The Dutch Ministry of Infrastructure and Water Management is committed to enhancing the accessibility and sustainability of the Dutch mobility system. Working from home (WFH) has been discussed as a policy lever to decrease commute travel and, thereby, congestion for decades. During the COVID-19 pandemic, this discussion regained momentum. WFH was a key factor for the decrease in commute travel by public transport and car in the Netherlands, which decreased congestion. Against this background, the Ministry wants to stimulate WFH post-pandemic to retain some of the sustainability and accessibility benefits identified during the pandemic. WFH can enhance the accessibility of the mobility system thanks to reduced commute trips during peak hours.
Although the stimulation of WFH may be a policy lever to increase the accessibility of the mobility system, the full effect of WFH on overall personal mobility is unknown. Studying pre-, during and post-COVID-19 measures data, this study assesses the impact of a change in WFH on activity-travel patterns. Commute travel, non-work travel, and mode use together define activity-travel patterns in this research. The main research question is as follows: How did changes in WFH influence activity-travel patterns during the pandemic in the Netherlands? To answer this question, data from the Netherlands Mobility Panel (MPN), collected between 2019-2022 is used. Latent class analysis is used to identify seven distinct activity-travel patterns. Next, two latent transition models are estimated. The first model, for 2019-2021, studies the effect of an increase in WFH on transitions in activity-travel patterns. The second model, for 2021-2022, studies the effect of a decrease in WFH on transitions in activity-travel patterns.

The application of LTA, a longitudinal clustering method, sheds light on complex transition behaviour in the population during- and post-COVID-19 measures. The results show that activity-travel patterns before a change in WFH and the level of an increase in WFH matter for the impact of WFH on transitions. Depending on the initial class membership, differences in transitions emerged. To a certain extent, all effects of WFH on travel, substitution, complementarity, modification, and neutrality exist in the population, but these depend on initial class membership. The results for an increase in WFH are significant, while results for a decrease are not. For the time being, these findings do not exclude the existence of structural changes in working and travel behaviour. Significant effects on transitions appear for a small and a large increase in WFH. After an increase in WFH, most classes are more prone to take up another activity-travel pattern. In both cases, most classes have an increased probability of transitioning towards the low mobility class, which underpins more sustainable patterns. Nonetheless, more diverse results appear for a small increase in WFH, and significant transitions towards other car profiles appear. Analysing the impact of a small increase on class sizes confirms this. Overall, the car class sizes remain relatively high after a small increase in WFH. Thus, an increase by 1-3 days working from home may not lead to more sustainable activity-travel patterns in terms of trip rates per purpose and mode. Nevertheless, it needs to be kept in mind that this study only analysed trip rates per purpose and mode, a small increase in WFH may still lead to a peak-travel reduction, which benefits accessibility. Further analyses should investigate peak-travel to conclude on the accessibility benefits of small increases in WFH. At the same time, governments and employers should take measures to counter-act low mobility associated with WFH which is detrimental for physical health.