Moving between mobility cultures: what affects the travel behavior of new residents?

Thomas Klinger, Martin Lanzendorf, 2016, in Transportation

doi:10.1007/s11116-014-9574-x
Location Bremen, Hamburg and the Ruhr area, Germany
Population Other (specify)
Sample size 1420
Factor analysis type principal components, varimax rotation
Stepwise regression no
Removal of insignificant variables no
Reviewed by SH

Abstract

This paper analyzes the complex interdependencies between residential relocation and daily travel behavior by focusing on modal change. To help explain changes in daily travel patterns after a long distance move between cities the concept of urban mobility cultures is introduced. This comprehensive approach integrates objective and subjective elements of urban mobility, such as urban form and socio-economics on the one hand, and lifestyle orientations and mode preferences on the other, within one socio-technical framework. Empirically, the study is based on a survey conducted among people who recently moved between the German cities Bremen, Hamburg and the Ruhr area. Bivariate analyses and linear multiple regression models are applied to analyze changes in car, rail-based and bicycle travel. This is done by integrating variables that account for urban mobility cultures and controlling for urban form, residential preferences and socio-demographics. A central finding of this study is, that changes in the use of the car and rail-based travel are much more dependent on local scale, such as neighborhood type and residential preferences, whereas cycling is more affected by city-wide attributes, which we addressed as mobility culture elements. © 2015, Springer Science+Business Media New York.

Factors

Variable Pattern loading
Where is transport policy more continuous? (Res preference/perception) 0.669
Where is transport policy more innovative and advanced? (Res preference/perception) 0.661
Where is the development of the transport system more often blocked by political conflicts? (Res preference/perception) -0.508
Where does transport policy focus more on environment-friendly modes? (Environmentalism) 0.49
Variable Pattern loading
Where is transport more reasonably priced? (Cost) -0.699
Where is life on streets more bustling? (Res preference/perception) 0.525
Where is the atmosphere on streets more aggressive? (Environmentalism) 0.511
Where is car use more dangerous? (Safety) 0.478
Where is public transit use more dangerous? (Safety) 0.46
Where do people use the car more often? (Mode-liking) 0.421
Variable Pattern loading
Where is car use more convenient? (Convenience) 0.855
Where is car use more fun? (Mode-liking) 0.846
Where are car users more accepted by other road users? (Social norms) 0.711
Where are roads and parking lots of higher quality? (Convenience) 0.577
Where is car use more dangerous? (Safety) -0.519
Where does transport policy focus more on car users? (Res preference/perception) 0.401
Variable Pattern loading
Where do people cycle more often? (Res preference/perception) 0.834
Where are cyclists more accepted by other road users? (Safety) 0.826
Where are cycle paths and bike racks of higher quality? (Safety) 0.821
Where is cycling more fun? (Mode-liking) 0.807
Where is peoples' travel behavior more environment-friendly? (Environmentalism) 0.706
Where is cycling more dangerous? (Safety) -0.627
Where do people use the car more often? (Mode-liking) -0.594
Where does transport policy focus more on environment-friendly modes? (Environmentalism) 0.559
Where do local media focus more on environment-friendly modes? (Environmentalism) 0.514
Where does transport policy focus more on car users? (Res preference/perception) -0.464
Variable Pattern loading
Where do transport issues have a higher weight in public discourse? (Res preference/perception) 0.806
Where do transport issues have a higher weight in conversations with friends and colleagues? (Res preference/perception) 0.762
Where do local media focus more on car use? (Res preference/perception) 0.641
Where is the development of the transport system more often blocked by political conflicts? (Res preference/perception) 0.411
Variable Pattern loading
Where public transit supply more attractive? (Res preference/perception) 0.842
Where do people use public transit more often? (Social norms) 0.756
Where is public transit use more dangerous? (Safety) 0.723
Where do people combine different modes more often? (Res preference/perception) 0.61
Where do people spend more time on streets and public places? (Res preference/perception) 0.599
Where is transport policy more innovative and advanced? (Res preference/perception) 0.468
Where is life on streets more bustling? (Res preference/perception) 0.441
Variable Pattern loading
Where is walking more convenient? (Convenience) 0.726
Where are pedestrians more accepted by other road users? (Safety) 0.712
Where is walking more fun? (Mode-liking) 0.685
Where are walking paths and connections more attractive? (Res preference/perception) 0.635
Where is walking more dangerous? (Safety) -0.609
Where do people walk more often? (Res preference/perception) 0.567
Where are cyclists more considerate? (Res preference/perception) 0.453

Models

Dependent variable change in car use
Model type linear regression
Sample size 1333.0
R2 nan
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence nan
Variable Standardized_coefficient p-value
Car use before move -0.531 <0.05
Sex (female) -0.021 nan
Degree, student -0.034 nan
Age: 30 years and older 0.06 <0.05
Employed 0.099 <0.05
Increase in income 0.043 <0.05
Change in number of adults 0.002 nan
Change in number of children 0.062 <0.05
Increase of car availability 0.17 <0.05
Increase of transit availability -0.111 <0.05
Increase of bicycle availability 0.004 nan
Highway accessibility 0.087 <0.05
Parking availability 0.104 <0.05
Transit accessibility -0.164 <0.05
City center accessibility -0.049 <0.05
Extended activity space 0.054 <0.05
Move towards edge of city 0.013 nan
Cycling orientation and environment-friendly transport policy -0.027 nan
Transit orientation and street life -0.087 <0.05
Walking orientation -0.023 nan
Car orientation 0.032 nan
Agglomeration effects and lack of safety 0.05 <0.05
Media coverage of transport issues 0.026 nan
Advanced transport policy -0.022 nan
From Bremen to Hamburg 0.037 nan
From Ruhr to Bremen 0.018 nan
From Bremen to Ruhr 0.034 nan
From Hamburg to Ruhr 0.109 <0.05
From Ruhr to Hamburg 0.027 nan
Dependent variable change in rail transit use
Model type linear regression
Sample size 1342.0
R2 nan
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence nan
Variable Standardized_coefficient p-value
Car use before move -0.56 <0.05
Sex (female) -0.022 nan
Degree, student 0.0 nan
Age: 30 years and older -0.094 <0.05
Employed -0.023 nan
Increase in income -0.027 nan
Change in number of adults 0.006 nan
Change in number of children -0.052 <0.05
Increase of car availability -0.068 <0.05
Increase of transit availability 0.142 <0.05
Increase of bicycle availability 0.022 nan
Highway accessibility -0.047 <0.05
Parking availability -0.079 <0.05
Transit accessibility 0.155 <0.05
City center accessibility 0.092 <0.05
Extended activity space 0.027 nan
Move towards edge of city 0.0 nan
Cycling orientation and environment-friendly transport policy -0.037 nan
Transit orientation and street life 0.148 <0.05
Walking orientation 0.013 nan
Car orientation -0.042 <0.05
Agglomeration effects and lack of safety -0.006 nan
Media coverage of transport issues -0.019 nan
Advanced transport policy 0.042 <0.05
From Bremen to Hamburg -0.059 nan
From Ruhr to Bremen -0.051 <0.05
From Bremen to Ruhr 0.012 nan
From Hamburg to Ruhr 0.029 nan
From Ruhr to Hamburg -0.033 nan
Dependent variable change in bike use
Model type linear regression
Sample size 1356.0
R2 nan
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence nan
Variable Standardized_coefficient p-value
Car use before move -0.461 <0.05
Sex (female) -0.006 nan
Degree, student 0.045 <0.05
Age: 30 years and older -0.021 nan
Employed -0.005 nan
Increase in income -0.044 <0.05
Change in number of adults -0.022 nan
Change in number of children 0.003 nan
Increase of car availability -0.07 <0.05
Increase of transit availability -0.05 <0.05
Increase of bicycle availability 0.078 <0.05
Highway accessibility -0.077 <0.05
Parking availability -0.006 nan
Transit accessibility -0.003 nan
City center accessibility 0.029 nan
Extended activity space -0.005 nan
Move towards edge of city 0.003 nan
Cycling orientation and environment-friendly transport policy 0.223 <0.05
Transit orientation and street life 0.021 nan
Walking orientation 0.041 <0.1
Car orientation -0.009 nan
Agglomeration effects and lack of safety -0.033 nan
Media coverage of transport issues 0.004 nan
Advanced transport policy -0.005 nan
From Bremen to Hamburg 0.007 nan
From Ruhr to Bremen 0.05 <0.1
From Bremen to Ruhr -0.03 nan
From Hamburg to Ruhr -0.101 <0.05
From Ruhr to Hamburg -0.037 nan

The Attitudes and Travel Database is produced with support from the Center for Teaching Old Models New Tricks at Arizona State University, a University Transportation Center sponsored by the US Department of Transportation through Grant No. 69A3551747116.

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