In response to pressing climate issues, Europe is transitioning towards more sustainable transportation. Despite the potential environmental benefits, train travel often loses out to other modes of transportation in long-distance journeys (300+ km). Based on previous research, transfers seem to have a great impact on the attractiveness of train journeys. This study investigates the effects of different transfer attributes on travel choice behaviour in long-distance leisure trips. Through a combination of a literature review and focus groups, key attributes influencing travellers' itinerary choices were identified and incorporated in a stated choice experiment. The experiment, involving 431 respondents, used a Latent Class Choice Model (LCCM) to analyze preferences and willingness to pay for improvements in transfer attributes. The study finds that travel cost and travel time are of the most importance. The number of transfers and transfer time are less critical but still impactful. The service level has a small impact. When the transfer occurs in the journey is insignificant. Four distinct classes of travellers were identified: Time-Valuing Eco-Advocates (44\%), Cost-Sensitive Train Travellers (25\%), Train Dislikers (18\%), and Transfer-Averse Train Sceptics (13\%). The results indicate that reducing travel costs and time should be prioritized over improving transfers to maximize the attractiveness of train travel. However, optimizing transfer time and minimizing the number of transfers will still enhance the appeal for specific traveller classes. By analysing the results, it was found that although direct train services are generally preferred, well-designed transfer options can improve market potential. This does however require significant improvements in the European railway network design and regulations.

The integration of air and rail travel has been increasingly adopted by major European airlines such as Air France-KLM and Lufthansa, as part of their efforts to reduce short-haul flights within Europe. This in order to improve local air quality, reduce greenhouse gas emissions, and contribute to the European Commission's goal of achieving Net Zero emissions by 2050. While much of the existing literature has focused on the substitution of short-haul flights with high-speed rail for direct origin-destination travel, this study explores the integration of air and rail transport in multi-legged journeys. Specifically, it examines the incorporation of high-speed rail as spokes in the hub-and-spoke model used by major airlines.

This study aims to quantify the preferences of potential air/rail travellers in order to provide airlines, airports, and other stakeholders with insights into the key features such as service, comfort and operational factors of an integrated air/rail service. A stated preference survey, distributed among the Dutch Railways (NS) panel, was used to collect data, with a total of 541 respondents. The data is analysed using linear regression analyses and a multinomial logit model to estimate coefficients for the included parameters. Additionally, a latent class choice model was used to capture heterogeneity among the respondents in order to identify several consumer segments.

This study found that integrated ticketing was the most attractive service attribute, while priority lanes provided the highest comfort. Travel cost emerged as the most crucial determinant for choosing air/rail over air/air journeys, followed closely by the spend at the airport and train station in an air/rail journey. The latent class choice model revealed that younger, less experienced travellers were most likely to switch from air/air to air/rail, particularly in scenarios involving high levels of service and comfort integration.

This latent class choice model identified three customer groups: waiting time disfavourites (young, less experienced travellers), plane lovers (middle-aged, experienced travellers), and air/rail service admirers (mostly elderly, retired). Waiting time disfavourites, who prioritize minimizing waiting time at airports and stations, choose air/rail in 53.0% of cases. Plane lovers strongly prefer air/air, with 85.1% favouring it. Air/rail service admirers, valuing service highly, choose air/rail in 97.9% of cases.

According to a real-life scenario analysis about the introduction of an air/rail terminal at Frankfurt Airport, the current offered services and comfort features increases the share of air/rail from 31.4% (102 passengers) to 45.7% (148 passengers), which equals a substitution rate of 14.3%. With further integration, the air/rail share could be increased to 76.4% (249 passengers) among the first group of young, less experienced, travellers. However, the impact on plane lovers is minimal, with a maximum substitution rate of 19.7%. The third group already favours air/rail over air/air, so a maximum substitution rate of 2.7% can be achieved. However, overall, a maximum air/rail share of 67.7% can be reached, equal to 173 additional passengers choosing for air/rail.

The transportation sector significantly impacts the environment, contributing to 29.4% of the European Union’s greenhouse gas (GHG) emissions in 2021. International efforts have been made to mitigate this impact, such as the implementation of the European Green Deal, aiming for a 90% reduction in transport-related emissions by 2050. Despite these efforts, long-distance travel, particularly by air and road, continues to contribute heavily to GHG emissions, driven by less sustainable modes like planes and cars. Rail transport, though a more sustainable option, remains underutilized, accounting for a small share of long-distance travel in Europe. Transfers in railway journeys have been identified as a major barrier to the wider adoption of rail travel. These transfers can increase travel time, induce stress, and reduce comfort, making rail less attractive compared to other modes. This study seeks to understand how railway transfers affect traveller behaviour and mode choice in long-distance leisure travel across Europe...

The increasing demand for sustainable energy has driven interest in Airborne Wind Energy (AWE) systems. This thesis explores how public acceptance of various AWE designs is influenced by specific design attributes. Recognizing local opposition as a barrier to new technologies, the study aims to identify strategies to enhance social acceptance of AWE systems. The research investigates the relationship between design attributes (kite type, kite size, kite colour, operating height, obstruction lights) and social acceptance through literature review and surveys. Key findings indicate that designs featuring small, white, soft-wing kites operating at high altitudes are perceived as safer and more aesthetically pleasing, thus gaining higher acceptance. These insights can guide developers and policymakers in creating AWE designs that align with public preferences, ultimately facilitating broader implementation of AWE technology.

This study examines how sustainable commuting alternatives can be designed and implemented to maximise adoption among hospital employees, particularly considering non-standard employment schedules and location-specific challenges. Conducted as part of the 'Living Lab Sustainable Transport' initiative, the research aims to provide insights for the Academic Medical Center and Pon Mobility Nederland on how to maximise the adoption of eco-friendly commuting options, while addressing the unique challenges of shift work and irregular schedules. By analysing employee preferences for alternative commuting options, such as cycling, e-bike leasing, shared e-bikes and public transport, the study aims to offer practical recommendations for promoting a modal shift away from car-based commutes. A Discrete Choice Experiment (DCE) was conducted to assess key factors influencing commuting decisions, including financial incentives, travel time, and perceived comfort. Findings indicate that employees with irregular schedules require additional support, particularly regarding safety concerns and flexibility for off-peak commutes. Financial incentives, such as full public transport reimbursement, e-bike travel allowances, and increased parking costs, were effective in encouraging more sustainable commuting behaviours. The results contribute valuable insights for the healthcare sector and other industries facing similar commuting challenges, offering a framework for promoting sustainable commuting practices while addressing the unique constraints of shift work and location-specific factors.

Climate change and global warming are some of the greatest challenges the world is currently facing. This challenge has structural impacts on the natural environment as well as on human well-being. As a response to the concerns regarding climate change, the Netherlands started a renewable energy transition. Nevertheless, the realisation of the Dutch energy transition is far from being achieved. Changes in energy behaviour such as the adoption of energy-efficient technologies will help to achieve the Dutch energy transition goals. Businesses and policymakers in the energy sector can accelerate this process. To do so it is vital for them to know the preferences of the energy consumers. Stated choice experiments are a useful method to measure choice behaviour and consumer preferences. The method uses experiments with hypothetical choice situations in which the respondents are asked to choose between multiple options. However, it is the question of whether this method is useful for measuring energy consumer preferences. Prior academic research showed that energy consumer behaviour strongly depends on situational and contextual factors. Context-dependent stated choice experiments can serve as a solution because they include a stated choice context related to the choice situations. In this research, the contexts will

It is well known among the academicians and urban transport studies have repeatedly reiterated that transport transit-oriented development (TOD) can and is increasing the propensity to use transit. TOD essentially brings housing, jobs, entertainment options, restaurants, groceries closer to the transit stop.But the success of a TOD area is only possible when people are living in TOD areas and more often than not, also their workplaces are in TOD areas. In that case both workplaces and residence are close to transit stops, thereby making transit a dominant mode choice. But what happens when only side of a work-based trip is well connected will people still use transit for work? Does living closer to transit stop (access time), still play a key role in influencing people to use transit even if workplace is further away from transit stop? This study tries to answer this ambiguity by considering multiple combinations of access and egress walking time. By doing so this study aims to specify the importance of access and egress time, both individually and the combined effect on the propensity to use transit.

Free-floating moped sharing systems are becoming more and more popular and provide new ways to travel inside urban areas. The vehicles offer the flexibility of one-way transportation, though the downside is that it creates a spatiotemporal imbalance of the vehicle distribution within the system. The operators of such systems are challenged to cope with this imbalance by either applying an operator-based relocation or user-based relocation strategy. As studies on operator-based relocation strategies are in abundance, this research focused on user-based relocation. A user-based relocation strategy assumes the participation of the user, though (monetary) incentives are required to encourage users to participate in the process of relocating vehicles. This research assessed how vehicle choice is influenced by these price deviations (dynamic pricing) through a context-related stated choice experiment. The dynamic pricing user-based relocation strategy was also tested on a real-life moped sharing system to assess the influence on the system performance. At last, an observed vehicle choice experiment was conducted to evaluate the trade-off by users between discounted vehicles and walking distance. The outcomes presented in this report ought to apply to other vehicle sharing systems with equal design and management configurations.

Participatory Value Evaluation (PVE) is an innovative methodology that supports public policy-making by estimating the societal value of public policies or projects through citizen participation. This thesis studies the decision-making processes applied by participants using a case study of infrastructure projects within the municipality of Delft. The study tests the perfect rationality and utility maximisation assumptions underlying the choice modelling methodology for the project portfolio-construction task of PVE surveys.

For decades researchers deliberated and continue to debate on how to support and assist humans in decision-making. This resulted in the development of Intelligent Decisions Support Systems (IDSSs). An IDSS is an application of artificial intelligence (AI) that desires to enhance and support decision making by enabling tasks to be performed by a computer while mimicking human capabilities. The two most generally classified types of IDSSs are knowledge-based and non-knowledge based systems. A knowledge-based system, also called an Expert system, directly translates domain knowledge into a set of rules or cases to support human decisions. In contrast, non-knowledge based IDSSs apply the rapidly growing branch of AI known as machine learning (ML), that grounds its decision-support on feature extraction of labelled training data. Recently, a company called Councyl, in collaboration with the TU Delft, developed a new approach to AI that has the potential to constitute a novel type of IDSS for judgement purposes. The new approach to AI is called BAIT (Behavioural artificial intelligence technology). BAIT utilises discrete choice modelling (DCM) to codify the domain expertise of experts’ in order to provide introspection on their decisions and support future judgments.
As BAIT is a new IDDS approach it requires testing in different settings to gain insight into the usefulness and effectiveness of this new method.

Limiting climate change forces us to switch to a more sustainable mobility. Travelling by train is more sustainable. Night trains might be a solution, they over several advantages such as a higher comfort level and can travel long-distances during the night. However, there currently is no knowledge about the Willingness to Use night trains. This study is the first into this Willingness to Use night trains, as an alternative for flying, for long-distance European travel. To do so, this paper makes use of two Stated-Preference experiments. A comfort rating experiment, in which the comfort rating is the dependent variable. In this experiment, it is explored to which extent night train characteristics influence the ’perceived comfort’ rating. In the mode choice experiment, it is in turn investigated how this comfort rating is traded-off against more traditional mode choice attributes such as trip time and trip costs. The study presents the results of linear regression and a Panel Mixed Logit model, estimated on 804 collected responses in the Netherlands. The results of both models are combined to derive Willingness-to-Pay values for an improvement in one of the comfort attributes, given an initial comfort level. Furthermore, several segments were identified using a latent class choice model. At last, the Willingness to Use the night train is explored for several scenarios. It is shown that when the night train is introduced as-is, it is predicted to have a market share of about 60%. Positioning the night train as a low-cost competitor results in a significant drop in market share.

The aim of this thesis was to find the preferences of bus users in rural areas of the Netherlands for alternative public transport. Two alternatives for bus were proposed: a demand responsive transport service and a multi-modal alternative that combined express bus with bike-sharing services for last mile transport. A stated choice survey was conducted to find the preferences of bus users between bus, DRT and the multi-modal alternative.

This study aims to explore the preferences of citizens regarding fairness considerations related to the distribution of the effects of road safety policies in order to provide with policy recommendations that will help to promote more fair road safety policies. To achieve this aim the Discrete Choice Approach is going to be followed, using stated preference data. This requires a Stated Preference experiment to be conducted, which consists of two distinct parts. The first part is related to the citizen’s perception of fairness of different types of distribution of the effects of road safety policies, while the second one is related with the importance of this perceived fairness in the preference of citizens over specific road safety policy alternatives. In the first case, two Linear Regression models have been estimated, while for the second case, three Discrete Choice models. This study has shown that the Discrete Choice Approach can actually give some insight to moral dilemmas as it is suggested in literature. It also showed that low public acceptance can be a show-stopper for road safety policies, thus looking only at the aggregate effects of a road safety policy can be often misleading. The way that the effects of road safety policies are distributed among different groups of people can have a significant influence on the public acceptance of road safety policies.

Rail vehicle valuation is traditionally performed by taking the book value of a vehicle, complemented with a deviation factor for technical characteristics and condition based on the experience of an appraiser. This process is costly and time-consuming for large and/or spread-out fleets and creates financial risks for all parties involved in the transaction through under- or overpricing. To develop more automated and digital approaches to enable more rapid and in-depth economic and financial analysis, insight is needed in the relationship between vehicle value and its determinants. This research aims to identify the main determinants of rolling stock value, and describes – in both economic and statistical terms – the dependence of value on these factors where possible. It reveals that the traditional linear approach to vehicle appraissal does not capture the non-linear effects found between various determinants and vehicle value for both locomotives and freight wagons.

The development of automated vehicles offers advantages for the transportation systems of the future. As a result, new and unknown challenges within the field of transportation arise. Moreover, there are uncertainties within the behavioural responses of travellers and amongst other things, the changes in the modal split within the transportation market. There is a lack of extensive knowledge of public transport user preferences regarding automated vehicles. In this study, the relative preferences for a trip with a self-driving bus were compared to a trip with a regular bus. To establish this, a stated preference experiment was conducted. Based on the responses of 282 respondents, a mixed logit model including latent variables was estimated. Based on the estimation results, it can be concluded that public transport users currently show a lower preference for the self-driving bus than for the regular bus. Moreover, travellers’ preferences to travel on the autonomous bus improve when no surveillance is present. Travellers with an increased level of trust are found to perceive more utility of a self-driving bus. This effect is stronger for women, which could explain the outcome that women are less likely to travel by autonomous bus than men. These relative preferences result in the self-driving bus being a competitive alternative for short urban trips, which allow for the increase of the travel costs for the self-driving bus compared to the travel costs for the regular bus. At last, the estimation and application outcomes of this study provide an increased understanding of the stated preferences of public transport users for self-driving vehicles operated as public transport services for urban trips.

Innovating the last mile of parcel and meal delivery Logistic service providers are looking for ways to innovate their delivery process in order to optimize their operations, lower operational cost, and to be able to meet growing consumer demands in terms of convenience, predictability, accuracy and flexibility in delivery time and place. Ordering products, produce and meals online, to be delivered at your door, is becoming increasingly common. This leads to an increase in demand for home deliveries. From the operational cost perspective of logistic service providers (LSP), the so called last mile of the delivery is very expensive. The last mile is the very last part of the journey. For parcel delivery, this is typically the trip from the LSP’s distribution centre to the consumer home. LSP’s are contracted to deliver parcels to the consumer. Therefore, retailers are in fact the customer from a LSP’s perspective. Improving cost and quality of delivery services is important for LSP’s for two reasons. Firstly, to lower operational cost in order to improve their market position. Secondly, to leverage a better consumer experience to the retailers. There are innovations – often involving aspects of automation – which may optimize this last mile, therewith potentially reducing the operational cost of delivery and enhancing flexibility and quality for the consumers, in theory making them interesting investments. This research focusses on the consumer side of this topic, and looks into their preferences by means of discrete choice modelling in order to determine the consumer value of these innovations. Preferences can be specific to a type of commodity. For example, different trade-offs may be made when ordering a book rather than ordering a pizza. To capture these differences to a certain extent, this research takes into consideration parcel delivery and meal delivery.

The combination of cycling and public transport (PT) use has been found to be very successful in the Netherlands. On average, 47% of daily train users cycle to a railway station and this number is expected to grow to until at least 2030. As a result, railway stations suffer from bicycle parking capacity shortages. Large investments are needed to meet the growing demand for bicycle parking capacity, while the expansions take up the limited space around railway stations. To address the ever-growing demand for bicycle parking capacity and to continue the success of the combined use of bicycle and PT, alternative solutions beyond building new bicycle parking facilities are needed.
Bicycle sharing is a promising strategy to tackle bicycle parking capacity shortages at railway stations as it could significantly reduce the number of parked bicycles. A fundamental prerequisite is that a bicycle sharing system (BSS) makes use of the already parked bicycles, which is not the case with the available PT-bicycle system in the Netherlands. Existing literature shows that bicycle sharing between current cyclists has the potential, in theory, to reduce the number of parked bicycles by 22-25% at the central railway stations of the four largest cities in the Netherlands. When bicycles are also shared with travellers currently using other modes 37-50% capacity savings could be achieved. Currently there is a lack of knowledge about bicycle sharing from a user’s perspective to make a more realistic estimation of the expected potential. The important factors in bicycle sharing among potential users need to be clarified in order to estimate the potential demand and to progress towards the design of the organisation of an efficient system. Therefore the objective of this study is to investigate the preferences of current bicycle-train users and the demand for bicycle sharing in order to design an efficient bicycle sharing system (BSS).