in Travel Characteristics of Bike-Sharing between College Students and Office Workers Based on Theory of Planned Behavior

As an important component of bike-sharing (BS) users, the travel behavior of college students and office workers is important to the promotion of BS within Chinese cities. To explore the influencing factors for the behavioral intentions of BS, this paper makes a different analysis between the two groups. Based on the theory of planned behavior, and using environmental awareness as an extended variable, a BS travel intention model was developed. A total of 676 valid questionnaires were collected and analyzed from college students and office workers in Zhengzhou. The results indicate that attitude, subjective norms, perceived behavior control, and environmental awareness have a positive impact on the behavioral intentions of BS. However, the influence degree of each variable is different between the two groups. Perceived behavior control, including travel time, travel cost, and cycling difficulty, has the greatest impact on BS behavioral intention for college students. Meanwhile, subjective norms, including policy and media publicity, has the most significant impact on BS behavioral intention for office workers. The impact of environmental awareness on college students' use of BS is higher than that of office workers. We also found that undergraduates use BS more frequently than postgraduates. The findings provide the clear influence factors on behavioral intentions of BS between college students and office workers, that can help policy optimization in terms of bike-sharing systems, giving some suggestion for an approach devoted to deepen the individual-context interactions.

Non-linear effects of street patterns and land use on the bike-share usage

Non-linear effects of street patterns and land use on the bike-share usage

How Do Land Use, Built Environment and Transportation Facilities Affect Bike-Sharing Trip Destinations?

The purpose of this research is to investigate the effect of land use, built environment and public transportation facilities’ locations on destinations of bike-sharing trips in an urban setting. Several methods have been applied to determine the relationship between predicting variables and trip destinations, such as ordinary least squares regression, spatial regression and geographically weighted regression. Additionally, a comparison between the proposed models, count models and random forest has been conducted. The data were collected in Budapest, Hungary. It has been found that touristic points of interest, and healthcare and educational points have a positive impact on bike-sharing destinations. Public transportation stops for buses, trains and trams attract bike-sharing users, which has a potential for the bike-and-ride system. Land use has different effects on bike-sharing trip destinations; mostly as a circular shape variation within the urban structure of the city, such as residential, industrial, commercial and educational zones. Other variables, such as road length and water areas, form as constraints to bike-sharing trip destinations. Geographically weighted and spatial regression performs better than count models and random forest. This study helps decision-makers in predicting the origin-destination matrix of bike-sharing trips based on the transportation network and land use.

Factors associated with bicycle helmet use and proper fit: a cross-sectional survey of Montreal cyclists during the COVID-19 pandemic.

With increased bicycle use during the COVID-19 pandemic and growing availability of bicycle-sharing programs in Montreal, we hypothesize helmet use has decreased. The aim of this study was to evaluate helmet use and proper fit among Montreal cyclists during the pandemic relative to historical data. Nine observers collected data on bike type, gender, helmet use, and ethnicity using the iHelmet© app at 18 locations across the island of Montreal from June to September 2021. Proper helmet wear was assessed at one busy location. Multiple logistic regression was used to identify factors associated with helmet wear and results were compared to a historical study. Of the 2200 cyclists observed, 1109 (50.4%) wore a helmet. Males (OR = 0.78, 95%CI = 0.65-0.95), young adults (OR = 0.65, 95%CI = 0.51-0.84), visible minorities (OR = 0.38, 95%CI = 0.28-0.53), and bike-share users (OR = 0.21, 95%CI = 0.15-0.28) were less likely to be wearing a helmet, whereas children (OR = 3.92, 95%CI = 2.17-7.08) and cyclists using racing bicycles (OR = 3.84, 95%CI = 2.62-5.62) were more likely to be wearing a helmet. The majority (139/213; 65.3%) of assessed cyclists wore properly fitting helmets. Children had the lowest odds of having a properly fitted helmet (OR = 0.13, 95%CI = 0.04-0.41). Compared to 2011, helmet use during the pandemic increased significantly (1109/2200 (50.4%) vs. 2192/4789 (45.8%); p = 0.032). Helmet use among Montreal cyclists was associated with age, gender, ethnicity, and type of bicycle. Children were least likely to have a properly fitted helmet. The recent increase in popularity of cycling and expansion of bicycle-sharing programs reinforce the need for bicycle helmet awareness initiatives, legislation, and funding prioritization.

The impact of public bike-sharing systems on mobility patterns: Generating or replacing trips?

Bike-sharing systems allow occasional and regular users to travel by replacing other transport modes for the same trip or generating a new journey. Our research assesses the demand for Lisbon’s public dock-based bike-sharing system (BSS), named GIRA. This paper aims to identify the determinant factors that influence the potential of the BSS to generate new trips or replace previous modes using a conditional logit model based on a survey of 3112 BSS users. The survey results indicate that GIRA generated approximately 20% of the BSS trips, i.e., they would not have been realized if GIRA did not exist. The remaining BSS trips replaced other motorized (55%) and non-motorized (25%) trips. The main determinants explaining a higher likelihood of replacing different modes are having a yearly GIRA pass and a bike-sharing station within a 5-min walk. In contrast, regular car users are more likely to generate new trips, suggesting they use bike-sharing for recreational purposes. The findings provide policymakers with an assessment of determinants which may influence bike-sharing users to generate or replace trips from other modes and, consequently, define policies to potentially increase bike-sharing.

The COVID-19 impacts on bikeshare systems in small rural communities: Case study of bikeshare riders in Montgomery County, VA.

The shared and micro-mobility industry (ride sharing and hailing, carpooling, bike and e-scooter shares) saw direct and almost immediate impacts from COVID-19 restrictions, orders and recommendations from local governments and authorities. However, the severity of that impact differed greatly depending on variables such as different government guidelines, operating policies, system resiliency, geography and user profiles. This study investigated the impacts of the pandemic regarding bike-share travel behavior in Montgomery County, VA. We used bike-usage dataset covering two small towns in Montgomery county, namely: Blacksburg and Christiansburg, including Virginia Tech campus. The dataset used covers the period of Jan 2019-Dec 2021 with more than 14,555 trips and 5,154 active users. Findings indicated that a bikeshare user's average trip distance and duration increased in 2020 (compared to 2019) from 2+ miles to 4+ and from half an hour to about an hour. While there was a slight drop in 2021, bikeshare users continued to travel farther distances and spend more time on the bikes than pre-COVID trips. When those averages were unpacked to compare weekday trips to weekend trips, a few interesting trip patterns were observed. Unsurprisingly, more trips still took place on the weekends (increasing from 2x as many trips to 4x as many trips than the weekday). These findings could help to better understand traveler's choices and behavior when encountering future pandemics.

Impacts of the COVID-19 Pandemic on Bikeshare Usage by Rider Membership Status Across Selected U.S. Cities.

Bikesharing is a popular transportation mode for people to commute, for leisurely travel, or for recreation purposes in their daily tasks. Throughout 2020, the COVID-19 pandemic had significant impacts on bikeshare usage in the United States. Previous studies show that the pandemic negatively affected bikeshare activity patterns. To examine the effects of the pandemic on bikeshare behavior across membership types, this study investigated trip volume- and trip duration patterns of both members and nonmembers of five bikeshare systems across the United States. The results showed that member ridership significantly decreased throughout the pandemic, but nonmember ridership tended to be stable. It was also found that trip durations increased across both groups throughout the pandemic. Additionally, inferences were made to determine the level of support for a reversion to prepandemic normality as the pandemic progressed and reopening occurred in phases. The findings from this study could benefit bikeshare agencies in developing postpandemic recovery strategies.

Bike-sharing, car-sharing, e-scooters, and Uber: Who are the shared mobility users and where do they live?

• Bike-sharing users are worried about change, while Uber users are less worried. • Car-sharing is strongly associated with lack of access to a private car. • Shared mobility users are likely to reside in central, denser, transit-oriented locations. • Bike-sharing users live closer to the city center than other shared mobility users. • Citizens without tertiary education more likely to use shared e-scooters and Uber. This research provides new evidence on factors associated with the use of four different shared mobility options – bike-sharing, e-scooter sharing, car-sharing, and ridehailing (Uber) – in the same urban region. Factors examined are sociodemographic characteristics, concern about climate change, access to a private car, and built environment characteristics of users’ residential locations. The analyses are based on survey and GIS-measured, individual-level geospatial data from Oslo and its surrounding Viken county in Norway. Findings suggest that bike-sharing users are more likely to be younger, men, single, concerned about climate change, and living in denser neighborhoods with good access to public transport. E-scooter sharing users are more likely to be younger, men, without disabilities, and less educated, and live in denser neighborhoods. Car-sharing users are more likely to be living with a partner or spouse and children, not have access to a private car, and live in transit-oriented neighborhoods. Uber users are more likely to be younger and less educated, have higher incomes, be less worried about climate change, and live in proximity to the city center. These outcomes offer input for critical issues of urban and transport planning including compact urban form, sustainable mobility, and transport equity.

Examining the varying influences of built environment on bike-sharing commuting: Empirical evidence from Shanghai

Commute behaviors, as the primary part of urban mobility, remains largely underexplored, especially for bike-sharing users. Recent development in data availability open up new possibilities to delve into bike-sharing commuting over long-term periods on a large scale. This study proposes a methodological framework that enables a logical identification of bike-sharing commuting activities and a comprehensive examination of urban built environment effects on shaping commuting patterns. To this end, a series of data mining methods are developed in support of the identification of regular bike-sharing commuting, and the concepts of home-work balance and mobility trend are proposed to describe underlying commuting patterns. The XGBoost model and Necessary Condition Analysis (NCA) method are then adopted respectively to test the sufficiency and necessity of built environment on commuting patterns. The results confirm the massive existence of individual-level bike-sharing commuting activities and the pivotal role of bike-sharing in urban commuting. Also, the spatial distributions of home-work balance and mobility trend driven by job-housing separation show different clustering patterns. Besides, the synergy of sufficiency analysis and necessity analysis investigates the complex interplay of built environment-commuting patterns. This critical analysis of bike-sharing commute provides insights into sustainable transit planning and urban design.

Changes in physical activity after joining a bikeshare program: a cohort of new bikeshare users

BackgroundThere are hundreds of bikeshare programs worldwide, yet few health-related evaluations have been conducted. We enrolled a cohort of new bikeshare members in Philadelphia (Pennsylvania, USA) to assess whether within-person moderate and vigorous physical activity (MVPA) increased with higher use of the program and whether effects differed for vulnerable sub-groups.MethodsDuring 2015–2018, 1031 new members completed baseline and one-year follow-up online surveys regarding their personal characteristics and past 7-day MVPA minutes per week (minutes per week with- and without walking). Participants were linked to their bikeshare trips to objectively assess program use. Negative binomial (for continuous outcomes) and multinomial (for categorical outcomes) regression adjusted for person characteristics (socio-demographics, health), weather, biking-infrastructure, and baseline biking.ResultsParticipant median age was 30, 25% were of Black or Latino race/ethnicity, and 30% were socioeconomically disadvantaged. By follow-up, personal bike ownership increased and 75% used bikeshare, although most used it infrequently. Per 10 day change in past year (PY) bikeshare use, non-walking MVPA min/wk increased 3% (roughly 6 min/wk, P < 0.014). More days of bikeshare was also associated with change from inactive to more active (odds ratio for ≥ 15 days in PY vs. no bikeshare use 1.80, CI 1.05–3.09, P < 0.03). Results were consistent across vulnerable sub-groups. In general, impacts on MVPA were similar when exposure was personal bike or bikeshare.ConclusionsBikeshare facilitated increases in cycling, slightly increased non-walking MVPA, and showed potential for activating inactive adults; however, for larger program impact, members will need to use it more frequently.

Review on public bike share schemes in large developing cities: A case study of Delhi, India

In recent years bike share schemes have become increasingly popular in developing countries. Many cities have initiated bike-sharing schemes to promote sustainable mobility, increase bicycle usage, and enhance public transport's first and last-mile connectivity options. During the last few years, India also experienced a boom in bike-sharing schemes. However, unlike developed countries in Europe and America, limited research is available on bike-share schemes in developing countries like India. As a result, these countries face many problems in planning, designing, and operating bike-share schemes. This article considered Delhi a case study to address some of these problems and contribute to India's knowledge of bike-share schemes. The study considered different bike-share scheme operations in Delhi to analyse the bike-share characteristics and evaluate their impact on bike-share usage and ridership. Further, spatial analysis of bike-share schemes was also conducted to analyse the accessibility of bike stations to other facilities such as public transport systems, points of interest and their impact on bike-share usage and ridership. Moreover, a user-based survey was conducted to understand bike-share users' socioeconomic, trip characteristics, and preferences. Furthermore, a swot analysis was conducted to explore the city's strengths, weaknesses, and opportunities for operating bike-share schemes. Finally, based on the evaluation of bike-share schemes in Delhi, the study proposed various planning and policy-level recommendations to improve the bike-sharing schemes in similar size cities in developing countries like India.

The effects of bike-share users’ socio-demographics and trip features on the bike-transit relationships

Understanding how bike-share interacts with public transit is vital to determining the potential benefits of bike-share on the existing urban transportation system. This study examines the effects of bike-share users’ socio-demographics and trip features on whether bike-share users integrate or substitute public transit by conducting a questionnaire survey of Seoul’s bike-share users. The multinomial logistic model (MLM) was used for the statistical analysis. Our results showed that the bike-share’s trip purpose and perceived utility are significantly associated with the modal integration and substitution between bike-share and public transit. In particular, bike-share users are more likely to integrate with public transit when they make utilitarian trips near public transit stations. Furthermore, those who substitute public transit intended to save travel costs and exercise. The study’s findings can be utilized for establishing strategies to maximize the utility of bike-share in conjunction with the public transit system.

Can an Incentive-Based approach to rebalancing a Dock-less Bike-share system Work? Evidence from Sacramento, California

• Incentivizing users to walk farther is a way of rebalancing a bike-share fleet. • The impact of incentives on willingness-to-walk (WTW) to get a bike was examined. • Half of bike-share users would use a bike located 8.9-minutes away without an incentive. • WTW for incentives at origins and destinations were 3.8 min/US$ and 4.2 min/US$. • Results suggest the potential effectiveness of incentives as a rebalancing policy. Bike-share services will produce more limited benefits if users cannot find bikes when and where they need them. Bike-share operators must thus have process for “rebalancing” the bikes within the system to ensure that they are available where demanded. A potentially cost-effective strategy for rebalancing bikes is to offer incentives of some sort to users to walk farther to get a bike (origin-based incentive) or bring a bike to the undersupplied area (destination-based incentive). This paper aims to examine bike-share users’ willingness-to-walk to pick up a bike or drop off a bike at some distance from their origins or destinations if rewarded and to identify characteristics influencing willingness-to-walk. We use data from a survey of dock-less e-bike-share users conducted in the Sacramento region. The analysis shows that half of the respondents use bike-share if the available bike is located 8.9 min away. Our estimates of willingness-to-walk farther than the mean distance for incentives at origins and destinations were 3.8 min and 4.2 min per dollar, respectively. Our results give operators and policy makers insights into the potential effectiveness of incentives as a strategy for spatially rebalancing bike-share fleets.

Bike share and user motivation: exploring trip substitution choices among bike share users in a North American city

Bicycle share schemes have been implemented in scores of cities throughout the world over the last decade. Policy makers have embraced the technology of bike sharing to address a number of public policy problems, including congestion mitigation, improving air quality, and encouraging active mobility. While many of these systems have seen large numbers of users, understanding the motivations and perceptions of those using bike share systems is still relatively nascent. This study contributes to the evolving literature of bike share user motivation by using an intercept survey of bike share riders in a neighborhood of Chicago, USA where high levels of bike share usage have been prevalent. In particular this research explores the relationship between respondents’ motivations to use bike share and modal shift. We find that the odds of shifting from walking to bike share are predicted by a desire for convenience; the odds of shifting from automobiles to bike share are predicted by the desire for exercise and the cost savings of bike share; and the odds of shifting from train use to bike share are predicted by bike share cost savings. The findings from this research can help policymakers anticipate the impacts on modal shift from the perspective of the motivations of users.

Correlates of bike share use and its association with weight status at an urban university

BackgroundResearch on the influences on bike share use and potential favorable relationships between use and obesity is limited, particularly in the U.S. context. Therefore, the aims of this exploratory study were to examine correlates of awareness and use of Boston’s Bluebikes bike share system and assess the association between use and weight status.MethodsStudents, faculty, and staff (n = 256) at a public urban university completed an online survey that assessed sociodemographic, behavioral, and physical activity characteristics, Bluebikes awareness, and use of Bluebikes and personal bikes. Multivariable logistic regression models were estimated to examine associations between sociodemographic and behavioral factors and bike share awareness and use; and between use and overweight/obesity status.ResultsRespondents were mostly students (72.2%), female (69.1%), White (62.1%), and the mean age was 32.4±13.8 years. The percentage of respondents classified as aware of Bluebikes was 33.6% with only 12.9% reporting any use of the system. Living in a community where bike share stations were located (odds ratio (OR) = 2.01, 95% confidence interval (CI): 1.10, 3.67), personal bike ownership (OR = 2.27, 95% CI:1.27, 4.45), and not exclusively commuting to campus via car (OR = 3.19, 95% CI:1.63, 6.22) had significant positive associations with awareness. Living in a bike share community (OR = 2.34; 95% CI:1.04, 5.27) and personal bike ownership (OR = 3.09; 95% CI:1.27, 7.52) were positively associated with bike share use. Any reported use of Bluebikes was associated with 60% lower odds of being overweight/obese (OR = 0.40; 95% CI:0.17, 0.93).ConclusionsSeveral environmental and behavioral variables, including access to stations and personal bicycle ownership, were significantly associated with Bluebikes awareness and use. Findings also suggest a potential benefit to bike share users in terms of maintaining a healthy weight, though further longitudinal studies are needed to rule out the possibility that more active and leaner individuals tend to use bike share more frequently.

COVID-19 impacts on mobility, environment, and health of active transportation users

Active transportation could be an effective way to promote healthy physical activity, especially during pandemics like COVID-19. A comprehensive evaluation of health outcomes derived from COVID-19 induced active transportation can assist multiple stakeholders in revisiting strategies and priorities for supporting active transportation during and beyond the pandemic. We performed a two-step reviewing process by combining a scoping review with a narrative review to summarize published literature addressing the influence of COVID-19 on mobility and the environment that can lead to various health pathways and health outcomes associated with active transportation. We summarized the COVID-19 induced changes in active transportation demand, built environment, air quality, and physical activity. The results demonstrated that, since the pandemic began, bike-sharing users dropped significantly while recreational bike trips and walking activities increased in some areas. Meanwhile, there have been favorable changes to the air quality and the built environment for active transportation users. We then discussed how these changes impact health outcomes during the pandemic and their implications for urban planning and policymaking. This review also suggests that walking and biking can make up for the reduced physical activities during the pandemic, helping people stay active and healthy.

Analisis Tarif Penggunaan Bike-Sharing Berdasarkan Ability-to-Pay dan Willingness-to-Pay di Kampus Institut Teknologi Kalimantan

ITK needs to provide a facility that restricts private mode that operates on campus. Bike-sharing encourages greener mobility in the campus area. This study aims to get a model of bike-sharing users, with the market being the student who lives surrounding the campus area. The method uses both conventional and electric bikes' ability-to-pay and willingness-to-pay of students toward bike-sharing. The results show that the student's highest potency of the bike-sharing user is 82%, and the lowest is 44%. The highest potency of the electric bike for bike-sharing is 81%, and the lowest potency is 31%. The result also indicates that the students tend to use bike-sharing and consider tariffs rather than payment methods for conventional and electric bikes. The ability-to-pay and willingness-to-pay indicate the students are a choice raider. The value of ability-to-pay shows it is higher than willingness-to-pay towards the bike-sharing facility.

Approaching Sustainable Bike-Sharing Development: A Systematic Review of the Influence of Built Environment Features on Bike-Sharing Ridership

Bike-sharing is known as a sustainable form of transportation. This travel mode is able to tackle the “last mile” transit issue and deliver financial, well-being, and low-carbon lifestyle advantages to users. To date, many studies have analysed the influence of various factors, including built environments, on bike-sharing ridership. However, no study has exclusively synthesised these findings regarding the association between built-environment attributes and bike-sharing ridership. Thus, in this study, a systematic literature review was conducted on 39 eligible studies. These studies were assessed with respect to (1) bike-sharing usage, (2) studies’ geographical distribution, (3) data collection and analysis method, and (4) built environment factor type. Most studies were carried out in the US and Chinese cities. Variables associated with diversity, density, and distance to public transport stations and public transport infrastructure were frequently employed by the studies reviewed. It was found that BS stations with an average capacity of 24.63 docks and street network systems with an average length of 12.57 km of cycling lanes had a significant impact on the bike-sharing ridership. The findings of these studies were combined, and a series of recommendations were proposed based on them for bike-sharing service providers and researchers in academia. The findings of this evaluation can help practitioners and scholars understand the important built environment elements that influence bike-sharing ridership. Knowledge in this field will enable bike-sharing service providers to direct their resources sufficiently to enhance the more essential aspects of bike-sharing users’ satisfaction.

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

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.