The Value of Travel Time (VTT) is perhaps the most important number in Cost Benefit Analysis as the travel time savings are often the largest benefit. The VTT is often derived from discrete choice experiments (DCEs), where respondents trade off time, money, and other attributes. However, respondents who are reimbursed for their travel costs might approach these trade-offs differently since they usually don’t bear the full cost of travel. This raises the research question: To what extent does travel cost reimbursement (TCR) affect the value of travel time?

We investigate the impact of TCR on the VTT using datasets from the Netherlands (NL2022) and the United Kingdom (UK2014). We hypothesize that TCR might influence the VTT directly, lead to less consistent choices among respondents, and result in a higher willingness to accept (WTA) among those with TCR compared to those without. Using Multinomial Logit (MNL) and Mixed Logit (ML) models, we analyze the effect of TCR on the VTT, whilst allowing for heteroskedasticity. We also separate TCR interactions into WTA and willingness to pay (WTP) components, while accounting for socio-economic interactions to ensure robust findings across different experimental setups.

Our results show that commuter respondents in the NL2022 dataset with full TCR have a VTT approximately 29% to 45% higher than those without reimbursement. In the UK2014 dataset, the increase is even more pronounced, ranging from 58% to 143%. This effect is significant and consistent in experiments where only time and cost are considered. However, as more attributes are introduced, the difference in VTT becomes insignificant. We found no consistent patterns of scale heterogeneity in the VTT for respondents with and without TCR, leading us to reject the hypothesis that TCR recipients make less consistent choices. Moreover, while the interaction with VTT is more pronounced in the WTA domain than in the WTP domain, the model accounting for this does not outperform a model assuming equal TCR interaction in both domains.

In conclusion, VTT is significantly different for commuters depending on whether they receive travel cost reimbursement. However, these differences cannot be explained by scale heterogeneity or differences in WTA and WTP. We argue that national VTT values should consider travel cost reimbursement, particularly as these values are often based on 2-attribute time-cost experiments.

Recently, the deficiency present in female-specific health has been emphasized.Knowledge and consequently treatments with regards to female-specific symptoms and chronic deceases have been lacking. Previous research has shown the opportunity of female health apps to decrease this discrepancy.
Female health apps simultaneously contribute to women’s health understanding and awareness, while also supplying data for necessary female-specific health research. However, this requires uptake and engagement among consumers. More importantly, it requires uptake among diverse women subgroups of the population. Otherwise, the apps likely contribute to increased health disparities present between different socio-demographic groups and biased female health research.
Therefore, research uncovering the influence of app factors on female health app uptake, while accounting for the diversity in the female population is necessary. The specific female health apps under scrutiny in this research are fertility & menstrual tracking apps (MTA), due to their relative popularity, diverse potential consumer group and importance in women’s lives. Consequently, the following research question is answered in this research to contribute to closing the knowledge gap of MTA preference among diverse women: ’To what extent do various factors influence fertility & menstrual tracking app uptake by women from diverse backgrounds?’

Tourists travelling by airplane contribute significantly to the CO2 emissions. The number of flights covering longer distances is rising and, consequently, implies more energy consumption. This leads to a greater environmental impact compared to flights covering shorter distances. Although people are expected to continue travelling, adjusting the holiday destinations and modes of transport can effectively reduce the environmental footprint of tourism, all while maintaining pleasurable travel experiences. To minimize CO2 emissions by adjusting holiday destinations, destinations closer to home should be chosen. A trade-off seems to appear when selecting a holiday destination, involving a balance between the attractiveness of a specific destination and the different travel-related considerations. More attractive destinations can be reached with increasing distances, yet this also increases travel time and cost which are both preferred to be minimized. So far, research into the value of distance in this trade-off in the context of holiday destination choices is found to be limited. Therefore, this research studies how people value distance, controlling for travel time and travel cost, when choosing the destination for their holiday to gain a more comprehensive understanding of tourism travel behaviour. Since long-distance flights have larger CO2 emissions compared to flying over shorter distances, this study compares distances for holiday destinations that require long-distance flights with flights covering shorter distances. Additionally, these results can lead to interesting insights for policymakers. The main research question examined in this study is:
‘What is the value of physical distance for Dutch tourists in the choice of their summer holiday destination?’

For this study, a stated preference survey was created to collect data for addressing the research question, resulting in a sample of 254 Dutch tourists. To understand if distance holds intrinsic value, once controlling for travel time and for travel cost, and to investigate if the value of distance would change when travel time and cost are considered, two versions of a stated choice experiment are included in the survey. The respondents are randomly assigned to one of the choice experiments, resulting in half of the respondents completing one version while the other half completing the other.

Since people prefer different types of holidays, including all attractiveness attributes in choice sets may lead to many immediate ’no-go’ options. Therefore, the survey started with an additional experiment for all respondents. In this experiment, the respondents rated the attractiveness of different holiday destinations on a 10-point rating scale. A regression model was estimated based on the observed ratings. This gives an indication of the attractiveness of holiday destinations.

To investigate the intrinsic value of distance and if the value of distance changes considering travel time and cost, the results of the two versions of the choice experiments are estimated with a Multinomial Logit model. When comparing the results of both versions it was found that in version Choice experiment presenting all attributes a very small positive value exists, so small that it can be negligible. This suggests that once controlling for travel time and costs, there is no intrinsic value in distance. This was unexpected as it was expected that further distances would have a positive influence on the utility...

As one of the largest innovation hubs in the world, the Brainport Eindhoven region experiences significant economic and population growth. However, with this success comes a challenge: the transportation infrastructure is increasingly strained, with new housing developments and population growth escalating the transport demand. The economic growth includes plans by hightech giant ASML to roughly double its workforce in Veldhoven to 35,000 by 2030, which poses significant consequences for accessibility, environmental quality, and safety unless effective policy measures are implemented...

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.

The growth of e-commerce has increased the demand for last-mile delivery. This increased demand
poses the sector of last-mile delivery with challenges such as traffic congestion, route optimization and environmental concerns. Delivery to a Service Point or a Parcel Locker, self-collection alternatives, have to potential to address these challenges. This research employs a discrete choice experiment to gather insights into consumer preference for regular parcel delivery and to uncover previously unexplored consumer preference for alternative delivery preference in the case of delivery failure. This second aim constitutes the main addition of this study. An online survey was conducted which resulted in 210 valid responses. The results show that in the case of anticipated failed delivery, most consumers prefer delivery to their neighbours or have the parcel left at an agreed place around the house. The distance to a Service Point or Parcel Locker is the most important delivery attribute guiding this decision. However, both now and in the future, demand for the PL as an alternative delivery option in case of delivery failure seems low, with few policy options to increase this demand. Regarding parcel delivery preference at checkout, the price of Home Delivery is most dominant in the trade-off consumers make. In contrast to other studies, the opening hours or the delivery moment do not contribute significantly. To best increase the demand for self-collection alternatives, parcel delivery companies should focus on: shortening the distance to the Parcel Lockers or Service Points, locating Parcel Lockers in commercial buildings as opposed to public spaces, and increasing the awareness of Parcel Lockers and increasing the awareness of the benefits of self-collection in general. However, the results of this study indicate that in order for the PL to become dominant ’at online checkout’, both a price incentive and a shortening of the distance from consumer to PL are necessary, but at significant cost. Further research should aim to investigate the demand for changing delivery options through notifications and the viability of
the last-mile delivery market agreeing on lower prices for self-collection as proposed in scientific literature.

This study examines the relative importance of contract attributes in the context of Vehicle-to-Grid (V2G) contracts by means of a choice experiment. The experiment was conducted with 67 Dutch car drivers, including both EV drivers and non-EV drivers. They were asked to choose between two V2G contracts with different contract attributes and an option “no V2G contract”. The contract attributes had varying levels of remuneration, guaranteed minimum driving range, and required plug-in time during weekdays and weekends. The data collected was analyzed using a Multinomial Logit model (MNL) to estimate the utility function of the V2G contracts and to identify the most important attributes for the respondents. Besides, an estimation could be made on the preference of a V2G contract over no contract at all. The results showed that, surprisingly, the attribute remuneration had a relatively low importance coefficient and did not have a significant impact on the perceived utility of the respondents. On the other hand, it could be proved that consumers perceive different utility during weekdays and weekends, preferring more flexibility in the weekends. Guaranteed minimum driving range resulted to be the most important contract attribute. The results show that there is a relatively high willingness to participate in V2G contract both among EV-drivers as potential future EV-drivers. The results can be used for policymakers and aggregator companies to design more effectively V2G contracts and to promote the adoption of EVs in a more sustainable way enhancing the energy transition. According to this study the V2G system results to be profitable for the aggregator for various scenarios and really promising. Some application possibilities are suggested in this research, and from them could be concluded that there can be achieved satisfaction for all stakeholders involved.

The livestock sector accounts for 14-15% of the global greenhouse gas emissions. Furthermore, the current meat consumption patterns are associated with multiple health risks and are unsustainable in the long term. Therefore, the shift to a more plant-based diet and reduced animal-source intake is desired from a societal perspective. One attempt to fuel this evolution is the new wave of meat alternatives that are designed to successfully replace meat in everyday meals. However, the current market share of meat alternatives in the Netherlands remains around 4.5%. Section 1 demonstrates that in-depth knowledge about the heterogeneity of Dutch consumer preferences regarding meat alternatives is currently lacking. This thesis contributes to identifying the sources of consumer heterogeneity regarding meat alternatives, focusing on both product-related attributes and person-related characteristics. In addition, this thesis explores and proposes strategies for the manufacturers of meat alternatives with the knowledge of consumer heterogeneity in the Netherlands. The main research question defined for this thesis is: What are the consumer profiles of the sub-segments within the potential meat alternative adopter segment, and what trade-offs do those segments make when choosing between meat and meat alternatives? As explained in Section 2, A Latent Class Choice Model (LCCM) is estimated to examine the trade-offs made when choosing between meat alternatives and conventional meat by individuals from the different consumer segments of Dutch society. Sociodemographics and psychographics are included in this model to identify the consumer profiles of these segments. The LCCM is estimated using data derived from an online stated choice experiment. In this experiment, respondents were asked to choose between two vegetarian mince options that varied in Eco-score, Nutri-score, price, taste, texture, appearance and animal-welfare label. These attributes were identified through a literature review presented in Section 3 and validated by means of a focus group. To examine the trade-offs that are made when choosing between conventional mince and vegetarian mince, one base alternative was added to each choice set that represented the average conventional mince. The person-related characteristics were selected based on the literature review of Section 3 and measured using 5-Point Likert-scales. The product-related attributes were combined to present unique alternatives based on an experimental design, as demonstrated in Section 4. The choice situations were designed to be as real as possible by presenting them as online shopping experiences. Filter questions were added to ensure that the sample population consisted of only potential adopters of meat alternatives. In total 260 complete valid responses were collected as demonstrated in Section 5. The psychographics were aggregated into 9 factors through explanatory factor analysis. The 9 resulting factors are pro-meat attitude, foodneophilia, pro-meat-alternative attitude, sustainable behaviour, foodneophobia, health consciousness, environmental concern, pro-animal attitude and preparation skills. By comparing the LCCM estimation with a multinomial logit model that completely ignores consumer heterogeneity as shown in Section 6, there can be concluded that heterogeneity exists in meat alternative preferences. Heterogeneity was best captured by estimating a three-class LCCM. The resulting classes presented in Section 7 are Price Sensitive Consumers, Health and Environment Lovers and Taste Driven Consumers. The Price Sensitive Consumers segment is unique due to the high relative importance of the price and the non-linear relationships of utility with both the Eco-score and the Nutri-score. The individuals from this segment are generally meat avoiders, students and do not have a pro-animal attitude. The preferences of the Health and Environment Lovers segment stand out because of the high importance of the Eco-score and the Nutri-score, and the low importance of taste. Individuals from this segment tend to be meat avoiders or reducers, have a university Master’s or PhD background, have a pro-animal attitude, have high objective knowledge and score low on foodneophobia. The last segment is the Taste Driven Consumers segment, this segment is only sensitive to the taste and appearance of an alternative. This segment consists predominantly of omnivores with lower educational backgrounds, individuals with low objective knowledge, foodneophobic individuals and individuals who disagree with a pro-animal attitude. In Section 8, product alteration strategies and marketing advice is proposed. In addition, a threefold of foreseeable futures are explored with expected market shares, revenues and environmental impact. If the Price Sensitive Consumers segment is chosen as the target segment, it is advised to keep the selling prices low, keep the Nutri-score above C and the Eco-score above D. In addition, it is advised to produce products that qualify for a future animal-welfare label. Marketing experts should focus on tailoring their marketing to reach the student population and aim marketing at improving objective knowledge. When targeting the Health and Environment Lovers, it is advised to optimize both the Eco-score and the Nutri-score. In addition, it is advised to keep the price low. Marketing strategies should aim at highlighting what makes a certain alternative unique as compared to other alternatives. Furthermore, it is advised to frame the alternatives as exciting and new and accentuate the animal-friendly benefits of the product. When deciding on the Taste Driven Consumers segment, it is advised to focus on producing alternatives that taste and look similar to meat. As for marketing strategies, it is advised to take the foodneophobic character of this segment into account and aim at familiarizing the individuals with meat alternatives. To conclude, there are three segments within the Dutch potential adopters of meat alternative segment. All three segments have different preferences when it comes to meat alternatives. Therefore, manufacturers of meat alternatives should decide on which of the three segments they want to target and alter their products and marketing strategies accordingly. Further research recommendations based on the current study are 1) further investigating the influence of psychographic characteristics on consumer heterogeneity regarding meat alternatives, 2) identifying the potential adopters of meat alternatives segment in the Netherlands 3) determining the generalizability of these findings to other meat alternatives and 4) developing detailed marketing strategies based on the finding of this research.

The banking sector is currently dealing with Anti-Money Laundering (AML) issues, with stricter legislation in Know Your Customer (AML) being the instigator. De Nederlandsche Bank is pursuing fully explainable and transparent models with a risk-based approach. Councyl provides such a model: Behavioural Artificial Intelligence Technology (BAIT). This study aims to analyse the current environment BAIT would be implemented, to see if the tool fits the requirements of the banking sector. The inherent features of BAIT, adding to the four functions make it an interesting tool for banks to consider.

The implementation of a bus system is an attractive alternative for decision makers since it has a short lead time and the service can be easily adapted depending on the demand. Due to the flexible nature it allows for the use of fulfilling different magnitudes of demand. Usually bus service provide a lower level quality service, however busses can be configured in such a way that they also provide higher level of service up until a point where they compete with rail systems. In the Netherlands referred to as HOV (“Hoogwaardig Openbaar Vervoer”, high-level public transport). This is a large spectrum with many different configurations. One should still consider the need for a HOV bus service as it comes with extra investment costs compared with the regular bus. Therefore, this research was looking into where there is no difference in valuation between a regular bus line and a higher level of service bus line. Through interviews, analysis of current lines and looking into what decision makers promise as a higher level of service attributes could be defined which could be seen as characteristic for a higher level service bus service. Additionally, the commuters perspective played a important role as most literature mostly considered only the decision makers perspective. A method has been demonstrated which shows how commuter needs can be used as and translated to operational characteristics with which decision makers specify, plan and design current and future higher level of service bus lines. The method includes a MNL model which expresses the valuation of the characteristics attributes of high level bus services which allows for the prediction of the modal split between a bus service and the current commute. This gave insight on which attributes a differently valued between a regular bus and a HOV bus and when a HOV bus service is equally valued as a regular bus service, hence not justifying investments in a higher level service. It was found that in most cases the HOV bus service results in a higher modal split despite of having a lower valuation for most of the characteristic attributes. The commuter seems to have more trust in the reliability promoted by higher level bus services.

Many cities are planning car-reduced neighbourhoods, to provide more housing and stimulate sustainable mobility. Nonetheless, it is important to know what potential residents value, to be able to attract them. This study investigated the preferences of potential residents regarding the accessibility of car-reduced neighbourhoods, available amenities, green and amenities in public space. It revealed that the car is still very important when deciding where to live. Also, other forms of transport are important, especially if one wants to relinquish his car. Nonetheless, this study also shows that car-reduced neighbourhoods are able to attract car-owning residents, especially when a train station is available and cars have access, but with limitations.

The transition towards greener mobility will play a significant role in decarbonizing the economy. Hence, policy makers need tools that allow them to test alternatives towards that goal. This drive has led to the development of increasingly accurate transport models, with the latest generation being activity-based transport demand models. These models, however, are hard to build, as they are very data-intensive and complex, therefore in this research project a methodology is conceived which attempts to use readily available data from the Dutch travel demand survey (ODiN) and open source software such as ActivitySim, originally developed as a package in Python to make activity-based models in the United States.

While a very time-intensive task, the data was able to be processed for use in ActivitySim. The data was mostly complete, but needed to be complemented with data from the \textcite{centraal_bureau_voor_de_statistiek_statline_2019}, and information about members of the household other than the survey respondent, and joint tours, is missing. The data, however, can be processed in a way that can be reapplied in the future, which lowers the barrier to develop a model with Dutch survey data.

Choice is modeled as logit discrete choice models, and the estimation of the parameters required is facilitated by ActivitySim, which has built-in functionality to support it, and with an integrated workflow the model parameters can be estimated with little effort. With this procedure, and choosing workplace and school locations in advance, a good degree of accuracy was achieved, but it was shown that the sampling method used to deal with the very large choice set introduced significant bias to the model output, as observed in the travel distances, which were shorter in the simulated output than in the observations in the survey data.

While ActivitySim has a sampling methodology to deal with large choice sets, an alternative method, Stratified Importance Sampling with activity spaces, is implemented based on the survey data, from where the sample is determined using the travel distances observed and which produces more accurate outputs when compared to the default sampling.

The result of this research is a framework to easily develop and estimate an activity-based transport demand model that is able to provide insights on the travel demand, and especially on how to influence individual choice behavior, which can facilitate the procurement of quality analysis for decision support in the arena of sustainable mobility, hopefully helping accelerate the mobility transition.

It was concluded that using ODiN data and ActivitySim presented as advantages an easy and replicable formulation, and the availability of data that can be used for sustainable mobility policy analysis; yet, this formulation fails to account for household interactions, something that activity-based models often promise to do, and the documentation provided by ActivitySim while extensive is still inadequate in some regards to understand how to process the data.

The resulting model is, however, highly accurate, despite needing some considerations and improvements. The model needs to sample destination choice alternatives, because otherwise its big size would bring the model to a halt, and it does so using a sampling method that is programmed into ActivitySim. This method was shown to introduce bias to the simulation output even if the choice model was properly estimated, and hence an alternative sampling method based on Stratified Importance Sampling was implemented, and the model output greatly improved as a result. Hence, we conclude that it is possible to obtain highly accurate and efficient activity-based models using available data such as ODiN and open source software such as ActivitySim.

It is argued that a formulation like this can be highly beneficial to the evaluation of sustainable mobility policies, as it lowers the barrier to obtain the accurate and detailed outputs that other models cannot produce, and it provides accurate destination choices that will then inform other submodels that are necessary to evaluate sustainability impact, such as mode choice, travel distance and travel time to evaluate emissions.

We continue by discussing the limitations stemming from the available data and the lack of information for other household members and joint travel, the trend-breaking nature of the COVID-19 pandemic and is impact on mobility in further years, and the possible untested bias of the newly proposed sampling method; and giving recommendations on how to effectively use of a model developed with this framework.

Finally, further research is proposed regarding remote work, the improvement of the choice models, and on the sampling method used.

This paper investigates the kilometer charge and the potential effects of emission-based differentiation, how this policy is supported among Dutch citizens and how it affects different groups. It investigates the behavioural change caused by the new policy using Dutch stated preference discrete choice data. Two stated choice experiments are performed, one exploring the demand for privately used alternative fuel vehicles and one on the modal shift for one-person trips with varying distances. A mixed logit model was applied to determine to what extent specific groups were price-sensitive to the kilometer charge. We find that well-educated,high-income people, who either frequently use their car or own a business car, are more incentivised by the kilometer charge to purchase alternative fuel vehicles. In general, people value purchase prices over the kilometer charge and range. Moreover, it turns out that these groups are willing to purchase a substantially more expensive car in exchange for a lower variable kilometer charge. By applying a multinomial logit model for all distances in the mode choice experiment, we find that the least sensitive group towards the kilometer charge for a modal shift are high-educated, older, commuting car users that live relatively far away from the nearest train station. Furthermore, the larger the travel distance, the higher The value of travel time savings ranges from 4.44 - 14.00 euro for distances including train and car whilst small city trips with bike and car as mode alternatives have a value of 6.86 euro. The found behavioural effects were used to evaluate the impact of constructed scenarios with varying tariffs for the kilometer charge, ultimately showing that an emission-based differentiation can positively affect tax income and emission savings. Besides that, this implementation form is the most supported by the Dutch population. In addition to these substantial insights, this paper makes a contribution by showing how stated preference discrete choice data can enhance the decision-making of such pricing policies.

The aim of this study is to capture heterogeneity in travel behaviour during unplanned train disruptions focusing on the rise of teleworking due to the COVID-19 pandemic to improve train services and help predict passenger flows during disruptions. To perform the analyses, a dataset is elicited from 815 Dutch train commuters by distributing an online questionnaire. A labelled stated choice experiment was designed and a latent class choice model was estimated. The biggest indicators of travel behaviour are the moment of discovering the disruption, the disruption length and job characteristics. Four latent classes were uncovered: the ’Trade-off teleworkers’, ’Sceptic returners’, ’Trusting workplace travellers’ and ’Endless waiters’. Each class has a different initial preference for a travel option and different sensitivities to the travel attributes as well. Individual
characteristics such as age, necessity to arrive at the workplace, ability to telework, telework attitude and the amount of trust in the provided travel information play a role in predicting choice behaviour during unplanned train disruptions. Based on the results advice is given on how the level of service during disruptions can be improved.

Reaching the Paris Climate Agreement goals by 2050 is currently one of the largest societal challenges we are facing. Much is to be gained in the transport of people and goods, which accounts for 25% of the total carbon emissions in Europe. Presently, Air Passenger Transport (APT) hinders carbon emission reductions due to its large environmental impact and evermore growing market share (Van Goeverden et al., 2017). So far, the environmentally friendly high-speed rail only competes with APT up to approximately 600-800 kilometers. Hyperloop as kickstarted in 2015 by Elon Musk has the potential to substitute APT beyond that range, with electric propulsion of magnetically levitating passenger capsules within semi-vacuum tubes. However, research towards Hyperloop’s potential travel demand has remained sparse as of now. Within the financial appraisal of infrastructure projects, forecasted travel demand of the infrastructure is a vital aspect. Namely, ticket revenues and societal value through environmental benefits and travel time savings can result from travel demand. So far, only straightforward analyses have been done to forecast potential Hyperloop demand, using data from previous travel surveys that do not include Hyperloop. Used data does not cater to travellers’ overall (dis)like for Hyperloop, or travellers’ trade-offs including Hyperloop-specific transport mode attributes. Moreover, since potential Hyperloop implementation lies in the future, various future contexts surrounding travel behavior could also influence its competitive potential. To account for these issues, this research estimates future Hyperloop travel demand by conducting a Stated Choice Experiment (SCE) amongst Dutch travellers. Here, future decision-making contexts and travellers’ (dis)like for Hyperloop are included.

Amsterdam Airport Schiphol (AAS) is the third largest airport in Europe in terms of passenger volumes and has been growing rapidly over the past years. This growth is expected to continue in the future (KiM, 2018). Due to the rapid growth in travel demand, AAS reached the maximum allowed number of flight movements of 500.000 per year in 2018 (Schiphol Group, 2018a). According to an Environmental Impact Assessment (EIA) carried out by Schiphol Group (2018), growth to 540.000 flight movements per year in the period of 2020-2023 is possible without violating current restrictions on noise nuisance and emissions. This number of 540.000 flight movements per year also represents the maximum number of flights that can be safely handled at AAS without further expansion and will soon be reached as well1 (Schiphol Group, 2018a). In the case of WLO scenario high, more than a quarter of the passenger demand in 2050 cannot be handled at AAS without violating set restrictions (CPB & PBL, 2015). AAS wants to maintain its leading position in the European transport market and wants to deal with the growing passenger demand, while staying within the set restrictions in terms of the number of flight movements per year. In order to deal with the expected increase in travel demand for long-distance travel in the future, AAS is considering alternative ways of transport and aspires to become the multimodal hub of Europe. To realize this, the focus of AAS is on short-haul flight substitution within Europe by HSR or by innovative modes. The hyperloop, initially introduced by Elon Musk (2013), is one of the innovative modes being considered by AAS and the Dutch Government (Ministery of Infrastructure and Water Management, 2020). Hyperloop consists of pods travelling through a tube, propelled by magnetic levitation, while maintaining a partial vacuum in this tube (Musk, 2013). The literature on hyperloop has focused on the different technical aspects and the technical feasibility of hyperloop (Gkoumas & Christou, 2020a, 2020b), others highlight the energy consumption, and some criticize hyperloop for not being feasible, but nobody has examined to what extent HPT can function as substitute for short-haul flights and which role HPT could play in the future of multi-modal transport. The aim of this study is to design the future transport system of hyperloop passenger transport (HPT) in the transport market with air passenger transport (APT), highspeed rail (HSR) and HPT for longdistance travel within Europe and to assess whether or not the passenger demand in WLO scenario high can be met, including the share of passengers that cannot be dealt with by means of APT alone. The methodology this thesis has used is discrete choice modelling (DCM). Trade-offs and mode choice of passengers when choosing between APT, HSR and HPT are analysed in order to assess the impact of different system designs of HPT on the potential of HSR and HPT in the substitution of short-haul flights at AAS. A stated preference (SP) experiment has been carried out in order to collect choice data. The focus of this study is solely on substitution of flights at AAS with both origin and destination in Europe, i.e. OD-substitution, and examines destinations that are located approximately 500 km from AAS. Substitution of transfer passengers, both within Europe and for intercontinental destinations, is disregarded in this study. The second research objective this study seeks to address is a methodological research objective. The aim is to examine the impact of using images in the presentation of unfamiliar alternatives in the introduction of the SP experiment on preferences, attitude and drop-out of respondents. Based on these two research objectives, the following research questions have been defined 1. How could different design scenarios for hyperloop passenger transport influence traveller’s mode choice between, and the transport demand for, air passenger transport, highspeed rail, and hyperloop passenger transport for the future long-distance transport market within Europe at AAS? 2. What is the impact of the way in which HPT is introduced in the stated preference experiment on preferences, attitude and drop-out of respondents?

The outbreak of the COVID-19 pandemic in 2020 seriously impacted the world. Some previous researches suggest that global incidents could strongly influence the demand for passenger air transport services (Sobieralski, 2020). And the impacts on the demand can be ascribed to the change in the air travel behaviour of travellers (Ito & Lee, 2005). However, the influence of a pandemic on passengers’ air travel behaviour has been rarely studied. This thesis studies the differences in air travel behaviour between the COVID-19 period and the non-pandemic period, in order to benefit the decision-making of policy-makers.In this thesis, it is assumed that the COVID-19 pandemic influences air travel behaviour through changing the air transport context. Three context aspects are found to influence how air travellers behave during the pandemic. Firstly, the policies including travel restrictions and travel recommendations imposed by the government discourage travel motivation. Secondly, the rise in public risk perception triggers their health-protective behaviour which leads to low willingness to fly or changes in travel choice decision-making. The operation adjustments of the airlines in response to the COVID-19 pandemic also influence the offered flight options in the market which could change flight choice behaviour.Two important air travel choice behaviours during the COVID-19 pandemic are further studied, which are the choice between flying and not flying (willingness to fly) and the choice between flight alternatives. Stated choice data is used since it avoids the bias of revealed choice data in studying willingness to fly. Discrete choice modelling is used because of its advantage in studying individual choice.Air travel convenience and airborne health safety are considered important to air travel choice-making during the pandemic. Therefore, they are added as two attributes in the stated choice experiment. The perception of them is scaled by the perception rating experiment using the Hierarchical Information Integration theory. The results show that the perception of air travel convenience is influenced by the requirement of health-related paperwork, such as health statement and virus test result, for travelling and the travel flexibility, such as change and return policy given, by the airlines. The perceived health safety is influenced by the intensity of the virus precautionary measures implemented in the cabin.The results of the stated choice experiment show a considerable change in the attribute trade-off between flight alternatives made by air travellers during the pandemic. Perceived health safety is the foremost factor that air travellers consider. If an intermediate serious pandemic is assumed, air travellers are willing to pay at least 100% more money to improve the virus precautionary measures by 1 level compared to the non-pandemic situation. This percentage difference becomes larger when the safety level Increases to a higher level, which means that air travellers are more willing to take the safest flight during the pandemic. Transfer and flying time are considered as other two important attribute during the pandemic because they indicate the chance of the exposure to the risky environment. Therefore, travellers are willing to pay 87.9 euro during a serious pandemic to reduce 1 transfer, while they would only pay 42.6 euro during the non-pandemic period. Correspondingly, the ticket price of the flight becomes less important in the exchange for a better performance of other attributes.The willingness to fly is significantly deteriorated by the COVID-19 pandemic. In the case of a serious pandemic, the willingness to fly reduces from 83.5% to 37.6% if the flights in the market have a medium attribute performance. Although improving several flight attributes including price, transfer, travel convenience and health safety can pull up the willingness to fly, however, the negative impact of the pandemic is so strong that even the most extreme attribute improvement, ignoring the profitability and sustainability, still cannot totally offset the willingness to fly reduction because of the COVID-19.The following recommendations are given to policy-makers. Firstly, meeting the customers’ expectation of health safety is the best way for airlines to compete during the COVID-19 pandemic. Two methods to do so include providing non-stop flights as much as possible and improving the intensity of virus precautionary measures in the cabin. Reducing the price is still effective in attracting customers, but less than during the non-pandemic period. Secondly, airlines can increase their load factor by improving flight attributes. But the negative impact of the virus cannot be fully compensated. Thirdly, because the willingness to fly is strongly related to the seriousness of the pandemic, the government should never underestimate the rebound of travel motivation in order to avoid the uncontrollability of the pandemic when the situation gets better. Fourthly, as the COVID-19 is unlikely to disappear soon, the low willingness to fly will remain and threaten the survival of airlines. The governments should work out a sustainable financial aid plan with airlines that can also balance the other goals for the society including economic growth and environmental protection.