  This study investigates travel behavior determinants based on a multiday
travel survey conducted in the region of Ghent, Belgium. Due to the limited
data reliability of the data sample and the influence of outliers exerted on
classical principal component analysis, robust principal component analysis
(ROBPCA) is employed in order to reveal the explanatory variables responsible
for most of the variability. Interpretation of the results is eased by
utilizing ROSPCA. The application of ROSPCA reveals six distinct principal
components where each is determined by a few variables. Among others, our
results suggest a key role of variable categories such as journey
purpose-related impedance and journey inherent constraints. Surprisingly, the
variables associated with journey timing turn out to be less important.
Finally, our findings reveal the critical role of outliers in travel behavior
analysis. This suggests that a systematic understanding of how outliers
contribute to observed mobility behavior patterns, as derived from travel
surveys, is needed. In this regard, the proposed methods serve for processing
raw data typically used in activity-based modelling.
