Hamed Eftekhar

Effect of Traveler’s Nationality on Daily Travel Time Expenditure Using Zero-Inflated Negative Binomial Regression Models: Results from Belgian National Household Travel Survey

In this study, data stemming from the 2010 Belgian National Household Travel Survey were used to assess the effect of a traveler’s nationality on daily travel time expenditure. Negative binomial (zero-inflated) models were estimated to isolate the effect of nationality after other contributing factors such as sociodemographics, residential characteristics, transport options, and temporal characteristics were controlled for. The results indicate that even if one controls for a series of other influencing factors, nationality plays a significant role in differences in travel time expenditure. This finding is especially relevant in the development of policy packages that are targeted at social inequalities. From a methodological perspective, methodological options—two weighting schemes and two bootstrap solutions—were presented to provide sufficient support for the conclusions. To generalize the results in further studies, an oversampling of travelers of different nationalities is strongly recommended. Future research should focus more on the underlying psychological constructs of why ethnic and cultural differences persist even if one accounts for other determinants.

Investigating scalability in population synthesis: a comparative approach

ABSTRACT In this paper, we investigate the influence of scalability on the accuracy of different synthetic populations using both fitting and generation-based approaches. Most activity-based models need a base-year synthetic population of agents with various attributes. However, when several attributes need to be synthesized, the accuracy of the synthetic population may decrease due to the mixed effects of scalability and dimensionality. We analyze two population synthesis methods for different levels of scalability, i.e. two to five attributes and different sample sizes – 10%, 25% and 50%. Results reveal that the simulation-based approach is more stable than Iterative Proportional Fitting (IPF) when the number of attributes increases. However, IPF is less sensitive to changes in sample size when compared to the simulation-based approach. We also demonstrate the importance of choosing the appropriate metric to validate the synthetic populations as the trends in terms of RMSE/MAE are different from those of SRMSE.