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TRIMIS

Adaptative Strategies in Long-Term Mobility Choices (400-06-039)

PROJECTS
Funding
Netherlands
Netherlands Flag
Duration
-
Status
Complete with results
Geo-spatial type
Other
STRIA Roadmaps
Smart mobility and services (SMO)
Transport mode
Multimodal icon
Transport sectors
Passenger transport

Overview

Objectives

Current models of long-term mobility decisions assume that these decisions are static, neglecting:
- That they are the outcome of longer-term adaptive processes
- That decisions are driven by life-time utility rather than current utility
- The effect of social environment and households? aspiration levels
- The interdependency between decisions regarding residential and job location and car ownership.

This project seeks to extend the theory by developing an integrative modelling framework of long-term mobility decisions accounting for the above factors. Longitudinal data (both retrospective and prospective) and social network data will be used to estimate and validate the model.

Funding

Parent Programmes
Institution Type
Research agency
Type of funding
Public (national/regional/local)
Funding Source
NWO

Results

Scientific article

  1. H. Peremans, C Lecluyse, A.G. de Kok, O. Gabali, T. van Woensel(2009): Time-dependent vehicle routing subject to time delay perturbations IIE Transactions pp. 1049 - 1066
  2. T. Arentze, D. Ettema, H. Timmermans, T. Oakil(2011): A longitudinal model of longer-term mobility decisions: Framework and first empirical tests Journal of Urban Planning and Development pp. 220 - 229

Publical information

  • A. Toasin(2009): Towards a dynamic longitudinal model of longer-term mobility decisions: Framework and first empirical tests

Results

The analyses suggest that various relationships exist between long-term mobility decisions. They have investigated relationships between a more comprehensive set of long-term mobility decisions and life events.

Mobility decisions are not taken in isolation of life events such as cohabitation, divorce, child birth, home leaving of children and death of family members. In addition, and in contrast to earlier studies, we have also included work-status related events into the analysis of relocation, car ownership decisions and commute mode changes. These events include retirement and switching between full-time and part-time employment. The results indicate that work-status related events are important. Retirement shows a positive relation with car disposal. Switching from full-time to part-time employment encourages commute mode shift from car and discourages shift from bicycle. In terms of demographic events, we have included start of cohabitation, birth of a child, home-leaving of a child and separation of partners. A new insight is the found relationship of life trajectories and demographic events with commute mode shift decisions. Birth of the first child encourages a shifting towards car commuting and away from bicycle commuting. Start of cohabitation encourages bicycle commuting, whereas separation or divorce favours a shift both towards and away from car commuting. Such influences are not addressed in existing literatures. In addition, the results confirm the findings of previous studies in housing and transportation. For example, relocation as a result of start of cohabitation, birth of the first child and separation, car acquisition as a result of cohabitation, birth of any child and birth of the first child, and car disposal in relation with separation are important findings in our analyses.

Partners

Lead Organisation
EU Contribution
€0
Partner Organisations
EU Contribution
€0

Technologies

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