In many countries around the globe, high-quality bus services are being implemented. Also in the Netherlands, bus operators have implemented services that are classified as Buses with a High Level of Service, BHLS (also Hoogwaardig Openbaar Vervoer, HOV, in Dutch). Upgrading conventional services to BHLS can lead to large ridership increases and modal shift rates from the car to the bus.

The objective of this work is to develop knowledge on the importance of BHLS aspects with respect to ridership and advise bus operators and transit authorities about the implementation of BHLS aspects. To investigate this, first the aspects of BHLS are determined based on a literature review. Then, the performance of bus lines on these BHLS aspects is assessed in a Dutch case study to investigate how BHLS in practice relates to the findings in literature. This is done for BHLS services as well as conventional services. The performances of the different services are compared to each other to explore what BHLS means in practice and how that relates to literature. Once the performance of each line is assessed, the relation of the BHLS aspects with ridership is investigated. This is done using a multiple linear regression model. Lastly, the impact of the deployment of dedicated BHLS vehicles on the operational efficiency is researched. Two sets of vehicle schedules are developed for a scenario where all lines are carried out by one single vehicle type and for a scenario where BHLS services have their own dedicated fleet. A framework is developed which can be used to estimate how much ridership should increase to cover the costs of a dedicated fleet.

Public transport operators face significant challenges in maintaining a high Quality of Service, which is essential to encourage a modal shift from private vehicles to public transport. One major factor affecting service quality is crowding. This issue can be mitigated by increasing capacity, for example through the deployment of articulated buses. However, the impact of articulated buses remains relatively underexplored. This study investigates the effects of introducing articulated buses in public transport networks, focusing on their potential to alleviate crowding, address labour shortages, and enhance the passenger experience. Using a mixed-methods approach, both operational and passenger-level implications of deploying articulated buses are examined.

Optimisation of public transport networks are crucial for a well-functioning city or a large urban agglomeration. Public transport is the most efficient way for large groups of people to travel in and to a city. In this report the optimisation is confined to the network optimisation of the bus. Based on the available budget choices have to be made for the network design to maximise the ridership.
The focus of this thesis is the stop and line spacing of the bus, the distance between sequential bus stop and parallel bus lines respectively. Changing the stop and line spacing have an effect on the running time of bus users, with a trade-off between the walking and in-vehicle time. A self-designed total travel time model optimises the weighted total travel time with weights on the walking time and frequency. The frequency here is based on a combination of stop and line spacing. The stop and line spacing affect the running time and thus how much a vehicle serves a route per hour. This in turn determines the frequency. The result of the total travel time model is an optimal stop spacing of around 540 meter and a line spacing of 700 meter. Analytical models by other researchers found an optimum stop spacing in between 600 and 650 meter and a line spacing of 750 meter. In practice guidelines are used where the stop spacing is around 400 meter and the line spacing is around 550 meter. The result of the self-designed model is different because the walking weight is exponential and the frequency weight is tied to the running time of the bus. The conclusion is that the optimal stop spacing is higher than is mostly applied in bus networks. A higher stop spacing means a higher average speed and a lower travel time in the bus. The downside of a higher stop spacing is that the walking distance increases which effects the ridership. This is the reason the self-designed total travel time model has a larger focus on the walking distance, and has resulted in a lower optimal stop and line spacing than in analytical models of other researchers.
The effect the walking distance has on the use of the bus is different in different area types in an urban agglomeration. A regression analysis on the relation between the stop spacing and sociodemographic characteristics has been performed for the analysis of this effect. The data used for the regression analysis is gathered for the city of Rotterdam and the surrounding towns. For an area with a high population density, income, and car ownership in combination with a large distance, around 10 km, from the city center a stop spacing of 600 to 700 meter is recommended. The lower the distance to the city center, the lower the stop spacing, and thus for a similar area type around 5 km from the city center a stop spacing of 500 to 550 meter is recommended. For an area with an average population density, income and car ownership in combination with a high distance (10 km) to the city center a stop spacing of 475 to 525 meter and in combination with a lower distance (5 km) a stop spacing of 450 to 475 meter is recommended. The reason why these values are lower than for the first area type is because there are more activity facilities. This means that there are more potential destinations in this area type and for users a stop close to a destination is important for the choice to use public transport. The larger the area of these facilities, and the higher the number of facilities, the lower the stop spacing. In the city center the recommended stop spacing is therefore 425 to 450 meter. The exception to this is the area close to the central station of Rotterdam, here the stop spacing is higher (550 to 600 meter) because close to a station people are not going to use the bus, but the train which has a higher operation speed and thus is a higher quality mode. For an area with a low population density, income and car ownership a stop spacing of 550 to 650 meter is recommended. In this area type there are a lot of captive riders, who are dependent on public transport and are willing to walk further than other types of public transport users. For this group it is important that bus stops are close to activity centers. If the stop spacing in this area becomes too high the number of trips made by captives decreases, even if the number of users stays the same. Having bus stops close to destinations compensate for the higher stop spacing. These destinations could also be a train, metro and/or tram stop. This complies with the higher willingness to walk, and makes the bus network more efficient.
For the line spacing it is more complicated to recommend values for certain area types. However recommendations are given to the network type and design, which is closely related to the line spacing. Because different area types have different characteristics a hybrid network is the most effective solution. In the city center a grid network is used to distribute users equally. Radial lines are used to connect areas outside the city center with the city center and ring lines are used to create connections between these areas if the demand for this is there. The further away from the city center the lower the bus stop density.

Urban planning in the Global North has historically prioritised car infrastructure, leading to car-dependent cities with congestion and pollution. In recent years, especially in north-western Europe, there has been a policy shift toward healthier and more sustainable urban environments, with strategies such as reducing parking capacity gaining attention. While this measure can discourage car use and free up urban space for alternative purposes, its city-wide impacts—particularly on public transport and cycling—remain underexplored.

This thesis investigates how large-scale parking space removal affects travel behaviour in Rotterdam, a city with relatively high car use but suitable conditions for car-lite policies. Three intervention scenarios (20%, 40%, and 60% parking reductions) are analysed using the V-MRDH macroscopic, multimodal transport model. To address the model's limitations, a supplementary estimation method was developed to more realistically approximate shifts in transport demand.

Results show that a 20% reduction could lead to a peak-hour modal shift of up to 2,566 motorists, corresponding to increases of 2.8% in public transport and 2.2% in cycling. Although average loads remain within capacity, some tram and bus lines face overcrowding during the busiest 15 minutes. The findings highlight the need for strategic public transport planning and model enhancements to accurately assess behavioural responses to parking policy changes.

As cities are densifying, low-car neighbourhoods are increasingly seen as a solution to reduce car dependency, improve public space, and encourage alternative mobility options. This study examines the impact of such a development by evaluating the mobility behaviour and perceptions of residents in Cartesius, a newly developed low-car neighbourhood in Utrecht. Using a revealed preference approach, this research analyses survey data (N=70) and qualitative insights from conversations with residents to explore the influence of residential self-selection on mobility adaptation. Findings indicate that even non-self-selected residents—those who did not actively choose a low-car environment—reduce car ownership and car use while increasing reliance on public transport and shared mobility. This suggests that well-designed low-car policies can influence travel behaviour beyond pre-existing preferences. Meaning that large-scale low-car policies could be viable for a broader population beyond those who actively choose this lifestyle.

Technological advancements have transformed how travellers access and navigate transport systems. This thesis analyses how such developments impact (potential) public transport users, especially those struggling with digital technologies. It also explores ways to mitigate potentially exclusionary effects of digitalisation in transport, helping transport operators, authorities and policymakers ensure that digitalisation does not disadvantage vulnerable users.

In response to the growing housing shortage in the Netherlands, particularly in urban areas where land availability is constrained, local governments are increasingly considering urban expansion into peripheral areas, even those near freeways. These areas offer convenient car access but pose challenges for sustainable development due to the potential for increased congestion. This research focuses on developing mobility design strategies to reduce car usage and promote public transit in such peripheral areas. The central research question is: "Which mobility design strategies, regarding public transit and car parking planning, should be implemented to reduce car usage and enhance the attractiveness of public transit in a peripheral urban area?" To address this question, a Discrete Choice Model was developed to analyze commuting mode choice behavior under different scenarios. The research began by identifying influencing factors from the literature, including relevant urban transportation modes (bus, light rail, car, and bike), trip characteristics, personal attributes, and environmental factors. The study focuses on Rijnenburg, an outskirt area of Utrecht, which is poised for significant urban development but faces challenges due to its car-friendly location at the intersection of two major highways. Three design scenarios—Conventional, Sustainable, and Ambitious—were developed based on existing municipal development strategies. These scenarios consider various factors such as public transit stop density, line frequency, route planning, vehicle type, parking facility location, and parking costs. A Stated Preference survey was conducted to gather data from 200 respondents, which informed the construction of both a Multinomial Logit (MNL) model and a Panel Mixed Logit (Panel ML) model. While the MNL model was ultimately chosen for its balance of accuracy and interpretability, the study revealed a strong preference for bikes over cars among respondents, highlighting the potential for shifting mode choice through strategic design interventions. The analysis showed that the Ambitious scenario, which includes tougher interventions such as higher parking costs and restricted parking locations, was most effective in reducing car usage. However, the scenario's feasibility was questioned, leading to a recommendation for a hybrid approach combining elements of the Sustainable scenario with stricter car parking measures. The research also highlighted several limitations, including potential biases in the survey sample and the exclusion of certain factors from the model. Nonetheless, the findings suggest that a combination of mobility strategies—focused on optimizing public transit accessibility and increasing barriers to car use—can significantly contribute to sustainable urban development in peripheral areas like Rijnenburg. In conclusion, the recommended strategies, particularly the reduction of transfers in public transit and the strategic location of parking facilities, are expected to play a crucial role in promoting sustainable mobility in Rijnenburg. Further research is recommended to refine these strategies and explore their applicability to a broader range of contexts.

Transportation planning is increasingly incorporating public participation, with Participatory Value Evaluation (PVE) emerging as a key method. However, the validity of PVE, particularly its face validity across different demographic groups, remains under-explored. This study addresses this gap by analyzing face validity evaluations from three recent PVE consultations in the Netherlands. Statistical analyses, content analysis, and expert discussions were employed to examine how factors such as age, gender, and education influence these evaluations. The findings indicate that while PVE is generally perceived positively, specific groups—particularly older adults and those with lower education levels—consistently evaluate its face validity negatively. To enhance the legitimacy of PVE in transportation planning, tailored strategies are recommended to address these persistent negative evaluations.

The National Model System (Landelijk Model Systeem [LMS]) is used to model and predict travel behaviour for the whole of the Netherlands. The LMS is a multimodal model that makes predictions for the main road and rail network of the Netherlands and is an important tool for policy making. One of the inputs of the LMS is data based on yearly travel surveys (Onderzoek Verplaatsingen in Nederland [OViN]).

The work in this thesis shows that the LMS is currently unable to accurately capture the effect of the differences in spatial environment effectively. The LMS uses the Degree of Urbanisation (DU) to model the spatial environment, which proves insufficient to correctly model travel behaviour.

This conclusion was reached by using a cluster analysis and propensity score matching and by comparing the ‘real’ modal split (OViN) with the ‘predicted’ modal split (LMS). All zones in the Netherlands were clustered based on characteristics of the spatial environment. This was done using the so-called D-variables.

The propensity score matching showed that the differences in modal split between the different DUs and the different clusters are caused by both demographic characteristics and differences in the spatial environment. However, the effect of the spatial environment is larger.

Policy makers and other users of the LMS should be aware that testing policies or future scenarios in the LMS that change aspects of the spatial environment might introduce additional uncertainties in the forecasts of some regions.

This research evaluates the accessibility in industrial areas to the labour force by applying a spatio-temporal accessibility model in the IJmond region, located in The Netherlands. Industrial areas are crucial for regional economic activity, impacting employment opportunities for the labour force, especially those with lower incomes. This research aims to understand how the spatiotemporal configuration of industrial areas affects accessibility for different demographic groups and its implications for transport equity. The study shifts focus from job accessibility for workers to workforce accessibility from the employers' perspective, highlighting challenges faced by industrial areas regarding public transport. A gravity model is built to analyse spatiotemporal accessibility using socio-demographic data from CBS and geographic data from IBIS. Findings indicate significant disparities in non-spatiotemporal accessibility levels between car and public transit, with car accessibility generally higher. Focusing on spatio-temporal accessibility for transit has shown that levels decrease further during the night. Many industrial areas become 'unreachable' by public transit during nighttime hours with those that remain reachable, facing significantly longer travel times. In addition, it has been found that low-income workers tend to live closer to industrial areas and in higher concentrations compared to high-income workers. Recommendations include developing alternative transport solutions that will primarily support shift workers during nighttime, enhancing pedestrian and cycling routes, and utilizing more detailed neighbourhood-level data for future studies that aim to improve accessibility and gain more insights into equity in industrial areas.

In the upcoming years more train passengers are expected and with more trains on the tracks railway systems require greater resilience. Switches can play a major role during disruptions as they enable trains to be rerouted onto other tracks, allowing them to bypass the disruption but switches also facilitate overtaking, meet-pass operations at stations as well as diverging and merging at junctions. Since switches consist of numerous parts and the fact these are moving infrastructure elements they are subject to failure itself. Maintenance is expensive and ProRail, the Dutch infrastructure manager, only has a limited budget from the government and if certain switches are only used during disruptions it sounds logical to remove those switches. With on average 50 disruptions per day in the Netherlands with both small and huge impact, it is important to get insights into the relationship between resilience and the location of the switches.

In this thesis a model is constructed that evaluates the impact of a set of disruption scenarios on different switch configurations. Four key performance indicators are found in literature that can measure resilience quantitatively: costs (number of switches), rate of cancelled services, punctuality and time to recover. In interviews with rail experts, weightings for the four KPIs are derived which are used to calculate a score for all disruption scenarios and infrastructure layouts. A trade-off between costs and resilience is made in order to find the optimal switch configuration for a double track and four track layout which provides the highest capacity during disruptions. The set of disruptions including cause, location and duration come from an extensive analysis of disruption events of the past 6.5 years in the Netherlands.

Currently, NS is cancelling many trains since NS is examined on punctuality and not on the number of trains. This research aims to cancel as few trains as possible which is also examined in a case study where the model is validated. The Dutch railway line Utrecht Centraal – Arnhem Centraal appears to have a weak spot and by proposing new switch location configurations on a part of this line the score increased, despite the fact that more switches have been included in the proposed solution. Since the big renovation, 108 switches in Utrecht Centraal were removed by ProRail which improved punctuality, capacity and speed but decreased the flexibility: a disruption between Utrecht and Arnhem (or Eindhoven) currently has a lot of impact on the train service between Amsterdam and Utrecht, because short turning options in Utrecht are rare. This means that trains are now being cancelled completely or short turn already in Amsterdam. By using smart options with new rerouting strategies, capacity between Amsterdam and Utrecht can be kept high with the proposed solution during a disruption between Utrecht and Arnhem or Eindhoven.

The study emphasises the importance of understanding individuals' mode choice between train and car to reduce CO2 emissions. It addresses two significant gaps in the existing literature, focusing on the impact of detailed attitudes towards mode use over time and the impact of train travel time components on actual mode use. The study reveals that environmental awareness and cost-consciousness drive increased train usage and reduced car usage, while status-sensitivity has no significant influence on mode use over time. Additionally, travelers place varying importance on different train travel components, with transfer time significantly impacting the modal share of the train. Furthermore, the perceived valuation of train travel time components emerges as a more reliable indicator of individuals' mode choice between train and car than the actual door-to-door train travel time. To encourage a shift from car to train use, the study emphasizes the need to encourage travelers to consider cost and environmental factors related to mode use, as well as the need to minimize transfer time and enhance the appreciation of transfer time

The transport sector needs to change to meet some of the global challenges we face: climate change, population growth and urbanisation. It needs to become more sustainable, which is why the Netherlands wants to introduce more high-quality bus systems. However, there are some barriers to implementing these systems.

In this thesis, through a literature review and interviews with Dutch stakeholders, a definition of the high-quality bus system is found, including its main characteristics. The most important part of this thesis is to map the existing problems. In order to solve these problems, a roadmap is designed to help with the implementation by breaking the process down into smaller, more manageable steps.

A high-quality bus system should above all be fast, frequent, and reliable, but comfort is also important for such a system. The most commonly used terms are Bus Rapid Transit (BRT) and Bus with a High Level of Service (BHLS). The literature and the interviews confirm that there are still many problems that should be addressed in the roadmap, from cooperation problems to short-term thinking by politicians, from blind commitment to rail to underestimating the social value of public transport.

The proposed roadmap consists of eight blocks. It begins with the creation of a city-wide vision for mobility and the formulation of a programme of requirements for the entire public transport system (i). These are translated into objectives and a programme of requirements for the line to be designed (ii). In addition, cooperation with all parties should be well regulated (iii). The next important step is to analyse the target group of (potential) passengers, the stops and the bottlenecks and intersections (iv). Only after that is the system choice made (v). If a high-quality bus system is chosen, it needs to be designed (vi). Among other things, the route, the operation, the first/last mile transport and the branding have to be designed. When the design is ready, the line can be built, and operation can begin (vii). This can be done in stages, addressing the main bottlenecks first and the rest later. This is followed by the often overlooked evaluation, which is important for learning lessons for future projects.

Stakeholder feedback and a case study show the value of the roadmap for implementation in the Netherlands. By choosing the modality later in the process, compromises in quality are avoided. In addition, the in-depth analyses improve the quality of the line and enable faster implementation by identifying the main bottlenecks. The main value of the roadmap lies in its integral approach, rather than an approach from one perspective. This means that the problems of all stakeholders can be addressed to design a high-quality public transport system that works for all.

Night trains benefit society in multiple ways. They are environmentally friendly, improve the accessibility of regions and are space-effective. Understanding traveller's preferences enables night train operators to improve night train services and harness societal benefits better. This study conducted a stated preference survey with 1031 respondents from the Netherlands to dive deeper into the importance of operational factors like booking convenience, travel costs, long travel times of up to 18 hours and accommodations. Additionally, factors that make up a convenient booking scenario were revealed. Lastly, a latent class choice model (LCCM) was applied to derive insights into heterogeneity and to determine to which extent personal factors influence class membership. Results reveal that for a convenient booking scenario, being able to book one ticket and comparing travel options are most important. However, booking convenience only plays a minor role in determining night train mode choice. Travel costs and accommodation are significantly more important. Several classes have been revealed: Environmentally conscious comfort lovers make up 13% of the respondents, experienced night train travellers 29\%, cost-sensitive travellers 37% and flight lovers 20%. Applying a scenario analysis, night train market shares vary from 20% to 71%, with significant heterogeneity among respondents. For practitioners, this implies focusing mainly on prices and accommodation while taking the significantly different preferences of the population into consideration.

This study investigates the opinion and perceived equity of hospital employees regarding sustainable travel modes for their commute, the (e-)bike and shared bike combined with public transport in specific. The objective of the research is to be able to advise the Academic Medical Center and Pon on whether the alternatives are deemed successful, what factors affect the take-up of the alternatives and what measures improve the adoption among the employees, involving internal communication strategies. The used method is the conduction of semi-structured interviews with hospital employees, which allow for in-depth conversations that generate insight into the individuals rationale and behavior. The results indicate that there are two distinguished employee groups: employees with irregular hours and employees with regular hours. The irregular hours constrain the employees from using public transport and make cycling perceived as less safe. The employees with regular hours experience no environmental constraints to cycle or to use public transport, when well connected. The proposed alternative to meet all employees' needs is P+R facilities around the city of the medical center, where they can park their car and cycle the last-mile to work. This reduces commute emissions, reduces parking actions at the work end, and increases employee health and satisfaction. The study additionally emphasizes the need for inclusive communication with a broader focus than solely online notice.

This thesis explores the role of shared mobility as a sustainable and inclusive alternative to car ownership within the context of the mobility transition, focusing on how shared mobility can bridge accessibility gaps, particularly in urban areas where shared mobility options are limited. Using the Multilevel Perspective (MLP), this research analyses the niche replacement potential of commercial shared mobility in relation to the traditional car-ownership regime. A case study in Amsterdam Zuidoost is employed to explore how shared mobility can contribute to an inclusive mobility transition, addressing issues of urban inequality and societal exclusion from sustainable transportation alternatives. Qualitative methods are applied to assess the interactions between three key perspectives: policy, individual, and business. The findings reveal a gap between the societal need for the mobility transition, the mobility needs of residents in Amsterdam Zuidoost, and the business opportunities for shared mobility providers, leading to low implementation potential. This research advocates for a shift away from commercial shared mobility solutions towards to more cooperative, community-based models, such as Mobility as a Commons (MaaC) to empower local communities, diversify mobility options and promote a more inclusive transition towards sustainable urban mobility.

This study explores the potential role of e-scooters in supporting “first-mile” travel to train stations in the Netherlands, a critical stage in daily commuting for many Dutch travellers. In a nation where bicycles are a primary mode of transport—especially for trips under 5 kilometres—the introduction of e-scooters offers an alternative with similar benefits: environmental friendliness, cost-effectiveness, and ease of manoeuvrability. With their compact size and accessibility through sharing services, e-scooters can complement the existing bicycle culture, promising an appealing option for urban mobility.

The research focused on examining the role of e-scooters in “first-mile” travel through a stated preference choice experiment, given that e-scooters were newly legalised. A sample of 156 participants responded to six hypothetical travel scenarios, where they chose between familiar modes like walking, cycling, e-bikes, and e-scooters based on different factors such as carry-on ticket costs, parking times, and travel times. These scenarios were designed to reflect typical Dutch commuting choices while testing the appeal of e-scooters as a new transport option.

Analysis of the data using a Multinomial Logit (MNL) model yielded several insights into travel behaviour. There was a clear baseline preference for familiar modes, with participants showing a higher likelihood of choosing options like cycling or walking. Travel cost and time emerged as significant decision-making factors, with higher costs and longer times deterring mode choice. Notably, gender differences surfaced in this context, with males displaying greater tolerance for longer bike trips than females, indicating variations in time-cost sensitivities across demographics.

Experience with transport modes also influenced choices; prior e-scooter use was positively correlated with selecting this option again, suggesting that familiarity can increase comfort and confidence in choosing new modes. Established travel habits showed a strong impact on choice consistency, with individuals who typically walked or cycled to stations likely to maintain these habits, reinforcing the role of routine in travel preferences.

To illustrate the findings, a simulation modelled two scenarios. In the “Extreme Low” scenario, where e-scooter costs were low and parking time was minimal, walking was favoured for short distances (under 0.5 km), while cycling became dominant as distance increased. In contrast, the “Extreme High” scenario, with no fees and longer parking times, significantly boosted e-scooter attractiveness, particularly beyond 1.5 km, where it surpassed both walking and cycling. This outcome underscored the sensitivity of user preferences to economic factors, with e-scooters emerging as a highly competitive option when cost barriers were removed.

Overall, this study highlights the substantial potential for e-scooters to influence first-mile travel choices, particularly when costs are favourable and convenience is enhanced. By offering a viable alternative for medium-distance trips, e-scooters could reshape first-mile mobility in the Netherlands, complementing the well-established cycling culture and contributing to sustainable urban transport.

Travelling to work is one of the essential activities in individuals’ daily lives. However, commuters who depend on public transport often face significant challenges in accessing job opportunities, resulting in transport-related social exclusion risks. In recent years, shared mobility services have gained popularity as a solution, offering greater flexibility in first/last-mile segments of multimodal trips. These services have promising potential to improve accessibility for those who rely on public transport, thereby addressing issues of accessibility inequity. Such an intervention aligns well with the unique Dutch cycling culture, where cycling already accounts for a substantial portion of transit journeys. However, limited bike availability at the egress side diminishes the utilization of bikes for the last mile of a trip. To address this issue, integrating shared bikes with transit as an egress mode could be an effective intervention.

This thesis conducted a ”what-if analysis” in the Amsterdam Transport Region to investigate the impacts on job accessibility for different commuters and the equity of the whole transportation system if shared bikes are provided at transit stations as the egress mode. The results highlight the considerable potential of this integration in improving job accessibility and promoting social equity.

Implications drawn from the analysis provide valuable insights. Statistically, groups without car access can benefit more than groups with car access from integrating transit and shared bikes, but benefits might favour high-income groups. Geographically, accessibility improvements are mainly distributed to commuters living next to transit stations, while equity improvements are concentrated in areas with dense and developed public transport systems. Additionally, commuters living close to transit stations are more likely to contribute significantly to the overall accessibility deficiency, even though they have convenient first-mile segments. These implications guide policymakers in prioritizing interventions for targeted groups or regions, and facilitating the creation of a more equitable transportation system.

This studydives into factors influencing the shared e-moped usage in first- and last mile. Other studies show that the service area size, vehicle availability the shape of city and the temperature affect the shared e-moped usage. This study confirms the service catchment, temperature and vehicle availability factors. It adds to this that also factors such as the share of young people, bus frequency, shared bike availability, walking distance, visibility and points of interest have an influence. This study also provides a quantification to show which factor has the biggest influence. According to the model results, the vehicle availability at a station is the most important factor. Next to the factors, this study also shows what the usage patterns of shared e-mopeds in first- and last mile transportation are. This study, therefore, helps in understanding the usage of shared e-mopeds as a first- and last mile mode.