Commuting mode choice in transit oriented development: Disentangling the effects of competitive neighbourhoods, travel attitudes, and self-selection

Kamruzzaman, M., Shatu, F.M., Hine, J. Turrell, G., 2015, in Transport Policy

doi:10.1016/j.tranpol.2015.06.003
Location Brisbane, Queensland, Australia
Population Other (specify)
Sample size 3537
Factor analysis type exploratory factor analysis, oblimin rotation
Stepwise regression no
Removal of insignificant variables yes
Reviewed by AR

Abstract

This research identifies the commuting mode choice behaviour of 3537 adults living in different types of transit oriented development (TOD) in Brisbane by disentangling the effects of their "evil twin" transit adjacent developments (TADs), and by also controlling for residential self-selection, travel attitudes and preferences, and socio-demographic effects. A TwoStep cluster analysis was conducted to identify the natural groupings of respondents' living environment based on six built environment indicators. The analysis resulted in five types of neighbourhoods: urban TODs, activity centre TODs, potential TODs, TADs, and traditional suburbs. HABITAT survey data were used to derive the commute mode choice behaviour of people living in these neighbourhoods. In addition, statements reflecting both respondents' travel attitudes and living preferences were also collected as part of the survey. Factor analyses were conducted based on these statements and these derived factors were then used to control for residential self-selection. Four binary logistic regression models were estimated, one for each of the travel modes used (e.g. public transport, active transport, less sustainable transport such as the car/taxi, and other), to differentiate between the commuting behaviour of people living in the five types of neighbourhoods. The findings verify that urban TODs enhance the use of public transport and reduce car usage. No significant difference was found in the commuting behaviour between respondents living in traditional suburbs and TADs. The results confirm the hypothesis that TADs are the "evil twin" of TODs. The data indicates that TADs and the mode choices of residents in these neighbourhoods is a missed transport policy opportunity. Further policy efforts are required for a successive transition of TADs into TODs in order to realise the full benefits of these. TOD policy should also be integrated with context specific TOD design principles. © 2015 Elsevier Ltd.

Factors

Variable Pattern loading
Closeness to public transport (Res preference/perception) 0.7
Ease of walking to places (Res preference/perception) 0.666
Wanted to live close to shops (Res preference/perception) 0.73
Access to freeways or main roads (Res preference/perception) 0.311
Variable Pattern loading
Closeness to schools (Res preference/perception) 0.722
Closeness to childcare (Res preference/perception) 0.633
Variable Pattern loading
Closeness to the city (Res preference/perception) 0.602
Closeness to work (Res preference/perception) 0.527
Access to freeways or main roads (Res preference/perception) 0.386
Variable Pattern loading
Closeness to open space (e.g. parks) (Res preference/perception) 0.886
Near to green-space or bushland (Res preference/perception) 0.658
Variable Pattern loading
I need a car to do many of the things that I want to do (Convenience) 0.782
I could not manage pretty well without a car (Convenience) 0.628
Variable Pattern loading
Public transport is inconvenient and unreliable (Convenience) 0.812
Traveling by public transport is not very pleasant (Mode-liking) 0.624
Using public transport takes too much time (Convenience) 0.685
Public transport can sometimes be difficult than driving (Convenience) 0.413
Variable Pattern loading
Traveling by car is safer overall than taking public transport (Safety) 0.69
Traveling by car is safer overall than walking (Safety) 0.661
Variable Pattern loading
People need to walk and cycle more to improve the environment (Environmentalism) 0.931
People need to walk and cycle more to reduce global warming (Environmentalism) 0.79
People need to walk and cycle more often to reduce traffic congestion (Transport policy) 0.754
People need to use public transportation more often to reduce traffic congestion (Transport policy) 0.527

Models

Dependent variable Mode of transport to work: car/taxi/motorcycle
Model type binary logit
Sample size 3537.0
R2 nan
Adjusted R2
Pseudo R2 (Nagelkerke) 0.27
AIC nan
BIC nan
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence -1362.535
Variable Odds_ratio p-value
Constant 9.61 <0.05
Neighborhood tpye(ref: traditional suburbs) nan nan
Urban TOD 0.69 <0.05
Travel attitudes and preferences nan nan
Negative perception about PT 1.4 <0.05
Car dependent 2.06 <0.05
Travel Time( ref: less than 15 minutes) nan nan
15-30 min 1.59 <0.05
30-60 min 0.63 <0.05
More than 60 min 0.46 <0.05
Socio-demographics nan nan
Female (ref: male) 1.32 <0.05
Car availability (ref: yes, always) nan nan
Yes, sometimes 0.25 <0.05
No (ref: yes, always) 0.33 <0.05
Do not drive (ref: yes, always) 0.13 <0.05
Current living arrangment(ref: living alone) nan nan
Couple living with > = 1 children 1.3 <0.05
Health Status 0.84 <0.05
Dependent variable Mode of transport to work: public transport
Model type binary logit
Sample size 3537.0
R2 nan
Adjusted R2
Pseudo R2 (Nagelkerke) 0.44
AIC nan
BIC nan
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence -1080.13
Variable Odds_ratio p-value
Constant 0.08 <0.05
Neighbourhood type(ref: traditional suburbs) nan nan
Urban TOD 1.46 <0.05
Built environment indicators nan nan
Net employment density 0.99 <0.05
Travel attitudes and preferences nan nan
Negative perception about PT 0.48 <0.05
Sensitive to environmental externalities 0.86 <0.05
Car dependent 0.44 <0.05
Reasons to choose current address nan nan
Accessibility and mobility of places 1.29 <0.05
Natural environment 0.87 <0.05
Travel time(ref: less than 15 minutes) nan nan
15-30 min 10.29 <0.05
30-60 min 41.8 <0.05
More than 60 min 59.91 <0.05
Socio-demographics nan nan
Female (ref: male) 1.49 <0.05
Age 0.97 <0.05
Car availability (ref: yes, always) nan nan
Yes sometimes 5.12 <0.05
Do not drive (ref: yes, always) 1.97 <0.05
Level of education(ref: upto year 12) nan nan
Diploma/certificate 0.73 <0.05
Household size 0.84 <0.05
Dependent variable Mode of transport to work: active transport
Model type binary logit
Sample size 3537.0
R2 nan
Adjusted R2
Pseudo R2 (Nagelkerke) 0.18
AIC nan
BIC nan
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence -1139.875
Variable Odds_ratio p-value
Constant 0.11 <0.05
Neighbourhood type(Ref: traditional suburbs) nan nan
Activity centre TOD 0.71 <0.05
TAD 0.55 <0.05
Built environmental indicators nan nan
Net employment density 1.01 <0.05
Intersection density 0.53 <0.05
Travel attitudes and preferences nan nan
Sensitive to environmental externalities 1.15 <0.05
Car dependent 0.54 <0.05
Travel time (ref: less than 15 minutes) nan nan
15-30 min 0.41 <0.05
30-60 min 0.79 <0.05
Socio-demographics nan nan
Female(ref: male) 0.7 <0.05
Car availability (ref: yes, always) nan nan
Yes, sometimes 2.93 <0.05
Do not drive(ref: yes, always) 3.45 <0.05
Level of education (ref: upto year 12) nan nan
Graduate and over 1.41 <0.05
Current living arrangement(ref: living alone) nan nan
Other 2.18 <0.05
Health Status 1.24 <0.05
Dependent variable Mode of transport to work: other
Model type binary logit
Sample size 3537.0
R2 nan
Adjusted R2
Pseudo R2 (Nagelkerke) 0.15
AIC nan
BIC nan
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence -413.785
Variable Odds_ratio p-value
Constant 0.2 <0.05
Neighbourhood type(ref: traditional suburbs) nan nan
Urban TOD 0.44 <0.05
Activity Centre 0.33 <0.05
Potential TOD 0.38 <0.05
Built environmental indicators nan nan
Cul-de-sac density 0.11 <0.05
Travel attitudes and preferences nan nan
Car dependent 1.37 <0.05
Travel time (ref: less than 15 minutes) nan nan
15-30 min 0.16 <0.05
30-60 min 0.17 <0.05
Socio-demographics nan nan
Female (ref: male) 0.43 <0.05
Emploment status: full time (Ref: part time) 0.5 <0.05
Level of education(ref: upto year 12) nan nan
Graduate and over 0.54 <0.05
Health status 1.3 <0.05

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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