Shifting towards sustainable mobility is essential to reduce global emissions and alleviate congested transport systems, while the transport sector is responsible for more than a third of all carbon dioxide emissions from end-use sectors. The car has a much larger carbon footprint than alternatives such as the train, cycling, or the bus, and in the Netherlands, more than half of all kilometres driven annually come from business traffic and commuting. Employers therefore have a major role in a shift towards sustainable mobility by stimulating employees to travel less, more efficiently, or differently. But this shift is complicated, while a universal solution to achieve sustainable mobility is lacking. There is no “one-size-fits-all” solution, and research measuring effects after policy implementation remains limited.

This research investigates the relationships between day-to-day changing factors such as weather conditions and seasonality and the commuting behaviour of ASML’s employees. Also, implemented mobility policies are evaluated. Using a two-year dataset capturing daily commuting volumes by car, bike, bus, and office presence, this quantitative case study applies a range of methods to explore day-to-day variability in travel behaviour. These include Ordinary Least Squares (OLS) regression, Multinomial Logistic Regression (MLR), and Time Series Analysis techniques such as decomposition, SARIMAX modelling, and Interrupted Time Series (ITS) analysis.

Findings show that weather has a significant influence on commuting behaviour, particularly cycling. Darkness, which is generally understudied, appears to be one of the prevailing factors, especially as many employees commute during rush hours when darkness is present. The results also reveal that commuters tend to fall back on unsustainable practices when opportunities arise—for example, on Fridays and during school holidays when office attendance is lower, resulting in more available car parking and fewer cycling commuters.

Based on the findings, two categories of policy recommendations are proposed:

The first category involves improving policy assessment. To strengthen data-driven evaluation, it is essential not only to collect but also to validate and verify data. In addition to quantitative analysis, qualitative methods are needed to gather commuter perceptions. Enhanced collaboration across organizations and stakeholders is also vital for better data-sharing and evaluation. Given the high day-to-day variability in commuting, both short-term fluctuations and long-term effects should be considered.

The second category concerns promoting sustainable commuting behaviour. Incentives for travelling during non-peak hours and cycling during dark periods are important. Alongside ‘pull’ measures, ‘push’ strategies discouraging car use should be explored. Though the Netherlands has strong cycling infrastructure, weather and seasonality remain influential, requiring attention to facilities such as better-lit cycle paths, favourable traffic lights for cyclists, and drying services at work, which are part of an inexhaustible list of possibilities.

This research highlights that a mix of policy measures is necessary to achieve a meaningful shift towards sustainable commuting and offers valuable insights for policymakers, researchers, and commuters.