Investigating the capacity of continuous household travel surveys in capturing the temporal rhythms of travel demand

Wafic El-Assi (), Catherine Morency, Eric J. Miller and Khandker Nurul Habib
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Wafic El-Assi: University of Toronto
Catherine Morency: Polytechnique de Montréal
Eric J. Miller: University of Toronto

Transportation, 2020, vol. 47, issue 4, No 9, 1787-1808

Abstract: 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.

Keywords: Continuous surveys; Mixed effects model; Variance partition coefficient analysis (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11116-019-09981-x

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