According to the BREVER-law, humans maintain a consistent travel time budget, adjusting their behaviour to fit this intrinsic limit. This suggests that while travel speeds have increased, total travel time remains constant, allowing people to cover longer distances without reducing time spent travelling. This theory also implies uniformity in travel time across geographies, though its validity is contested, particularly when considering finer spatial scales.

In the Netherlands, despite recent decentralisation of infrastructure spending, investments have predominantly favoured the Randstad region. However, the current Dutch administration’s coalition agreement suggests a shift towards improving rural accessibility, motivated by reports indicating significant differences in accessibility between urban and rural areas. This raises the question: do these accessibility differences translate into measurable variations in travel time expenditures across the country? Understanding this could inform whether infrastructure investments in rural areas are the most effective use of resources.

Research into travel behaviour is well-established, yet intra-country patterns in travel time expenditures remain underexplored. Most studies focus on inter-city comparisons or urban-rural divides, often overlooking more granular spatial analyses. Additionally, much of the existing research in the Netherlands relies on outdated data. This study seeks to update and deepen understanding of spatial patterns in travel time expenditures across the Netherlands, addressing the research question:

Using recent national travel survey (ODiN) data from 2018 and 2019, involving 104,818 individuals, this research examines municipal-level travel time expenditures. Spatial autocorrelation analysis reveals weak to moderate, but significant spatial coherence in travel time expenditures across the country, challenging the notion of spatially uniform travel times. High travel time expenditures are concentrated in parts of the Randstad and North Holland, while lower expenditures are found near the country’s borders. These regions of high expenditure tend to house more young adults, fewer car owners, and higher-income, highly educated individuals, while no clear differences in built environment stood out.

Further analysis using spatial and non-spatial regression models highlights the importance of socio-demographic factors over built environment variables in explaining travel time expenditures. High income and education levels are associated with higher travel times, suggesting that these factors overshadow the influence of the built environment. Additionally, a notable ‘border effect’ emerges, where municipalities near borders exhibit lower travel time expenditures, potentially due to a psychological barrier limiting cross-border travel.

The findings call into question the rationale for infrastructure investments aimed at improving rural accessibility, especially given the high travel time expenditures in the well-connected Randstad. The research suggests that targeting specific population groups, rather than regions, might be more effective in achieving mobility goals. 

This study updates the understanding of travel time expenditures in the Netherlands, emphasising the dominant role of socio-demographic factors. Future research should explore individual travel preferences and experiences, conduct more detailed analyses at finer spatial scales, and investigate the observed border effect to inform more effective infrastructure and mobility policies.