Abstract
Continuous household travel surveys have been identified as a potential replacement for traditional one-off cross-sectional surveys. Many regions around the world have either replaced their traditional cross-sectional survey with its continuous counterpart, or are weighing the option of doing so. The main claimed advantage of continuous surveys is the availability of data over a continuous spectrum of time, thus allowing for the investigation of the temporal variation in trip behavior. The objective of this paper is to put this claim to the test: Can continuous household travel surveys capture the temporal variation in trip behavior? This claim can be put to the test by estimating mixed effects models on the individual, household, spatial and modal level using date stemming from the Montreal Continuous Survey (2009–2012). A mixed effects model (also know as a hierarchical or multilevel model) respects the hierarchical design of a household survey by nesting or crossing entities where necessary. The use of a mixed effects econometric framework allows for partitioning the variance of the dependent variable to a set of grouping factors, strengthening the understanding of the underlying causes of variation in travel behavior. The findings of the paper conclude that the temporal variability in trip behavior is only observed when modelling on the regional level. Further, the study suggests that a large proportion of the variance of trip behavior is attributed to different grouping factors, such as region or municipal sector for regional trip behavior models.
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Notes
A mixed effect model is also known in literature as a multilevel model, hierarchical linear model, and random intercept/coefficient model (Rabe-Hesketh and Skrondal 2012).
The fixed effects factor was removed from subsequent notation as the focus is more on the correct representation of the random effects.
The model was re-estimated while eliminating the hhsize variable. All parameter estimates were more or less identical. A likelihood ratio test was conducted to determine whether the model is better off without hhsize. Nevertheless, the null hypothesis could not be rejected and it was decided to keep the variable.
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Acknowledgements
The study was partially funded by an NSERC Discovery grant. The authors would like to thank the AMT (Metropolitan Transportation Agency) for providing access to the data (continuous survey) for research purposes, as well as to Hubert Verreault (Polytechnique Montreal) for his contributions in data processing. An earlier version of the paper was presented at the 2017 International Conference on Travel Survey Methods in Montreal, Canada, and the paper has benefited from the comments and suggestions of the conference attendees.
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El-Assi, W., Morency, C., Miller, E.J. et al. Investigating the capacity of continuous household travel surveys in capturing the temporal rhythms of travel demand. Transportation 47, 1787–1808 (2020). https://doi.org/10.1007/s11116-019-09981-x
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DOI: https://doi.org/10.1007/s11116-019-09981-x