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国际学术期刊
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国际学术期刊
Residential dissonance and mode choice
发布时间:2013-11-2815:49:36来源:作者:Md. Kamruzzaman, Douglas Baker, Simon Washington, Gavin Turrell   

Md. Kamruzzamana,
Douglas Bakera,
Simon Washingtona,
Gavin Turrellb,
a School of Civil Engineering and the Built Environment, Queensland University of Technology, 2 George Street, Brisbane, Queensland 4000, Australia
b School of Public Health and Social Work, Queensland University of Technology, Victoria Park Road, Kelvin Grove, Brisbane, Queensland 4059, Australia


Highlights

•The impact of residential dissonance on mode choice is verified using panel data.
•Changes in mode choice behaviour of TOD and non-TOD dissonants are measured.
•Travel preferences are more important in mode choice than built environment.
•Attitudinal importance in mode switch behaviour is demonstrated.
•Dissonants were slow to adjust their behaviour to surrounding land uses.


Keywords
Residential dissonance; Transit oriented development; Travel behaviour change; Residential self-selection


Abstract
Residential dissonance refers to the mismatch in land-use patterns between individuals’ preferred residential neighbourhood type and the type of neighbourhood in which they currently reside. Current knowledge regarding the impact of residential dissonance is limited to short-term travel behaviours in urban vs. suburban, and rural vs. urban areas. Although the prevailing view is that dissonants adjust their orientation and lifestyle around their surrounding land use over time, empirical evidence is lacking to support this proposition. This research identifies both short-term mode choice behaviour and medium-term mode shift behaviour of dissonants in transit oriented development (TODs) vs. non-TOD areas in Brisbane, Australia. Natural groupings of neighbourhood profiles (e.g. residential density, land use diversity, intersection density, cul-de-sac density, and public transport accessibility levels) of 3957 individuals were identified as living either in a TOD (510 individuals) or non-TOD (3447 individuals) areas in Brisbane using the TwoStep cluster analysis technique. Levels of dissonance were measured based on a factor analysis of 16 items representing the travel attitudes/preferences of individuals. Two multinomial logistic (MNL) regression models were estimated to understand mode choice behaviour of (1) TOD dissonants, and (2) non-TOD dissonants in 2009, controlling for socio-demographics and environmental characteristics. Two additional MNL regression models were estimated to investigate mode shift behaviour of (3) TOD dissonants, and (4) non-TOD dissonants between 2009 and 2011, also controlling for socio-demographic, changes in socio-demographic, and built environmental factors. The findings suggest that travel preference is relatively more influential in transport mode choice decisions compared with built environment features. Little behavioural evidence was found to support the adjustment of a dissonant orientation toward a particular land use feature and mode accessibility they represent (e.g. a modal shift to greater use of the car for non-TOD dissonants). TOD policies should focus on reducing the level of dissonance in TODs in order to enhance transit ridership.


Article Outline
1. Introduction
2. Literature review
2.1. Transit oriented development (TOD)
2.2. Determinants of (changes in) mode choice behaviour

3. Data and methods
3.1. Study area
3.2. Data
3.3. Methods
3.3.1. Identification of actual neighbourhood type
3.3.2. Identification of preferred neighbourhood and residential dissonance
3.3.3. Dependent variables and data analyses


4. Modelling results
4.1. Socio-demographic effects on (changes in) mode choice behaviour
4.2. Built environmental impact on mode choice behaviour
4.3. Residential dissonance impact on (changes in) mode choice behaviour

5. Discussion and conclusion
Acknowledgment
References


Figures
   

Fig. 1.

Environmental indicators of two individuals.


Fig. 2.

Cluster analysis to derive TOD and non-TOD areas in Brisbane.


Fig. 3.

Location of TOD and non-TOD type of areas in Brisbane.



Tables

Table 1. Socio-economic characteristics of the respondents participated in the surveys.

Table 2. Pattern matrix showing variables loading on the travel attitude factors that are significant in the final model.

Table 3. Descriptive statistics showing main mode of travel in 2009.

Table 4. Descriptive statistics showing main mode of travel in 2009.

Table 5. Multinomial logistic regression analyses results showing mode choice behaviour in TOD and non-TOD areas in Brisbane in 2009.a

Table 6. Multinomial logistic regression analyses results showing mode switch behaviour in TOD and non-TOD areas in Brisbane between 2009 and 2011.

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