Loading…
How does the built environment affect transit use by train, tram and bus?
While much research has explored the influence of the built environment on public transport use, little focus has been given to how this influence varies by public transport mode. Using a case study of Melbourne, this study assesses the influence of the built environment and other characteristics (t...
Saved in:
Published in: | Journal of transport and land use 2020-01, Vol.13 (1), p.625-650 |
---|---|
Main Authors: | , , , |
Format: | Article |
Language: | English |
Citations: | Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | While much research has explored the influence of the built environment on public transport use, little focus has been given to how this influence varies by public transport mode. Using a case study of Melbourne, this study assesses the influence of the built environment and other characteristics (transit service quality, demand management and socio-demographics) on commuting by train, tram and bus. Key findings indicate that the built environment has a significant influence, but with notable differences between individual public transport modes. Commuting by tram was found to have the strongest association with the explanatory variables, while bus had the weakest explanatory power. Differences in the geographical coverage of public transport services in Melbourne play a key role in explaining the influence of the built environment. Population density is positively associated with tram use, which operates in older, higher density environments, but is negatively associated with train and bus use. Furthermore, the association with land-use mix is only significant for train and tram use, as buses tend to operate in areas with greater land-use homogeneity. When focused on inner Melbourne only, the influence of the built environment is diluted, while distance to public transport becomes more significant. The findings have important implications for practice, not only in terms of improving transit demand forecasting but also in targeting changes to the built environment to leverage higher transit ridership by mode. |
---|---|
ISSN: | 1938-7849 1938-7849 |
DOI: | 10.5198/jtlu.2020.1739 |