1. Introduction
Encouraging the shift towards sustainable mobility strategies based on public transport, shared micromobility and active modes of travel is one of the main challenges of European cities [
1], since they are increasingly facing problems of traffic congestion, road safety, energy dependency and air pollution. In this context, advanced urban planning activities are shifting towards a focus on active modes of transport [
2], among which is the development of strategies and design elements which enhance the accessibility, comfort and safety of the urban setting for cycling.
This has become even more crucial considering the unprecedented effects of the COVID-19 pandemic on urban mobility. The European Commission [
3] has recently provided ad hoc guidelines for implementing short-term transport planning interventions to face the current critical situation. Among the principles included in the document, the section ‘
Active Mobility’ has a specific focus on cycling:
“Many European cities are taking steps to make active mobility (e.g., walking and cycling) a safe and more attractive mobility option during the COVID-19 outbreak. Urban areas could consider temporary enlargements of pavements and increased space on the road for active mobility options to facilitate the needs of the population to move in a safe and efficient way, while reducing speed limits of vehicles in increased active mobility areas”.
In this regard, the activities of urban transport planners and decision makers are projected ahead towards investigating sustainable future mobility solutions taking into account the need to effectively plan the city in order to ensure public health but also to enhance social, environmental and economic resilience [
4]. This includes both interventions on road network and public transport services (e.g., temporary cycling paths and sidewalk infrastructures, queue management in transit infrastructures), to guarantee the possibility to access public transport, services retail and goods within a comfortable distance from home [
5].
Despite recent efforts towards universal design in mass transportation [
6], the measures currently in place to design and manage public transport do not sufficiently consider women’s needs as vulnerable users of the service. As highlighted by the European Charter for Women Rights in the City [
7] and by the 2030 Agenda for Sustainable Development adopted by all United Nations Member States [
8] (i.e., SDG 11.2-Sustainable Transport for All), public transport should be designed to be gender-inclusive:
“By 2030, provide access to safe, affordable, accessible and sustainable transport systems for all, improving road safety, notably by expanding public transport, with special attention to the needs of those in vulnerable situations, women, children, persons with disabilities and older persons”.
Women, in fact, experience and use transport systems differently than men, since they are more concerned with economic, accessibility and security issues [
9]. In particular, statistical facts and figures showed the low use of bike-sharing schemes by women and the need to increase their participation [
10,
11,
12], given that men cycle on average three times as often as women and travel more than four times as far. One of the barriers reported by women users of bike-sharing schemes are the unsafe driving conditions and the need of more traffic rules and speed limits on public roads, with many claiming they prefer cycling in zones with lower traffic [
11,
13].
In this framework, the H2020 DIAMOND research project (see:
https://diamond-project.eu, accessed on 30 March 2021) aims at transforming data from various sources into actionable knowledge for ensuring the inclusion of women’s needs and expectations in transport systems. The research follows a gender-sensitive approach that brings together urban and mobility experts, transport authorities, computer and data scientists, mobility economists and social scientists. The project focuses on four Use Cases: (
i) Public Transport Infrastructures (Railways); (
ii) (Emotion in) Autonomous Passenger Car; (
iii) Vehicle (Bike) Sharing Fleet Management; (
iv) Employment of Women in Rail Industry and Freight/CSR Protocols. Within the objectives of the third Use Case of the DIAMOND project, the paper proposes a data driven approach for investigating the level of accessibility, comfort and security for women of the bike-sharing service that is managed by Syndicat Mixte Autolib et Velib Métropole (VELIB) in the territory of the Paris Region-Petite Couronne (France).
The methodological approach that sets the current research work is based on the use of Geographic Information Systems (GIS) for the analysis of several geolocated structured open data focused on: (i) land characteristics (e.g., urban fabric of land use, points of interest); (ii) sociodemographic characteristics of the inhabitants (population density, gender, age and nationality of the inhabitants); (iii) mobility characteristics (e.g., transport services; cycling infrastructures). This was aimed at identifying and characterizing a short list of suitable bike-sharing docking stations, as characterized by high and low levels of accessibility for women. Results of GIS-based analysis were merged with VELIB’s proprietary data related to the travel demand of the selected docking stations. Then, the selected docking stations were further investigated through onsite observations focused on universal design indicators, survey questionnaires and social media data focused on women’concerns, needs and expectations related to the bike-sharing services. The disaggregated data was used to understand and trace the mobility patterns of women as users of the bike-sharing services, to ask their opinion and to identify the factors important for them, in order to plan and design a fair, gender equitable and integrated bike-sharing schemes.
First, the paper proposes a thematic literature review focused on gender inclusion in bike-sharing schemes (
Section 2), in order to provide a preliminary assessment of women’s needs and barriers (i.e.,
Fairness Characteristics). Then, it presents the methodology which sets the current work (
Section 3) and the results of the analyses (see
Section 4) with reference to: Structured Open Data, Travel Demand Data, Onsite Observations, Users’ Satisfaction Index Questionnaires and Social Media Data from Twitter. The paper concludes with final remarks about the achieved results and future work.
2. Literature Review
A bicycle-sharing system, or public bike share (PBS) scheme is a transport service in which bicycles are provided for a shared use on short term basis to individuals for a fee or free. Bicycle-sharing contributes towards achieving sustainable and inclusive transport services in urban centres. Women make more shorter and multipurpose or multistop trips and complex trips than men, due to the constructed normative gender roles in most societies [
14,
15]. The complex mobility pattern of women due to caring and parenting responsibilities makes the use of traditional public transportation time consuming and inconvenient [
14,
15,
16]. Cycling or bicycle sharing services provide a better alternative to meet the complex urban mobility needs of women. Existing evidence suggest that traditionally, women cycle less than men [
17]. However, recent evidence from the UK suggest a narrowing gender split of bike-share usage compared to general cycling [
18,
19].
The aim of the H2020 DIAMOND project is to investigate the mobility needs and challenges of women in relation to bike sharing services in order to produce guidelines for providing more inclusive infrastructure, improve planning and distribution of docking points, engender fair inclusion for women and address the social imbalance within the domain of transport. Therefore, the final goal of the research is to identify and reduce the barriers preventing women from using bike sharing services and, then, to increase the percentage of women using bike sharing services to meet their mobility needs.
Bicycle-sharing services is fraught with several barriers and limitations, which prevent women from using the services. Taking advantage of a preliminary work already presented by the authors [
20], the review of extant literature focused on identifying pertinent issues and challenges bothering on women mobility experience as users of bike sharing service and barriers preventing women from using bike sharing services. Literature review was conducted through several academic database (e.g., Web of Science, Scopus, Google Scholar, ResearchGate, etc.) and organized in a tabular structure (see
Table A1 and
Figure A1). Overall, the process allows the identification of about eighteen
Fairness Characteristics (FCs) influencing women participation in bike-sharing systems, which were validated through the execution of several focus groups and semistructured interviews. The FCs have been grouped into four
Cluster of Fairness Characteristics (CFCs):
CFC-Accessibility & Spontaneity (e.g., availability of bikes at the docking stations, distance to the nearest station, type and quality of the cycle paths, etc.);
CFC-Safety & Security (e.g., perception of danger and insecurity while cycling and using the current bicycle infrastructures, etc.);
CFC-Social Constraints (e.g., perceptions and cultural stigmatization associated with cycling and bike-sharing, etc.);
CFC-Weather & Topography (e.g., impact of weather and the urban terrain on cycling and bike-sharing, etc.).
The availability of bikes at the stations when needed, the distance to the nearest station and the type and quality of the cycle paths available are some of the issues users have to take into consideration when planning a trip involving bike-sharing services. CFC-
Accessibility & Spontaneity is defined in terms of those characteristics of the service related to the ease with which all women groups can access and use the bike-sharing services for a trip. Significant differences are reported between women and men cyclist and bike-share users due to their respective normative gender roles [
17,
21]. The fairness characteristics for this CFC include the following:
According to TfL [
22], there is poor awareness of local walking and cycling routes among low-income and minority groups. Similarly, Stredwick [
21] found a low-level of awareness of practical cycling (such as cycling with children or carrying luggage or shopping on a bike). This observation is described in FC-
Public awareness. Public awareness campaigns of bikes sharing schemes, promoting cycling/bike-share as a legitimate form of transport and offering lessons on practical cycling amongst women and minority groups could ramp-up women interest in cycling and using bike-sharing services.
Majority of the bike-sharing services rely on the use of credit/debit card, smart phones and require internet access to sign-up for membership and for rental. This requirement prevents potential users of bike-sharing services from using the services [
23]. This is highlighted in FC-
Sign-up and booking process. McNeil et al. [
24] found that some individuals from minority and low-income background and the elderly are less likely to have smart phones, reliable internet access or credit/debit cards.
Accessibility in terms of FC-
Membership cost, includes entry cost, rental charges above a stated threshold, the cost of other essential cycling accessories (such as helmet, clothing etc.) and a possible liability cost resulting from the theft or damages of the bike. Bikeplus [
25] found the entry cost of bike-sharing services to be lower than the cost of owning a bike; however, entry costs and rental charges above a stated time limit of some schemes are observed to be higher [
26], which come as a major barrier to the full adoption of the services, particularly, by commuters from minority and low-income groups [
27].
FC-
Spontaneity of accessing bike/dock relates to the possibility of finding a bike at the station and finding a vacant docking point at the trip destination station to return a bike after the trip in a traditional dock-based bike-share systems. This relates to the reliability of the service and significantly influence trip makers decision on whether or not to include bike-sharing as an option in their daily travel plans [
28]. This has been reported to be one of the major barriers to cycling. The inability to guarantee a bike at the station or an empty docking point to return a bike after the trip when needed has resulted in many users giving up on using the schemes or using them for important trips [
18].
FC-
Proximity of docking station relates to how far a user has to walk to pick-up a bike or walk to the trip destination after returning a bike. Some users report travelling further from their trip destination to return a bike after their trip because the station at their destination did not have an empty dock to return the bike. The spatial distribution of docking stations is seen as a critical factor influencing bike-share usage; the proximity to members as well as to low-income and minority neighbourhoods promotes membership [
26].
Women are mostly encumbered due to their parenting and gender role; this significantly affects their mobility options [
29]. FC-
Travelling with children/carrying things, describes the lack of child seat and good-sized carry baskets on most bike-sharing services limits the use of such services for shopping trips and trips involving children by women. This raises gender and social justice concerns since women make more ‘escort’ trips with children, and more shopping trips, than men.
FC-
Insufficient infrastructure focuses on the lack of protective Infrastructure (segregated cycle infrastructure), discontinuity of the cycle infrastructure including cycle path and cycle facilities. This raises safety concerns particularly for users with dependants who considers the infrastructure unsafe for cycling with kids and identified as barriers to women in the use of bike-share services [
21,
30]. Similar to road network improvement, cycling infrastructure makes cycling and bike-share attractive to users and potential users [
23,
31].
The second CFC-Safety & Security relates to factors influencing the perception of danger and insecurity while cycling and using the current bicycle infrastructures. The fairness characteristics for this CFC include the following:
FC-
Driver behaviour: While more research is required to understand why more women experience and report more incidents than men, cyclists believed most of the near misses and scary incidences can be blamed on factors such as speed, drivers passing too close, negligent opening of a vehicle door and aggressive driving on the road, which is preventable [
32]. The attitude and behaviour of drivers towards cyclists is seen as a major deterrent to cycling and the use of bike-sharing services, particularly among women [
23,
33].
FC-
Separate infrastructure: while sharing the road space with motor vehicles seems problematic for females, it is believed that the slower cycling speed of women on the road [
34] could be a plausible explanation as drivers become impatient with the slow riding speeds. Developing a safe and protective cycling network separated from vehicular traffic have a positive effect on women perception of safety and could get more women cycling and using bike-share [
21,
30]. Segregated infrastructure, alongside interventions targeted at road culture and driver behaviour, is suggested to have stronger influence on the rate of cycling of women [
35,
36].
FC-
Harassment: Women are susceptible to harassment, verbal abuse and attacks in the public space and are more likely to report sexiest harassment from other road users when cycling than men [
21,
37,
38]. Howland et al. [
17] found the fear of harassment by men and drivers is a significant barrier to cycling and the use of bike-sharing services by women. Street harassment is one of the barriers to cycling and the use of bike sharing. Consequently, continuous public education could help address this social menace.
FC-
Safe environment and personal safety: The subjective safety (perceptions of insecurity) and the objective safety (measured risk level) have greater implication on the rate of cycling [
36]. The likelihood that a rider was a woman is higher than a man if the cycling environment is friendly. Off-road infrastructure, on-road infrastructure without parked vehicles and residential streets are considered safer than mixed-traffic roads by cyclists [
36]. The findings of our interview also suggest that the level of lighting and visibility at the stations, the presence/absence of emergency help buttons at the bikes stations and the characteristics of the lanes (width, location, lighting, etc.) have significant impact on cycling, which is consistent with the subjective and objective safety findings reported in Kumar et al. [
36] and Ravensbergen et al. [
38].
FC-
Confidence/experience: Less experienced cyclists, or those with little confidence on their own cycling abilities, see the interaction with vehicles on on-road cycling infrastructure more challenging and intimidating [
34]. The fear women have of traffic results from the sense of inexperience and lack of self confidence in cycling [
37]. These are barriers and possibly explain why women are more uncomfortable cycling in traffic [
21]. Off-road and dedicated and enforced on-road infrastructure may encourage inexperienced cyclists and get more women cycling and using bike-sharing services.
FC-
Traffic safety: Road safety is a gendered issue when it comes to cycling; women report twice as many incidents of ‘frightening near misses’ and more concerned about cycling on the road in traffic than men [
32,
36,
39]. Cycling on the road with vehicular traffic is very intimidating for women [
21] and disproportionately impacts a woman’s decision to cycle [
27].
There is sociocultural dimension to barriers of cycling, and this is more pronounced in women than men. This is presented in the third CFC-Social Constraints. The perceptions and cultural stigmatization associated with cycling and bike-sharing is fuelled by gender stereotyping in society and the perception that cycling is for the poor. The fairness characteristics for this CFC include the following:
FC-
Subjective norm (peer influence): Important others have significant influence on behaviour and on the decision to cycle or otherwise; peers and coworker normative beliefs on cycling can influence women’s participation in cycling to and from work [
40].
FC-
Sociocultural constraint (negative perception): There exist culturally embedded perceptions about the symbolic value of cycling. Cycling is perceived as a transport mode reserved for people of low status, with evidence of poverty and the inability to afford a car [
22,
37]. The stigmatisation of cycling in most communities serves as a major barrier to the desire to cycle and use bike-sharing services. Campaigns to promote cycling as a legitimate form of transport for all income groups and encouraging all income groups to cycle could help overcome this myth, encourage cycling and the use of bike-sharing services [
37]. Additionally, the appearance of women (the wearing of skirts, high heeled shoes, hair style and the likelihood of carrying a purse) constrains and limits the rate at which women cycle [
41]. End-of-trip or workplace facilities and the design of bikes are suggested to address this barrier.
FC-
Family responsibilities: The constructed normative roles of women including childcare prevent women from cycling and using bike-sharing services because of the complexity of cycling with children and for shopping [
41]. Education on practical cycling and the possibility of cycling with children and for shopping could help address this barrier and encourage more women to cycle and use bike-sharing services.
The fourth and last CFC-Weather & Topography relates on the impact of weather and the urban terrain on cycling and bike-sharing. The fairness characteristics for this CFC include the following:
FC-
Weather: The impact of weather on cycling is emphasised in literature. The demand for cycling and bike share is subject to seasonal variation and weather such as humidity, temperature, wind and rains [
33,
42].
FC-
Topography: The presence of hills along cycle routes have negative impact on cycling and a barrier to women urban cycling and bike share [
33,
43]. The development of electric assisted bikes has overcome this barrier and further makes long distance trips possible [
25].
3. Enabling Data and Methodology
Within the scope of the H2020 DIAMOND project, the objective of the proposed analysis was to investigate the women’s needs and expectations as users of bike-sharing services managed by VELIB in the territory of Paris Region-Petite Couronne (1358 docking stations in total). This was aimed at supporting the development of EU policies and guidelines for gender-equitable bike-sharing fleet management, focusing on the Clusters of Fairness Characteristics defined through the proposed thematic literature review (see
Section 2): (
i) Accessibility & Spontaneity; (
ii) Safety & Security; (
iii) Social Constraints; (
iv) Weather & Topography.
In this framework, the methodology which sets the current work was based on a series of (geolocated) Structured Open Data, which were retrieved, sorted and filtered from open data repositories, national geoportals and census databases (see
Section 4.1). In analogy with a previous work already presented by the authors [
44], preliminary structured open data analysis was based on GIS (all GIS-based analyses presented in this paper have been performed by using the software QGIS v.3.16.1) in order to identify and characterize a short list of relevant docking stations, in which to perform further data collection activities. A series of thematic maps related to the localisation and density distribution of datasets were designed to assess the level of accessibility of the bike-sharing docking stations managed by VELIB, focusing on the following:
Territorial Data: density distribution of urban fabric on land use (including continuous urban fabric, discontinuous dense urban fabric and isolated structures) and points of interest (e.g., commercial activities, schools, facilities, public services, attractions, etc.);
Sociodemographic Data: density distribution of total population, female population, elderly population and foreigner population per census section;
Mobility Data: density distribution of public transport services (e.g., metro and commuter railway stations, bus stops, tram stops, etc.) and cycling infrastructure.
The proposed approach for structured open data collection allowed the identification of a short list of twenty heterogeneous and nonadjacent docking stations, characterised by positively and negatively relevant characteristics related to the objectives of the analysis. In order to further characterise the shortlisted stations, structured open data were merged with:
Travel Demand Data (see
Section 4.2): to distinguish the selected docking stations in regard of utilisation patterns, such as trips related data (e.g., number of started and ended rentals, trip distance and duration, etc.) and users segmentation data (e.g., number of unique users, number of female users).
Onsite Observations (see
Section 4.3): to characterise the selected docking stations focusing on universal design indicators;
Users’ Satisfaction Index Questionnaires (see
Section 4.4): to characterise the sociodemographic characteristics and mobility patterns of the end-users and to correlate their level of satisfaction with the characteristics of the selected docking stations;
Social Media Data from Twitter (see
Section 4.5): to get insights on women’s and men’s concerns related to the bike-sharing service, as emerging from online conversations.
5. Discussion
The paper is based on an extended GIS-based analysis of Structured Open Data for maximising the diversity of the bike-sharing docking stations managed by VELIB in the territory of Paris Region-Petite Couronne (France), which were subsequently further characterised through Travel Demand Data, Onsite Observations, UESI Questionnaires and Social Media Data from Twitter. This was aimed at ensuring that the observed cases are representative of the different situations/locations of any single docking station.
In particular, GIS-based analysis aimed to assess the level of accessibility for the women users of the bike-sharing service managed by VELIB through the investigation of: (i) the level of urbanisation and attractiveness of the areas surrounding each docking station in terms of urban/periurban contexts, available services and facilities; (ii) the sociodemographic characteristics of the population living in the areas surrounding each docking station; and (iii) the level of connectivity of the bike-sharing service with other public transport services and cycling infrastructure. This enabled to identify and characterise a short list of twenty heterogeneous and nonadjacent docking stations.
The analysis of Travel Demand Data allowed researchers to correlate the overall level of accessibility for women of the selected docking stations with a series of Structured Proprietary Data (e.g., number of started and ended rentals, trip distance and duration, number of unique users, number of female users, etc). Results confirmed that the utilization/capacity ratio of the service is influenced by the level of accessibility of the docking stations. Moreover, the female user ratio related to the docking stations located in the territory outside the City of Paris is slightly lower compared to the one of the overall docking stations.
Then, the selected docking stations were further investigated through Onsite Observations focused on universal design indicators. Results showed that the majority of the docking stations display some negative connotations in relation to spontaneity of accessing the bike service and separate cycling infrastructure. Moreover, half of docking stations had negative features related to safe environment and perceived personal safety.
The analysis of UESI Questionnaires was focused on women’s concerns, needs and expectations related to the VELIB’s bike-sharing services. Results showed that the overall user satisfaction is strongly influenced by the booking and sign-up process, the proximity of stations, the possibility to use the services with children, the lack of cycling infrastructure and adequate lighting at the docking stations.
The analysis of disaggregated Social Media Data collected from Twitter has been applied to further investigate the opinion of the end users about the bike-sharing service managed by VELIB’s. Results showed a politicised conversation around VELIB for both genders, while women where found to make more references to the lack of reliability of the service and on the possibility to use of shared bikes for commuting.
The presented data collection campaign represents a valuable example of the potential of this methodological approach. Indeed, the research work was aimed at investigating the possibility to analyse digitally widespread data sources as a valuable support of the activity of decision-makers by unveiling hidden patterns and specific target-users’ needs. The diversity of the data collected and used for this study helps to build a narrative around the diversity of influences on cycling behaviour for women. However, the results of the analysis could be potentially biased by the impact of the lockdown period due to the COVID-19 pandemic. The timing of the data collection was also timely as Paris has seen a large increase in cycling during the COVID-19 pandemic. Therefore, the survey is likely to have captured a diversity of new and established users of VELIB’s service.
6. Conclusions and Future Work
The objective of the paper was to identify an appropriate sample of docking stations to be further investigated through travel demand data, onsite observations, survey questionnaires and social-media data collection, focusing on the women users’ needs and expectations as users of bike-sharing services. Results showed that women experience and use this transport mode differently than men, since they are more concerned with accessibility, safety and security, social constraints, weather and topography issues.
Future work will focus on the application of data analytics techniques based on Analytic Hierarchy Process (AHP) and Machine Learning techniques (Factor Analysis and Bayesian Networks). This is aimed at defining a hierarchical model for the design of parameters influencing the inclusion of women, by unveiling hidden mobility patterns through a gender-based intersectional analysis. Within the objectives of the H2020 DIAMOND project, the collected disaggregated data will be used to support the definition of guidelines and policies for the inclusion of women’s needs in the design of future bike-sharing transport services.