Cycling, Economic Growth, and Sustainability: A Comparative Analysis of Slovenia and Belgium

Abstract

This study explores the impact of economic and environmental factors on bicycle ownership in Slovenia to understand how cycling adoption supports smart transportation. Addressing the question of whether policy interventions are essential, particularly during economic downturns, this research highlights a gap in existing studies, which often overlook the economic dynamics influencing cycling. Using time-series econometric methods on data from 2004 to 2021, this study identifies two key factors driving bicycle ownership. Findings reveal that policy adjustments, especially in times of economic instability, significantly enhance cycling adoption and contribute to sustainable transportation in Slovenia. The relationship between cycling, economic growth, and environmental sustainability in Slovenia demonstrates that, unlike Belgium, Slovenia’s cycling rates benefit more from targeted policy interventions during economic challenges.

1. Introduction

The relationship between sustainable transportation practises, particularly cycling, and economic growth, alongside environmental sustainability, has become a focal point of interest among scholars and policymakers (Sousa et al. 2015). This study addresses a critical policy issue: how can cycling, as a sustainable transportation mode, contribute to economic development while mitigating the negative environmental impacts of urbanisation? The need for this research stems from the increasing urgency to transition towards greener transportation options in response to escalating concerns over climate change, urban congestion, and pollution. While prior research has explored aspects of sustainable transportation, a gap remains in understanding the nuanced interplay between cycling, economic indicators, and environmental sustainability, particularly in diverse national contexts (Harms et al. 2014; Nikolaeva et al. 2019; Ehnert et al. 2018; Tonne et al. 2021; Lovelace et al. 2017). This study aims to bridge that gap by offering a comparative analysis of Slovenia and Belgium, two countries with differing levels of cycling infrastructure and policy development (Wachnicka et al. 2023; Levulytė et al. 2016).

The motivation for this study is rooted in the pressing challenges associated with current commuting patterns, such as pollution, congestion, and public health risks due to sedentary lifestyles. Sustainable transportation, especially cycling, is posited as a solution capable of reducing greenhouse gas (GHG) emissions, improving public health, and contributing to economic vitality. However, cycling adoption varies across regions, influenced by economic conditions, infrastructure availability, and supportive policy frameworks. This paper, therefore, aims to provide a comprehensive econometric analysis of how cycling as a transportation mode intersects with economic growth and environmental outcomes.

The primary objective of this study is to investigate the relationship between the adoption of cycling as a sustainable mode of transportation and its effects on economic growth and environmental sustainability in Slovenia. Secondary objectives include examining the impact of socio-economic conditions on cycling adoption and evaluating how targeted policies can sustain or enhance cycling rates across varying economic cycles. Furthermore, a comparative analysis of Belgium’s well-established cycling culture will offer valuable insights into potential strategies that Slovenia might implement, helping to identify transferable practises and opportunities for policy improvements to promote sustainable transportation goals.

This study makes a novel contribution by comparing Slovenia—a country with emerging cycling infrastructure and policy frameworks—with Belgium, which has a well-established cycling culture and robust infrastructure. Using time-series econometric methods, this research analyses secondary data from 2004 to 2021, including Slovenia’s gross domestic product (GDP), environmental indicators, and household ownership of durable goods (bicycles), alongside Belgium’s cycling development and policy initiatives. Including economic indicators (real GDP, unemployment, wages) and environmental metrics (CO₂ emissions, road traffic accidents) allows for a holistic examination of cycling’s impact. Additionally, primary data from a case study in Belgium contextualise the findings, providing insights into best practises for cycling infrastructure and policy incentives.

Despite growing attention to sustainable transportation, research on the economic and environmental impacts of cycling remains scarce, particularly in cross-national contexts. This study fills this gap by examining the factors that promote or hinder cycling adoption and its broader societal benefits. This research highlights the challenges and opportunities of integrating cycling into daily commuting by comparing Slovenia and Belgium.

In clarifying the research question—What is the relationship between cycling as a sustainable mode of transportation and economic growth, alongside environmental sustainability, in Slovenia compared to Belgium?—this study seeks to offer policy recommendations that can drive the adoption of cycling in countries where it is still in its nascent stages. Unlike previous studies, this research does not merely hypothesise cycling’s potential (Teixeira et al. 2021; Banerjee et al. 2022; Christ et al. 2023); instead, it provides empirical evidence that can inform policies that foster sustainable economic growth and environmental resilience.

In conclusion, this research significantly contributes to the existing knowledge on sustainable transportation. It seeks to inform policymakers on designing adequate infrastructure and policies that promote cycling, thereby contributing to a more sustainable, economically viable, and environmentally friendly future.

2. Literature Review

The existing knowledge gap primarily pertains to the limited analysis of how economic fluctuations, especially downturns (Thorbecke 2023), influence the adoption of cycling as a mode of sustainable transport in emerging markets such as Slovenia (Ciascai et al. 2022; Roblek et al. 2021). While extensive research has been conducted on the advantages of cycling in cities with well-developed cycling infrastructure (e.g., Belgium and the Netherlands), there has been an insufficient examination of how economic and environmental factors dynamically affect cycling uptake in regions that are still cultivating their cycling culture (Kosmidis and Müller-Eie 2024; Logan et al. 2023; Bamwesigye and Hlavackova 2019). Moreover, there is a noticeable scarcity of comparative studies that investigate these effects across various economic conditions, particularly in Central and Eastern European countries (Mrkajic et al. 2015; Buehler et al. 2017).

Addressing this gap carries significant implications. By clarifying the economic drivers behind cycling adoption and the impact of policy interventions—especially during periods of economic instability—this study aims to provide insights for targeted policy approaches in countries seeking to enhance their sustainable transportation strategies (Albrecher et al. 2023). Such findings could pave the way for adaptive policy models that bolster cycling infrastructure and promote household adoption throughout economic cycles, ultimately contributing to sustainable economic growth and decreased environmental impact. This refined literature review will establish a strong foundation for positioning this study within this gap, underscoring its relevance and potential contributions to both academic discourse and practical policymaking.

2.1. Overview of the Strategic Documents

Cycling is viewed as a sustainable mode of transport in many countries, including Slovenia and Belgium. In Slovenia, cycling is incorporated into the national transportation development plan, aligning with the Sustainable Development Goals (SDGs). The government’s strategy aims to increase cycling’s share in daily commuting, which is seen as a way to address traffic congestion, improve public health, and reduce environmental pollution. Key investments in cycling infrastructure include urban and rural bike paths to enhance regional connectivity, alongside campaigns to raise awareness about the health benefits of cycling. Local municipalities are instrumental in implementing and maintaining these facilities, with additional efforts to enhance cyclist safety through better road design and regulations (Johansson et al. 2022; Phan and Wang 2014).

Conversely, Belgium boasts an advanced cycling infrastructure, especially in Ghent and Brussels. The Belgian government’s “Be Cyclist” national plan includes financial incentives for employees commuting by bike, expanded bike lanes, increased parking spaces, and integration with public transport. Belgium’s approach also involves close collaboration between various government levels and stakeholders. Its established cycling culture results from consistent government support and effective policies, making it a leader in sustainable commuting practises (Johansson et al. 2022).

A comparison of both countries reveals different stages of cycling infrastructure development. While Slovenia is still expanding its network, Belgium’s infrastructure is mature. Slovenia can benefit from Belgium’s experience, particularly in integrating policies and promoting cycling through financial incentives. Both nations recognise cycling’s role in achieving sustainable transport goals but differ in their starting points and resources.

2.1.1. Slovenia

In Slovenia, promoting cycling as a primary mode of transportation is not only an individual initiative but is also integrated into the broader framework of the national transportation development plan. This initiative aligns closely with the Sustainable Development Goals (SDGs) established by the United Nations, indicating a commitment to sustainable transport solutions. The Slovenian government recognises the crucial role of cycling in alleviating traffic congestion, improving public health, and reducing environmental pollution. This is reflected in strategic investments focused on developing comprehensive urban cycling infrastructure and rural bike paths that enhance connectivity across various regions. Furthermore, ongoing campaigns designed to promote the health benefits of cycling aim to shift public behaviour toward more sustainable commuting options (Johansson et al. 2022).

Strategic goals outlined in crucial documents, such as the National Sustainable Mobility Strategy 2030, emphasise the importance of integrating cycling with public transportation systems and reducing reliance on cars for short trips. A tiered approach has been adopted to establish a network of primary, secondary, and tertiary cycling routes throughout the country. However, despite these efforts, Slovenia continues to face several challenges, particularly concerning cyclist safety, the continuity of cycling paths, and the integration of cycling infrastructure with other modes of public transport (Vrčko et al. 2017). Addressing these barriers is crucial for realising the full potential of cycling as a sustainable commuting alternative.

2.1.2. Belgium

Belgium has a well-established cycling culture, particularly in cities such as Ghent and Brussels, where cycling infrastructure has been progressively developed. The Belgian government’s proactive policies, including financial incentives for cycling commuters, form part of a comprehensive national cycling plan titled “Be Cyclist”. This plan encompasses the expansion of cycling lanes, increased availability of secure bike parking, and improvements in the integration of cycling with public transport systems (Johansson et al. 2022).

Belgium’s strategic documents underline extensive collaboration between national and local governments and various stakeholders to promote cycling. Furthermore, Belgium places significant emphasis on safety measures and technological advancements, such as the adoption of electric bikes, positioning it as a leader in sustainable commuting practises. However, while the infrastructure is mature, continuous efforts are necessary to increase cycling participation rates, particularly to enhance the attractiveness of cycling for work commutes (Be Cyclist 2023).

2.1.3. Comparative Analysis

A recent study by O’Reilly et al. (2024) explores the economic, environmental, and policy-related factors influencing cycling adoption, using also Slovenia and Belgium as comparative case studies. The European Union’s (EU) goal of achieving climate neutrality by 2050 underscores the urgent need to reduce GHGs from the transport sector, which currently contribute to 25% of total emissions. Active transport modes, such as cycling, are increasingly prioritised in EU mobility policies due to their potential to improve air quality, alleviate urban congestion, and enhance public health. Evidence indicates that well-designed cycling infrastructure, including dedicated, separated bike lanes and interconnected cycling networks, significantly boosts cycling uptake.

The comparison between Slovenia and Belgium highlights notable disparities in the development of their cycling infrastructure and the cultural support for cycling (Van Reeth 2022; Haustein and Nielsen 2016; Evgenikos et al. 2016). Belgium boasts an extensive cycling network bolstered by a comprehensive policy framework, while Slovenia is still in the process of expanding its cycling infrastructure. Slovenia stands to gain considerably by learning from Belgium’s experiences, particularly in aspects such as financial incentives for cyclists, effective stakeholder partnerships, and the integration of cycling with other sustainable transport solutions.

Both nations acknowledge the strategic importance of cycling in enhancing public health and reducing emissions. However, the challenges and opportunities they encounter differ, shaped by each country’s infrastructural capabilities and cycling culture. Belgium’s well-established cycling ecosystem illustrates how policy and infrastructure can collaboratively promote cycling, while Slovenia’s ongoing developments signal promising growth as it builds upon these lessons to foster a more cycling-friendly environment (Johansson et al. 2022). The economic impact of cycling is evident in both Belgium and Slovenia, where cycling contributes to job creation, local spending, and reduced healthcare costs (Blondiau et al. 2016; Gössling et al. 2019).

2.2. Overview of the Previous Empirical Literature

2.2.1. The Environmental Benefits of Cycling

The environmental benefits of cycling have been extensively documented across various studies (Piatkowski and Bopp 2021; Bourne et al. 2020). Cycling has been shown to reduce carbon emissions, improve air quality, and contribute to decreased energy consumption. According to a study by Dolge et al. (2023), the transport sector continues to be one of Europe’s largest contributors to GHGs. Thus, promoting sustainable transport solutions, such as cycling, is critical for achieving the European Green Deal’s goal of decarbonising the transport sector (Brzeziński and Kolinski 2024; Paddeu et al. 2024). This research suggests that cycling can play a pivotal role in mitigating the carbon footprint of urban transportation systems, particularly in countries committed to investing in cycling infrastructure.

In Slovenia, cycling is perceived as a critical strategy for reducing GHG emissions, and the national plan emphasises the integration of cycling with other sustainable mobility solutions. Belgium, having a more developed cycling infrastructure, has already experienced positive outcomes regarding lower emission levels, particularly in urban areas (Johansson et al. 2022; Vasiutina et al. 2021). However, while these benefits are recognised, there remains a gap in the literature concerning quantifiable data on cycling’s long-term contribution to reductions in national GHG emissions, indicating a need for further research.

Contemporary research increasingly acknowledges cycling’s role in advancing smart and e-mobility (Bourne et al. 2020; Cai et al. 2024). A study by Wolniak (2023) highlights a strong correlation between countries with developed bicycle networks and their overall smart mobility indicators (Ibañez et al. 2023). Cities with extensive cycling infrastructure, particularly in Northern and Central Europe, have successfully integrated cycling into broader smart city initiatives, contributing to improved urban livability and sustainability.

Slovenia’s strategic focus on smart mobility is still in its early stages, particularly concerning developing smart cycling routes and integrating them with other transport systems. In contrast, Belgium has effectively incorporated cycling into its innovative mobility framework, featuring advanced cycling lanes, smart traffic management systems, and bicycle-sharing schemes in major cities like Brussels. However, limited research explores how cycling integrates with digital infrastructure and smart city technologies, an area that this study will investigate further.

2.2.2. The Economic and Other Impacts of Cycling

Despite the expanding body of research highlighting cycling’s benefits for economic growth (Andreev and Bratec 2024; Volker and Handy 2021), environmental sustainability (Mao et al. 2021), and the promotion of smart mobility (Alam et al. 2024; Lee et al. 2024), several significant gaps persist. Firstly, the literature has not adequately addressed the specific economic impact of cycling on national GDP, particularly within the context of developing cycling infrastructure. While various studies have examined potential job creation and the economic benefits associated with cycling tourism (Ciascai et al. 2022; Lukoseviciute et al. 2022; Piket et al. 2013), a comprehensive analysis of how increased cycling rates directly contribute to national economic growth is lacking, especially in countries like Slovenia and Belgium (Goel et al. 2022).

Secondly, although the environmental advantages of cycling are widely recognised, more quantifiable data regarding cycling’s role in reducing national GHG emissions are needed. Current research often focuses on urban areas (Gulc and Budna 2024), but broader analyses are necessary to assess the long-term impact of national cycling policies on environmental sustainability.

Thirdly, while substantial progress has been made in integrating cycling into smart mobility frameworks, particularly in countries like Belgium, there is still limited research on how digital infrastructure can enhance cycling’s role in urban mobility systems. As cities increasingly adopt smart city technologies, it is crucial to understand how cycling can be seamlessly integrated into these systems to maximise the benefits of sustainable transport planning.

Finally, cycling can have other positive impacts, such on sport and tourism activities, human health, and population wellbeing (Bojović et al. 2024).

2.2.3. Hypotheses Development

In light of this literature review, two hypotheses are proposed to guide this research:

H1: 

Cycling has a positive direct impact on economic growth.

H2: 

Cycling has a positive direct impact on environmental sustainability.

H3: 

Cycling has a positive direct impact on health.

These two hypotheses are grounded in the existing literature, demonstrating cycling’s potential to contribute significantly to job creation, public health, and sustainability. Nonetheless, as outlined in previous sections, notable gaps remain regarding the specific contributions of cycling to national economic growth and the long-term environmental benefits associated with cycling. This study aims to bridge these gaps by investigating how cycling impacts GDP growth and environmental sustainability indicators in Slovenia and Belgium. This research will focus on quantifying these relationships, ultimately providing a robust foundation for policymakers to make informed decisions regarding future investments in cycling infrastructure.

This literature review reveals substantial evidence supporting cycling’s benefits for economic growth, public health, and environmental sustainability. However, existing gaps highlight the need for further exploration, particularly regarding the direct impact of cycling on national GDP and the quantifiable long-term benefits of cycling for reducing GHG emissions. By addressing these gaps, this study seeks to contribute to a more comprehensive understanding of the role cycling plays in advancing sustainable transport systems, especially within Slovenia and Belgium, where cycling infrastructure and culture are at varying stages of development. This research will also explore the potential for the further integration of cycling into smart mobility frameworks, offering valuable insights for policymakers striving to promote sustainable and efficient urban transport systems.

3. Materials and Methods

Assessing the new dimensions in a less researched path to micromobility and cycling, this study encompasses factor analysis to evaluate the possibility of several factors influencing each other. Moreover, due to the lack of data, the frequency is yearly from 2004 to 2021. The data and variables are further presented in

Table 1. Summary statistics of the researched variables; the base year 2004 = 100.

Variable	Abbreviation	Minimum	Maximum	Mean	Standard Dev.
Share of households with consumer durables (bikes)	BIC_H	75.04	106.53	94.54	12.45
Number of bikes imported	BIC	45.49	100.00	58.66	12.65
Number of all bikes imported (including e-bikes)	BIC_T	45.49	100.00	60.26	13.03
Road traffic fatality rate	DEA	27.74	105.84	56.77	25.76
Absence from work due to illness, days per employee	SIC	80.60	114.18	93.32	8.04
Average CO2 emissions per km from new passenger cars	CO2_C	77.93	102.95	92.62	8.73
Real GDP	GDP_R	100.00	150.53	116.57	12.64
Number of unemployed persons	UE	69.26	100.00	78.75	7.78
Real gross wages	W	100.00	142.75	114.13	9.79
Loans in domestic currency (real)	CR	85.96	306.59	216.77	68.68
Loans in foreign currency (real)	CR_F	4.56	216.80	39.54	58.59
Slovenian stock market index (real)	SBI_R	10.00	213.08	45.70	55.95
Consumer price index	CPI	45.53	100.00	55.18	14.71
Dummy euro (2007–2021 is 1)	D_e	0	1
Dummy COVID-19 pandemic (2020 and 2021 is 1)	D_c	0	1

. The data are in indices, where the base year 2004 = 100.

On the other hand, the qualitative part of this study involves an interview with the Belgium representative, during which the most significant issues were discussed at the beginning of 2024.

3.1. Theoretical Framework

The theoretical framework for this study is centred on the economic, environmental, and social factors that influence cycling adoption, explicitly examining how these variables impact sustainable transportation. The selected variables—real GDP, unemployment rates, CO₂ emissions, household bicycle ownership, and road traffic fatality rates—are grounded in their ability to reflect broader economic health, environmental effects, and social behaviours. Economic indicators, such as GDP and unemployment rates, offer insights into household purchasing power and the likelihood of investing in cycling as a mode of transport. Simultaneously, environmental indicators like CO₂ emissions position cycling as a sustainable alternative to car usage, as lower emissions correlate with higher cycling rates (Bland et al. 2024). This framework supports the choice of variables by connecting economic stability, social resilience, and environmental outcomes as key factors influencing cycling behaviour in Slovenia and Belgium.

3.2. Data Collection, Sample, and Methodology

This study utilised a mixed-methods approach, collecting quantitative data from secondary sources pertaining to Slovenia (2004–2021) and primary data through an interview with Belgium’s Federal Bicycle Manager. The Slovenian data, obtained from national databases and governmental publications, encompass economic, environmental, and cycling-specific metrics. The interview with the Belgian representative offered qualitative insights into the policies that have fostered cycling in Belgium. This research examined 31 variables that reflect economic conditions, health, and transport characteristics in Slovenia, while the interview added context from Belgium’s established cycling infrastructure.

To analyse the quantitative data, factor analysis was employed to identify underlying dimensions that influence cycling adoption in Slovenia. Principal Component Analysis (PCA) was used to extract two primary components related to economic and socio-economic stability. Following factor extraction, regression analysis was conducted to investigate the relationship between these components and cycling adoption, using bicycle ownership (BIC_H) and bicycle imports (BIC_T) as dependent variables. The qualitative data from the interview served to contextualise Slovenia’s findings within the framework of Belgium’s policies, offering comparative insights that enriched this study’s discussion and conclusions.

The factor analysis with its $m·n$ observations is a suitable tool to perform this analysis for the quantitative part of this study, influencing Slovenia. The letter $m$ typically represents the number of factors extracted or retained during the analysis. These factors correspond to the underlying dimensions or latent variables that account for the shared variance among the observed variables. Determining the value of $m$ is a critical step, often guided by criteria such as eigenvalues, scree plot analysis, or the percentage of variance explained. In contrast, $n$ refers to either the number of observed variables or signifies the set of measured variables that factor analysis aims to reduce into fewer underlying factors. Both $m$ and $n$ are essential, as the number of variables (n) impacts the factor loadings and the interpretability of the factors, while the number of factors (m) affects the simplicity and explanatory power of the analysis.

The factor scores derived from the analysis can be utilised to create new variables that represent the two primary components. These scores streamline the dataset’s complexity while preserving the essential information captured by the components. Practically, these scores can be employed in subsequent analyses, such as regression models, to investigate how the underlying factors influence various dependent variables of interest. This study employed Principal Component Analysis (PCA) to reduce dimensionality and identify the latent factors affecting cycling adoption. These components encapsulate fundamental dimensions, such as economic stability and socio-economic conditions, summarising the key drivers that impact cycling behaviour. Following the PCA, these components were used as independent variables in regression models to assess their influence on bicycle ownership (BIC_H) and bicycle imports (BIC_T), which served as the study’s dependent variables. This approach enabled the analysis to concentrate on the most significant factors, providing insights into the economic and environmental determinants of cycling in Slovenia based on the established hypotheses.

4. Results

4.1. Summary Statistics

The descriptives in the summary statistics in Table 1 for 18 years provide a detailed examination of the summary statistics for various economic and social variables relevant to Slovenia. The variables range from household ownership of consumer durables such as bicycles to broader economic indicators like GDP, unemployment rates, and stock market performance.

4.1.1. Bikes

The index share of households owning bicycles in Slovenia (BIC_H) is high, ranging from 75.04% to 106.53%, with a mean of 94.54% and a standard deviation of 12.45, indicating that bicycles are a common mode of transportation. The number of bicycles imported (BIC) ranges from 45.49 to 100, averaging 58.66 with a standard deviation of 12.65. These import levels reflect demand influenced by policies, consumer preferences, and economic factors. Total bike imports, including e-bikes (BIC_T), range from 45.49 to 100, with a mean of 60.26 and a standard deviation of 13.03, showing a growing market for e-bikes since their inclusion in 2017.

4.1.2. Health

The road traffic fatality rate (DEA) index ranges from 27.74 to 105.84, with a mean of 56.77 and a standard deviation of 25.76. This variability raises significant public safety concerns, indicating the need for effective traffic management. Factors like seasonality and law enforcement may influence these fluctuations. Meanwhile, SIC, which measures average employee sick leave days, ranges from 80.60 to 114.18, with a mean of 93.32 and a standard deviation of 8.04. This narrower range suggests more consistent patterns in workforce health and sick leave policies.

4.1.3. Environment

The average CO₂ emissions per kilometre from the new passenger cars (CO2_C) index ranges from 77.93 to 102.95, with a mean of 92.62 and a standard deviation of 8.73. The values reflect Slovenia’s efforts to reduce vehicle emissions, which are crucial for meeting environmental targets.

4.1.4. Economics and Finance Risks

The real GDP (GDP_R) index in Slovenia ranges from 100.00 to 150.53, with a mean of 116.57 and a standard deviation of 12.64, indicating positive economic growth and moderate variability. The unemployment rate (UE) index ranges from 69.26 to 100, with a mean of 78.75 and a standard deviation of 7.78, suggesting stability with some influence from economic conditions. The real gross wages (W) index is between 100.00 and 142.75, averaging 114.13 with a standard deviation of 9.79, reflecting wage improvements. Domestic currency loans (CR) vary from 85.96 to 306.59, with a mean of 216.77 and a high standard deviation of 68.68, indicating significant borrowing fluctuations. Foreign currency loans (CR_F) range from 4.56 to 216.80, averaging 39.54 with a standard deviation of 58.59, highlighting sensitivity to exchange rate risks. The Slovenian stock market index (SBI_R) ranges from 10.00 to 213.08, with a mean of 45.70 and a standard deviation of 55.95, reflecting high volatility. The consumer price index (CPI) ranges from 45.53 to 100.00, with a mean of 55.18 and a standard deviation of 14.71, indicating significant changes in living costs.

4.1.5. Dummies

The dummy variables for euro adoption (D_e) and the COVID-19 pandemic (D_c) capture the impact of specific periods on the dataset. The euro adoption variable (D_e) is set as 1 for 2007–2021 and 0 for the remaining years. The COVID-19 dummy (D_c), set as 1 for 2020 and 2021, highlights the pandemic.

Overall, the summary statistics reveal various factors in Slovenia. Bicycles play a significant role in households and imports, reflecting a culture of cycling and sustainability. However, road safety remains a concern, given the variability in traffic fatality rates. Economic indicators such as GDP, wages, and unemployment demonstrate Slovenia’s economic stability and growth, albeit with fluctuations. The data underscore the importance of continued investment in sustainable transport, economic resilience, and public health initiatives to maintain and improve these trends.

4.2. Factor Analysis

Table 2. Component matrix.

Variable	Component 1	Component 2
BIC_H	0.611	−0.650
BIC	0.654	0.587
BIC_T	0.508	0.760
DEA	0.928	−0.039
SIC	−0.302	0.838
CO2_C	0.640	0.284
GDP_R	−0.613	0.640
UE	0.138	0.788
W	−0.794	0.500
CR	−0.606	−0.278
CR_F	0.837	−0.040
SBI_R	0.755	0.035
CPI	0.855	0.429
D_e	−0.863	−0.175
D_c	−0.419	0.628

Extraction method: Principal Component Analysis. Two components were extracted.

presents the factor analysis using PCA, which identified two main components explaining 72.21% of the total variance. The scree plot (Figure 1) shows a clear “elbow” after the second component, indicating that adding more components would offer minimal additional explanatory power. Although these two components capture significant variability in the data, about 27.79% of the variance remains unexplained, likely due to dataset complexity or noise.

The KMO measure of sampling adequacy was found to be 0.483, below the generally acceptable threshold of 0.5. This indicates that the sampling adequacy for the factor analysis is marginally adequate. The reliability test results, indicated by a Cronbach’s Alpha of 0.58 for standardised items, suggest that the model demonstrates acceptable internal consistency, nearing the 0.6 thresholds often regarded as sufficient in exploratory research.

Communalities represent the proportion of each variable’s variance that the extracted components can explain. Most variables exhibit high communalities after extraction, such as the number of bikes imported, including e-bikes (BIC_T) with 0.836, the DEA with 0.862, and the CPI with 0.915. These high values indicate that the extracted components adequately explain the variance of these variables. However, some variables, like CR loans with a communality of 0.444, are less well described.

The component matrix (Table 2) reveals how each variable loads onto the two extracted components. Variables such as the number of BIC and the CPI have high positive loadings on the first component, suggesting a strong association with this factor. Conversely, the W variable has a high negative loading on the first component (−0.794), indicating an inverse relationship.

The second component appears to capture variables related to social and economic conditions, such as absence from work due to SIC with a loading of 0.838 and the number of UE with a loading of 0.788. This component reflects socio-economic factors distinct from the first, which seems more associated with consumer behaviours and market performance.

The first component, with high loadings from variables such as BIC, CPI, and CR_F, appears to represent a factor related to market and consumer dynamics, possibly reflecting broader economic conditions and consumption patterns. This component’s influence on variables like the SBI_R suggests that it captures aspects of economic performance and market sentiment.

The second component, with strong loadings from BI_SIC and BI_UE, seems to relate to socio-economic stability and health-related factors. This component captures the impacts of workforce health and employment conditions on the broader economic environment. A moderate loading from the dummy variable representing the COVID-19 pandemic (D_c) on this component further highlights the relevance of external shocks and public health crises in shaping socio-economic outcomes.

Overall, the first component is economic and market dynamics. On the other hand, the second component is socio-economic stability and health factors.

4.3. Regression Analysis

The result of the regression analysis is as follows:

$${BIC\_T}_t=60.28+0.51·C_{\begin{array}{c}1\\ \left(4.86\right)\end{array}}+0.78·C_{\begin{array}{c}2\\ \left(7.27\right)\end{array}}+\epsilon ,$$

(1)

$${BIC\_H}_t=94.54+0.81·C_{\begin{array}{c}1\\ \left(5.23\right)\end{array}}-0.65·C_{\begin{array}{c}2\\ (-5.57)\end{array}}+\epsilon ,$$

(2)

where $t$ statistics are in parenthesis. BIC_T ($R^2=0.84)$reflects a broader market demand that includes not just households but also businesses, public entities, and trends influenced by broader market conditions, and BIC_H ($R^2=0.79)$focuses specifically on individual household behaviours, which are more directly influenced by personal economic stability and priorities. The results of the regression analysis are of utmost importance to management and policy strategies. Confusion about the results could arise because while overall market BIC_T can still be high during economic or social instability (e.g., due to a push towards cycling as a safe, cost-effective transportation method), BIC_H might not always mirror this trend if economic pressures are being faced. Essentially, businesses, municipalities, or changes in transportation policies might drive bike imports, whereas households under financial stress may cut back on non-essential spending.

During social or economic instability, households prioritise essential spending and are less likely to invest in discretionary items like bicycles (Equation (2)). However, overall market demand for bicycles (Equation (1)) remains strong, potentially driven by companies, government initiatives, or broader market trends. This suggests an opportunity for businesses and public entities to invest in healthier options like cycling, most likely when individual households are more financially constrained.

4.3.1. Explanation of Equation (1)

The first component positively influences bike imports, driven by strong economic performance reflected in GDP, consumer spending, and market stability. This suggests that as the economy improves, demand for consumer goods, including bicycles and e-bikes, rises.

The second component indicates persistent demand for bikes, even amidst socio-economic challenges and public health issues, possibly due to changing transportation needs, such as cycling during crises like COVID-19.

Thus, specific policy interventions for bike demand are not necessary for overall sales. However, as noted by Gričar et al. (2023), during economic growth, other goods like cars may not encourage increased bike usage. Promoting cycling as a practical mode of transport rather than just a recreational activity can support a culture of commuting by bike.

4.3.2. Explanation of Equation (2)

The first component positively influences bicycle ownership among households, as economic prosperity leads to more disposable income for purchasing bicycles. Conversely, the second component negatively affects ownership, suggesting that in unstable socio-economic conditions, households prioritise essential spending over bikes, despite a buoyant market driven by other factors like public purchases and subsidies.

To boost bicycle demand during economic shocks, policy interventions such as subsidies or tax reductions are needed. The quality analysis of this interview is outlined in the next section.

4.4. Results of the Interview

The interview with the representative of the Federal Bicycle Manager of Belgium, conducted online in May 2024, provided insights into Belgium’s strategies for promoting cycling as a primary means of transportation to work. The conversation covered various measures the federal and regional governments implemented to encourage cycling, assess the success of cycling infrastructure, and explore transferable practises for other countries like Slovenia.

Question 1: How does Belgium promote cycling as the primary means of transportation to work?

The representative explained that Belgium has taken several measures to promote cycling as a commuting option. The federal government introduced the first federal bicycle plan, “Be Cyclist”, which includes 52 measures to improve cycling conditions. One of the key initiatives is the improvement of the bicycle commuting allowance, which pays employees EUR 0.35 per kilometre cycled to work. Other measures include anti-theft stickers with QR codes for bike identification, creating a national bike register, and expanding cycle highways, especially along train tracks, to connect different regions. The federal and regional governments also collaborate on bicycle leasing programmes, which have become more popular than car leasing in some areas. This initiative includes options for e-bikes and comprehensive packages with insurance and maintenance, making cycling a safer and more appealing choice.

Question 2: How would you rate the success of developing cycling infrastructures as one of the factors in promoting cycling to work?

The representative noted the significant impact of cycling infrastructure on promoting cycling. He mentioned the saying “Build them and they will come”, highlighting that the presence of cycling lanes and infrastructure directly correlates with increased cycling rates. The number of cyclists in the Flemish region, which has extensive cycling infrastructure, is much higher than in the Walloon region, which has less infrastructure. Brussels also saw a substantial increase in cycling during the COVID-19 pandemic after installing more cycling paths, with cycling rates growing annually by 200%. These data underscore the importance of dedicated infrastructure in encouraging cycling as a daily commuting option.

Question 3: What practises could be transferred to other environments (e.g., Slovenia) to encourage greater use of cycling as a way of transportation to work?

The representative suggested several practises that could be transferred to Slovenia, including the development of bicycle highways, which are not yet present in Slovenia. He emphasised the importance of integrating bicycle lanes with existing transportation infrastructure, such as train tracks, for easy and direct routes. Another transferable practice is the implementation of cycling allowances, where employees are financially compensated for cycling to work. He also advocated for making deliberate urban planning choices, such as reallocating space from cars to bicycles, which can significantly reduce traffic congestion and encourage cycling.

Question 4: Do you think cycling as a way of transportation to work depends on appropriate infrastructure and accessibility, as well as the provision of parking spaces?

The representative confirmed that the availability of safe parking spaces and dedicated cycling lanes are critical factors influencing the decision to cycle to work. Surveys among federal personnel indicated that commuters’ top priorities were secure bicycle storage and safe cycling lanes. These elements assure cyclists that their bicycles are safe and their commuting routes are protected from motor traffic, making cycling a more viable and attractive commuting option.

Question 5: How do you set up bicycle service points and tyre-filling stations in Belgium?

The representative mentioned that bicycle service points are mainly located in train stations and are associated with the train company, providing services such as bike rentals and basic repairs. While some municipalities have started implementing bicycle tyre filling stations, no uniform system is nationwide. Bicycle shops privately run most service points outside of train stations.

Question 6: Are any special reliefs available (e.g., tax reliefs, financing) in Belgium for people who cycle to work?

Belgium offers various incentives for cycling, including a bicycle commuting allowance of EUR 0.35 per kilometre. The representative explained that individuals must declare their cycling route using Google Maps and report each day they cycle to receive the allowance. Additionally, companies installing bicycle parking facilities are eligible for tax reductions, further supporting cycling infrastructure.

Question 7: How can cycling policy in Belgium be improved?

The representative suggested that a more integrated, inter-federal bicycle plan involving federal and regional governments would enhance coordination and policy effectiveness. He also advocated for reducing the number of subsidised “salary cars” given as part of job compensation, which currently undermines cycling initiatives by encouraging car use. Shifting subsidies from cars to bicycles could significantly boost cycling rates.

Overall, this interview highlighted Belgium’s comprehensive approach to promoting cycling through financial incentives, infrastructure development, and policy integration, offering valuable lessons for other countries aiming to increase cycling as a mode of transportation to work. However, theft protection is ensured through optional fungible tokens (NFTs) in QR codes.

5. Discussion

This study investigates the intricate relationship between cycling, economic growth, and environmental sustainability in Slovenia and Belgium. The findings reveal notable economic and environmental impacts that support the set H1 and H2 and inform sustainable policy directions. This research underscores how the promotion of cycling (Scotini et al. 2017) as a sustainable mode of transportation contributes to GDP growth, enhances public health outcomes, and facilitates reductions in emissions. These economic benefits manifest both directly—increased demand for bicycles and cycling-related services—and indirectly—reduced healthcare costs attributable to healthier populations. The positive economic ramifications corroborate the previous work of Blondiau et al. (2016), which illustrated that rising cycling rates stimulate local economies through job creation and expenditure within the cycling industry. Similarly, Bland et al. (2024) highlighted the economic returns of large-scale investments in cycling, bolstered by comprehensive cost–benefit analyses.

Belgium’s established cycling infrastructure, paired with supportive policies such as financial incentives for cycling commuters, serves as a pertinent model, demonstrating how comprehensive policy frameworks can enhance cycling adoption and stimulate economic activity. Belgium’s robust cycling ecosystem leverages financial incentives, including commuting allowances, which encourage cycling for work and consequently stimulate demand across various sectors, including bicycle manufacturing and maintenance services. Recent studies, such as those by Spinney (2020) and Spierenburg et al. (2024), support the notion that integrated cycling policies and infrastructure investments can effectively mitigate costs associated with vehicular traffic, improve air quality, and bolster economic activity. These efforts are congruent with EU objectives aimed at reducing GHG through the promotion of low-carbon mobility options.

Conversely, Slovenia is in the nascent stages of developing its cycling infrastructure and culture. The present study’s regression analysis suggests that while Slovenia is beginning to reap economic benefits from cycling, targeted policy interventions are essential, particularly during economic downturns, to sustain household-level cycling adoption. Recent findings by Yasir et al. (2022) corroborate this notion, indicating that during periods of economic instability, household expenditure on non-essential goods, such as bicycles, tends to decline. Consequently, policy strategies that prioritise subsidies, tax incentives, and low-interest loans for bicycle acquisitions are critical for maintaining cycling rates among households, echoing Blue’s (2014) emphasis on targeted financial support as a strategic mechanism for promoting sustainable transportation amid economic recessions.

The environmental advantages of cycling are similarly substantial. Increased cycling adoption correlates with a reduction in CO₂ emissions and mitigates the adverse effects of motorised transport. Findings from this study resonate with the research of Johansson et al. (2022), who underscored cycling’s role in diminishing urban air pollution and alleviating traffic congestion. In Slovenia, a notable increase in household cycling adoption has been linked to measurable declines in emissions, highlighting the environmental benefits of integrating cycling into national and urban transportation policies. Belgium’s experience further substantiates this, demonstrating that when cycling is embedded within urban transport strategies, significant reductions in emissions and traffic congestion are achieved, thereby benefiting public health and enhancing urban quality of life.

Addressing this research question sheds light on how cycling, as a sustainable mode of transportation, contributes to both economic growth and environmental sustainability in Slovenia, particularly concerning economic stability and policy support. Factor analysis has identified economic conditions and socio-economic resilience as vital components that influence the adoption of cycling. Additionally, regression analysis indicates that both bicycle ownership (BIC_H) and imports (BIC_T) tend to rise during periods of economic stability. This growth is fuelled by a higher GDP, lower unemployment rates, and increased household purchasing power, suggesting that economic stability fosters investments in cycling. Conversely, during economic downturns, data reveal a drop in household cycling rates, highlighting the need for targeted policy interventions, such as subsidies and tax incentives, to promote cycling adoption. These findings suggest that while cycling offers significant environmental and economic benefits in Slovenia, flexible policies are crucial for sustaining these advantages, especially in times of economic hardship.

Moreover, these findings support H1, indicating that cycling positively impacts economic growth, as seen in Slovenia’s GDP increase associated with higher cycling rates. Similarly, H2 is upheld, with results showing that cycling adoption contributes directly to environmental sustainability by reducing CO₂ emissions and traffic congestion, particularly as more households choose cycling over motorised transport. Overall, this study confirms that cycling adoption in Slovenia enhances economic resilience and environmental sustainability, especially when supported by adaptive policies during economic instability.

Finally, cost–benefit analyses, such as those presented by Gössling et al. (2019), demonstrate benefit–cost ratios exceeding 5:1, reinforcing the argument for prioritising investments in cycling as inherently advantageous from a socio-economic perspective. These insights highlight the need for adaptable policies that respond to varying economic conditions, facilitating sustainable growth in cycling as a practical mode of transport across a range of economic contexts.

6. Conclusions

This study highlights the significant impact of cycling on economic growth and environmental sustainability in Slovenia and Belgium. The factor analysis demonstrated the following:

• Economic Stability (Component 1). Economic prosperity and favourable market conditions positively influence both bicycle imports (BIC_T) and household ownership of bicycles (BIC_H). This underscores the role of economic stability in driving consumer behaviour toward more sustainable transportation options, aligning with Belgium’s successful strategies that integrate financial incentives and extensive cycling infrastructure.
• Environmental and Socio-Economic Resilience (Component 2). These show divergent effects; they positively impact overall market demand for bicycles (BIC_T), likely driven by corporate and public investments during times of economic or health crises, but they negatively affect individual household ownership (BIC_H). This finding suggests that while businesses and governments may continue to support cycling through initiatives during challenging periods, individual households may deprioritise bicycle purchases due to financial constraints.
• So, the main findings are as follows:
• Economic Impact (H1). Regression analysis confirms a positive relationship between Component 1 (economic stability) and cycling adoption, as measured by bicycle ownership (BIC_H) and imports (BIC_T). Higher levels of GDP, income, and purchasing power—factors encapsulated within Component 1—drive increased cycling adoption, supporting the hypothesis that cycling positively contributes to economic growth in Slovenia.
• Environmental Impact (H2): The results show that Component 2 (environmental and socio-economic resilience) significantly influences cycling adoption, correlating higher cycling rates with reductions in CO₂ emissions. This supports the hypothesis that increased cycling adoption directly impacts environmental sustainability by reducing reliance on motorised vehicles and contributing to cleaner urban environments.
• H3: In this study, although direct health data were not the primary variables, the observed indirect economic benefits—such as reduced absenteeism linked to improved health among cycling populations—support this hypothesis. For example, in Belgium, where cycling is widely embraced, the established correlation between regular cycling and positive health outcomes reinforces this hypothesis. Consequently, our findings are consistent with the broader literature highlighting cycling’s role in enhancing health, demonstrating that the greater adoption of cycling can lead to healthier, more resilient communities.
• Policy Implications: During economic downturns, household-level cycling rates tend to decrease, highlighting the importance of policy interventions, such as subsidies or tax incentives, to sustain cycling adoption. Targeted policies during unstable periods are crucial to maintaining cycling’s economic and environmental benefits.

The Belgian model offers a valuable roadmap for Slovenia, where cycling infrastructure is still developing. Slovenia can enhance cycling adoption at the household level by adopting similar financial incentives and focusing on infrastructure expansion, especially during stable economic conditions. During periods of instability, targeted interventions such as subsidies or tax benefits could maintain household participation in cycling, aligning with broader sustainability goals.

In conclusion, this comparative study illustrates that economic conditions and targeted policy interventions significantly influence the adoption of cycling as a sustainable mode of transportation. Belgium’s success provides a robust framework that Slovenia and other emerging cycling nations can emulate to foster a more sustainable, economically vibrant, and environmentally responsible future. The results emphasise the need for a flexible policy approach that adapts to economic contexts, ensuring continued support for cycling at both the individual and market levels.

6.1. Implications

The findings of this study highlight the necessity for context-sensitive and adaptive policy interventions to foster cycling adoption, with implications that reverberate through broader economic and environmental policy frameworks. During periods of economic growth, policies should prioritise enhancing household access to bicycles through financial incentives, such as subsidies and tax benefits, alongside continued investments in cycling infrastructure. These strategies resonate with patterns observed in Belgium’s success, where cycling adoption thrives on individual financial incentives and well-integrated cycling infrastructure.

Interestingly, this study indicates that individual household investment in cycling diminishes during economic downturns, revealing a crucial role for government and corporate entities in promoting cycling through institutional support. When personal financial capacity is constrained, these entities can stimulate market demand via workplace programmes, corporate-sponsored cycling initiatives, and public investment. This approach aligns with the findings of Yasir et al. (2022), who suggest that institutional support during economic instability can stabilise sustainable transport options, fostering resilience despite financial challenges.

Belgium’s “Be Cyclist” programme is a valuable model for Slovenia and other nations, illustrating that a combination of dedicated cycling lanes and public transport, coupled with financial incentives, can elevate adoption rates. Tailoring such comprehensive programmes to Slovenia’s evolving cycling infrastructure could accelerate sustainable mobility and reduce the nation’s dependence on motorised transport. In line with EU objectives for climate neutrality by 2050, promoting cycling as a cost-effective, health-enhancing, and environmentally sustainable mode of transport becomes imperative.

The findings of this study offer important insights for policymakers by pinpointing the economic and environmental factors that significantly influence the adoption of cycling. Notably, this research emphasises the need for adaptive policies that respond to changing economic conditions. To enhance the relevance of these policies, future studies could benefit from incorporating the perspectives of stakeholders, such as local governments and cycling advocacy groups, to better refine and implement targeted interventions effectively.

In summary, this study enriches the scholarly discourse on sustainable transportation by illustrating that cycling policies should be robust and responsive to varying economic conditions. Such an approach ensures that cycling remains viable across diverse economic scenarios, advancing environmental sustainability and public health goals in harmony with broader European policies. This study advances scientific understanding of cycling as a sustainable transport mode, demonstrating that economic and environmental factors significantly influence adoption rates using econometric methods.

6.2. Study Limitations and Future Research

This study’s limitations include its reliance on secondary data, which may overlook specific local nuances in cycling behaviours. Additionally, the potential exclusion of confounding variables, such as distinct cultural influences or regional policy variations, could affect the accuracy of our findings. Although the econometric models employed are robust, they may not fully capture these nuanced dynamics.

This research’s delimitations are centred on Slovenia and Belgium, facilitating a focused comparison between an emerging and mature cycling culture. The data span from 2004 to 2021, highlighting recent trends while restricting historical insights.

Future research could enhance understanding by examining the long-term impacts of cycling policies across various demographic groups and adopting techniques like vector autoregression to analyse causality and interdependencies among variables. Furthermore, investigating technological advancements, such as e-bikes and smart infrastructure, could reveal emerging trends, while comparative studies across a wider range of countries would aid in generalising findings and refining policy recommendations.