COVID-19 had (and still has) a huge impact on travel behaviour. Most research on the effects of COVID-19 on travel behaviour is based on daily travel behaviour. Long-distance travel is most of the time not included. Therefore, this paper studies the impact of perceived COVID-19 risk on mode-choice for long-distance travel in Europe. This paper uses a Stated-Preference approach which consists of two parts, the perceived risk rating experiment and the main mode choice experiment. In total 1147 responses were collected. In the rating experiment, respondents rated their perceived risk based on eight attributes. In the main choice experiment, respondents chose between train, plane and care based on travel time, travel cost, travel comfort and perceived risk. With this, the Value of Risk (VoR) for a decrease in perceived risk is derived, both expressed in travel cost and travel comfort. Moreover, the Willingness to Pay (WtP) for comfort and Value of Time (VoT) are derived. With the combination of both models, the WtP for risk attributes given a perceived risk level is derived. The combination of both models shows the Willingness to Pay values for the different risk attributes, given a certain perceived risk level. To test the influence of perceived risk on modal split, three routes with real-world values are used. The results implicate a maximum of 5% market share difference possible. This shows that perceived COVID-19 has a moderate effect on modal split.

Following the emergence of new mobility trends, in which shared mobility plays an essential role, Public transport operators face the challenge of reacting in a convenient way to the changes brought to the transportation scene. Even though different collaborations are being put in place between public operators and shared mobility providers, the effects they may have in mode choice are still uncertain, and to the best of the author’s knowledge still to be studied. Accordingly, a stated choice experiment was conducted in the city of Rotterdam, in which preferences towards shared bicycles and shared mopeds were analysed under the assumption of a perfect integration between transit and shared mobility. The results suggest that under said conditions, shared modes have the potential to be interesting egress alternatives for trips by metro, which could imrprove preferences towards the metro. Furthermore, considering choice determinants exhibited during the experiment, it is noticed that egress cost and total travel time are key aspects for traveller’s choices. Finally, young people, respondents that claimed having used shared modes before, and frequent transit users showed a better perception of shared modes.

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.

Over the past decades, car ownership in the Netherlands has been on an increase. Besides being an environmental burden, passenger cars also require a lot of space. Mitigating the impact of passenger cars on climate change and public space requires a shift to a more sustainable view of transport, in which neighborhood mobility hubs might play a role. As a relatively new concept, mobility hubs are starting to gain attention in academia and practice. The first findings, however, showed that the adoption rate of mobility hubs might be low and no good image of the user can be formed yet. This research therefore aims to identify which user groups are likely to adopt mobility offered by neighborhood mobility hubs in the Netherlands. To do this, a conceptual model is based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and subsequently, a survey was distributed in the Netherlands (N=298). After analyzing the data using an Exploratory Factor Analysis, a Latent Class Cluster Analysis was executed in order to find groups in the sample population with similar preferences and socio-economic profiles. By means of the latter, four distinctive groups of travelers are uncovered. Two clusters have intentions to use neighborhood mobility hubs: hub huggers (45%) and hub-ready impacting travelers (25%). The other two clusters, anti-new mobility individuals (22%) and traditional car owners (8%) are not yet ready to use neighborhood mobility hubs. There are some determinants that are likely to play a role in future mobility hub usage: people with prior experience with shared transport and households who do not own a car are more likely to use neighborhood mobility hubs in the future. People who currently use a sustainable travel mode (train or (e-)bike) to reach their work and/or study are more likely to be the adapters of neighborhood mobility hubs. This also holds for people who have a social and environmental responsibility, innovative mindset and clearly see the benefits of using a mobility hub and who are (most often) higher educated and younger of age.

Bike-train usage contributes to more sustainable and also more reliable transport. Nowadays, approximately 45% of the train passengers in the Netherlands access the station by bike. Therewith, the focus of policy makers shifts to the total “door-to-door” travel experience. Bicycle usage is stimulated, and the facilities are adapted accordingly. From a lot of perspectives, this can be seen as a positive trend. Unfortunately, it also has negative consequences in terms of capacity problems in parking facilities and costs. To be able to guide a better service to multimodal travellers, more insights should be gathered regarding their experience and willingness to pay for certain aspects. Most studies focus on the characteristics of bike-train users and their behaviour. In consequence, the quality of the parking facility is considered very limited. The impact of this quality on the user experience is considered even less. For example, the impact of a free of charge parking period is not known. More aspects influencing the users’ experience and behaviour might exist as well. Studies also often focus on one station or one area, which makes it hard to draw general conclusions. Lastly, the relationship between the willingness to pay and the expected subscription price is unknown. By getting a better understanding of the attributes influencing the choice behaviour of facility users, an insight is given into the preferences of passengers concerning bicycle parking. The effects of pricing policies on the user experience and utilisation at various facilities are of great interest to NS (Dutch Railways). For a full overview, there has to be differentiated to types of facilities and types of stations. The following research question is answered during this thesis: What is the willingness to pay of various types of bike parking-users at train stations for different types of facilities and at different types of stations? Literature addresses several attributes which are influential when using the bike-train combination. Attributes can be split into user characteristics, parking facility characteristics and station characteristics. Based on an ongoing data collection effort (Keten Belevings Monitor or KBM), user characteristics of guarded bike parking users can be analysed. It can be found that young people, between 18 and 24 years old, are the main bike-train users, while people over 65 are less present. Furthermore, users are often frequent travellers (at least once a week) and going to work or school. Of all commuters, 90% travels frequently. Social and recreational purposes are performed on a less frequent basis and are in general performed by older people. Based on these characteristics, five traveller profiles can be identified which each consist of at least 5% of the current bike-train users. These can be labelled as commuters to work, students commuting to school, youth travelling for leisure activities and adults with a leisure purpose, divided into medium and low frequent travellers (respectively between 1 and 3 times a month and less than once a month). Distribution of users towards different types of stations can be made as well. Suburban stations tend to be more used by commuters to work. This also results in more frequent travellers at suburban stations. Social and recreational travellers tend to be more attracted to intercity stations. Also, long-term parking occurs more often at intercity stations.