A comprehensive study of life course, cohort, and period effects on changes in travel mode use

doi:10.1016/j.tra.2012.10.019

Transportation Research Part A: Policy and Practice

Volume 47, January 2013, Pages 167-181

https://doi.org/10.1016/j.tra.2012.10.019 Get rights and content

Abstract

This paper studies changes in people’s travel mode use from one year to the next. It is informed by three distinct discourses: travel behaviour change, the mobility biographies approach, and cohort analysis. The data used is the German Mobility Panel (GMP) 1994–2008 in which households and their members are asked three times in three subsequent years to report the trips they made over a week. The changes reported are regressed to key events over the life course, cohort effects and period effects, while various sociodemographic and spatial attributes are controlled. Due to the non-independent nature of panel observations, a cluster-robust regression approach is used. The findings suggest that behind the aggregate stability in travel mode use over time there is much change ‘under the surface’, induced by life course changes, individual and household sociodemographic, and spatial context. The changes found induced by life course related key events favour the notion of mobility biographies. However, taken over all key events seem to be relatively loosely associated with mode use changes. Nonetheless, various significant effects of baseline variables suggest that mode use may change even in the absence of a key event.

Highlights

► Focus is on changes in individual travel mode use. ► Changes are regressed to key events over the life course, cohort effects and period effects. ► Findings suggest that change is induced by life course related key events, sociodemographics, and spatial context.

Introduction

Changes in individual travel behaviour have become a major field of research in transportation studies in recent years (Ampt, 2003, Cao et al., 2007, Ker, 2008). Such changes may occur on a day-to-day basis (Pendyala, 2003) or in the longer term. In the latter case they have been linked to people’s life courses and conceptualised as being triggered by key events in an individual’s mobility biography (Lanzendorf, 2003, Scheiner, 2003). However, behavioural changes in the long term may not just be part of individual mobility biographies, but also of collective cohort and/or period related changes, in which individual life courses are embedded.

This paper studies changes in people’s travel mode specific trip rates (for convenience: mode use) from one year to the next. The data used is the German Mobility Panel (GMP) 1994–2008 in which households and their members are asked three times in three subsequent years to report the trips they made over a week. The changes reported are regressed to key events over the life course, cohort effects and period effects, plus various sociodemographic and spatial attributes.

The goal of this paper is to contribute to and extend the recently emerged mobility biography approach by simultaneously studying this rather comprehensive set of baseline and change variables. Knowledge about the impact of life course related key events and other variables may contribute to understanding of the effectiveness of planning schemes, particularly those which are related to such events (e.g. residential moves).

This research is informed by three distinct discourses: behavioural change, the mobility biographies approach, and cohort analysis. Within the context of this journal, the use of the mobility biographies approach is relatively novel. In the next section the state of the research is introduced. Subsequently, the data and the methodology are described, followed by the results. The paper finishes with an outlook to further research.

Section snippets

Travel behaviour change – state of the research

Travel behaviour change has long been (relatively) neglected in research, even though time geography recognised the usefulness of the life path concept for travel studies as early as the 1970s (Hägerstrand, 1975). In an early study on the dynamics of travel behaviour, Clarke et al. (1982) distinguished between three levels of dynamics: first, short-term microdynamics, capturing people’s 24 h daily activity/travel choices (see for an overview of day-to-day variability of travel Pendyala, 2003);

Data

The data used is the German Mobility Panel (GMP) 1994–2008.⁴ The GMP is a household survey with the sample organised in overlapping waves. Every household is surveyed three times over a period of three consecutive years (Chlond and Kuhnimhof, 2005), e.g.

Descriptive analysis

In the following some descriptive statistics of mode use change associated with life course events are presented. The events are selected based on their significance in regression. As expected, those who did not experience a key event over the year under study show little change in mode use (Table 4). To facilitate interpretation, the table also includes state variables of trip frequencies for the total sample.

The birth of a child is associated with both more driving and more walking,

Conclusions

This paper has investigated changes in travel mode specific trip rates from 1 year to the next using descriptive statistics and multiple regressions. A cluster-robust estimation methodology has been used to account for the clustered nature of the data.

The results show that behind the aggregate stability in travel mode use over time there is much change ‘under the surface’, induced by life course changes, individual and household sociodemographics, and spatial context. The changes found induced

Acknowledgements

This research was funded by the German Research Foundation (DFG) as part of the project ‘Alltag im Wandel des Geschlechterverhältnisses: Aktivitäten, Wege, Verkehrsmittel und Zeitverwendung’ (Everyday life in the context of changing gender relations: activities, trips, travel modes and time use, 2009–2011).

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A comprehensive study of life course, cohort, and period effects on changes in travel mode use

Abstract

Highlights

Introduction

Section snippets

Travel behaviour change – state of the research

Data

Descriptive analysis

Conclusions

Acknowledgements

Transportation Research Part A

Transportation Research Part F

Transportation Research Part F

Transportation Research Part F

Transportation Research Part A

Transport Policy

Journal of Transport Geography

The impact of residential neighborhood type on travel behavior: a structural equations modeling approach

Annals of Regional Science

Does habitual car use not lead to more resistance to change of travel mode?

Transportation

Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach

Transportation

Some issues of dynamics in forecasting travel behavior – a discussion paper

Transportation

Paths in transnational time-space: representing mobility biographies of young Swedes

Geografiska Annaler B

What does a one-month free bus ticket do to habitual drivers?

Transportation

Family changes and public transport use 1984–1987

Transportation

Survival and arena: on the life history of individuals in relation to their geographical environment

The Monadnock

Random-effects regression models for clustered data with an example from smoking prevention research

Journal of Consulting and Clinical Psychology