Gaining Traction on Social Aspects of E-Biking: A Scoping Review

Abstract

E-biking is alluring for its various physical, environmental, and financial benefits and the ability to travel farther and faster, and being physically easier to ride than astride an analog (traditional) bicycle. E-bikes are also a source of controversy, especially in places where analog bicycles have been allowed but e-bikes represent a “slippery slope” of technology permissions and/or in situations where the function of e-bikes may increase concerns about safety. Despite an increase in use and conversation about such use, academic literature focused on e-bikes’ social aspects remains sparse. The objective of this work is to describe the existing literature on the characteristics of social aspects of e-biking, particularly in leisure contexts. Analyzing the literature on e-bike social research is crucial considering e-bikes’ rapid rise in popularity and potential effects on access, inclusion, leisure, and sustainability. As e-bike prevalence and use increases worldwide, it is important to understand what topics characterize the existing e-bike literature, and, particularly in leisure-focused studies, to ascertain where studies may lend insight toward aims of inclusive and sustainable access, and related policy considerations. The Integrated Recreation Amenities Framework (IRAF) provides a conceptual framework for considering this question, as it focuses on the topical, spatial, and temporal scales of outdoor leisure-related activities toward sustainable conditions and explicitly provides an opportunity for emergent and case-specific factors to be considered alongside established ones. In this work, we explore the following: (1) How are e-bikes discussed across disciplines? and (2) How are e-bikes discussed in leisure-focused articles? Using a scoping review approach, we analyzed a corpus of 279 peer-reviewed articles relevant to the social aspects of e-bikes. Primarily using the IRAF for conceptual framing, our results center the geographies and contexts, topical areas, interdisciplinarity, and emergent additional social considerations of e-biking in general and in leisure-specific studies. The results enable us to connect interdisciplinary topic discussions and suggest where foundational and connective studies are warranted. This can inform decision making related to e-bike adoption, encourage multi-scalar thinking, and extend interdisciplinary research.

1. Introduction

E-bikes, a type of bicycle with an attached electric motor that assists with propulsion and can be run on electricity as well as conventional pedaling, have soared in global popularity over the last decade [1]. Consistent among the various types of e-bikes commercially available (e.g., pedal-assist and throttle-assist) are the battery, controller, and motor components [2]. The pedal-assist e-bike requires the rider to manually use the pedals to assist the motor with propulsion, and the throttle-assist e-bike does not require any physical effort from the rider. E-bikes are attractive for their physical, environmental, and financial benefits and their ability to allow a rider to travel farther and faster, and being physically easier to ride than an analog (traditional) bicycle (i.e., run solely on conventional pedaling without electronic assistance). They can be used as daily transportation and for commuting, an occupational tool for delivery service workers, a leisure and outdoor recreation activity, and more. They can also facilitate inclusion for those who find they cannot (or can no longer) use an analog bicycle as they desire, updating cycling to a more socially sustainable form of transport and leisure. However, e-bikes are also a source of controversy, especially in places where analog bicycles have been allowed but e-bikes represent a “slippery slope” of technology permissions and/or in situations where the function of e-bikes may increase concerns about safety [3].

The COVID-19 pandemic and, consequently, the increased interest and demand for safe outdoor leisure and recreation [4], especially among older populations, launched e-bikes into mainstream popularity [5]. Accordingly, the global e-bike market experienced a boom as sales increased 240% between 2019 and 2021, four times the rate at which analog non-motorized bicycle sales increased [6]. E-bike production grew slowly between 1993 and 2004, but, by 2019, the market was estimated to be at $15.42 billion and continued to grow by 7.5% in 2020–2024, with the pedal-assist electric bikes and use in urban settings, being the dominant (88.4%) propulsion type and use of e-bikes [7]. The COVID-19 pandemic highlighted the need for socially distanced forms of transportation and leisure, and e-biking rode into this need. E-bike popularity reached record heights during and after the pandemic, and the projected compound annual growth rate between 2022 and 2030 is 10% [5].

Reasons for this growth include technology and tradeoffs [8]. Among most types, motor power typically ranges 200–1000 W, weighing 20–45 kg, and not exceeding 45 km/h (about 28 MPH) [2]. A heavier bike can make it harder for the rider to maneuver and propel themselves, as well as drain the battery life [9]. Increased battery capacities allow users to ride longer distances or steeper grades, but doing so may increase the overall weight of the bike. Lithium-ion batteries generally allow a compromise between battery capacity and e-bike weight, which has increased the appeal (and cost) of e-bikes, although batteries continue to evolve (e.g., solid state) alongside conversations of sustainable manufacturing and product lifespans [9,10]. Technology has continued to advance, creating e-bikes that are increasingly lightweight and less expensive, making it even more convenient for users to travel, commute, and recreate with their e-bike. Additionally, rising fuel prices and demand for vehicles over the last decade have contributed to a growth in e-bike adoption and will likely continue to be a factor due to the shrinking crude oil supply.

Due to the higher speed potential of an e-bike compared to an analog bicycle, safety remains a concern among users [2]. For example, perhaps due to their high numbers of e-bikes, China has the most research on e-bike crashes and studies here typically focus on conflict, erratic behaviors, and crash and injury data retrieved from hospital records [2,11]. Looking on a global scale, Scarano et al. performed a systematic literature review on cyclist safety research (2012–2021) and found that many highly cited studies focus on contributing factors to crash severity and frequency, risk factors, and bicycle networks [12]. Macioszek and Granà corroborated this in their 2022 work, focusing on factors that increase injury severity among vehicle crashes with any type of cyclist and finding that those related to age, alcohol intoxication, speed, road type, time, and vehicle driver characteristics are paramount corollaries to safety concerns [13]. The growing field of cycling safety research will be important as e-bikes continue to gain popularity and become a more mainstream transportation mode.

However, global statistics are insufficient to explore the full range of questions and concerns related to e-bikes, as e-bike use and research differs across geographies and populations. For example, publications from China and other Eastern countries primarily focus on operations, safety, and market growth, while Western studies from North America and Europe mainly research emerging markets, health, and behavior [2]. Scooter-style e-bikes look more like motorcycles and are more common in China, while bicycle-style e-bikes look like analog bicycles and are more common in Western countries [2,14]. This may propel some of the differences seen in publication topics. Use may also vary by population within a geography. When e-bikes were first introduced, the primary adopters were older people with mobility constraints, which initiated an association between e-bikes and old age (not the original creators’ intention) [15]. The benefits were not obvious to those whose conventional cycling abilities were not limited [15]. However, more recent studies on e-bike use demonstrate that a variety of age groups have adopted e-biking for general transportation, commuting to work or school, running errands, delivery services, leisure, and recreation [15,16]—all suggesting a wider appeal and sustainability of the technology.

The rapid growth in the popularity of e-bikes has important implications for research across disciplines including transportation, energy, environmental studies, health, engineering, sustainability sciences, and public policy. E-bikes represent a potential strategy for contributing to sustainable transportation systems worldwide, thereby supporting efforts in social sustainability. Social sustainability is a theoretical framework that comprises four major components: equity (justice), safety (securing for humans and non-humans), urban forms (sustainable built environment), and eco-prosumption (mitigation measures) [17]. Fundamentally, the ontological foundation of social sustainability is safety and addressing the risks to people and the planet that are associated with climate change. The growth in popularity of e-bikes can support social sustainability by providing environmentally conscious mobility and leisure, contributing to human health and wellbeing, and being part of the development of sustainable cities and communities. However, the academic literature on e-bikes, particularly the academic literature regarding social aspects of e-biking, remains sparse and perhaps characterized as still in the exploratory stages [18]. Many publications exist on the technical and mechanical aspects of the e-bike itself, but far fewer studies research the cross-disciplinary social implications (e.g., [18,19]). The early stages of e-biking research primarily focused on electrical technology and crash dynamics. The later stages of research began to shift towards travel behavior, then safety and health [18,19].

Overall, there has been a shift in the mobilities discipline to a more multi-disciplinary, comprehensive approach [20]. Yet, even with this shift in focus, there is a lack of studies within regional and cultural contexts that could shed light on variations between transportation infrastructure, natural environment, and psychological and cultural aspects that influence the adoption and use of e-bikes [20]. Accordingly, our aim in this work is to understand the characteristics of social aspects of e-biking, particularly in leisure contexts, so as to describe the current state of knowledge worldwide and evaluate the extent to which the literature addresses aspects of social sustainability. To achieve this, we conducted a scoping literature review to systematically map the existing social science e-bike literature and address two research questions: (1) How are e-bikes discussed across disciplines? and (2) How are e-bikes discussed in leisure-focused articles? Our work details the procedures, findings, and conclusions related to these aims. In particular, the results focus on geographic use distributions, topical representations and integrations, the interdisciplinarity of articles and authors, thematic keyword clusters, and social aspects of the leisure articles (safety, equity, motivations, and constraints).

2. Methods

We used a PRISMA guide for scoping reviews, modified for the context of this social science study and inspired by other scoping reviews on cycling topics, such as mountain biking impacts [21]. Below, we detail the scoping review steps within the typical format of data collection and analysis approaches, addressing the areas of the PRISMA checklist for scoping reviews. Because our research team represents a diversity of natural resource social scientists, our approach was collaborative and generative, centering conversations on research decisions and results interpretations at every stage.

2.1. Data Collection and Eligibility Criteria

Our protocols for data collection and inclusion followed a systematic process (Figure 1). We used the Web of Science database for this inquiry, as it captures a range of sciences well and emphasizes the international context of our topic. Using Web of Science to identify relevant documents, we searched with the following parameters on 26 September 2023, saving the outputs for examination: search term “e-bik*” and publication dates 2001–2023. The search was intentionally broad and without qualifier Boolean terms, to capture the breadth of work on e-bikes. This yielded 2673 articles. The search results were exported into a Google Sheets spreadsheet, where the lead researcher reviewed each article’s title and abstract. From this point onward, articles were manually included or excluded following a strictly adhered-to process. Articles were excluded from further steps if they (1) did not mention e-bikes and did not contain a human element, (2) were not written in English, or (3) were not published as a journal article (e.g., dissertation, thesis, conference/proceedings paper, editorial material, study protocol, and meeting abstract). This initial process resulted in 1897 articles being excluded and 775 being retained (29.0%). Two authors then conducted a second round of review on these 775 initially qualifying articles, reading each article’s entire contents and validating each other’s article inclusion process. From this, articles were excluded if user experience and e-bikes were not the focus. This eliminated another 496 articles as non-relevant to the aims of this study, yielding 279 articles in the final corpus (10.4% of the search results (Phase One) and 36.0% of the title and abstract relevance results (Phase Two)) (Figure 1). A PDF of each of these articles was downloaded from its original source for researcher review.

The 10-member research team then trained on data entry and input these 279 qualifying articles (hereafter named the dataset or the corpus) into Google Sheets. To ensure inter-coder reliability, we all interacted with a common instruction manual and article set. These were then cross-checked for data entry discrepancies and discussed to achieve a shared understanding of the coding framework. This increased our confidence in the validity of the effort across the team. Data entry formats were mainly binary or categorical, with some open-text response areas. We encouraged entry of summaries of information from the article and illustrative direct quotes as warranted. Any ambiguity or disputes about an article’s data or leisure or non-leisure focus were resolved through team discussion.

One of the primary areas for categorization was through the Integrated Recreation Amenities Framework (IRAF) [22]. The IRAF enables us to find and understand the complex interactions occurring between systems and new areas, as varying relationships exist among our scales of analysis. This framework builds on the traditional threefold framework of outdoor recreation settings [23] to further clarify areas of managerial, resource, and social topics, as well as to acknowledge spatial and temporal scales and to leave cognitive space for undefined and emergent topics that may be context-specific. The IRAF is premised on sustainability, as considerations and tradeoffs for balance among its areas are necessary to retain or enhance the long-term viability of a recreation amenity and thus is well-suited for considering social sustainability. It is a conceptual model with spatially, temporally, and topically integrated areas that allows us to examine research in a multi-scalar way. This framework has previously been used to explore topics such as the content of climate action plans within a region [24] and mountain biking impacts [21]. Using this framework was a means to further categorize the social studies of e-bikes into domains commonly used in outdoor recreation and leisure inquiries without being constrained solely to these categories. Considering the content of the e-biking articles and study aims, the following nine IRAF categories were used. Within managerial topics, we defined and used: (1) economic (economic impact or demand studies, financial effects, or decision-making about e-bikes); (2) policy/governance (formal or informal approaches to management of e-bikes or e-biking, including rules and regulations); and (3) design (e-bike creation or features, including development or improvement of e-bikes such as speed, safety, or durability). Within resource topics, we defined and used: (4) abiotic (consideration of or impacts to non-living objects or elements in an ecosystem, carbon dioxide emissions, etc.); (5) biotic (consideration of or impacts to living organisms in an ecosystem); and (6) infrastructure (physical developments to accommodate e-bikes/e-biking specifically or within a group of other uses such as paved trails, or impacts on such infrastructure of e-bike use). Within social topics, we defined and used: (7) culture (human and nature connections with e-bikes, valuations of e-bike use in the setting, or user or population identity or social norms around e-biking); (8) experience (socio-psychological processes or products associated with e-biking, such as motivations, perceptions, or conflict based on user or population’s interaction with e-bikes including feelings of safety and unsafe situations like accidents); and (9) wellbeing (health impacts, outcomes, or benefits, which can be of a variety of types such as physical, social, or emotional). These categories and their definitions are rooted in Kuklinski and colleagues’ application of IRAF to mountain biking in their 2024 scoping review.

Categories for data entry were collectively decided among the research team. The lead and second author created the primary definition of overarching and specific categories, based on a read across e-biking articles, familiarity with scoping review formats, applicability to the research questions, and knowledge about the concepts and frameworks to be used. These categories were further refined among the research team as data entry commenced. Data input for the included articles included the article’s:

• Metadata: title, corresponding author’s departmental affiliation, journal title, year of publication, author-defined keywords, and DOI;
• Study geography: country/ies of study, setting type (protected area, city, etc.), whether the study setting included public lands, and major category of setting (urban transit, rural connectivity, or both);
• E-bike uses studied: bikeshare programs, occupational (e.g., delivery service), commuting, leisure/outdoor recreation, hospitality/tourism, and/or general transport/vehicle alternative (e.g., errands, general inquiry across uses, unspecified);
• IRAF categories: economic, policy/governance, design, abiotic, biotic, infrastructure, culture, experience, and/or wellbeing topics examined.

Coding for distributions of use was based on reading a sample of the dataset and applying the research team’s knowledge of a range of biking activities. In this way, our approach was responsive to the context and content. We coded for the geography of the study using the aforementioned attributes (country, setting, and public lands). Next, we coded for the population of focus—a detailed statement on who these populations were (e.g., e-bike adopters of older ages, San Francisco residents, and visitors to Devil’s Backbone Open Space), and, then, whether the population was defined by location, demographics, and/or interests. Finally, we examined the ways in which e-bike uses were studied, or the main intent of the e-bike use. These encompassed domains of bikeshare programs, occupational (e.g., delivery service), community, leisure, hospitality/tourism, and/or general transportation/car alternatives (e.g., errands, general inquiries across uses, and unspecified).

For articles determined to have a leisure focus, we entered additional information as available and appropriate within an article, relating back to IRAF categories. We also captured aspects common in leisure studies, such as research intention (social aims, research questions, or hypotheses), details on e-bike trip durations/frequency, methods (types of data collection: surveys, policy review, big data, economic analyses, interviews, experiments, etc.), and theoretical frameworks (if any) guiding the study.

2.2. Data Analysis

We critically appraised the evidence sources in a mixed-methods format. This relied mostly on quantitative crosstabulations and qualitative thematic coding. For numeric data, we indicated minima, maxima, and ranges across the variables of interest. Many of the categories above were noted in an article as presence/absence of binary data, which lent itself toward reporting of percentages within and across categories and representation through Venn diagrams. Instead of using a traditional equal-area Venn diagram to convey the overlap between the IRAF categories, we opted for a proportional Venn diagram using eulerr software (version 6.1.1), allowing us to observe the proportionality of topics relative to each other [25].

We examined cross-disciplinarity by creating standardized groupings of the journals that articles were published in and repeated a similar action with simplified groupings of the affiliation of the corresponding authors. A similar journal and affiliation would indicate a disciplinary discussion. A dissimilar journal and affiliation would indicate a cross-disciplinary discussion. This framing allowed for a crosstabulation of interdisciplinarity.

For textual data, we coded multiple levels of themes for safety, equity, motivations, and constraints, categorizing these within the IRAF (Figure 2). In the e-biking literature, safety refers to concepts including speed, accidents and injuries, conflicts with other cyclists, pedestrians, and vehicles, and infrastructure. Safety is an important aspect to consider with e-bikes because of the risks to human health for the rider and others around them. However, it is also important to consider from a social perspective because safety attitudes and perceptions around e-bikes can influence riding behaviors [26].

E-biking-related equity concepts included differences in use according to age, gender, socio-economic status, and physical ability. One important note regarding equity in this work is that, due to the global nature of our study, conversations of racial equity were not as prevalent as they typically are in the United States (where the research team is based). Equity within the transportation and mobility disciplines involves creating transport systems that are accessible [27]. Increasing e-biking equity and accessibility can include creating payment plans or having discounted prices for low-income riders, promoting and educating diverse groups of people about e-bikes and their benefits, and building infrastructure that is physically accessible and safe for riders with mobility differences and constraints.

Motivation concepts, referring to the driving forces that influence people to buy and use an e-bike, are diverse among different socio-demographics. A 2021 study of e-bike users in the United States found motivations including financial savings from less fuel and vehicle expenses, an interest in the innovative technology of e-bikes, reduced riding effort and increased mobility, and environmental benefits [28]. Individuals may be motivated to use an e-bike for any combination of these reasons, and these motivations may change over time, especially as the technology and engineering aspects of e-bikes continue to improve.

Barriers are factors that discourage individuals from using an e-bike, and, similar to motivations, can differ among population groups and circumstances. They include, but are not limited to infrastructure, social shaming, and safety concerns. Infrastructure is one such barrier and can include a lack of bicycle infrastructure like protected bicycle lanes and paths close to and within economic and shopping centers, schools, and places of employment. Without efficient bicycle infrastructure, e-bike riders can find it difficult and troublesome to use their e-bike for practical purposes such as commuting and running errands. Negative social stigma and shaming is another barrier that may dissuade people, as some believe that using an e-bike is “cheating” and “low-effort”. Participants in the 2021 study explained that they had received negative comments from co-workers and competitive road bike racers, and the impact of these comments caused some e-bike riders to alter their behavior to avoid interactions with shaming individuals and groups [28]. One of the largest barriers to e-bike use is safety concerns. Current and potential e-bike users have several safety-related concerns including crashes and injuries associated with vehicles, pedestrians, or other cyclists especially when associated with risky riding behaviors such as using a mobile phone while riding, riding in bad weather, or lack of safe infrastructure altogether [29,30].

After examining the results, we report on the trends of each variable and what each tells us about the discussion of e-bikes across disciplines and in leisure-focused articles.

3. Results

The corpus represented 279 works from 2007–2023. Publication about the social aspects of e-bikes has continued to grow, with a single-digit number of articles produced in 2007–2016, 17–27 per year in 2017–2020, and 46–60 articles per year in 2021–2023.

3.1. Use Distribution

There are many different types of e-bike use studied across the corpus, including general transport (38%), commuting (28%), leisure/tourism (16%), bikeshares (13%), and occupational (5%). To understand the geographical distribution of studies on e-bike use, we examined the country/ies studied, which were grouped into continents for the purposes of our results (Figure 3). In total, thirty-six individual countries were studied in the English-language literature, along with studies that focused on larger geographical areas including North America, South America, Europe, the United Kingdom, and multiple continents/countries at once. Africa and South America were not represented in the corpus. Europe was studied most often (n = 131), followed by Asia (n = 87), North America (n = 33), multiple continents (n = 17), and Australia and New Zealand (n = 6). For these continents, the most prevalent use type studied was general transport (33–50%), followed by commuting (22–30%), leisure/tourism (11–21%), bikeshare (7–21%), and occupational and delivery services (0–10%). Asia is the continent with the highest percentage of occupational studies and is the only continent in which more studies focused on occupational use were published than on bikeshare systems.

The types of settings examined were primarily urban and urban transit, totaling 64.5% of the dataset. In decreasing order, the settings garnering more than 1% of the dataset were urban transit (57.7%), a mixture of urban and rural settings (19.7%), urban-specific (6.8%), broadly defined regions (1.4%), and rural connectivity with other areas (1.1%), with seven other categories having less than 1% each. Public lands were represented in a relatively small portion of the dataset, with six articles (2.2%) discussing e-bikes in these designated landscapes.

The populations studied reflected the emphasis on settings, with 77.4% (n = 216) of the articles focusing on a location-defined population. This was followed by 41.2% examining communities of interest, 19.7% studying demographic characteristics, and 1.4% examining e-bike characteristics by occupation/profession. About one-fifth of the corpus (20.8%; n = 58) had a leisure focus.

3.2. Integrated Recreation Amenities Framework

To address our second research question regarding the discussions about e-bikes outside of and within the leisure discipline, we used the IRAF categories to understand what general themes were present. This required the separation of the corpus into leisure-focused (n = 58) and non-leisure-focused (n = 221) subsets. From there, we analyzed the presence of the IRAF categories in the subsets. About half (53%) of the non-leisure articles discussed at least one topic in each of the three IRAF categories, compared to 67% of the leisure articles. The resource category had the largest difference in percentage, where 70% of the non-leisure-focused articles mentioned at least one resource topic, compared to 86% of the leisure-focused articles. There was more similarity in the rate of focus on managerial and social categories between the two subsets, although always higher in the leisure-focused subset. The non-leisure-focused and leisure-focused subsets had similar rates of mention of at least one managerial topic, with 71% and 76%, respectively. All (100%) of the leisure articles and 92% of the non-leisure articles mentioned at least one social topic. Figure 4 depicts the specific overlaps in topical representation between and among the managerial, social, and resource categories for non-leisure and leisure-focused articles. For example, 67% of the non-leisure articles mentioned at least one social and one resource topic within the same work; yet, this combination was much more represented in the leisure-focused subset, with 86% of articles having at least one social and one resource topic simultaneously considered in a study.

3.2.1. Managerial Focus

Of the 221 articles in the non-leisure focused dataset, 156 (71%) referred to managerial impacts associated with e-biking. Forty-four of the fifty-eight (76%) leisure-focused articles referred to managerial impacts. Within the IRAF managerial component are three subcategories: economic, policy and governance, and design.

Seventy-three (33%) non-leisure articles and twenty-five (43%) leisure articles discussed economic impacts. For example, Mela and Girardi produced a study aiming to monetarily quantify health benefits from shifting to active mobility modes from personal vehicles, which was also the first to focus on e-biking [31]. Health impacts were quantified in terms of premature deaths avoided and years of life gained, and then converted to monetary units.

One hundred and five (48%) non-leisure articles and twenty-eight leisure articles mentioned policy and governance impacts. For example, Ruan et al. investigated the role of government in shaping the industry development of e-bikes and found that matching policies with characteristics of innovation led to successful technology development and industry emergence [32].

Sixty-four (29%) non-leisure articles and twenty-six (45%) leisure articles referenced design aspects. For example, Peine et al. observed how designers of the e-bike considered ideal representations of different groups of adopters while designing the e-bikes and noted that properties of innovation emerged as connections between technological possibilities and adopter groups [15].

3.2.2. Resource Focus

We found that 154 of the 221 non-leisure focused articles (70%) referred to resource impacts related to e-biking, and 50 of the 58 (86%) leisure-focused articles referred to resource impacts. The subcategories of the resource component include abiotic, biotic, and infrastructure.

We found that 90 (41%) non-leisure articles and 33 (57%) leisure articles discussed abiotic impacts. An example of this is how Li et al. studied the ability of shared e-bike systems to reduce carbon emissions in urban areas and reported a reduction in carbon emissions by 108–120 g/km in two provincial cities in China and recommended deploying e-bike systems in contexts with a goal of overall carbon emission reduction [33].

Thirty-six (16%) non-leisure articles and nine (16%) leisure articles mentioned biotic factors. For example, Senese and colleagues studied an e-biking project in the Italian and Swiss Alps intended to promote geodiversity, geoheritage, and eco-tourism [34]. They found that the project enabled all levels of e-bike riders to get closer to areas rich in biodiversity, geodiversity, and cultural elements in a sustainable way, and concluded that e-bikes represent a wonderful opportunity to enjoy natural landscapes.

One hundred and ten (50%) non-leisure and forty-five leisure articles (78%) referenced infrastructure. Exemplifying this, Felix et al. researched the effects of the implementation of cycling infrastructure and an e-bike sharing system in Lisbon, Portugal [35]. They observed a significant increase in the volume of bicycle and e-bicycle use in areas with newly improved infrastructure and e-bike sharing systems.

3.2.3. Social Focus

Two hundred and four of the non-leisure focused articles (92%) referred to social impacts regarding e-biking. All fifty-eight (100%) of the leisure-focused articles referred to social impacts. The social component is broken down into the following subcategories: culture, experience, and wellbeing.

One hundred and thirty (59%) non-leisure articles and forty-five (78%) leisure articles discussed cultural impacts. For example, Parsha and Martens explored how social identity influences the perception of cycling among women with varying levels of income in Tel Aviv, Israel, and found that e-bikes were most closely associated with images of danger and toughness that women do not relate with [36]. These results exemplify the importance of promoting e-biking as being “socially invisible” and changing cultural perceptions of the e-bike to be simply a transportation mode.

One hundred and sixty-one (73%) non-leisure articles and 55 (95%) leisure articles mentioned experience aspects. Plazier and colleagues typify this type of inquiry, researching the experiences of e-bike users and observed that their experiences were worse when riding in a city versus outside of it, noting that they enjoyed quieter and enjoyable routes over faster, more direct ones, and that these results should be considered in future environmental and transport design [37].

Ninety-five (43%) non-leisure articles and 37 (64%) leisure articles referenced wellbeing impacts. For example, Lopez-Doriga et al. studied the health impacts of transitioning from conventional transportation modes to electric micro-mobility and found that switching from passive modes to e-bikes was beneficial for physical health, primarily driven by the increase in physical activity [38]. Within wellbeing impacts, equity and safety—two key components of social sustainability—did emerge as themes represented in the corpus [17].

3.3. Conversation (Inter)disciplinarity

To address our research question of how e-bikes are discussed across disciplines, we compared the departmental affiliation of the corresponding author and the journal in which it was published (Figure 5). The corresponding author’s affiliation (listed department, school, etc.) and the type of the journal were both sorted into 14 categories of the same titles: business; economics; energy; engineering and technology; environmental studies; geography and geosciences; health sciences; interdisciplinary; not specific enough to discern; other social sciences; parks, recreation, tourism, or leisure; psychology; transportation; and urban and regional planning. Researchers in transportation-affiliated departments have published the most on social aspects of e-bikes, totaling 79 articles (28.3% of the corpus). This is followed by engineering and technology (n = 48; 17.2%), and health sciences (n = 42; 15.1%). A different pattern exists in the types of journals publishing e-bike articles. The most prevalent journal grouping was transportation (n = 127; 45.5%), followed by health sciences (n = 37; 13.3%) and environmental studies (n = 36; 12.9%). All 14 departmental affiliations were represented, but there were no articles in psychology journals or journals of unclear affiliation.

Next, we considered the intersections of author affiliation and journal for each article to assess our first research aim, on discussions of e-bikes across disciplines. If the affiliation and journal were in the same category, we considered this a disciplinary or within-discipline article. Again, transportation and health sciences affiliations had the highest number of disciplinary journal articles, with 52 (65.8% of all articles from a transportation department) and 16 (38.0% of all articles from a health sciences department), respectively. Although other department affiliations had lower numbers of disciplinary articles, they also had fewer articles in general, and, thus, some of these author affiliations are speaking at similarly high rates within their discipline. For example, two articles were from authors in a parks, recreation, tourism, or leisure department, but both articles (100%) were published in parks, recreation, tourism, or leisure journals: one on e-bike use on natural surface trails in Colorado, United States [39], and another on e-mountain bike use in Scotland [40].

Contrastingly, interdisciplinary conversations about social aspects of e-biking were common. Most corresponding authors published in journal groups different from their departmental affiliation. Notably, there were high rates across departmental affiliations of publishing in transportation journals. Excluding the transportation disciplinary conversations, engineering and technology authors had the next highest representation in transportation journals (26 articles; 9.3% of the corpus and 54.2% of the engineering and technology department articles) (e.g., a comparison of use characteristics between docked and dockless e-bikes in San Francisco [41]; and if/how e-bike complement public transportation and shared hub locations in Scotland [42]).

The spread of a journal grouping across departmental affiliation groupings can also provide a sense of the interdisciplinarity of conversations. Again, transportation journals led in breadth; the transportation journal grouping published studies in 12 of the departmental groupings (85.7%). This was followed by the environmental studies journal grouping (11 departmental groupings; 78.6%) and the energy journals grouping (10 departmental groupings; 71.4%).

3.4. Keyword Co-Occurrence

Using VosViewer software (version 1.6.20), we imported all the author-defined keywords for each article. This allowed for a network analysis, to visualize which keywords were most often associated with each other. We did this for the non-leisure articles and the leisure articles, to elicit similarities and differences in the keyword co-occurrences.

Based on how often the keywords were associated with each other versus how often they were not associated with other keywords, the VosViewer categorized network groupings (Figure 6). The VosViewer allows for thresholds of keyword occurrence to drive the network composition, with fewer keyword co-occurrences necessary resulting in a denser graph and more keyword co-occurrences resulting in a sparser graph. We then named these groupings based on their most salient attributes. Figure 5 presents the threshold we found most meaningful for interpretation across the non-leisure and leisure articles: a 5% threshold. This means that a keyword in the non-leisure articles had to have been listed in at least eleven articles, and a keyword in the leisure articles had to have been listed in at least three articles.

Comparing these two graphs shows some similarities and differences between the two article subsets. Two groupings of keyword co-occurrences appear similar in both. First, we have “choice and outcomes” in the non-leisure articles (e.g., [43]), and “mode choice and behavior” in the leisure articles (e.g., [44]). These both center on the behavior of choosing e-bikes and the other modalities of transportation potentially considered in that decision. Second, “individual experience” was present in both subsets. In both, the keywords center on the activities associated with e-biking and the perceptions of e-bike users about the modality (e.g., [30,45]).

Specific to the non-leisure articles were the keyword co-occurrence groupings of “urban factors” and “sustainable transportation”. Urban factors centered on safety and speed issues with other e-bike users and vehicles, studies in China, and cities. Sustainable transportation centered around the phrase “sustainable transportation” (one keyword) and three derivations of e-bike. Of all the groupings delineated, sustainable transportation was defined by the fewest keywords (four total) and was, therefore, most lacking in context richness to situate the “sustainable” term.

The leisure articles had four additional specific keyword co-occurrence groupings. “Structural” factors included infrastructure and studies in North America. “Safety” keywords focused on models, perceptions, and the safety of micromobility choices. “Planning” keywords were about the sequencing of e-biking into life, planned behaviors, and travels, and the determinants of this. Finally, the “physical health” factor focused on physical activity, health, and mobility.

3.5. Social Aspects of Leisure Articles

For this research, we sought to understand any additional social aspects we should look at within the IRAF that are important to this study’s context. We decided to further examine safety, equity, motivations, and barriers, because it was helpful within the IRAF to understand these concepts regarding e-biking and because safety and equity are critical components of social sustainability [17].

Delving deeper into the leisure-focused subset of articles, we analyzed the conversations happening within each of the additional safety aspects of the IRAF: safety, equity, motivations, and constraints. This was measured by reading quotes and summaries extracted directly from leisure-focused articles that were thematically coded. The most prevalent discussion underneath the safety theme is the risk to cyclists, which was present in 24% of the articles. This is followed by cyclists’ behavior, accidents, and safety infrastructure. For example, articles in this category focused on the risk factors (e.g., traffic and speed) that led to cyclists being injured. Within equity, discussions of expanded access, gender, ability and mobility, health benefits, and age were the most prominent, with expanded access being the most frequent and present in 19% of articles. For example, articles in this category discuss improved mobility because of e-bike use when compared with analog bikes. Within motivations, infrastructure was the most common discussion, being in 24% of articles, followed by environmental benefits, geography, and convenience. Within constraints, conversations about cost concerns were present in 26% of articles, followed by demographic and physical rider reasons, safety, and infrastructure.

4. Discussion and Conclusions

Our study examined a corpus of articles pertaining to social aspects of e-bikes: 279 articles, of which 58 had a leisure-specific focus. These articles concerned use distributions, IRAF categories, conversation interdisciplinarity, keyword co-occurrences, and social aspects of leisure. In summary, e-bikes are most frequently discussed in the transportation, environmental studies, and energy disciplines, with many discussions of e-bikes as alternate transportation modes, their environmental benefits, and their energy-saving aspects. Many studies researched what choices people made about their typical mode of transportation, and under what conditions they would choose to ride an e-bike (e.g., [44,46,47]). Next, e-bikes are substantially discussed as a social aspect within leisure, with conversations surrounding mode choice, determinants, attitudes, behavior, safety, and health. Several studies focused on the reasons why people chose to use an e-bike and what may have motivated or constrained them from purchasing and adopting one (e.g., [30,48,49]). E-biking can be looked at within the field of environmental social science, which requires a high level of cross- and interdisciplinary work that transcends boundaries. Below, we focus the discussion on the ways in which the social studies of e-bikes represent interdisciplinary aims and/or highlight nuanced areas of focus overall and for leisure-focused articles specifically.

The uses of e-bikes are varied and vary with geography. Across the research studies, the relative percentages of articles examining e-bikes as bikeshares, occupational uses, means of commuting, leisure/tourism components, and general transportation or vehicle alternatives varied with continents of focus. This perhaps exemplifies two points. First, examining specific uses and users of e-bikes is richly contextual and, although considered a popular technology worldwide, there is a multitude of geographic and cultural nuances in how people use e-bikes. Second, this corresponds to the work in the IRAF on motivations and constraints. Examining the leisure-focused articles across this geography yielded motivations for adoption, the effects of this choice, and incentives. It also suggested major constraints about physical limitations and costs. This provides insight into the 11–21% of articles in different continents that examine leisure uses and could provide a framing for considering major areas of motivations and constraints for the other categories of uses as well.

Given both, areas where e-bikes are prolific (e.g., Europe, Asia, and specific countries therein) could be optimal places for more detailed research, given the breadth of e-bike users. Conversely, that no studies have been conducted in Africa or South America indicate geographies in need of concerted research. The relatively low rate of social research in North America (11.8% of the corpus) also indicates that further investigations are needed that delve into the motivations and constraints of users here and in non-bikeshare-program-focused studies, given the already substantial level of focus on these programs in the literature. That almost two-thirds of the corpus focused on urban settings and urban transit further highlights the research richness in these places and how rural and public land studies, both representing less than 3% of the corpus, could help to examine whether social trends in heavily populated areas are consistent or depict nuances across geographies. This could indicate areas of learning/adoption from urban areas but also the distinct recognition of rural factors characterizing e-biking and e-bike users. For example, e-bikes as an occupational or commuting means may be more pronounced in these urban locations, whereas e-bikes as a form of leisure/tourism may gain prominence in rural and public land areas.

Likewise, our IRAF investigation highlights areas where research has disparate abundances. Leisure-focused articles tended to incorporate more of a consideration of resources (biotic, abiotic, and/or infrastructure in a site) than non-leisure-focused articles. This may indicate that more of the leisure articles are occurring already in rural and public land settings and offer opportunities for researchers to consider resource impacts in their social studies in addition to the managerial and social foci. It is important to note how the IRAF model transcends social considerations here, particularly with the concept of infrastructure. Indeed, infrastructure can be seen as either a positive motivator or a negative barrier to e-bike use [50].

However, given that over half of the corpus in both subsets of articles have examined at least one aspect of managerial, resource, and social categories, this indicates that the social research on e-bikes is inherently multi-topical and that researchers are responding to this with their approaches. This is an interesting counterpoint to Kuklinski and colleagues’ work on mountain biking [21], as they found that only 26% of the studies examined (broadly, studies on any impacts of mountain bikes/mountain biking) were integrative of topics across all three major IRAF categories. We propose that perhaps this difference is because understanding the experience (i.e., the social characteristics) is more often reliant on also understanding aspects of the managerial and resource characteristics as well. Thus, work on the social sciences of cycling, despite the differences between the mountain and electric modalities, may ultimately be more holistic in approach to a spread across topical categories. This points to social inquiries on cycling types as an important contribution across disciplines that may speak more to one type of category than another (e.g., policy and governance versus natural and cultural resource management) and as an example for integrative work. Interdisciplinary inquiries allow researchers to cut through partitions and highlight the complex interactions and coordination needed to understand and solve issues [51] and can be effective when researching the relatively new concept of e-biking.

Again, this integration was further supported by the conversation interdisciplinarity. Although there were differing numbers and percentages of publications from various author affiliations and in various journal types, 70.9% (n = 198) of the articles qualified as interdisciplinary ones. Within the disciplinary articles, transportation’s dominance (almost two-thirds of the disciplinary articles, 52 of the 81) is unsurprising, considering that e-bikes are a form of transportation and, thus, would find natural resonance both in this field of scholarship and the type of journal. Thus, the high rate of interdisciplinary conversations on the social aspects of e-bikes further speak to the integrated considerations across disciplines and outlets, with some areas of concentrated disciplinarity that may lend structure to the more dispersed set of colleagues and literature.

More research needs to be carried out on these social aspects of e-biking to understand specific motivations and barriers to e-biking and increase the usage of e-bikes [19,52]. Our research into the keyword co-occurrence highlighted two major areas (choices and individual experiences) that capture elements about where research is robust across the dataset. Areas of safety, equity, motivations, and constraints were found in the keyword co-occurrence groupings for the leisure-focused articles, but, at most, each was substantially discussed in a quarter (26%) of these. This indicates a need for more detailed work on these concepts within leisure-focused e-biking studies, as well as thoughtful consideration for their employment across non-leisure inquiries. That “sustainable transportation” was identified as a grouping but with the fewest additional keywords creating a rich picture of these studies indicates that sustainability in the context of e-bikes may require further definition and crosswalks to standardized search terms. Additionally, many current studies are carried out with those already familiar with e-bikes (i.e., current owners). Future research should begin to include more non-users, as they possess different attitudes, perceptions, and use patterns compared to those already experienced with e-bikes and should be considered in promotional campaigns [53]. Additional opportunities our work identified include studies on public land e-bike use, accessibility, equity, and the more frequent use of social science theories, such as social sustainability. These all indicate that a targeted inquiry on how e-bike studies define and parse sustainability may be necessary. This could have a particular focus on the social aspects of e-biking but also transcend into the larger corpus of work on the topic (e.g., e-bike manufacturing and battery production).

Finally, our results in the keyword co-occurrences and detailed coding on leisure-focused studies indicate that these types of inquiries are more connective-bridging to different theories and concepts to understand leisure e-bike users’ decision-making processes and what may inform their choices. Contrastingly (though not exclusively), the non-leisure e-bike research appears to be more foundational, centering more on descriptive inquiries of e-bike use and mapping use patterns. Both foundational and connective inquiries are needed, but, perhaps, leisure-focused inquiries can lean into more of the foundational elements of understanding e-bike users in these contexts, considering this is a specific context and subgroup of users. Likewise, non-leisure inquiries may be more ready to grow into more complex connections to theory.

This research has several policy implications regarding e-biking. Understanding the factors and relationships affecting e-bike use and/or non-use can aid policymakers in creating more nuanced and effective policy regarding e-bike use in differing contexts. For example, in many areas, e-bikes are not permitted, which excludes those using them as personal mobility aids from receiving disability-related benefits [50]. The popularity of e-bikes creates regulatory problems for governing bodies who do not yet have policies regarding their use. Governing bodies should provide more clarity on e-bike-specific regulations, making them separate from analog bicycles. Doing so enables governments to create promotional programs with succinct goals that can increase e-bike use and provide social, health, and environmental benefits [53]. Managers need to craft policies rooted in interdisciplinary science to best capture the dispersed nature of e-biking research. Taking a cross-disciplinary approach enables policymakers to gain a more holistic understanding of specific determinants and barriers to e-bike use and create more nuanced policies to effectively and safely promote adoption. The robust interdisciplinarity of e-bike social research can serve as inspiration for policymakers on how to integrate disciplines and perspectives on an often-controversial topic. Additional policies could target the reduction in negative environmental impacts, and safety and transportation system efficiency improvement, and prioritizing accessibility and mobility for users.

There are also important managerial implications. Knowing and understanding public opinions, attitudes, and perceptions provides guidance for land managers and governmental agencies’ regulation and educational efforts [39]. The interdisciplinary nature of this corpus suggests that community leaders could feel empowered to invite a diversity of entities to discuss e-bike opportunities and concerns, as there could be widespread and unique interests represented. Creating programs that enable people who have never previously ridden an e-bike the opportunity to do so and gain familiarity with an e-bike can substantially increase their intention to buy one [54]. There are also societal implications. Understanding safety, equity, motivations, and barriers of population groups provides opportunities for incentive and outreach programs to engage groups of people who can benefit from using an e-bike, especially marginalized groups [50].

Our work considered a subset of the likely literature on social aspects of e-bikes, limiting our search to peer-reviewed journal articles written in English, cross-listed to Web of Science, and available for download through Michigan State University’s library. However, these constraints fit the scope of our investigation, as we were looking at the published academic work available to us. Even with these considerations, we sourced a robust number of initial and qualifying articles, indicating the inclusive parameters of our search. We also recognize that our qualitative judgements on relevance and inductive coding may have omitted or emphasized particular themes and articles. However, again, we feel we have mitigated this with detailed, stringent protocols and a broad research team trained in the particulars of this inquiry and of social science topics, more broadly. Different research teams may find different areas of interest within the dataset of qualifying articles. To encourage transparency and any others’ efforts with this set of articles, we present the full list of 279 articles with their citation metadata in Supplementary Materials.

In conclusion, the major areas of momentum in social studies on e-bike use are integrative in topics and disciplines. Underrepresented topics and contexts warranting future study may be those in leisure/tourism contexts and rural areas, and on public lands, as well as how e-bike use considers multiple topics within and across managerial, resource, and social categories of topics (and any emergent ones).