Activity-Based Patterns of Everyday Mobility: The Potential for Long-Term Behaviour Change Across Five Groups of Travellers

Abstract

Significant differences in our mobility patterns can be found in relation to both range/distance and form. While some people travel on multiple occasions to global destinations over the course of a year, others travel mainly locally, that is, by bicycle or on foot. Policymakers and planners need to have a clear conception of the different mobility patterns if they are to develop valid and precise measures promoting more sustainable forms of mobility. This paper points to five key mobility types based on an exploratory cluster analysis of approximately 20,000 Norwegian travel diaries. Three of the defined groups are dominated by the private car, while two are oriented towards the use of public transport, bicycling and walking. The key differences and similarities between the mobility types are discussed and the relationship between everyday travel patterns and long-distance travel is analysed. Opportunities and challenges for transformations in the everyday travel habits of the five groups are discussed in the final section.

Key Words:

• sustainable transport
• mobility types
• cluster analysis
• everyday travels

Notes

1. The intention of this part is to provide an overview of the field. For a more thorough review and assessment of the different segmentation approaches, see Haustein and Hunecke (2013).

2. Norway has a population of approximately five million people.

3. The score is essentially based on the average distance between the objects and can vary between −1 and +1. Specifically, a silhouette measure of less than 0.20 indicates a poor solution quality, a measure between 0.20 and 0.50 a fair solution, whereas values of more than 0.50 indicate a good solution.

4. In the NTS data, long travel is defined as trips of 100 km or longer. Trips abroad will as a rule also be considered as long travel, even if over a shorter distance.

5. Sig. = .000

6. ANOVA, Sig. = .000.

7. An exception is the German NTS that uses a combination of frequency of public transport, car, and bike use, car availability and accessibility to segment the population into seven user groups, for example, captive public transport users and cyclists (Infas & DLR, 2010)

8. The average amount of daily travel has proved to be surprisingly similar among citizens in most EU countries. A study of seven EU countries found an average of 3.2 trips; lowest in the UK with 2.8 trips and highest in Germany with 3.4 (Denstadli, 2011).