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.

In order to stop climate change, it is inevitable to transition to more environmental-friendly ways of transportation, such as cycling. An important criterion for selecting the bicycle as a modality is the distance to the destination. An increase in travel distance coincides with a decrease in modal share of bicycles compared to alternative modalities. Literature does not explain why cycling is preferred for certain distances and not for others, except for some practical reasons. This thesis investigates the built environment in relation to cycling distance. Literature indicates the built environment as being important for destination choice, mode choice and route choice. Moreover, literature also indicates a relationship between cycling distance and these decision choices. As urbanization of the built environment increases, more destinations are within reach and this tends to reduce travel distance. At the same time, network friction reduces due to increasing network density. Finally, preferences to cycle through or avoid certain characteristics of the built environment may result in detours, which increase travel distance. People’s decisions on travel destination, transportation mode and route appear to be crucial for choosing the bicycle as mode of transport. Humans make these decisions simultaneously, but in this thesis, it is assumed that it is done in the order: destination, mode, and route. By making this assumption, it is possible to say that (a) destination choice is connected to Euclidean distance, (b) mode choice is connected to network friction, and (c) route choice is connected to behavioural detour. The 7D’s framework of Ewing & Cevero (2010) has been used to quantify the built environment. It will turn out that only the first three D’s (Design, Density and Diversity) are influencing cycling distance. The choices for destination, mode and route choice are also influenced by the following elements: network density, cycle paths, green environments, smooth surface, built environment density and the mixture of functions in the built environment. This research has been conducted with bicycle trip data within the municipalities of Amsterdam, Amstelveen, Diemen and Ouder-Amstel. Those municipalities offer a fitting case study, since the ‘Greater Amsterdam’ has a varied built environment and has a need to reduce car traffic significantly. In this thesis, the relation of the elements with cycling distance are statistically tested with a multiple linear regression analysis. In order to do so, elements have to been quantified and combined with the bicycle trips. Explanatory models are developed to explain cycling distance, Euclidean distance, and detour distance with the elements of the built environment. The models constructed in this thesis show that the elements green environments, waterbodies, smooth surface material, and cycle paths have a positive increasing impact on cycling distance, while network density and built environment have a negative decreasing impact. No clear impact on travel distance is found for the element mixture of functions. This thesis also show that the built environment is more important for determining the Euclidean distance than its importance detour distance. The results from this thesis confirm the relationship between built environment and cycling distance. To be specific, the results show that the built environment density is most important for Euclidean distance and therefore destination choice. Green environments and waterbodies are incentive elements of the built environment to overcome the distance added by the network friction. The two elements can also affect the cycling distance due to the choice of behavioural detour. This shows that bicycle use for longer distances can be stimulated by adding more green and potential waterbodies in the built environment.

This research aims at analyzing route choice behavior of E-bikers, in terms of which factors play a role and to what extent. The research is performed based on E-bikers route data in Ghent. Two interesting developments are aimed to include as well, in terms of multi-attribute cost functions as input for route generation and including land use attributes to cyclist’s route choice models.