Quantifying the Relation between Activity Pattern Complexity and Car Use Using a Partial Least Square Structural Equation Model

François SPRUMONT, Ariane SCHEFFER, Geoffrey Caruso, Eric Cornelis, Francesco VITI

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Abstract

This paper studies the relationship between activity pattern complexity and car use using two multi-day surveys involving the same participants but collected just before and about one year after they relocated their workplace. Measurable characteristics related to two latent variables, namely activity pattern complexity, or trip chaining (e.g., number of activities done within and outside the home–work tour), and to car use (e.g., usage rate, distance travelled by car) were selected. The study shows that the methodology adopted, partial least square structural equation modelling, quantifies the relation between the two variables, and is robust towards changes in important contextual characteristics of the individuals, namely workplace location. The findings indicate that the number of activities chained to commuting travels strongly impact mode choice and, in particular, car use. The paper also shows that chaining non-work-related activities has a stronger impact on car use. The results of this study suggest that planning and management solutions aimed at reducing car use, but focusing only on the commuting trip while neglecting the impact of other daily activities, may be less effective than expected.

Translated title of the contributionQuantifier la relation entre un profil complexe d'activités et l'usage de la voiture en ayant recours à un modèle partiel d'équation structurelle aux moindres carrés
Original languageEnglish
Article number12101
JournalSustainability
Volume14
Issue number19
DOIs
Publication statusPublished - Oct 2022

Keywords

  • mode choice
  • multi-day survey
  • structural equation modelling
  • trip chaining
  • workplace relocation

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