Passenger railway demand fluctuates daily, peaking at the start and end of the workday due to commuting to school and work. During the off-peak the volumes drop and most people travel for other purposes, like leisure and social visits, which results in different travel destinations. Despite this, many European Railways use fixed line plans and cyclic timetables that remain constant throughout the day. While this approach makes schedules easy to remember and provides ample off-peak travel options, it is primarily designed for peak-hour demand, making it less efficient for the off-peak. Furthermore, due to the different mix of travel purposes, a schedule based on peak-hour demand is not necessarily optimal for off-peak demand. This paper aims to combine the benefits of a cyclic timetable with the flexibility of an acyclic timetable in order to follow the time-dependent demand more closely. We propose a mixed-integer linear programming model that finds a timetable for a day consisting of several periods which each have its own line plan. The resulting timetable is required to be cyclic within each period and provide a good transition between the periods. The model is successfully tested on a case study with changing stopping patterns using data from the Dutch railway network, for which an optimal timetable is found. In this timetable, the transition between cyclic schedules can be done without cancelling trains or shifting trains from the new cyclic times.

Reducing transport poverty can improve well-being and expand employment opportunities. This study investigates the relevance of socio-demographic and urban density predictors in relation to transport poverty contributor metrics for neighborhoods in the Amsterdam metropolitan area. Utilizing a spatial econometric framework, we assess the relevance of these predictors across three dimensions of transport poverty: mobility, accessibility, and affordability. Contrary to existing literature, our findings indicate that the demographic factors of gender and younger age are not significant predictors at the neighborhood level. Furthermore, the research identified a correlation between higher urban density and transport poverty. While higher urban density is associated with decreased car ownership rates and increased accessibility, it simultaneously correlates with higher public transport costs relative to income. Additionally, the method revealed a high cumulative spatial effect of income in connection with transport affordability, indicating spatially extensive income-related transport affordability disparities. Our research offers new insights into factors related to neighborhood-level transport poverty. The observed spatial dynamics call for targeted strategies that address the unique challenges for implementing equitable transport policies in both densely populated urban areas and less urbanized regions.

Offering shared mobility options at transit stops can potentially increase the service area of a stop and consequently, possible detours in transit lines can be eliminated to decrease in-vehicle travel times for through-passengers and reduce operational costs. However, current research mostly focusses on shared mobility options and expected behaviour only, whilst not looking at this integrated transit network design problem. Additionally, most focus of current studies is on the integration of shared mobility in urban areas and/or around train stations, leaving a gap on suburban areas and transit lines with lower demand. In order to answer our research question “what the effects are of increased route directness for low-demand transit lines in conjunction with offering shared mobility at transit stops”, we developed a mesoscopic model extension for the aggregated four-step transport model to model changes in travel behaviour as a result of straightened transit lines and the simultaneous integration of shared modes. Discrete choice models are used to accurately model first and last mile preferences of people, based on the access and egress distance, demographics and available (shared) modes. Finally, the probability of passengers cancelling their complete trip as a result of increased first and last mile distances is also explored. This model framework was applied to nine case studies in the Netherlands. The synthesis of the case studies resulted in key factors contributing to a promising redesign of the transit network. The main factor is that through-passengers should significantly outnumber local passengers, by at least 75%-25%. Additionally, the increase in access and egress times should not be significantly larger than in-vehicle time savings of through-passengers. Moreover, it is found that the mode share of micromobility in the first and last mile is approximately 15% across the different cases, whereby the highest usage can be seen for people under the age of 25 and for distances greater than 1 km. Finally, it is concluded that the additional costs of shared mobility are on average only 10% of the savings in operational costs.

Integrating bike-sharing programs with public transport enhances accessibility and car-independent mobility, yet a comprehensive societal cost-benefit analysis of this integration remains scarce. This study addresses this gap by conducting an ex-durante analysis of the OV-fiets program in the Netherlands, a station-based round-trip bike-sharing system designed to improve last-mile connectivity for train commuters. The analysis reveals that in the average (balanced) scenario, the net present value (NPV) of the OV-fiets scheme is positive, with a benefit-cost ratio (BCR) of 1.5. This indicates that the scheme has benefited the Dutch society over the 20-year period (2004–2023). In the pessimistic scenario, the NPV remains slightly positive with a BCR of 1.1. This implies that even under the least favourable conditions, where high costs and low benefits are assumed, the scheme still slightly exceeds the break-even point. Conversely, in the optimistic scenario, the BCR rises significantly to 2.4. Primary benefits include enhanced accessibility, reduced road congestion, and improved health outcomes. This research underscores the considerable societal value of the OV-fiets program in the Netherlands, warranting continued investment in the program and emphasising the need for ongoing bicycle safety measures and infrastructure improvements. However, OV-fiets might be successful in the Netherlands; our analysis also shows that copying it into other contexts is not straightforward. The seamless integration of bikes with trains is crucial, and the operators should be able and willing to accept operational losses.

Access/egress travel to train stations poses a significant barrier to increasing the number of train travellers. The last mile is challenging for travellers, given the lack of private modes to reach the destination, strongly limiting the egress range from the station. An often-cited solution is shared micromobility (SMM): bicycles, e-bikes, e-scooters and e-mopeds. Through a stated preference survey, we analyse activity-end mode-choice preferences for SMM, walking and public transport (PT) among the Dutch population. Using a latent class choice model, we uncover three user groups: Multimodal SMM enthusiast (58%), who choose based on the trade-offs between various travel characteristics, while not having strong modal preferences. They are the most open, ready and able to use SMM. SMM hesitant cyclists (16%) have a strong preference for cycling and while they are open to using SMM, they may not feel themselves ready, stating that use of SMM can be difficult and dangerous. SMM-averse PT users (27%) are most likely to use PT and avoid SMM as they find it too difficult and dangerous to use. For policymakers, the high preference to walking over short egress distances reaffirms the need for continued focus on transit-oriented development. For longer distances, policymakers should focus on improving PT service in high-density high-demand areas, as high frequencies and dense PT networks can be justified, while stations in low-demand areas are better served by SMM. Policymakers should also prioritise SMM modes that are cheaper and that travellers are familiar and comfortable with, such as bicycles.

Shared micromobility may enhance accessibility as part of a comprehensive public transport network. A qualitative stakeholder perspective is needed to reflect the practical opportunities and challenges for integrating shared micromobility and public transport. This research synthesizes literature alongside 25 interviews with professionals across North America and Europe to answer: 1) what challenges and opportunities do different integration approaches offer? And 2) what should be prioritized when integrating shared micromobility and public transport? We frame integration efforts in three pillars: 1) institutional, 2) physical, and 3) digital integration. Findings show that integration efforts are effective only when foundational preconditions are met including high-quality public transport, dedicated micromobility infrastructure, supportive land uses, and issue framing. Institutional and physical integration are both necessary to facilitate multimodal travel and create cohesive regional travel networks. Digital tools can support integration but often requires substantial resources, and faces data sharing and privacy, feasibility, and scaling challenges.

Shared micromobility (SMM), including bicycles, e-bikes, scooters, etc., is often cited as a solution to the first and especially the last mile problem of public transport (PT), yet when implemented, they often do not get adopted by a broader travelling public. As behavioural adaption is largely related to peoples’ attitudes and perceptions, we develop a behavioural framework based on the UTAUT2 framework to gain better understanding why individuals may (not) be willing to use SMM. Through an exploratory factor analysis (EFA) and a latent class cluster analysis (LCCA), we study the adoption potential of SMM and assess drivers and barriers as perceived by different user groups. Our findings uncover six user groups; Shared mobility positives, Car-oriented sharing neutrals, Older apprehensive sharers, Young eager adopters, (Shared) Mobility avoiders and Skilled sharing sceptics. The Young eager adopters and Shared mobility positives tend to be the most open to adopting SMM and able to do so. Older apprehensive sharers would like to, but find it difficult or dangerous to use, while Skilled sharing sceptics are capable and confident, but have limited intention of using it. Car-oriented sharing neutrals and (Shared) Mobility avoiders are most negative about SMM, finding it difficult to use and dangerous. Factors relating to technological savviness, ease-of-use, physical safety and societal perception seem to be the strongest adoption predictors. Younger, high-educated males are the group most likely and open to using SMM, while older individuals with lower incomes and a lower level of education tend to be the least likely.

Unplanned train disruptions are a source of passenger dissatisfaction because they are often accompanied by overcrowding and lack of information. To better accommodate passengers during disruptions and preventing travellers from switching to other less sustainable modes of transport, mitigating control strategies can be applied by railway operators. This however requires predicted passenger flows over all available travel options as an input. Due to the COVID-19 pandemic these passenger flows have becomes less predictable, as many travellers have gained an additional feasible alternative to cope with unplanned disruptions on outbound commuter trips − they may return home and start teleworking. Because this travel option is only available to teleworkers and now utilized more than before the COVID-19 pandemic, heterogeneity in route choice behaviour has increased. To fill this knowledge gap and provide predictions of passenger flows, an online survey containing a labelled stated choice experiment was carried out among Dutch train commuters. Consequently, a latent class choice model was estimated to investigate the influence of disruption characteristics, teleworking, COVID-19 risk perception and information provision on travel behaviour during train disruptions in the Netherlands and uncover heterogeneity in behaviour. Our results indicate that the strongest predictors of route choice behaviour are the moment of discovering the disruption, the disruption length and job characteristics. Uncovering four latent classes shows the different valuations of crowding, waiting times and additional travel times among commuters. Commuters with the option to telework are more likely to return back home during disruptions as well as commuters who are sceptic towards the provided information and those who are still conscious of COVID-19. Commuters who cannot telework and trust the provided information are more likely to reroute within the train network whereas commuters who cannot telework and do not trust the provided information are more likely to wait for the disrupted services to resume.

Car dominance in urban landscapes poses environmental, health, and congestion challenges. This comprehensive study examines the potential of shared mobility in car-free areas. Specifically, it investigates the mobility behaviour of inner-city older adult residents (50 + ), traditionally heavy car users through a case study of small-medium-sized Dutch cities and a stated preference experiment. This study applies a Latent Class model to analyse the heterogeneity in passengers’ preferences, identifying four distinct groups: Price Sensitive & Private Car Enthusiasts, Time-Conscious Travellers, Pro-Cycling & Conventional travellers, and Micromobility Enthusiasts. The model predicts class membership based on travel behaviour data from the stated choice experiment and examines the role of key factors such as travel cost, travel time, and walking distance in shaping mode choices across five transport options: bike, e-bike, e-scooter, e-Brommobiel, and e-car. The findings reveal that a significant portion of travellers recognise the value of shared mobility options in reducing private car dependency, underscoring the need for targeted interventions to address barriers and enhance accessibility to promote shared mobility adoption. Based on these distinct passenger segments, the study proposes specific policy measures that not only enhance transport planning but also address existing challenges and user concerns in sustainable urban mobility.

Many cities have ambitious climate targets, like becoming climate-neutral by 2050, 2040 or 2030, but are uncertain about how mobility and land use should change in order to reduce GHG emissions to levels consistent with the cities’ aims. Finding answers on this, and also on the question of how to strike an effective balance between desired fundamental transformation and realistic expectations, was at the heart of the Interreg Europe project 2050 CliMobCity (2050 Climate-friendly Mobility in Cities). The project partners were four medium-sized but otherwise quite different cities (Bydgoszcz, Plymouth, Thessaloniki and Leipzig), along with the Potsdam Institute for Climate Impact Research (PIK) and TU Delft. Each partner city conducted a so-called demonstration study, which required defining ambitious packages of measures (mobility, land use, electrification) and forecasting changes in mobility by macroscopic transport modelling. PIK then analysed GHG emissions using its carbon model. This paper extends the demonstration studies into a case-study approach. This is preceded by an exercise in consistently structuring types of GHG and mobility performances and corresponding measures. The case-study approach is supplemented by a review of the literature on shared and micromobility. A conclusion drawn from the case study is that none of the partner cities is in fact sufficiently reducing GHG emissions. Even if electricity production was completely green, the remaining gap between GHG reduction aims and analysed GHG delivery lies between 30–81 %, dependent on the scenario and city. Shared and micromobility seem not to lead to strongly deviating conclusions. We discuss policies to close the gap. One major option discussed is tackling GHG emissions from urban freight, in forms such as organising public-private cooperation designed to accelerate the electrification of freight vehicles.

Regional non-electrified railway networks require replacement of diesel traction to meet increasingly stringent emission reduction targets. Since full electrification of these networks is often not economically viable due to their low utilization, battery-electric multiple units (BEMUs) are recognized as a potentially suitable long-term solution, offering zero-emission train operation while requiring only partial tracks electrification. One of the main challenges when introducing BEMUs is determining an optimal electrification layout, i.e. the location and the length of electrified track sections while taking into account the vehicles’ and infrastructure technical characteristics and constraints alongside the requirements related to maintaining current timetable and quality of service. This paper formulates this as an intermittent partial electrification network design problem and develops an optimization framework that integrates high-fidelity BEMU simulation model in deriving a cost-optimized network electrification configuration. The proposed method is demonstrated using the existing non-electrified regional railway network in the Netherlands with the rolling stock and transport services of Arriva as a case. The obtained solution provides about 30% lower capital costs compared to the conventional continuous partial electrification approach, and about 3.5 times cut in these costs compared to the fully electrified network. Additionally, further costs reduction is observed by increasing the maximum current absorption limits at standstill and by introducing flexibility in terms of operational margins.

Passenger railway demand fluctuates daily, peaking at the start and end of the workday due to commuting to school and work. During the off-peak the volumes drop and most people travel for other purposes, like leisure and social visits, which results in different travel destinations. Despite this, many European Railways use fixed line plans and cyclic timetables that remain constant throughout the day. While this approach makes schedules easy to remember and provides ample off-peak travel options, it is primarily designed for peak-hour demand, making it less efficient. Furthermore, due to the different mix of travel purposes, a schedule based on peak-hour demand is not necessarily optimal for off-peak demand. This paper aims to combine the benefits of a cyclic timetable with the flexibility of an acyclic timetable in order to follow the time-dependent demand more closely. We propose a mixed-integer linear programming model that finds a timetable for a day consisting of several periods which each have its own line plan. The resulting timetable is required to be cyclic within each period and provide a good transition between the periods. The model is successfully tested on a case study with changing stopping patterns using data from the Dutch railway network, for which an optimal timetable is found. In this timetable, the transition between cyclic schedules can be done without cancelling trains or shifting trains from the new cyclic times.

Mobility is vital for societal wellbeing, economic growth, social inclusion, and access to essential amenities. However, the current system faces significant challenges, including environmental impact, unequal access, and safety concerns. […]

Train passenger demand fluctuates throughout the day. In order to let train services, such as the line plan and timetable, match this fluctuating demand, insights are needed into how the demand is changing and for which periods the demand is relatively stable. Hierarchical clustering on both regular and normalized origin–destination (OD) data is used to determine for each workday continuous time-of-day periods in which the passenger demand is homogeneous. The periods found for each workday are subsequently used as input in a clustering algorithm to look for similarities and differences between workdays. The methods for finding homogeneous periods during the day and week are applied to a case study covering a large part of the railway network in the Netherlands. We find large differences between the periods based on regular OD matrices and those based on normalized OD matrices. The periods based on regular OD matrices are more compact in terms of passenger volumes and average kms travelled and therefore more suitable to use as input for designing a service plan. Comparison of different workdays shows that mainly the peak periods on Friday are far away from Monday to Thursday, and hence could benefit from an altered service plan.

Enabling cycling at the home side or at the activity side of transit trips has been recognized as a promising solution to address transit network discrepancies and enhance connectivity between residents and employment opportunities. However, this multimodal solution is conditional to bicycle parking and cycle lanes, and urban planners need tools to identify relevant locations for these infrastructures. This research presents a novel method to quantify the impact of potential cycling infrastructures on job accessibility. Using a logsum-based indicator, we assess the spatial distribution of accessibility improvements across neighborhoods when residents have the option to cycle from and to transit stops. Then, we quantify the individual contribution of every potential bicycle parking location and cycle lane to the overall accessibility improvements. The proposed approach offers valuable support to urban planners in identifying the best locations for (1) multimodal bicycle parking and (2) cycle lanes to foster synergies between cycling and transit. To demonstrate the efficacy of our method, we apply it to the case study of Amsterdam. The findings reveal that bicycle parking at metro stops and cycle lanes connecting these stops to dense and remote locations contribute the most to accessibility improvements, as they effectively connect these areas to high-frequency and high-speed transit lines. Additionally, we observe that few strategic infrastructures account for most of the accessibility improvements in Amsterdam.

Latent Class Analysis was used on the 2018/19 Dutch National Travel dataset to assess travel behaviour profiles and its connection with sociodemographic and spatial factors to grasp travel patterns in a more holistic context than previous research

Public transport systems offer significant potential for mitigation of transport sector’s greenhouse gas (GHG) emissions - the second largest contributor in the European Union (EU) accounting for 23.2% of the total GHG emissions in 2020. The Sustainable and Smart Mobility Strategy, part of the European Green Deal, stipulates higher utilization of public transport systems together with the diffusion of zero-emission vehicles, renewable and low-carbon fuels, and related infrastructures as prerequisites in reaching the overall decarbonization targets.

As major fleet operators, and in some cases builders of extensive infrastructure systems, public transport operators (PTOs) will require effective management of GHG emissions and established procedures for their transparent reporting. Current practices include mainly voluntary carbon footprint reporting often limited to the well-to-wheel (WTW) scope, i.e., direct emissions from fuel combustion (tank-to-wheel, TTW) and upstream emissions linked to the fuel production (well-to-tank, WTT). Due to the implementation of the Corporate Sustainability Reporting Directive (CSRD) which stems from the European Green Deal, further new reporting obligations and standards will follow for many PTOs from the reporting year 2025 onwards. Reporting under the CSRD will follow the European Sustainability Reporting Standards (ESRS) which define new mandatory disclosures for climate reporting. In particular, in addition to Scope 1 and 2 emissions, the reporting of Scope 3 emissions will become mandatory in accordance with the GHG Protocol. This imposes significant challenges for PTOs in accounting the full life cycle emissions which were traditionally omitted and considered as out of influence, with these emissions assumed a responsibility of vehicle suppliers.

Another reason for neglecting emissions associated with upstream (e.g., vehicles and equipment production) and downstream (end-of-life) processes in the past is the absence of a globally-recognized and accepted standard for the calculation of the carbon footprint that adopts a life cycle perspective and covers the entire transport supply chain. As the only international and transport-specific standard, ISO 14083 (previously EN 16258) provides general principles and guidelines, while limiting the scope to WTW emissions. PTOs and transport sector in general are faced by the existence of a diverse mix of state-supported standards, standards self-developed by associations, recommendations by research bodies, regional approaches, methods and tools for individual modes of transport, mainly focusing on the freight transport and logistics sector.

This paper aims to provide a thorough systematic review of the existing standards, guidelines, methods and tools developed for transport-related GHG emissions calculation and reporting, and to synthesize a methodological framework for the assessment of life cycle emissions from public transport services. The review begins with a juxtaposition of outputs provided by each standard or method with PTO’s reporting needs. The paper then discusses the analysis scopes of existing standards/methods in regard to the types of GHG emissions reported, life cycle analysis boundaries, modal coverage, and fuel/energy coverage. Further, an explanation of the calculation processes used by the standards/methods, including a discussion of data needs and limitations is provided. Based on the results presented, a methodological framework for the calculation of life cycle GHG emissions is presented and showcased for the railway and bus transport services of Arriva in Limburg region in the Netherlands. The case study considers heterogenous train and bus fleet, including both electrical and diesel powertrains, allowing for the comparative assessment of various propulsion systems. It also provides deeper understanding of the environmental impacts of emerging technology such as Lithium-ion batteries, often regarded as a critical component in novel powertrain solutions in the transport sector associated with a high degree of uncertainty in their overall carbon footprint. Finally, a discussion of the need for a consistent accounting and calculation standard for PTO’s life cycle GHG emissions management concludes the paper.

The outcomes of this study can be leveraged by PTOs in determining their overall emissions and identifying the main contributors to their overall carbon footprint. In addition to the corporate responsibility and the compliance with the new regulation, applying appropriate measures and good reporting practices can help PTOs to improve their market share, company image, and value. For instance, the Dutch “CO2 Performance Ladder” management tool provides a concrete award advantage during the tendering process for certified companies in the Netherlands and Belgium. This system managed by the Foundation for Climate Friendly Procurement and Business (in Dutch: SKAO) is being adopted in Ireland, France, the United Kingdom (UK), and Germany. Furthermore, consistent calculation and declaration procedures can help PTOs in their preparation for different trading schemes, such as the European Trading System (ETS), the world’s first carbon market established within the EU in 2005.

Recent literature has given increasing attention to the different ways in which people can be excluded from transportation systems, with a reduction in economic, social, and recreational opportunities as a result. These theoretical insights into how transport poverty and transport accessibility can be measured and understood do not always relate directly to actual planning processes. Different government agencies have authority over different policy and infrastructure elements and within a transportation authority, different departments have different actors, goals, and approaches. An important first step in making advances in social inclusion is for transportation authorities to be able to evaluate their current approach as a starting point for policy improvements. Presently, however, no systematic method exists for conducting that evaluation. This article refines an existing Transportation Related Social Exclusion (TRSE) framework and develops a method for comprehensively evaluating existing TRSE reduction efforts in transportation policy. It applies this method to the operating agreements for the three public transportation concession areas in the Amsterdam Transport Region, using textual analysis to develop a policy overview for ten dimensions of TRSE. The application of the method reveals that different forms of TRSE receive substantially different levels of attention within the Amsterdam Transport Region. The evaluation serves as a tool for systematically understanding how different dimensions of social exclusion are being addressed, allowing for a starting point for discussing whether or not existing policy is adequate and creating opportunities for incorporating new theoretical concepts into practice.

Introduction: The world is facing multiple challenges, e.g. in the realm of health, urbanization, climate change and social inclusion. Mobility can be part of the problem yet has the potential to be part of the solution. Serious games can support decision-making in a complex environment. This paper describes a serious game that aims to stimulate individual learning of (future) professionals in transport and urban planning, and facilitate discussions on goals and arguments concerning different (new) mobility options. Methods: This paper presents the first version of the serious game: ‘the Optimal Mobility Mix’. This card game was developed and played in five sessions in the Netherlands, India and the USA with over 100 participants. Feedback was collected informally in a debrief, through a survey (N = 25) and through observation. Results: During the game, participants formed small groups and collaborated to select a mobility mix using playing cards that aligned with the five societal goals (effective mobility, efficient city, economy, environment & health and equity), of the 5E framework (Van Oort et al., 2017). The survey indicated that the game was highly interactive, fun and relevant. Although the game's ‘reflection of reality’ scored relatively low, it still remained positive. Conclusions: Overall, the game successfully facilitated discussion on societal goals and transportation modes and appears positive on its learning objectives. The effect of the game in policy and decision making practice will be tested in future research. Striking a balance between capturing the complexity of reality and creating an accessible and flexible model for professionals to interact with – in the form of a game, is an ongoing challenge. Future developments aim to involve key players and broader planning-related policies through a codesign process with game design iterations. To support this process, observations and recordings can be intensified to improve feedback processing.

Making the mobility sector sustainable is a key part in the transition to a climate- and carbon-neutral society (European Parliament, 2023). For trips too long to be performed by active modes (walking, cycling), public transport is the most sustainable alternative available to travellers. With a high capacity and efficient use of resources, it is ideal for transporting larger numbers of people over longer distances. (Brons et al., 2009).
In the Netherlands, 39% of all train passengers arrive to the station by bicycle, with over half a million bicycle parking spaces offered around the country (Dutch Railways, 2023). And although some travellers have their own bicycle on both the home and activity side of the train trip, most only have a bicycle on their home-end, meaning they have to rely on other forms of transportation on the activity-end, such as walking or local public transport (buses, trams, metros). A bicycle-sharing scheme is also available at almost 300 stations, with over 21 thousand bicycles, resulting in 5.4 million total trips in 2022 (Dutch Railways, 2023).

In recent years, the rise of digitalisation and increased use of smartphones have brought along with them many new shared (electric) (micro)mobility alternatives to the mobility ecosystem, such as car-sharing, (electric) bicycle-sharing, e-scooters, e-steps to name but a few. Currently mainly present in larger cities and used predominantly for shorter trips within urban areas, they do hold the potential to improve the accessibility of public transport stations, especially for more distant access/egress trips due to the assistance of electric motors.

To get a crucial understanding of train travel, micromobility and how they can interact and complement each other, we investigated the perceptions and preferences of individuals; how they perceive these emerging modes, how likely they are to use them and what they find important when making their travel decisions. We looked into the joint access-mode and train station choice, analysing how the quality of access modes and train service at a specific station affect each other; in other words, how do people trade-off attributes from different legs of the same trip. Secondly, we investigated the potential to use various shared mobility services, included a comparison when pitted against the car and bicycle.
Lastly, we evaluated the impact of introducing shared e-mopeds on public transport, considering it as both an egress mode at the activity-end of the trip, as well as a potential competing mode for the main leg of the journey.

We show that more positive perceptions of micromobility and a higher intention to use such services is often linked with past experience using such services, digital savviness (knowing how to use a smartphone), a more multimodal travel behaviour portfolio (particularly frequent use of public transport) and a higher achieved level of education. We analysed latent market segments and uncovered similar patterns, with a somewhat large share of those ready to use (shared) micromobility, with around a quarter of the population being more sceptical, but then also residing in rural areas, having a lower level of education and being less skilled with digital technology.
These results provide valuable insights for policymakers on how to proceed with introducing such services. Selecting the correct policy is vital to achieve a desired modal shift, as introducing new modes can also result in shifts from modes which are already at a satisfactory level (e-mopeds attracting cyclists for example). We show that shared e-mopeds can be both a competitor and ally to public transport, meaning that the service implementation strategy is key to secure the desired outcomes and mitigate the negative side-effects.
Future research should also compare how the various new micromobility services compete with each other for new and existing travellers. Additionally, checking for potential induced demand of such services, both as a the main mode or simply as an access/egress mode, would be valuable for policymakers.