Determinants and barriers of walking, cycling and using Personal e-Transporters: a survey in nine European cities

Deliverable D1.1.2 of ISAAC - Stimulating safe walking and cycling within a multimodal transport environment


De Ceunynck, T.; Wijlhuizen, G.J.; Fyhri, A.; Gerike, R.; Köhler, D.; Ciccone, A.; Dijkstra, A.; Commandeur, J.; Dupont, E.; Cools, M.



This report describes the results of an extensive online survey that has been conducted to collect empirical data on the psychological determinants and barriers of a travel mode shift in favour of active transport modes. The modes that have been focused on are walking, cycling and the use of Personal e-Transporters (PeTs) (e.g. electric scooter, monowheel, Segway,…). The survey was conducted in nine cities spread over the four countries of the consortium partners involved in the ISAAC-project: Tilburg and Groningen (The Netherlands), Ghent and Liège (Belgium), Trondheim and Bergen (Norway), and Dortmund, Düsseldorf and Berlin (Germany). A representative sample (in terms of age and gender) of 250 respondents per city was interviewed. The aim is to better understand people’s travel mode choices, and to investigate how the use of more sustainable active transport modes can be increased.

A factor and cluster analysis was conducted to identify coherent groups of participants that are similar to each other regarding psychological determinants of travel mode choice, but different from participants in other groups. Two clusters of participants with similar psychological determinants of travel mode choice were identified. The difference between both clusters was mostly explained by cycling related factors. As a result, a clear ‘pro-cycling’ cluster was identified (55.6% of participants in the sample), consisting of people with more favourable cycling-related factors, and a ‘non-pro-cycling’ cluster of people with less favourable cycling-related factors. This suggests that the psychological determinants of cycling have a higher level of variation compared to the psychological determinants of walking. In other words, respondents’ answers related to cycling are more diverse than answers related to walking, or alternatively, people’s feelings related to cycling are more ‘pronounced’ than those related to walking.

Significant differences in respondents’ characteristics are identified between both clusters. Higher shares of respondents from Groningen, Tilburg, Ghent and Düsseldorf are found in the pro-cycling cluster, while this cluster contains a lower fraction of respondents from Bergen, Liège and Trondheim. In addition, the pro-cycling cluster contains more young people (aged 18-34), more men and higher-educated, and more people living with a partner and children. They possess a higher number of all types of vehicles (including PeTs), except cars. The pro-cycling cluster also contains a higher share of respondents with a season ticket for public transportation and to a car or bike sharing system. The pro-cycling cluster contains fewer people who have difficulties to park a bicycle at home. Respondents in the pro-cycling cluster logically cycle significantly more often, but they also show higher rates of walking, riding a moped or motorbike, taking a taxi and using a PeT.

The analyses confirm that the classic components of the Theory of Planned Behaviour, supplemented by habit, provide the best fit for the behavioural model of cycling and walking. People’s intentions to walk/cycle for their everyday trips are most strongly affected by their attitudes related to these modes, and to a lesser extent by norms and perceived behavioural control.

The biggest obstacle indicated by all respondents combined that hinders them from cycling more frequently, is traffic safety. The second biggest obstacle is time, followed by the required physical effort and the environment (climate, hilliness,…). Cost is considered the least important obstacle. Significant differences between cities are observed. Traffic safety is considered a stronger barrier in the Belgian cities (mostly Liège) and in the German cities compared to the Dutch and Norwegian cities. From the cluster analysis it becomes clear that traffic safety is considered to be a significantly more important obstacle for respondents in the non-pro-cycling cluster. Improving traffic safety will therefore be a key element in realising a modal shift towards more cycling, especially for people who currently do not cycle much yet. The required physical effort and the environment (climate, hilliness,…) are also considered significantly more important obstacles by the non-pro-cycling cluster, but the difference between both clusters is smaller than for the traffic safety. Cost on the other hand is a relatively more important obstacle for the respondents in the pro-cycling cluster.

The biggest obstacle hindering more frequent walking is time. Physical effort, environment and traffic safety receive an approximately equal weight. The pro-cycling group (that walks significantly more than the other group) considers time a significantly more important obstacle for walking more frequently than the other group. There are no significant differences between both groups in terms of the importance of physical effort, environment and traffic safety as obstacles for walking more frequently.

Generally, respondents’ perceptions of PeTs are not (yet) very favourable. Respondents’ perceptions related to cost and safety received the lowest scores. Significant differences between the cities can be observed. The most favourable perceptions are reported in the German cities, especially in Dortmund. The least favourable perceptions are reported in the Norwegian cities Bergen and Trondheim. The current frequency of use of PeTs is highest in Groningen and in the German cities, where around 10% of participants indicates an occasional/frequent usage of PeTs (at least on a monthly basis, or more often).

The stage model shows that respondents’ stage of behavioural change towards using PeTs more frequently is affected by various aspects. Some noteworthy findings are the following. Respondents with higher cycling norms are more likely to be in the higher stages of behavioural change. Respondents who walk more often are more likely to be in the higher stages as well, but respondents with more favourable walking attitudes have a lower probability. Stronger transport mode habits are related to a lower chance of being in the higher stages. Respondents who indicate stronger cycling obstacles have a higher probability of being in the contemplation stage of using PeTs. Respondents with a subscription to a bike sharing service have a lower probability of being in the higher stages of behavioural change.

The findings in this report highlight the intrinsically different nature of walking and cycling as transport modes, with different factors and perceived obstacles affecting their usage. As a result, stimulating these modes will require a different approach. While this may seem like a trivial conclusion, it is not uncommon in research as well as policy and practice to treat ‘active modes’ as being a coherent way of transportation with similar features.

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