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Article

Choosing the Bicycle as a Mode of Transportation, the Influence of Infrastructure Perception, Travel Satisfaction and Pro-Environmental Attitude, the Case of Milan

by
Federica Biassoni
*,
Chiara Lo Carmine
,
Paolo Perego
and
Martina Gnerre
Traffic Psychology Research Unit, Department of Psychology, Catholic University of Sacred Heart, Largo A. Gemelli, 1, 20123 Milan, Italy
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(16), 12117; https://doi.org/10.3390/su151612117
Submission received: 27 June 2023 / Revised: 4 August 2023 / Accepted: 7 August 2023 / Published: 8 August 2023
Review Reports Versions Notes

Abstract

:
The present study investigates how infrastructure perception, travel satisfaction and pro-environmental attitudes influence the motivations for choosing cycling as a mode of transport. The effects of demographic variables and mobility habits are also taken into account. Data are collected via a survey with cyclists living in Milan and the surrounding areas. The survey comprises a first set of items to explore the cyclists’ transportation habits and three self-assessment questionnaires: The Neighbourhood Environment Walkability Scale (NEWS)—A Short Form, The Satisfaction with Travel Scale (STS) and the Environmental Attitudes Inventory (EAI). A series of different multiple linear regression analyses and mediation models are conducted. The findings suggest that the frequency of cycling may be explained based on several factors. Males report cycling more frequently, younger adults report lower frequencies of bicycle use and the urban setting is more significantly related to bicycle use. Moreover, the results highlight the significant positive role of the perception of neighbourhoods (especially those with an easy access to non-residential areas) and of pro-environmental attitudes (especially of personal conservation behaviour) in promoting the frequency of bicycling, with the mediation effect of the variable ‘purpose of bicycle use’ (for leisure or to reach a destination) as well. Based on these findings, policymakers should focus on tailored strategies to promote cycling in different users.

1. Introduction

Environmental sustainability issues are increasingly important, and they are influencing the design of mobility-related infrastructures. Awareness of the problems related to air and noise pollution caused by motor vehicles has grown significantly in recent years, and alternative means of transport that can help reduce pollution are under consideration [1]. Undoubtedly, in the face of limited planetary resources, modern societies need to reassess their growth strategies and it becomes imperative to decouple energy consumption from economic growth [2].
The factors that could foster the behavioural changes necessary to encourage a shift towards more sustainable mobility choices are also being studied to influence the design of mobility infrastructures to improve the quality of life in the city and suburbs [3,4]. In this context, Mobility as a Service (MaaS) emerges as a transformative and pivotal concept in the realm of urban mobility [5]. MaaS embodies a progressive approach, seeking to revolutionise how individuals plan and undertake their journeys by seamlessly integrating a multitude of transportation options, including buses, trains, rideshares, bicycles and more, within a unified and user-friendly platform.
Bicycle riding is considered to be a sustainable alternative mode of transportation and a possible solution to air pollution because of its ‘zero-emission’ characteristic [6,7]. In addition, since it is a transportation mode that promotes physical activity and contact with the environment, it may promote health and individual well-being [8,9]. Lastly, bicycles overcome social exclusion because they are economical and are accessible to almost everyone. In conclusion, bicycles have individual and social benefits and positively impact physical health, psychological well-being, the environment and inclusion [10]. This framework that reflects the multiple advantages of cycling was detailed in the 2013 report Cycling, Health and Safety (OECD/ITF, 2013) [11], where the Organisation for Economic Co-operation and Development at the International Transport Forum addressed the positive impact that cycling has on the environment and peoples’ health.
Several disciplines have been interested in the development of research related to cycling in recent years, particularly in regard to its potential impact on human and environmental health. It has been investigated from the perspective of urban planning, sociology and architecture. However, it is also being investigated in terms of public policy because of increased interest about the connection between bicycle promotion and broader policies. Interestingly, Winters et al. [12] have noted that policies related to active travel may operate at various levels of the socioecological framework, including society, cities, routes and individuals.
The provision of convenient, safe and connected walking and cycling infrastructures is at the core of promoting active travel. The American Association of State Highway and Transportation Officials [13] authored the Guide for the Development of Bicycle Facilities to highlight the importance of this means of transport for the population. It also noted that the infrastructures devoted to bicycle mobility should be integrated into the existing designs for other vehicles. However, policies targeted at setting up new infrastructure plans may prove more effective when implemented in comprehensive packages that include educational interventions to promote behavioural changes towards sustainable mobility. Therefore, it is also important to approach this study from a human factor perspective. The cycling-related literature in psychology is still scant [14], but thanks to the increasing importance of issues such as well-being and sustainability, it has become more prevalent in recent years. Existing studies have investigated cycling in relation to several dimensions.
A primary dimension is the relationship between the characteristics of the environment and infrastructures and cycling habits. In a study by Badland et al. [15] that examined how commuting was influenced by the built environment, potential factors that influenced active transportation-related behaviours included mixed land use, residential density, road connectivity and daily commute distance. The results showed that active transportation behaviours were predominantly accepted and used for short-distance travel. Significant associations emerged between travel distance and the use of bicycles. It was found that the probability of engaging in active transportation for commuting decreased as the distance between home and the workplace increased. Moreover, Bieliński et al. [8] demonstrated that bicycles (bike sharing) were used by commuters, while scooter sharing services were more commonly utilised for leisure activities (thus, indicating a differentiation based on the purpose of use). Nielsen and Skov-Petersen [16] analysed how bikeability variables and cycling-related properties of the environment affected the likelihood of bicycling on trips to and from the workplace. The results highlighted significant effects on bicycle use caused by land density, accessibility, transport infrastructure and the regional position of urban areas. Significant variables include the number of retail jobs, high schools, population, bicycling infrastructures, public transport, parking and city dimensions. Stappers et al. [17] conducted a systematic literature review that was aimed at analysing how infrastructural changes in the built environment affected the choice of cycling as a physical activity. The implementation of individual on- or off-road bicycle lanes was found to have positive effects on the perception of safety and the frequency of bicycle travel aimed at physical activity. The influence of infrastructural dimension was also studied in relation to risk perception as one of the factors affecting cycling behaviour [18,19,20]. Sallis et al. [21] explored the correlation between the frequency of cycling and perceived safety improvements associated with road infrastructures. The results showed that perceived road safety improvements led to an increase in cycling. Feenstra et al. [22] investigated the socio-cognitive correlates of risky behaviours enacted by adolescents when using bicycles before the development of safety education programmes; it was found that these determinants were moderately effective in predicting risky behaviours while cycling. Schepers and Heinen [23] examined the impact on road safety due to switching to sustainable mobility modes (from car to bicycle) for short trips in Dutch municipalities.
Cycling was also investigated in relation to pro-environmental attitudes. It was found that this variable, along with others like perceived usefulness and familiarity with sustainable transportation modes, influences the choice towards active and sustainable transportation modes [24,25]. In particular, the choice to travel by bicycle can be linked to environmental conservation aims, such as reducing the dispersion of particles into the air that result in pollution. For instance, a sample of Turkish students was used by Yapici et al. [26] to explore the influence on cycling caused by environmental attitudes and perceived risks associated with environmental issues.
Different motivations, attitudes and intentions relative to bicycle use have been extensively investigated. Félix et al. [27] were interested in cities like Lisbon that had low numbers of cyclists and few bicycle lanes. Their research was focused on exploring motivations related to bicycle use in Lisbon, and they compared barriers perceived by cyclists and by those who did not use bicycles. The results showed that both groups considered perceived safety, physical effort, the lack of a safe bicycle network and bicycle ownership as barriers to bicycle use. In recent years, Bogotá has seen a significant increase in bicycle use among commuters. In relation to this, Rodriguez-Valencia et al. [28] investigated attitudes, personal preferences for transportation and motivations behind the change. They compared individuals who started using a bicycle regularly in the past three years to individuals who have been using a bicycle for a much longer amount of time. The difference between these two groups was their view of the bicycle; newer cyclists saw the bicycle as a money saver and a higher-quality means of transportation, while more experienced cyclists were motivated by passion. Zorilla et al. [29] utilised the Theory of Planned Behaviour to investigate how psychosocial factors could predict bicycle intentions in Mexico City. The results highlighted that attitudes toward bicycling, social comparison, social image and prestige were the most important factors influencing intentions to ride bicycles. Those who had positive attitudes and who considered bicycling as being pleasant, beneficial or important for commuting were more likely to use them. Motivations in relation to attitudes supported their intentions to ride bicycles, while social image had no significant effect.
Travel satisfaction in relation to bicycle travel, however, has not been thoroughly investigated to date. Travel satisfaction is defined as the relationship between general subjective well-being and well-being experienced during travel. Subjective well-being is composed of two dimensions: affective and cognitive. Hence, travel satisfaction is investigated through the cognitive evaluation and the affective (positive or negative) evaluation of the travel experience [30,31,32]. This dimension has been explored in relation to different modes of transportation. For example, Ettema et al. [32] analysed the travel satisfaction of drivers in the Netherlands; they noted that safety perception, relationships with other drivers, travel fatigue and road restrictions influenced this dimension. Travel satisfaction has also been studied in relation to service experiences in public transport from a cognitive and affective point of view, confirming a multidimensional experience [33]. A recent study investigated travel satisfaction in relation to active modes of transport. The results showed that walking and bicycling obtained high scores for physical and mental health, positive affection and general hedonic well-being. However, in relation to bicycles, subjects showed high levels of anxiety and fear related to lower safety perceptions. Such results are reflected in the well-being experienced by individuals during travel [34].

2. The Present Study

The Introduction section provided the theoretical framework of the present research. The present section focuses on the description of the study and its purposes. The Materials and Methods section is then dedicated to illustrating the process of recruiting participants, inclusion criteria and a comprehensive description of the assessment instruments that were employed. Following this, the Results section offers a thorough presentation of the study’s outcomes, specifically exploring the impact of demographic variables, mobility habits, perception of infrastructures, travel satisfaction and pro-environmental attitudes on the frequency of bicycle use. Finally, the Discussion section serves as a conclusive segment, offering a summary of the research findings and providing thoughtful interpretation of their significance.

2.1. Objective and Hypothesis

The aim of the present study was to examine the influence of infrastructure perception, travel satisfaction and pro-environmental attitudes on the motivation for choosing cycling as a mode of transport in Milan (the second largest and most populated city in Italy) and its surrounding areas. Starting from the premise that travellers select solutions aligned with their requirements and preferences to optimise their utility [35], a multifactorial perspective was adopted to consider subjective perceptions, personal attitudes and user experiences, together with demographic characteristics and mobility habits (in particular, whether the bicycles were used for leisure or to reach specific destinations).
Infrastructure perception relates to how individuals perceive the characteristics of the infrastructures within their immediate environments. The interactions that bicyclists have with the environment may be explored in reference to dedicated infrastructures, other road users, pleasantness of the landscape and the presence of accessible points of interest in their residential areas. Pro-environmental attitudes are defined as the set of attitudes and behaviours aimed at environmental conservation. Travel satisfaction is the set of moods and the subjective experience derived from travelling using a certain mode of transport (in the present study, cycling), and it measures the subjective well-being that people experience while travelling.
Two hypotheses served as the basis for the present study. The first hypothesis was that travel satisfaction predicted the frequency of cycling. This was consistent with the results of previous research on travel satisfaction and the choice of different transport modes [36]. The second hypothesis was that the travel purpose widely influenced the factors motivating the choice to cycle. In particular, we expected that cyclists who travelled to reach a destination (‘utilitarian cyclists’) were driven by environmental attitudes and infrastructure perceptions [37], while cyclists who travelled for leisure (‘hedonic cyclists’) were driven by the satisfaction of travelling [38].

2.2. The Novelty of the Study

The present study adds to the literature in various ways. First, we considered multiple factors influencing the choice of cycling that have previously been investigated separately or in relation to other modes of transport; we also analysed the contribution of each factor and their interactions. This thorough research offers a more holistic view of the intricate interactions between these variables that influence people’s decisions to cycle as a form of transportation. Second, within the theoretical framework of traffic psychology, which provides specific models for examining transportation-related behaviours and decision-making processes, we focused our investigation on three genuinely psychological factors in relation to sociodemographic characteristics. Third, the findings provide a contribution from the Italian context to the limited international research on this topic.
In addition, the posited goal is to provide stakeholders with evidence to be exploited for designing mobility-related infrastructures and for planning communication campaigns to promote healthy and sustainable travel behaviour by raising awareness about the benefits of urban cycling on the environment and individual well-being.
The successful implementation of an intervention to promote cycling will indeed require a focus on multiple factors. These include infrastructures, perceived safety and accessibility (crucial when people choose to travel by bicycle instead of car) and personal beliefs related to this mode of travel—particularly pertaining to environmental sustainability, health benefits and the pleasantness of the travel.

3. Materials and Methods

3.1. Participants

All subjects were unpaid volunteers who were recruited through local media advertisements and various social media channels. Participants were required to meet the following inclusion criteria: (1) they lived in Milan or in the surrounding area, (2) they were between 18 and 70 years old and (3) they cycled at least occasionally (non-cyclists were excluded). The general population considered target for this study comprised inhabitants of Milan and the surrounding area (about 3.24 inhabitants). The final valid sample consisted of 130 respondents.

3.2. Procedure

The survey was administered over a seven-week period from November 2021 to May 2022. The self-administered online survey took approximately twenty minutes to complete. Respondents were asked to read a written introduction explaining the study and to provide informed consent before they completed the survey. The data collected were analysed anonymously. The study was approved by the local ethics committee and was conducted in accordance with the Declaration of Helsinki; informed consents were obtained from all participants.

3.3. Measures

The first part of the survey covered demographic characteristics and mobility habits. In terms of mobility habits, the survey asked how often respondents used their bicycles, the main purposes of their bicycle use (for leisure or to reach a destination) and the settings in which they rode the bicycles (urban versus rural). Three self-assessment questionnaires were used: the Neighbourhood Environment Walkability Scale (NEWS), the Satisfaction with Travel Scale (STS) and the Environmental Attitudes Inventory (EAI).

3.3.1. The Neighbourhood Environment Walkability Scale (NEWS)–A Short Form

The short form of NEWS [39] assessed residents’ perceptions of neighbourhood design features related to physical activity. These included residential density, land use mix (including both indices of proximity and accessibility), street connectivity, infrastructures for walking/cycling, neighbourhood aesthetics, traffic and crime safety and neighbourhood satisfaction. NEWS was developed to collect residents’ perceptions of the extents to which neighbourhood characteristics described in the transportation and urban planning literature were associated with higher use of pedestrian and bicycle paths in the specific local areas where they lived. The long version of NEWS included 8 subscales with a total of 68 items measured on a Likert scale from 1 (strongly disagree) to 4 (strongly agree). The 8 subscales were: (a) residential density, (b) proximity to non-residential uses such as restaurants and retail stores (land use mix diversity), (c) ease of access to non-residential uses (land use mix access), (d) street connectivity, (e) pedestrian/bicycle facilities such as sidewalks and pedestrian/bicycle paths, (f) aesthetics, (g) pedestrian traffic safety and (h) crime safety. In this study, four scales were used (c, e, f, g) that applied to cycling. Those four scales were chosen in order to focus on dimensions that were more directly connected to the specific experience of cycling (ease of access to non-residential uses and facilities) and to the individual affective perception (aesthetic experience and perception of safety).

3.3.2. The Satisfaction with Travel Scale (STS)

Travel satisfaction related to cycling was measured using the STS, an instrument that measured user experiences related to travel in nine items, all rated on seven-point bipolar scales ranging from negative (−3) to positive (3) using adjective pairs (higher score implying higher satisfaction [31]. STS was investigated with reference to two affective dimensions and one cognitive evaluation dimension [30,33]. The affective dimensions included positive activation versus negative deactivation (e.g., excited vs. bored) and positive deactivation versus negative activation (e.g., relaxed vs. stressed). The cognitive dimension referred to the perceived quality of the use of a specific transport mode and was measured by a series of sentences about the subjective travel experience (e.g., ‘travel was the best/worst I can imagine’, ‘the trip was of a high/low standard’ and ‘travel worked out/did not work out well’). The Cronbach’s alpha of this scale varied from 0.84 to 0.88 [30,40].

3.3.3. The Environmental Attitudes Inventory (EAI)

Attitudes, beliefs and perceptions regarding the environment were measured using the EAI developed by Milfont and Duckitt [41,42]. The EAI measured 12 main factors related to two-dimensional structures–preservation and utilisation. Preservation attitudes express the belief that the conservation of nature should be a priority, while utilisation attitudes indicate the belief that the use of all-natural resources for human goals is proper and necessary [42]. Twelve subscales were developed, each one comprising 10 items: (1) enjoyment of nature, (2) support for interventionist conservation policies, (3) environmental movement activism, (4) conservation motivated by anthropocentric concern, (5) confidence in science and technology, (6) environmental threats, (7) altering nature, (8) personal conservation behaviour, (9) human dominance over nature, (10) human utilisation of nature, (11) ecocentric concern and (12) support for population growth policies. We used two subscales in this study, ‘personal conservation behaviour’ and ‘ecocentric concern’, since our focus was on those dimensions more deeply connected with the subjective concern for nature conservation and the related individual behaviours that can be performed. The responses to all measures were given on a 7-point Likert rating scale, ranging from 1 (strongly disagree) to 7 (strongly agree). The internal consistency (Cronbach’s alpha) is satisfying (M = 0.84) [42].

3.4. Data Analysis

To test our hypothesis, a series of different multiple linear regression analyses were conducted to identify the main predictors of the frequency of bicycle use. Demographic characteristics, mobility habits and the considered scales (NEWS, STS, EAI) with their subscales were considered as independent variables. The variables in this study were measured on interval scales (age, frequency of bicycle use, NEWS, STS, EAI) or on nominal scales (gender, purpose of use and setting). The assumptions of linearity, unusual points and normality of the residuals were met. In particular, considering the scale of measurement for the variables and the study’s objectives, the use of R-squared (R2) was considered appropriate.
The adjusted R2 was considered. In addition, we aimed to test if the ‘purpose of use’ variable acts as a complete or partial mediator between the predictors and the outcome (the frequency of bicycle use). The Sobel test was performed to test for the mediating effect. The significance level was set at 0.05. Jamovi (version 2.0.0.0) statistical software was used to perform all analyses.

4. Results

4.1. The Influence of Demographic Variables on the Frequency of Bicycle Use

Multiple linear regression was conducted to determine the extent to which gender, age and setting (urban vs. rural) predicted the frequency of bicycle use. The combination of the three variables explains 24% of the variance, representing a significant proportion of the explained variance (R2 = 0.24, F (1, 130) = 12.763, p < 0.001) (see Table 1 and Table 2). In particular, the male gender was more strongly associated with a higher frequency of bicycle use (β = 0.451, p < 0.001). The variable ‘age’ was also a statistically significant predictor of the frequency of bicycle use (β = −0.178, p = 0.01). Notably, the youngest participants (18–30) were less inclined to ride bicycles than the other two age groups (31–55 and 56–70).

4.2. The Influence of Mobility Habits on the Frequency of Bicycle Use

The urban vs. rural setting was more strongly associated with bicycle use (R2 = 0.01, F (1, 130) = 2.38, p = 0.05); a higher frequency of use was recorded in the urban setting (β = 0.17, p = 0.04). The purpose of use also predicts the frequency of use (R2 = 0.24, F (1, 130) = 39.9, p = 0.001); namely cycling to reach a destination predicts a higher frequency of use (β = 0.50, p < 0.001).

4.3. The Influence of the Perception of Road Infrastructures, Travel Satisfaction and Pro-Environmental Attitudes on the Frequency of Bicycle Use

Multiple linear regression was performed to predict the influence of the perception of road infrastructures, travel satisfaction and pro-environmental attitudes (measured with the three scales: NEWS, STS, EAI) on the frequency of bicycle use. A significant regression model was found (R2 = 0.29, F (1, 130) = 4.04, p = 0.009). The three variables together explained 29% of the variance.
Considering the four subscales of the NEWS as independent variables, the overall regression was statistically significant (R2 = 0.09 F (1, 130) = 3.39, p = 0.01). It was also found that the ease of access to non-residential uses was a significant predictor of the frequency of bicycle use (β = −0.19, p < 0.001).
With respect to the three dimensions of STS, the regression results showed that the overall model was not statistically significant (R2 = 0.4, F (1, 130) = 3.01, p = 0.06). However, the deactivation dimension was a significant predictor of frequency of use (β = 0.19, p = 0.003).
With respect to the two subscales of EAI, the overall regression results indicated that the model explained 5% of the variance and that environmental attitude was a significant predictor of frequency of use, despite the fact that the relationship was weak (R2 = 0.05, F (1, 130) = 3.42, p = 0.02). It was found that personal conservation behaviour significantly predicted the frequency of bicycle use (β = 0.02, p = 0.01).

4.4. Mediation Models

After determining which predictors were related to the frequency of bicycle use, three separate mediation models were tested that only considered the variables that resulted significantly from the previous regression analyses (Table 3). First, a simple regression analysis was conducted to test the influence of the various independent variables in predicting the mediator (i.e., the purpose for cycling; leisure vs. reaching a destination). The purpose for cycling proved to be a mediator in the relationship between the above significant variables and the frequency of use.

4.4.1. Purpose for Use as Mediator for the Effect of Demographic Characteristics

Upon analysing the indirect effect, the findings showed that the purpose for cycling did not mediate the relationships between gender and frequency of use (b = −0.04, z = −0.98, p = 0.33). Additionally, the ‘age’ variable was not significant (b = −0.04, z = −0.64, p = 0.52).

4.4.2. Purpose for Use as Mediator for the Effect of Mobility Habits

The effect of the setting on the frequency of use was fully mediated via the purpose for cycling (b = −0.26, z = 4.93, p = <0.001).

4.4.3. Purpose for Use as Mediator for the Effect of the Perception of Road Infrastructures, Travel Satisfaction and Pro-Environmental Attitudes

When the purpose of use was introduced in the model as a mediator, analyses revealed that the perception of road infrastructures and environmental attitude were significant predictors of the frequency of use. With respect to the three subscales that proved to have a significant effect on the frequency of use in the previous analysis (personal conservation behaviour, positive deactivation and ease of access to non-residential uses), there was a significant indirect effect of the subscales ‘personal conservation behaviour’ and ‘ease of access to non-residential uses’ on the frequency of use.

5. Discussion

The present study examined the role of three psychological variables, namely the perception of road infrastructures, travel satisfaction and pro-environmental attitudes as factors predicting the use of bicycles for transportation.
Data were collected via a survey with cyclists living in Milan and the surrounding areas. The survey comprised a first set of items to explore the cyclists’ transportation habits and three self-assessment questionnaires: the NEWS, the STS and the EAI. The results suggest that the frequency of cycling may be predicted on the basis of several factors.
First, a significant influence of demographic variables and mobility habits emerges. Males reported a higher frequency of cycling, which is consistent with many previous studies conducted worldwide that showed the same gender gap in cycling [43,44,45,46,47,48,49]. However, in contrast to other studies [50], our results did not highlight any significant gender influence on the perception of road infrastructures, on environmentally friendly attitude or on satisfaction with travel. Therefore, a possible explanation for the gender gap is that other factors not included in the present study need to be considered to explain why women do not use bicycles. One potential factor contributing to the gender gap in cycling is the tendency for women to utilise a wider range of transportation modes compared to men in their daily lives [47]. A plausible explanation for this underrepresentation of women in cycling is their heightened concern for personal safety [51,52]. With regard to age, younger adults reported lower frequencies of bicycle use. In line with McAndrews et al. [53], we found that young people living in Milan and the surrounding areas are less likely to cycle in an urban setting. Our hypothesis is that this result may be due to some specific social characteristic of the Italian setting; the younger participants in the sample typically represented young workers who were just beginning their careers, and many had jobs that required them to travel long distances to reach the workplace. Such kind of travel cannot be made by bicycle.
Regarding the influence of setting, the urban environment was more strongly associated with bicycle use than the non-urban environment, suggesting that urban areas provide a more suitable environment for bicycling compared to rural areas (also considering that most of the sample lived in an urban setting).
In this sense, cities were perceived as ‘bike-friendly’ environments, especially in regard to reaching a specific destination. Moreover, the results highlighted the significant positive role of the perception of neighbourhoods (especially of an easy access to non-residential areas) and of pro-environmental attitudes (especially of personal environmental behaviours) in promoting the frequency of bicycling. Data collected through the NEWS scale revealed that positive perceptions of infrastructures and, in particular, the perceptions of easy access to services like schools, restaurants and stores, play critical roles in the decision to bike. This was consistent with the recent literature [54,55,56], and was even more pronounced when the goals concerned reaching specific destinations. Infrastructures played important roles in the frequency of cycling for the utilitarian cyclists who used their bicycles to reach specific destinations. Hence, the perceived risk can significantly prevent individuals, particularly those who feel that the bicycle facilities are inadequate and unsafe, from choosing cycling as a transportation mode [57]. This concern becomes even more pronounced in urban areas, where roughly 40% of pedestrian and bicycle accidents occur in Italy [58]. In these conditions, addressing the safety and infrastructural issue becomes essential to promote cycling as a convenient and appealing mode of transportation. As for the EAI, data showed that people who cared about conserving resources and protecting the environment were more likely to choose bicycles as modes of transportation. Participants who professed to be environmentally conscious individuals usually rode their bicycles to reach specific destinations and not for leisure activities. According to the literature that consistently shows the significant relationships between environmental attitudes and ecological behaviours at different ages [59,60,61], we may assume that individuals characterised by higher degrees of an environmental attitude choose environmentally friendly modes of transportation like bicycles due to inner motivations rather than external factors like the characteristics of the physical environment and the infrastructures.
At the same time, a positive perception of infrastructures and an environmentally conscious attitude are not the only intervening factors. Some people cycle regularly because they truly enjoy cycling (e.g., because it is relaxing and comfortable). Although a statistical significance did not emerge, people reporting higher scores at the STS are more likely to use cycling for fun or sport.
According to Stern et al. [62], pro-environmental values and the satisfaction related to the travel experience are two distinct factors that influence intention and behaviour. Our results showed that individuals who cycled for leisure experienced higher satisfaction. Interestingly, it is possible to outline an effect of the interaction between different purposes of use and different motivations, since the hedonistic motivation seemed to be primarily for participants who rode bicycles for leisure, while the environmental attitude was the main factor that predicted choosing to ride a bicycle in order to reach a destination. Fostering and nurturing pro-environmental attitudes through public campaigns and educational initiatives can further encourage individuals to shift to cycling from other modes of transport.
Several limitations of this study are worth noting. First, the sample was influenced by self-selection (snowball sampling method), so it may not be fully representative of Milan’s population. Future research could consider a replication of the study that researches a nationally representative sample [12]. Second, even though a comprehensive set of predictors was used in the present study, a significant proportion of the variability in cycling behaviour is still unexplained. This result suggests that further sociodemographic variables and psychological variables should be included in future investigations, e.g., employment situation and safety and risk perception. Third, our results cannot be generalised for countries where the physical environment, mobility cultures and mobility policies significantly vary from those in Italy.
Nevertheless, this study provides some important avenues for promoting bicycle use. First, transport policies should take gender into account and improve urban mobility options for women (in line with [47,63,64]). By improving urban mobility options specifically for women, such as enhancing safety measures, providing well-designed cycling infrastructure, and addressing social and cultural factors that may discourage women from cycling, policymakers can work towards reducing the gender disparity in cycling frequency.
Second, the hedonistic motivation observed in the category of ‘leisure cyclists’ could be exploited to encourage these cyclists to cycle for routine trips as well, thus increasing the frequency of use through widening the purpose of use. Exploiting hedonistic motivation involves capitalizing on the inherent enjoyment of cycling to encourage individuals, particularly leisure cyclists, to consider using bicycles for routine trips as well. By expanding the purpose of bicycle use and highlighting the pleasurable aspects of cycling, policymakers can increase the frequency of bicycle usage among different user groups.
To achieve that goal, the hedonistic motivation could be empowered by designing safe, comfortable and attractive infrastructures that can provide high-satisfaction cycling experiences. The issue of creating environments that allow riders to experience positive affective deactivation while cycling seems pivotal for both targeted cycling and leisure cycling, which magnifies the importance of designing safer, more accessible, more comfortable and more attractive environments for cycling. Enhanced safety measures and well-designed infrastructures can contribute to positive cycling experiences, ultimately increasing the appeal of cycling for both leisure and utilitarian purposes. Finally, environmental attitudes, encompassing individuals’ beliefs, values and concerns about the environment, also play a significant role in bicycle use. People with pro-environmental attitudes are more likely to choose environmentally friendly modes of transportation, such as cycling. To promote bicycle use from an environmental perspective, it is important to continue fostering and nurturing pro-environmental attitudes. Public campaigns, educational initiatives and awareness programmes can highlight the environmental benefits of cycling, emphasizing its positive impact on air quality, reducing carbon emissions and mitigating traffic congestion. By reinforcing individuals’ pro-environmental attitudes, policymakers can encourage them to prioritise cycling over other modes of transportation.
In light of these findings, policymakers should develop strategies tailored to specific user groups, considering gender disparities and exploiting the pleasurable aspects of cycling. Other actions, namely improving urban mobility options for women, designing safe and appealing cycling infrastructures and nurturing pro-environmental attitudes can all contribute to increasing cycling and fostering sustainable transportation practices in urban areas. Furthermore, integrating bicycles with public transportation will enhance accessibility even further [65]. By addressing these factors, cycling can be promoted as a practical, enjoyable and eco-friendly mode of transport, contributing to a more sustainable and vibrant urban environment.

Author Contributions

Conceptualization, F.B. and C.L.C.; methodology, F.B., C.L.C. and M.G.; formal analysis, F.B. and M.G.; investigation, C.L.C.; data curation, C.L.C. and M.G.; writing—original draft preparation, F.B., C.L.C., M.G. and P.P.; writing—review and editing, F.B., C.L.C. and M.G.; supervision, F.B. and P.P.; All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of the Catholic University of Sacred Heart (protocol code 09-23, 27 January 2023).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are shared on request, the readers can contact the authors.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Table 1. Linear regression model summary table.
Table 1. Linear regression model summary table.
ModelRR-SquaredAdapted
R-Squared 		Standard ErrorFgl1gl2Sign.
Demographic variables on the frequency of bicycle use 0.490 0.26 0.24 1.014 12.763 1 130 <0.001 ***
Mobility habits 0.514 0.264 0.252 0.993 21.921 1 130 <0.001 ***
NEWS, STS and EAI0.160.300.29 1.0874.041130 0.009 **
Note: ** p < 0.01, *** p < 0.001.
Table 2. Regression coefficients table.
Table 2. Regression coefficients table.
BStandard ErrorBetatSign.Lower Limit Upper Limit
Gender −0.459 0.159 −0.198 −2.896 <0.001 *** −1.217−0.597
Male 1.044 0.183 0.451 5.71 <0.001 *** 0.6521.405
Female −0.522 0.91 −0.451 −5.713 <0.001 *** −0.703−0.341
Age 0.261 0.100 −0.178 2.616 0.01 ** 0.064 0.459
18–30 −0.42 0.205 −0.178 −2.045 0.04 * −0.826 −0.014
31–55 0.097 0.105 0.081 0.916 0.361 −0.112 0.305
56–70 0.097 0.07 0.11 1.249 0.214 −0.05 0.250
Purpose of use0.550.1660.4767.001<0.001 ***0.8321.488
Leisure−0.9770.194−0.406−5.033<0.001 ***−1.36−0.59
Reaching a destination1.250.1880.506.66<0.001 ***0.8821.627
Setting−0.3150.204−0.138−1.5430.05 *−0.7200.089
Urban0.4000.2000.1781.990.04 *0.0040.796
Rural−0.210.202−0.091−1.0330.303−0.6100.191
NEWS−0.0010.006−0.07−0.237<0.001 ***−0.0140.011
STS−0.0310.069−0.048−0.4540.651−0.1680.105
EAI0.0050.0070.0730.6940.489−0.0090.019
Note: * p < 0.05, ** p < 0.01, *** p < 0.001.
Table 3. Mediation model results table.
Table 3. Mediation model results table.
Mediation Model 95% C.I. (a)
Type Estimate SE Lower Upper Β Z P
GenderINDIRECT −0.04 0.06 −0.19 0.05 −0.04 −0.98 0.33
DIRECT −0.94 0.18 −1.28 −0.59 −0.41 −5.35 <0.001 ***
TOTAL −1.00 0.18 −1.37 −0.64 −0.44 −5,43 <0.001 ***
AgeINDIRECT −0.04 0.07 −0.17 0.09 −0.02 −0.64 0.521
DIRECT 0.56 0.20 0.17 0.94 0.23 2.83 0.005 **
SettingINDIRECT −0.26 0.10 −0.45 −0.66 −0.11 4.93 <0.001 ***
DIRECT −0.06 0.21 −0.48 0.36 −0.03 −0.28 0.777
TOTAL −0.32 0.20 −0.71 0.08 −0.14 −1.55 0.121
NEWSINDIRECT 0.009 0.004 3.28 × 10−40.019 0.095 2.027 0.04 *
DIRECT 0.008 0.006 −0.004 0.0219 0.083 1.258 0.208
TOTAL 0.016 0.008 −5.20 × 10−40.0342 0.1683 1.901 0.057
Ease of access to non-residential usesINDIRECT −0.012 0.006 −0.025 3.09 × 10−4 −0.044 −1.913 0.05 *
DIRECT 0.048 0.020 0.007 0.088 0.165 2.301 0.2
TOTAL 0.082 0.026 0.030 0.134 0.294 3.129 0.002 **
Bicycle facilitiesINDIRECT 0.027 0.011 −0.018 0.027 0.010 0.349 0.727
DIRECT −0.015 0.049 −0.113 0.082 −0.040 −0.315 0.752
TOTAL 0.035 0.064 −0.090 0.160 0.092 0.545 0.585
AestheticsINDIRECT 0.015 0.027 −0.039 0.069 0.036 0.542 0.588
DIRECT 0.063 0.041 −0.017 0.144 0.155 1.527 0.127
TOTAL 0.029 0.053 −0.074 0.134 0.075 0.558 0.576
Traffic safetyINDIRECT 5.51 × 10−4 0.025 −0.048 0.049 0.0021 0.021 0.983
DIRECT −0.042 0.037 −0.115 0.0312 −0.161 −1.128 0.259
TOTAL −0.012 0.048 −0.107 0.082 − 0.049 −0.25 0.797
STSINDIRECT −8.83 × 10−4 0.003 −0.007 0.005 − 0.010 −0.261 0.793
DIRECT 0.007 0.016 −0.025 0.040 0.085 0.444 0.657
TOTAL 0.049 0.021 0.007 0.092 0.589 2.309 0.02 *
ActivationINDIRECT −0.023 0.0288 −0.079 0.033 −0.072 −0.810 0.418
DIRECT 0.008 0.032 −0.054 0.071 0.035 0.274 0.784
TOTAL −0.056 0.042 −0.138 0.026 −0.23 −1.337 0.181
DeactivationINDIRECT −0.033 0.023 −0.079 0.012 −0.1365 −1.439 0.150
DIRECT 0.063 0.039 −0.014 0.140 0.1963 1.597 0.110
TOTAL 0.080 0.052 −0.021 0.183 0.257 1.554 0.120
CognitionINDIRECT 0.047 0.019 0.008 0.086 0.241 2.385 0.17
DIRECT −0.022 0.026 −0.075 0.029 −0.116 −0.849 0.396
TOTAL 0.0323 0.0346 −0.035 0.100 0.1683 0.934 0. 351
EAIINDIRECT 0.016 0.005 0.005 0.026 0.151 3.112 0.002 **
DIRECT0.0030.007 −0.011 0.0180.0320.4670.467
TOTAL 0.023 0.0090.0050.0400.2222.537 0.01 **
Personal conservation behaviourINDIRECT 0.0168 0.006 0.004 0.029 0.126 2.574 0.01 **
DIRECT 0.013 0.009 −0.004 0.031 0.101 1.455 0.145
TOTAL 0.03179 0.0118 0.008 0.055 0.244 2.676 0.007 **
Ecocentric concernINDIRECT 0.013 0.012 −0.010 0.037 0.051 1.097 0.272
DIRECT −0.022 0.017 −0.056 0.012 −0.085 −1.253 0.210
TOTAL −0.001 0.0231 −0.046 0.044 −0.004 −0.050 0.960
Note: * p < 0.05, ** p < 0.01, *** p < 0.001.
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Biassoni, F.; Lo Carmine, C.; Perego, P.; Gnerre, M. Choosing the Bicycle as a Mode of Transportation, the Influence of Infrastructure Perception, Travel Satisfaction and Pro-Environmental Attitude, the Case of Milan. Sustainability 2023, 15, 12117. https://doi.org/10.3390/su151612117

AMA Style

Biassoni F, Lo Carmine C, Perego P, Gnerre M. Choosing the Bicycle as a Mode of Transportation, the Influence of Infrastructure Perception, Travel Satisfaction and Pro-Environmental Attitude, the Case of Milan. Sustainability. 2023; 15(16):12117. https://doi.org/10.3390/su151612117

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Biassoni, Federica, Chiara Lo Carmine, Paolo Perego, and Martina Gnerre. 2023. "Choosing the Bicycle as a Mode of Transportation, the Influence of Infrastructure Perception, Travel Satisfaction and Pro-Environmental Attitude, the Case of Milan" Sustainability 15, no. 16: 12117. https://doi.org/10.3390/su151612117

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