This study explores how changes in infographic design, specifically branding, sourcing, and message framing, affect individuals’ intentions to change their sport supplementation behavior. With the increasing prevalence of dietary supplement use among adolescents and young adults, there is a growing concern about lower nutritional literacy and the associated health risks. Public health bodies, such as the Dutch Food and Consumer Product Safety Authority (NVWA), face the dual challenge of making scientifically accurate information both accessible and engaging, particularly in a digital media environment that favors shorter content and visual appeal...

Urban congestion and sustainability goals have prompted hospitals to explore strategies for reducing car dependency among employees. This study investigates which factors influence the likelihood of a modal shift toward cycling alternatives, in the context of a hospital facing significant traffic issues. To explore employee preferences, a Discrete Choice Experiment was conducted among hospital staff. The results reveal substantial heterogeneity in preferences, with delay emerging as a particularly influential factor in mode choice. Aside from delay, weather also showed a significant impact, with good weather increasing the likelihood of choosing a bicycle, and bad weather increasing the likelihood of choosing car or public transport. While current commuting patterns are relatively fixed for some, many respondents showed openness to switching to cycling, especially when practical barriers are addressed. Open-ended responses further showed that employees proposed concrete interventions, such as shared e-bikes and a different travel allowance stricture. These findings offer valuable input for developing targeted mobility policies aligned with both institutional sustainability objectives and employee needs.

This research examined the preferences and psychological barriers of Dutch households toward Home Energy Management Systems (HEMS) for charging electric vehicles (EVs) at home. Balancing electricity demand is increasingly critical due to growing grid congestion caused by the rapid adoption of EVs. Smart technologies like HEMS can shift EV charging to off-peak hours, easing grid strain and supporting renewable energy integration. Yet, despite technological readiness, adoption remains limited. Previous studies have largely examined either technical potentials or general behavioral barriers, leaving a gap in understanding specific user perceptions, especially the concept of ”hassle.” In this research, hassle is defined as the perceived effort, inconvenience, and cognitive load associated with managing energy behaviors without technical support.
The main research goal was to assess how different HEMS functionalities either reduce or potentially
introduce new forms of hassle in the context of manually shifting EV charging behavior. To achieve this, a Discrete Choice Experiment (DCE) was conducted alongside a comprehensive survey that included open-ended responses and statements evaluating psychological factors.
The DCE presented respondents with three distinct HEMS functionalities: basic in-home smart energy coordination, smart charging aligned with dynamic electricity prices, and grid balancing coordinated with external signals. Each functionality was evaluated at different price points and monthly subscription fees to measure willingness to adopt under varying conditions.
Findings revealed that households currently shifting EV charging manually reported moderate levels
of hassle, primarily due to cognitive effort, managing apps, and planning conflicts. Interestingly, all
three HEMS functionalities were expected to increase hassle rather than alleviate it. Grid balancing
was perceived as particularly burdensome due to significant concerns about losing control and unclear personal benefits. Key psychological factors identified included cost savings, environmental impact, comfort, privacy, and control. Cost savings and environmental benefits emerged as strong motivators, especially among younger respondents and those already engaged with smart home technologies. Comfort, defined as maintaining existing routines and minimizing active engagement, was highly valued and represented a significant barrier when compromised. Privacy and control were less prominent overall, though loss of control was frequently mentioned in qualitative responses, suggesting its importance should not be underestimated.
The DCE revealed that users were most likely to adopt HEMS profiles that matched their comfort
preferences and budget constraints. While functionalities like smart energy use and dynamic tariffs
were well-received overall, grid balancing showed more mixed responses. Adoption of this function was significantly lower among users who highly valued comfort, reflecting concerns about loss of control and flexibility. This suggests that preferences are not solely shaped by system complexity, but by how different features interact with personal routines and expectations.
These insights offer valuable guidance for policymakers and developers. To support broader HEMS
adoption, it is not enough to offer financial incentives alone, the systems also need to fit smoothly
into people’s daily lives. That means designing HEMS in a way that limits hassle and respects users’
routines and need for control. When technical features align with what people find comfortable and manageable, the chances of adoption increase. This can help make flexible energy use more common and support the energy transition in the Netherlands.

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.