E-bikes and the Built Environment: Cross-Sectional and Longitudinal Explorations of the Determinants of E-Bike Ownership and Use in the Netherlands

In recent years, e-bikes have received increasing attention from scholars in urban and transport studies. Reflecting this trend, a growing body of research has emerged to explore the factors influencing e-bike travel behaviour. Among these factors, the built environment plays a crucial role in shaping how and where individuals choose to use e-bikes. However, existing studies overlook indirect effects, long-term relationships, and variations in the effects of e-bike ownership and use determinants across different trip purposes. This thesis therefore examines the following central research question: What are the relationships between the built environment and e-bike travel behaviour in the short and long term, considering the roles of socio-demographic factors, weather conditions, and trip purposes? This thesis focuses on the case of the Netherlands. Unlike “Chinese-style” e-bikes that function more like small electric mopeds, e-bikes in the Netherlands require active pedalling and are legally treated as bicycles in the Dutch context, which has important implications for infrastructure use and travel behaviour. The empirical analyses in this thesis are based on large-scale Dutch datasets, including repeated cross-sectional and longitudinal surveys of travel behaviour between 2015 and 2021, complemented by socio-demographic information, such as age, income, household size, and education and built environment indicators such as density, accessibility, and land-use mix. This thesis starts with a broader scope exploring the relationship between the built environment and micro-mobility. While previous studies have examined the relations between the built environment and travel behaviour, most have focused on conventional transport modes such as cars and walking, leaving less attention on micro-mobility. Chapter 2 systematically reviews existing literature on various modes such as e-scooters, shared bicycles, and e-bikes. It reviews the descriptive and empirical studies that investigate the built environment and micro-mobility relationship at three levels: individual transport facilities or hubs (nodes), connecting infrastructure such as roads or cycle lanes (links), and the wider spatial structure of transport and land use systems (networks). It finds that the built environment and micro-mobility relationship varies over time and depends on spatial context as well as built environment aspects. In the short term, micro-mobility can change the urban design and transportation systems’ aspects of the built environment at the node and link levels (e.g., the introduction of docking stations and changes in the transport infrastructure use patterns). In the long term, micro-mobility can potentially change the land use patterns too (e.g., increases in transit nodes’ catchment areas or the relocation of complementary land uses to micro-mobility hubs). This network-level relation, however, takes time to materialize and is investigated by a handful of works so far. Recognizing the growing role of e-bikes in private urban mobility, this thesis narrows its focus in Chapters 3 to 5 to specifically examine how the built environment influences e-bike ownership and usage. Many studies focus on the determinants of e-bike use, but few investigate the role of the built environment and weather conditions in e-bike use for different purposes. Furthermore, the built environment not only directly influences e-bike use, but also indirectly affects e-bike ownership. However, efforts fall short in considering the intermediary role of e-bike ownership in e-bike use. To fill these gaps, Chapter 3 investigates the direct and indirect effects of the built environment and weather on people choosing e-bikes for their work commute and leisure trips, while controlling for the intermediary role of e-bike ownership. The results show that people living in very highly urban areas and going to destinations with high population density are less likely to use e-bikes for commute and leisure. Furthermore, people are more likely to use their e-bikes on less windy and warm days for their commute and leisure trips. As indicated in Chapter 2 micro-mobility and built environment relationship develops over time. However, how the determinants of e-bike ownership and use change over time is rarely investigated. Chapter 4 explores i) how e-bike ownership and use have changed over time in the Netherlands, ii) how e-bike ownership and use relate to different socio-economic and built environment determinants, and iii) how these relationships have changed over time. The results show that e-bike ownership and use in the Netherlands have experienced consistent growth over time. Throughout the study period, e-bikes are becoming more widely adopted across diverse socio-demographic groups, and the influence of household size, household income, age, gender and education on e-bike ownership and use is decreasing. Interestingly, the penetration of e-bikes in non-urban areas is growing. Given the dynamic nature of travel behaviour and fast emerging role of e-bikes, it is an essential and timely investigation to get a comprehensive understanding of the built environment and e-bike relationship. Chapter 5 utilizes a longitudinal approach to analyse the long-term relationship between the built environment and e-bike ownership as well as e-bike travel frequency, while controlling for socio-demographic factors and attitudes. The results indicate a rise in e-bike ownership and more frequent e-bike usage from 2015 to 2021. E-bikes are being adopted more widely across diverse socio-demographic groups. Living in areas with high potential accessibility and high address density leads to higher e-bike ownership and increased travel frequency. Finally, Chapter 6 summarizes the main findings of the studies presented in the previous chapters of this thesis. It highlights the dynamic nature of the built environment and e-bike relationship. Based on the findings, it provides insights for researchers, policymakers, urban and transportation system designers, planners, and public authorities to better understand e-bike travel behaviour. The chapter concludes with the limitations of this thesis and makes suggestions for future research.