Public transport investment is normally targeted at increasing accessibility which land rent theory identifies will in turn increase land values. There is clear policy interest in how much land values increase following a new transport investment so as to establish if there is sufficient land value uplift to capture to help pay or contribute to investment plans. Identifying uplift for residential land has been well studied in the context of new light rail systems and bus rapid transit (BRT) systems in developing countries but there is little evidence for BRT in developed countries. This paper has two objectives. First, to examine long term impact of BRT in a developed world context in Brisbane, Australia as studies in Sydney, Australia. This provides an addition to the BRT literature in developed countries where the only other suggests little uplift in comparison to developing world contexts. Second, to consider the spatial distribution of uplift which is an essential prerequisite to understanding the distributional impact if uplift is used to contribute to infrastructure provision. Spatial modelling is used to examine the accessibility impacts of the BRT and this is followed by Geographical Weighted Regression, used to examine the spatial distribution of accessibility. The results show there is greater uplift in Brisbane, as compared to Sydney, Australia which is likely due to the greater network coverage of BRT in Brisbane and a relative lack of rail based competition. Land value uplift is also spatially distributed over the network giving higher uplift in some areas than others and lower values than typically found with rail based systems in developed countries. Highlights • Being close to BRT adds a premium to the housing price • The price premiums varies over space • High-frequency feeder bus network appears to be the key for the capitalization effects • GWR improves spatial models by accounting for spatial non-nonstationarity

Public transport authorities and service providers place great emphasis on information provision to travellers both before and during travel. Information provided prior to travel has included brochures, printed timetables, newspaper advertisements, telephone services and marketing campaigns. During the trip, providers have tended to use maps at public transport stops (i.e. bus stops, train stations, ferry wharves, etc.) as well as timetables both static and dynamic or real-time. Some of these channels are still used but improvements in digital technology has led to a wider range of information distributed using different digital media. Whilst Transport for NSW continues to provide the more traditional information, as do the transport operators, there has been a plethora of third party applications which are accessible on the move. The literature recognises the importance of information provision and the need for information differs at the various stages of the trip, from planning, to point of entry into the system to wayfinding during the trip to egress from the system, but no systematic research exists as to which information is valued by which customers. Different passenger segments are likely to prefer information in different ways and it is important to identify the segments and their information preferences so as to promote public transport use. This paper provides a context for passenger information provision through existing literature which is used to frame an internet survey of the public's awareness and usage of public transport information. The paper explores the differences between casual and regular users of public transport as well as the usage and importance placed on the various sources of information currently available, including any differences relating to regular schedules, changes to regular services, planned and unplanned disruptions. The paper provides a reference for other states in Australia as to the value of different types of information.

No abstract

Pseudopanel data have been increasingly applied in travel demand analysis to investigate the long-run travel demand when genuine panel data are unavailable. However, conventional estimation techniques have typically been used without a careful consideration of some unique properties of pseudopanel data. This paper shows that ignoring these properties potentially leads to estimation bias or inefficiency not observed in genuine panel data. The method used is a Monte Carlo experiment with scenarios designed to generate various data possessing pseudopanel data characteristics under conditions of limited observations; the performance of various estimator is evaluated with the use of the simulation results. This research found that the large between-group variation of the exogenous variable and the variance of unobserved group effects in pseudopanel data are the primary causes of estimation bias and inefficiency. Other factors such as cohort sizes and nonspherical errors have a smaller effect on the estimators’ performance. An empirical application using Sydney Household Travel Survey data is also presented to illustrate the simulation findings.

Public transit is immensely important among recent immigrants for enabling daily travel and activity participation. The objectives of this study are to examine whether immigrants settle in areas of high or low transit accessibility and how this affects transit mode share. This is analyzed via a novel comparison of two gateway cities: Sydney, Australia and Toronto, Canada. We find that in both cities, recent immigrants have greater levels of public transit accessibility to jobs, on average, than the overall population, but the geography of immigrant settlement is more suburbanized and less clustered around commuter rail in Toronto than in Sydney. Using logistic regression models with spatial filters, we find significant positive relationships between immigrant settlement patterns and transit mode share for commuting trips, after controlling for transit accessibility and other socio-economic factors, indicating an increased reliance on public transit by recent immigrants. Importantly, via a sensitivity analysis, we find that these effects are greatest in peripheral suburbs and rural areas, indicating that recent immigrants in these areas have more risks of transport-related social exclusion due to reliance on insufficient transit service.