Dynamics in travel behaviour: who changes mode, why and when? A longitudinal analysis of mode choice behaviour in the Netherlands
Due to burgeoning economy, by 2022 traffic congestion is expected to have increased by 9 percent and travel delays by 28 percent, as compared to 2016 levels. Increasing congestion and travel delays are not solved solely by expansion of the road network. In the next years, policy measures should continue to stimulate the shift towards more sustainable modes of transport, for example public transport, cycling and walking.
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Our knowledge of changes in behaviour, such as changes in mode choice, is mostly based on data at aggregated level. This is not enough for a proper understanding of the dynamics in travel behaviour and changes in behaviour needed to reverse the worrying long-term trends of congestion, increasing oil consumption and greenhouse gas (GHG) emissions. In the development and implementation of policies and measures to facilitate the abovementioned mode shifts, it is important to understand changes at individual level over time.
In this presentation, we will show the results of an analysis of day-to-day variation in individual mode choice behaviour based on the multi-day trip diary of the MPN. This intrapersonal variation in mode use cannot be captured by one day travel surveys. Also, the repeated nature of the MPN-data allows to distinguish individuals over time who change their mode use behaviour from those who not. Who changes mode, why and when? To answer this question, the impact of different types of determinants, and changes in these influencing factors, on mode use behaviour will be examined. Different panel models that account for repeated response measures will be estimated to explore patterns in changes in mode choice. This is an important issue in panel data analysis, since repeated measures of the same individual will likely display similar, correlated values on several variables, in particular mode choice. This study aims to determine variation in mode use behaviour of individuals, and how individual characteristics and other travel related factors affect mode use behaviour over time. With this knowledge, policy makers could design more effective policy measures to stimulate the use of more sustainable transport modes.
Marie-José Olde Kalte: University of Twente & Goudappel Coffeng