E-bike Users Research Articles

What motivates consumers to adopt controversial green mobility innovations? The case of shared e-bikes and e-scooters

Green innovations sometimes have a debatable environmental impact, which could be related to how their adopters use them. This paper examines five factors encompassing a consumer trait of being innovative and various motivations that could help further understand the adoption of controversial green innovations. Mainly, this paper examines the use decision and users' behavioral intentions in two green innovations that have received mixed opinions – shared e-bikes and e-scooters, and how they are related to a consumer trait (eco-innovativeness) and consumer motivations (instrumental, environmental, hedonic, and symbolic). We surveyed shared e-bike and e-scooter users (n = 337) and non-users (n = 1001) in Sweden and applied structural equation modeling to test the relationship between the factors and adoption. Results show that eco-innovativeness and motivations affect use decisions and behavioral intentions differently. Specifically, environmental motivations negatively affect use decisions but are positively significant in future behavioral intentions. Hedonic motivations have the strongest effects, which could help explain the controversy surrounding shared e-bikes and e-scooters. Theoretically, we contribute to understanding how traits and motivations are significant in the diffusion of green innovations. The paper shows that despite being mainly promoted as good for the environment, other motivations could significantly drive the adoption of novel green products. Practically, this indicates that promotion and public policies surrounding green innovations should not be limited to communicating their functional and pro-environmental attributes.

Optimization Strategy for the Spatiotemporal Layout of E-Bike Charging Piles from the Perspective of Sustainable Campus Planning: A Case Study of Zijingang Campus of Zhejiang University

With the expansion of Chinese university campuses, electric bikes (E-bikes) have become the most sustainable and effective commuting option because they are a flexible and energy-saving travel mode. Consequently, campus E-bike charging piles have become one of the most essential public service facilities on campuses. However, since most Chinese campuses are closed and independent, the principles of urban public service facilities cannot be simply applied to the layout and use of campus charging facilities. Thus, this study focuses on Zijingang Campus at Zhejiang University, and proposes an optimization strategy for the spatial and temporal layout of E-bike charging piles on the campus. First, trip chain demand models are constructed to examine the travel patterns of E-bike users on campus and the demands for charging areas and time. Second, a space location model is constructed to locate the charging piles in areas with high demand. Finally, according to the charging times of different users, user charging time is integrated into the strategy. This study enhances the layout and utilization system of campus E-bike charging facilities by considering both temporal and spatial dimensions. Overall, this study contributes to the advancement of sustainable transportation infrastructure planning on a campus-wide scale, offering theoretical insights for the design and utilization of functional facilities in large-scale, semi-enclosed environments (e.g., university campuses).

User acceptance of smart e-bikes: What are the influential factors? A cross-country comparison of five European countries

Electric bicycles (e-bikes) have been promoted in many countries to replace motorised transport modes and mitigate transport externalities such as traffic congestion and emissions. However, there are also concerns about crash risks and crash severity for e-bike users. Leveraging new technologies could help improve e-bike safety, amongst other safety enhancing measures, but there is little knowledge of the users’ acceptance of such technologies. This study aims to explore the user acceptance of e-bikes (pedelec with power assistance up to 25 km/h or speed-pedelec with assistance up to 45 km/h) with active road safety assistance (in short: Smart e-bikes) to improve cycling safety by adopting the extended unified theory of acceptance and use of technology 2 (UTAUT2). A cross-country survey was administered in five European countries-Austria, Belgium, Germany, Greece, and the Netherlands, each differing in population, cycling culture and e-bike market sizes. A sample of 1,589 respondents, including e-bike owners and people interested in buying an e-bike, was analysed using a structural equation model (SEM). Conclusions indicate that performance expectancy, hedonic motivation and perceived safety were the strongest constructs of behavioural intention to use Smart e-bikes in the aggregated sample. All constructs vary significantly across the five countries, which can partly be explained by socio-demographic factors. Geographical factors such as city size, low availability of cycle paths and population density do not explain differences in user acceptance.

From Frustration to Innovation: Exploring the Lived Experiences of E-Bike Users on Limited Charging Infrastructure

This abstract summarizes a phenomenological study exploring the lived experiences of electric bike (e-bike) users dealing with limited charging infrastructure. Through purposive sampling, 8 participants were interviewed, revealing three prominent themes. The first theme, "Technical Challenges and Solutions," delves into battery-related issues and coping strategies. Participants shared their stress caused by battery limitations and sensitivity to water, alongside coping strategies and the effectiveness of maintenance routines. The second theme, "Infrastructure and Accessibility," highlights concerns regarding the absence of charging stations and the benefits they offer. Participants expressed worries about inadequate infrastructure while recognizing the important role of charging stations in facilitating e-bike usage. Lastly, "Cost-Effectiveness and Sustainability" highlights participants' perspectives on the economic benefits of e-bikes as sustainable transportation alternatives. This research illuminates the diverse experiences of e-bike users, shedding light on their challenges, adaptations, and aspirations amidst evolving charging infrastructure settings.

What determines the batteries recycling behavior of e-bike citizens in Guangzhou?: Integrating place identity and environmental concern into the extended norm activation model

Battery recycling is viewed in China as an important means of achieving primary sustainability goals and greater economic and environmental development. With the notice of high battery recycling intentions through relevant investigations, this study examine the influencing factors of these recycling behaviors of e-bikes citizens by incorporating the place identity and environmental concern into the Extended Normative Activation Model (NAM), which fill the research gap on how place identity and environmental concern affect the batteries recycling behavior. This study proposes that the consequence awareness, personal norms, and attitudes have mediating effect on place identity to the recycling behavior, and the environmental concern has moderating effect on consequence awareness, personal norms, and attitudes to the recycling behavior, respectively. Based on 1068 valid surveys, hypotheses were examined using partial least square structural equation modeling (PLS-SEM). The results show that personal norms and awareness of consequences positively impact e-bike users' intentions to recycle waste batteries, and environmental concerns have no moderating effect on attitude, recycling intention, personal norms, and recycling intention. Theoretical and practical implications are discussed at last.

Exploring the Factors Influencing Electric Bicycle Adoption: A Survey Among Future Adopters in India

Electric bicycles (e-bikes) are an emerging mode of sustainable transportation well-known for their individual and environmental benefits. Past research suggests factors for e-bike adoption from new and experienced e-bike users, but little is known about prospective users’ attitudes. Understanding the standpoint of non-users would reveal practical barriers impeding e-bike adoption in developing markets. We identify important drivers and barriers from a representative city-level sample of prospective e-bike users in India. The study employs exploratory factor analysis integrated with a multi-criteria decision-making model to identify latent components and prioritize their variables. The results revealed five factors: user-perceived benefit-specific motivators, travel quality-specific motivators, e-bike mobility-specific motivators, perceived social and economy-specific barriers, and e-bike infrastructure-specific barriers. Attributes such as monetary savings, reduced congestion, and last-mile connectivity were identified as the most important benefits, while fear of battery explosion and lack of cycling and charging infrastructure were perceived as the key barriers. Comparison by age shows “purchase cost” as the most influencing perceived social and economy-specific barrier among young male commuters. Comparison by income underlines the diminishing importance of “purchase cost” with increasing income among males. Regardless of age, income, and trip length, females prioritized “range anxiety” over “purchase cost.” The trip length-based comparison reveals the significance of “risk of theft” for males with longer trip lengths. In general, males of all groups preferred using e-bikes for “short non-commuting trips” substituting motorized transport, while females preferred using them for “last-mile connectivity.” These findings offer insights for designing effective e-bike promotion campaigns for the mass adoption of e-bikes.

What differentiates e-bike riders from conventional cyclists in Denmark? A user-based study

Among the many technology-related advances in two-wheeled mobility, the growing share of e-bikes stands out. Indeed, despite their increased cost and user-related constraints, e-bikes have gained ground in European cities over the last two decades. However, not much is known about the psychosocial and behavioural characteristics of e-bike users compared with conventional bike (c-bike) users. AimsTherefore, the aims of this study were: first, to explore differences between e-bike and c-bike users regarding individual features, cycling habits, and riding behaviour; and second, to identify individual characteristics, cycling habits, and behaviours predicting using an e-bike as the main cycling mode. MethodsThe study used data from 557 Danish cyclists aged over 18, proportionally distributed according to population data (13% e-bike and 87% c-bike users). The cyclists responded to an electronic survey on cycling affairs, addressing trip patterns, risk perception, cycling anger, distractions, and riding behaviours. ResultsOverall, no differences were found regarding personality, distractions, riding errors, or cycling anger. However, e-bike users self-reported significantly lower rates of traffic violations and higher rates of positive behaviours, traffic rule knowledge and road risk perception. Furthermore, structural (SEM) analyses suggest that e-bike riding can be predicted through demographic factors, psychosocial characteristics, and cycling behaviours. ConclusionThe results of this research provide insights into the characteristics and behaviours of e-bike and c-bike users in Denmark, indicating key differences between the two groups in relation to their demographic backgrounds and cycling habits. This underscores the importance of considering demographics, cycling habits, and psychosocial factors when studying and promoting the use of e-bikes.

Empowering the Capillary of the Urban Daily Commute: Battery Deployment Analysis for the Locker-Based E-bike Battery Swapping

In densely populated Asian countries, e-bikes have become a new supernova in daily urban transportation. To facilitate the operations of e-bike-based mobility, the present paper studies the management of the battery deployment for the e-bike battery-swapping system, where the unique features of e-bike riding are considered. Given the pedal-assisted mode, e-bike users could abandon waiting and return to the station later on without too much range anxiety. However, because of the time-varying nature of the customer arrival and the complicated user behaviors, the battery quantity at each station is altered to guarantee the designated service level. However, little research has been done on the operations management of the e-bike battery-swapping system. To bridge the gap, we propose a nonstationary queueing network model to characterize the customer behaviors during the battery-swapping service. Then we develop a closed-form delayed infinite-server fluid approximation for the battery deployment of the one-time-loop scenario under various quality-of-service targets. In addition, we handle the infinite-time-loop scenario with the simulation-based iterative staffing algorithm. In the simulation study, we observe that the proposed battery deployment algorithms can help stabilize the system performance in terms of abandonment probability and expected delay in the face of time-varying demand and complex customer behaviors. Moreover, we reveal that the number of return loops correlates with the service level targets on the battery deployment decision. Furthermore, a time gap exists between the demand and the optimal battery deployment, making proactive battery management in the system possible. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72271222, 71871203, 71872093, 72271137, L1924063], and the National Social Science Fund of China [Grant 21&ZD128]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.0132 .

Trends in Head and Neck Injuries Related to Electric Versus Pedal Bicycle Use in the United States.

To describe the incidence of head and neck trauma related to electric bicycles and to characterize head and neck injury patterns seen in electric bicycle (eBike) users versus pedal bicyclists in the United States. The National Electronic Injury Surveillance System (NEISS) was queried from 2009 to 2020 for patients with head and neck injuries related to electric and pedal bicycles. Extracted data included patient demographics, injury patterns, hospital admission, and helmet use. Univariate chi-squared analyses were performed to compare demographics and injury patterns between bicycle groups. Effect sizes were reported with Cramer V values (V). The incidence of eBike-related head and neck injuries increased from 2993 in 2009 to 9916 in 2020. Compared to pedal bicycle users, eBike users were more likely to have head injuries (60.4% vs. 52.0%) and fractures (10.9% vs. 6.0%), and were more likely to require hospitalization (20.6% vs. 10.4%). The effect size of helmet use was significantly greater in eBike users compared to pedal bicyclists when examining distributions of age group (V = 0.203 vs. V = 0.079), injury location (V = 0.220 vs. V = 0.082), and injury type (V = 0.162 vs. V = 0.059). Helmeted injuries in eBike users more commonly involved neck injuries and sprains, rather than head injuries and fractures. Head and neck trauma related to eBike use is increasing in the United States. Injury patterns and admission rates reflect greater injury severity in eBike users compared to pedal bicyclists. Helmet use may be particularly beneficial in mitigating head and neck injury in eBike users. 3 Laryngoscope, 134:2734-2740, 2024.

How does brand equity influence the intent of e-bike users? Evidence from Chennai city

E-bikes, a rapidly developing hybrid technology, threaten the notion of leisurely, non-motorized riding. This empirical study aims to determine the connection between brand equity, brand value, and electric bike purchase intention in Chennai. The descriptive research strategy was employed to collect the data from 151 respondents via questionnaire using judgment sampling, and hypotheses were tested using multiple regression. The consequences showed that the coefficient for brand loyalty was 0.643, and a one-unit increase in brand loyalty resulted in a 0.643% increase in purchase intent. The study’s results help managers better understand how to create a post-brand equity marketing strategy for long-term success in the market. An improved understanding of brand equity’s effects would help the auto industry gain consumer loyalty and enable long-term partnerships

Sensory and emotional dimensions of domesticating new technology: an experiment with new e-bike users in Norway

Cities face major challenges when it comes to sustainability and mobility. Transport’s contribution to climate change is well-established, and people need to move in the most sustainable way to reach the 2030 emissions targets set by the Paris Agreement. One possible pathway towards more sustainable mobility practices is electromobility. The electrification of micro-mobility is happening rapidly, and one of the most popular is the e-bike. For years, electric bikes were relegated to niche status, but they are now experiencing explosive growth in sales in many countries. In this article, we draw on an experiment with new users of e-bikes to study the integration of e-bikes into existing mobility practices and to explore their sustainability potential. Through the lens of domestication theory, we zoom in on the relations that formed between users, technology, and environments in the course of the experiment. Our analysis highlights how emotional and sensory experiences play crucial roles in the adaption of new mobility technologies. Based on our findings, we argue that to reach the sustainability potential of e-bikes, a set of support mechanisms must be developed according to a holistic and relational understanding of mobility that also takes emotions and sensory experiences into consideration.

E-Bike Charging Infrastructure in the Workplace—Should Employers Provide It?

Constructing charging infrastructure for e-bikes at home or in other locations is necessary to enable motor support while riding. This paper focuses on charging facilities at work and study locations. It analyzes the charging frequency preference of 281 e-bike commuters who work or study at RWTH Aachen University, using survey data with 1091 choices for hypothetical free charging, as well as the same conditions for hypothetical paid charging. We use a mixed logit model to estimate the factors influencing the charging frequency, focusing on the commuting distance, an e-bike’s resale value, the age of the owner, student status, and employment group. One charging event per day can be expected for four e-bike commuters when free charging is available. In the case of paid charging, there is one charging event per 12 e-bike users. The magnitude of the reduction caused by a charging fee depends on group membership and, probably, on income. Commuting distance only has a statistically significant influence on the charging frequency when charging is free, raising the question of whether charging at work is necessary to cover trip chains that include stops at work. Owners of more expensive e-bikes charge less often, likely due to higher battery capacities, while the influence of age is inconclusive. However, providing charging infrastructure for employees and guests could be used as a low-cost measure to promote cycling among commuters.

Inferring and comparing trip purposes of shared micromobility services: A case study of Ningbo, China

Over the past decades, shared micromobility services (SMSs) have experienced ever-fast growth around the world. Such increment has raised issues such as how to improve the efficiency of the service operation and regulation. To address these issues, it is essential to understand how and why these SMSs are used. This research aims to infer trip purposes of two types of dockless SMSs, i.e., dockless shared bikes and e-bikes, and make a comparison between them, mainly using a Latent Dirichlet Allocation (LDA)-based analytical framework. The proposed framework was applied in Ningbo, China by combining a large-scale bike-sharing trip dataset and a Points of Interest (POIs) dataset. In our case study, we successfully revealed seven typical trip purposes, i.e., transport, work, lodging, eating, shopping, education, and others. The results showed that eating is the most prevalent trip purpose for both bike and e-bike users. Surprisingly, the proportions of transport-related trips were insignificant compared to previous observations, for both shared bikes and e-bikes. Moreover, the shared bike played a more significant role than the shared e-bike in daily trips related to lodging and education, indicating that the role of the shared e-bike in these trips might have been overestimated previously. This study provides insight into the trip purposes of SMSs and gives targeted planning and operation suggestions, which can promote sustainable development of the urban micromobility systems.

Review of Current Practice and Research on E-Bikes in Transport Models

E-bike sales have been growing strongly across the globe in recent years. Despite the differences between e-bikes and conventional bicycles, bicycle traffic is typically considered a uniform mode in macroscopic transport modeling. This is problematic because such models do not allow for dedicated e-bike analysis and could therefore have adverse impacts on accuracy. In this study, we therefore investigated whether and how e-bikes are presently modeled in practice and how e-bikes should be modeled to improve data validity and usefulness. To this end, we conducted a review of 14 exemplary strategic transport models and carried out a structured exploratory literature review of existing empirical research. We queried four fields of research and investigated 29 relevant and unique sources covering influences on e-bike ownership and use as well as the characteristics of e-bike mode and route choice. Based on this work, we identified three key findings: (1) purchase choice and mode choice models must allow for scenario setting; (2) generalized costs should also include factors other than travel time, and the factors’ weighting parameters should be estimated separately between conventional bicycles and e-bikes; and (3) it is especially important for e-bike modeling to differentiate between person groups. Future research is needed to investigate route choice parameters for e-bike users, especially concerning the aversion to slopes, and methods to collect e-bike-specific data. Our findings demonstrated that, although modeling e-bikes is worthwhile, appropriate modeling approaches still need to be developed and applied to demonstrate their practicability and usefulness.

Pro-Environmental Attitudes, E-Bike Adoption Motivations, and Tourist Green Behavior

This study examines the relationship between pro-environmental attitudes, e-bike adoption motivations, and tourist green behavior (TGB). Environmental psychologists have increasingly focused on understanding “green” tourist behavior determinants. The TGB distinguishes tourists from pro-environmentalists for relatively everyday simple actions, and e-bike adoption motivations can serve as a mediator to better understand pro-environmental attitudes– tourist green behavior relationships. We tried to bridge this gap by conceptualizing TGB and investigating the mediating role of e-bike adoption motivations in the relationship between pro-environmental attitudes and TGB. Derived from an online survey-based sample of 682 e-bike users, the data were investigated using structural equation modeling analysis. Findings showed that directly and indirectly, pro-environmental attitudes significantly influenced TGB, and e-bike adoption motivations (e.g., cost-effective motivation, intrinsic motivation, technology motivation) mediate their concerned paths. Therefore, the stakeholders and marketing practitioners should emphasize the importance of pro-environmental attitudes and e-bike motivations within the TGB and e-bike adoption campaigns.

Comparing E-Bike Users’ Perceptions of Safety: The Case of Lausanne, Switzerland

Electrically-assisted bicycles (E-bikes) may broaden cycling to a wider spectrum of users, territories, and trips. But what are e-bike users’ experiences of safety in a low-cycling city, and how do they vary among different users? This paper conceptualizes perceived safety based on vélomobility as the meeting point between users with specific characteristics (age, gender, etc.) and an environment more or less amenable to cycling. It is based on data from a survey of 1260 e-bike users who received a subsidy in Lausanne, Switzerland. We use 13 variables to measure perceived safety, finding 3 components: comfort for cycling in different situations, satisfaction with cycling conditions, and barriers to e-bike use. Based on these components, we identify four groups of e-bike users: (1) confident all-rounders, (2) recreational on-roaders, (3) worried traffic-avoiders and (4) unconfident path-users. We find gender and age to be the main factors associated with being a member of a group with lower perceived safety. Low weekly frequency of e-bike use, reduced winter e-bike use, and cycling for recreational trips exclusively also reduce perceived safety. Despite the benefits of electrical assistance compared to conventional bicycles, low safety due to unwelcoming road conditions remains a major concern for many e-bike users.

What determines the battery recycling behavior of electric bike users?: Introducing recycling convenience into the theory of planned behavior

To protect the environment, China attaches great importance to waste lead-acid battery recycling of electric bikes (e-bikes). If China wants to do a good job in recycling, it cannot do without the strong support of e-bike users. The research introduces recycling convenience into the theory of planned behavior (TPB) to verify the impact of recycling convenience on user behavior. The structural equation model (SEM) was used to investigate the recycling behavior of 429 e-bike users in Tangshan, China. The results show that attitude, subjective norms, and recycling convenience all can affect e-bike users' behavior intention positively and significantly, while perceived behavior control can not affect intention significantly. Simultaneously, this study established the beneficial and significant effects that perceived behavior control and behavior intention can have on e-bike users' recycling behavior. In addition, the study also verified that recycling convenience can indirectly affect users' recycling intention by influencing users’ attitude and subjective norms, indicating that this extended theoretical framework of planned behavior is appropriate for e-bike user behavior research.

A quantitative traffic performance comparison study of bicycles and E-bikes at the non-signalized intersections: Evidence from survey data

As common transportation modes at non-signalized intersections, bicycles and e-bikes have been involved in most traffic crashes. Although a large number of studies have been dedicated to studying the safety problems caused by bicycles and e-bikes, there is still limited attention paid to the differences between them, especially at non-signalized intersections. This paper compares the differences between bicycles and e-bikes based on a self-administered questionnaire. This questionnaire was distributed to bicycle users (N = 453) and e-bike users (N = 439). The personal characteristics, decision-making capacity, the feeling of infrastructure, perceived level of service, and perceived level of risk were adopted as the performance indicators to depict the difference in the study area. Using statistical methodologies and the Structural Equation Model (SEM), key findings indicate that perceived level of service was found to be significantly different between bicycles and e-bikes at most non-signalized intersections. 43.4 % of e-bike riders often or always choose to avoid riding under extreme weather, while 58.7 % of bicycle riders avoid riding under extreme weather. Moreover, compared with bicycles, e-bikes’ decision-making capacity is affected more by infrastructure quality. The difference between bicycles and e-bikes highlights the need for differentiated development of cycling safety education and law enforcement.

Impact of electrically assisted bicycles on physical activity and traffic accident risk: a prospective observational study

BackgroundElectrically assisted bicycles (e-bikes) have become increasingly popular and may facilitate active commuting and recreational cycling.ObjectiveTo evaluate the physical activity levels and usage characteristics of e-bikers and conventional cyclists under...

E-bikes in rural areas: current and potential users in the Netherlands

This study considers how socio-demographic characteristics, mobility situation and attitudes explain current and potential e-bike use in rural areas. Due to longer distances between travel destinations, rural areas in most western societies are characterized by a high car dependence and low use of active modes like walking and cycling. Developing e-bike mobility in these areas can support more healthy and sustainable rural mobility. A large-scale mobility survey conducted among rural residents in the northern parts of the Netherlands provides insight in the determinants of current and potential e-bike use in rural areas. The participant characteristics show that in rural areas also, the e-bike is already used among a broad population of varied ages and backgrounds and for different purposes. Among respondents who did not own an e-bike, especially those with lower socioeconomic status and a household with children showed more willingness to use an e-bike in the future. No evidence was found for current or potential substitution of public transport use. Current e-bike users less likely use a car or regular bicycle as their primary mode of transport. Those who are willing to use an e-bike are less likely to currently use a regular bicycle as their main mode of transport. These findings suggest that the e-bike can substitute both car and bicycle use to some extent. However, bicycle users seem more reluctant towards owning or adopting an e-bike than car users, suggesting greater potential for a shift away from car travel. Furthermore, current and potential e-bike users hold more positive attitudes toward different aspects of e-bike travel than non-users. This provides impetus for future actions to further encourage e-bike use.