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Housing affordability is traditionally measured using the percentage of household income spent on housing. An important cost that is usually overlooked in measuring location affordability is the transportation or accessibility costs. In this paper, we present a modeling approach, driven by urban open data, to measure location affordability that incorporates both housing and transportation costs. We apply the developed model to assess housing affordability in Melbourne, Australia as a case study. Results suggest that neighbourhoods that appear to be affordable when only housing cost is considered are not necessarily affordable when transportation costs are taken into account. A negative correlation between housing affordability and transportation affordability is observed. We also identify the presence of a strong spatial clustering pattern in the affordability measure across the study area. A major methodological contribution of the paper is the inclusion of comprehensive private vehicle costs and public transportation expenses in the model that contributes to a more robust estimation and understanding of location affordability. The model also distinguishes between different trip purposes. Results suggest that plans and policies to improve housing affordability should be made in coordination with transportation infrastructure investment plans to ensure effective and equitable outcomes. Nevertheless, the focus of the paper is more on the measurement of affordability; rather than reviewing and recommending housing related policies. [ABSTRACT FROM AUTHOR]

Almost half of the world population lives in rural and remote areas facing more challenging and hazardous life conditions than the rest of the population. This paper and proposed method contribute to addressing an apparent gap in modelling travel-related decisions of rural and remote populations to enhance equitable access to basic amenities (e.g., education, health services, retail) for these populations. The application of these models is highly relevant for planning and policy purposes in remote communities. This paper uses data obtained from a mobility survey of remote Aboriginal communities in Central Australia to estimate purpose-specific destination choice models for access to basic services. The analysis is based on stated preference data to measure the attractiveness of destinations. Then, the models are used to analyse the impact of increasing the number of services provided in the remote communities. A better understanding of the impact of local development on travel patterns in remote communities is provided by analysing three aspects: attracted trips to the destinations, reduction of distance travelled by travellers in all the communities and improved equity in the distribution of travel distance among the communities. The case study illustrates the method successfully determines the most relevant parameters in the decisions of the surveyed individuals and determines potential destinations for local development, with the final objective of contributing to the alleviation of accessibility and inclusion problems in remote areas. [ABSTRACT FROM AUTHOR]

Daily mobility varies by gender and is likely related to contextual factors including the gender division of employment and family work, options for modes of transport, and support for work-family reconciliation. This paper compares travel time patterns of men and women using nationally representative time-diary data from Australia, the UK, Spain and Finland (n = 14,176). Despite similarities in men and women's total travel time within countries, results show substantial gender variation in the purpose of daily travel, the transport mode used, who is present, and the way parents in couple-headed households share travel with and for children in relative terms. The extent of the gender gaps vary cross-nationally in ways consistent with prevalent patterns in the gendered division of labour and social parenting norms, but relative gaps in child-serving travel were universal, attesting to the ubiquity of gendered mobility constraints in households with children. • Daily mobility varies cross-nationally by gender in purpose, mode and company. • Gendered mobility reflects national patterns of gendered division of labour. • Gendered mobility reflects national patterns of parenting norms and social trust. • Relative gender gaps in parents' travel with and for children are universal. [ABSTRACT FROM AUTHOR]

Abstract This paper assesses air connectivity between China and Australia for the period 2005–16 using a Connectivity Utility Model. Our direct connectivity measure shows that as a gateway city, Sydney continues to play a key role in facilitating the movements of people and goods between China and Australia. Guangzhou has become the city best connected with Australia since 2011 as measured by direct connectivity. When indirect connections are considered, the largest increases in overall connectivity from 2005 to 2016 can be observed among Australia's major capital cities, particularly Sydney, Melbourne and Brisbane. Chinese carriers are the key drivers behind the increases. There have been rises and falls for airports serving as a hub between China and Australia. Guangzhou has forged its strong status as a transfer hub between Australia and China thanks to the quick expansion of China Southern. The gaps between Guangzhou and other transfer hubs measured by hub connectivity have widened since 2010. Highlights • Air connectivity between China and Australia for the period 2005–2016 is assessed. • Chinese airlines makes a major contribution to the two countries' air connectivity. • Guangzhou has forged its strong status as an emerging transfer hub between Australia and China. • The development of other transfer hubs is assessed and discussed. [ABSTRACT FROM AUTHOR]

It is well known that journey-to-work (JTW) data can be represented using complex network graphs. What is less evident is the way in which this approach can be used to quantitatively analyse the structure, connectivity and dynamics of commuting behaviour. This paper employs a complex network approach to spatially disaggregated JTW data in order to examine commuting behaviour for six different modes of transport (car, car passengers, train, bus, cycling and walking) within three of the most populous metropolitan areas in Australia. A set of network measures ( degree, strength, clustering coefficient , maximum cliques , average shortest path length and betweenness ) are computed from both the unweighted and weighted graphs corresponding to JTW data for the Sydney, Melbourne and the South East Queensland regions from the time periods: 2001, 2006 and 2011. Results reveal a number of interesting dynamics, one being that Melbourne exhibits shorter (and presumed to be faster) alternate commuting paths than either Sydney or South East Queensland given its lower betweenness and shortest path values allied with higher clustering coefficients. The interpretation of these metrics demonstrates that complex networks have the capacity to reveal new insights from JTW data, by enabling a more comprehensive, systematic, empirical and fine-grained analysis of changes in commuting behaviour over time. [ABSTRACT FROM AUTHOR]

With the onset of COVID-19 restrictions and the slow relaxing of many restrictions, it is imperative that we understand what this means for the performance of the transport network. In going from almost no commuting, except for essential workers, to a slow increase in travel activity with working from home (WFH) continuing to be both popular and preferred, this paper draws on two surveys, one in late March at the height of restrictions and one in late May as restrictions are starting to be partially relaxed, to develop models for WFH and weekly one-way commuting travel by car and public transport. We compare the findings as one way to inform us of the extent to which a sample of Australian residents have responded through changes in WFH and commuting. While it is early days to claim any sense of a new stable pattern of commuting activity, this paper sets the context for ongoing monitoring of adjustments in travel activity and WFH, which can inform changes required in the revision of strategic metropolitan transport models as well as more general perspectives on future transport and land use policy and planning. • Two wave study examining work from home (WFH) and commute behaviour through COVID-19 pandemic. • New models for WFH and impact on commuting activity. • Evidence of changes WFH and commuting from immediately after restrictions to their initial easing • Small decreases in WFH and increases in car-based commuting starting to occur. • WFH has been a positive experience and many would to WFH more than before COVID-19, if they have an appropriate space. • Policy makers should encourage employer support for working from home and help identify and reduce barriers to doing so. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has changed the way we go about our daily lives in ways that are unlikely to return to the pre-COVID-19 levels. A key feature of the COVID-19 era is likely to be a rethink of the way we work and the implications on commuting activity. Working from home (WFH) has been the 'new normal' during the period of lockdown, except for essential services that require commuting. In recognition of the new normal as represented by an increasing amount of WFH, this paper develops a model to identify the incidence of WFH and what impact this could have on the number of weekly commuting trips. Using data collected in eight countries (Argentina, Australia, Brazil, Chile, Colombia, Ecuador, Peru and South Africa), we developed a Poisson regression model for the number of days individuals worked from home during the pandemic. Simulated scenarios quantify the impact of the different variables on the probability of WFH by country. The findings provide a reference point as we continue to undertake similar analysis at different points through time during the pandemic and after when restrictions are effectively removed. [ABSTRACT FROM AUTHOR]

Electric velomobility (e-velomobility) encompasses human movement using electric-assisted bicycles (pedelecs, or e-bikes), and the associated practices, systems and technologies. It is emerging as an active mode in developed economies. Electric bicycle sharing (EBS) schemes can attain higher per-vehicle use time and provide more equitable access than personal ownership. University campuses are ideal testing beds for such systems as young and lower-income groups are present there. The goal of this study is to understand the segmentation of the market for a hypothetical electric bicycle sharing scheme located in a multi-campus university. A cross-sectional survey was conducted at a multi-campus university in South East Queensland, Australia. Motives, reasons, and intention of students and staff for potential future use of a potential campus-based EBS scheme were revealed. Three distinctive potential user groups with varied modal, socio-demographic, and psychological characteristics emerged in the clustering analysis, namely: "multimodal enthusiasts" (28%), "car-loving pragmatics" (46%), and "car-loving skeptics" (26%). We identify the key market segments and potential adopters' demographics (residential location, country of origin, income, and academic major). Our results indicate that respondents who are more multimodal, especially those cycling often and with shared mobility experiences, are more positive about using e-bike sharing. Largely mono-modal car users tend to be more negative toward the scheme. International students also tend to be more positive. The individual preferences and attitudes toward campus-based shared e-velomobility, as revealed in this paper, provide important insights for planners, policymakers and sharing operators seeking to launch or improve uptake of such schemes. • Survey of university staff and students in Brisbane and Gold Coast, Australia. • Clustering shows three distinct segments of potential electric bike share (EBS) adopters. • Largest "Car-lover" segment skeptical toward EBS or with pragmatic reasons against. • High multimodality and non-local upbringing made more enthusiastic toward EBS. • Residential location, field of study, and income also affect EBS adoption. [ABSTRACT FROM AUTHOR]

This paper draws on findings from an Australia-wide survey with data collected in three waves throughout 2020 to explore the impact of COVID-19 on public transport trends in metropolitan areas of Australia. Following consideration of the public transport sector response to the pandemic and the emerging literature context, we explore three principal questions: (i) How has weekly travel composition changed across the waves? (ii) How has level of concern with using public transport changed over the course of the pandemic given new bio-security concerns? and (iii) How has attitudes to risk been associated with the changes in PT use? A key finding is that concerns over bio-security issues around public transport are enduring, that concern about hygiene is significantly negatively related to public transport use and that those with higher concern about the hygiene of public transport also held higher concern about COVID-19 at work. Even as COVID-19 restrictions are eased, both concern about crowds and hygiene have a significant and negative correlation with public transport use. Concluding remarks are offered on what might need to happen for public transport patronage to start returning. • New data on changing patterns of use and attitudes towards public transport, including biosecurity concern during COVID-19. • We investigate how has weekly travel composition changed since March 2020 • The level of biosecurity concern with using public transport over the course of the pandemic is documented. • We identify the drivers for use of public transport over the course of the pandemic • The implications for public transport operations and policy are set out. [ABSTRACT FROM AUTHOR]

We are told that electric vehicles, cars in particular, will be good for the environment. But what exactly might this mean? It is true that end use emissions will be significantly reduced when we move from fossil fuels to green energy sources? Assuming that the demand for such cars, including battery electric vehicles (BEVs) in particular will grow, we can expect a significant number of such vehicles manufactured in future years. Given the potentially relatively lower cost (fewer moving parts) compared to internal combustion engine vehicles as well as the significantly lower usage costs per kilometre, we would expect a level of uptake that could impact on the performance of the road network (perhaps increased congestion and crash risk) but also a concomitant reduced use of public transport and fuel excise loss. In this paper, we apply the MetroScan modelling system in the Greater Sydney Metropolitan Area (GSMA) over the period 2021–2056 to identify the likely impact that the growth in BEV ownership and use will have on vehicle kilometres, modal shares, government revenues, levels of CO 2 emissions and other impacts. Moreover, we investigate the introduction of a BEV usage charge proposed in Australia to see what it might do to these key performance indicators and whether it can offset the adverse effects during BEV uptake such as government fuel excise revenue loss and increased congestion. [ABSTRACT FROM AUTHOR]

The continuous growth in urban population has led to intense competition for space among the various actors in the urban system. Planning and managing this competition requires a better understanding of both personal travel and goods movements. Urban planning in the past has however, focused on providing a sustainable and efficient transport system to solve personal mobility challenges with almost total neglect of the goods movement sector. However, with the growing importance of freight to both local and national economies, and also the disproportionate impacts of freight related activities on congestion, pollution, accidents and other road hazards, there is a stronger call for a better understanding of the freight system. Central to freight movement models is an understanding of where the freight commodities are produced and consumed. An important driver in the production and/or consumption of each commodity is the production and consumption of other commodities. In this paper, these important interactions between commodities are captured in a path analysis freight model which incorporates models of commodity production and consumption. We identify the key factors driving the consumption and production of each commodity. To be suitable for forecasting and policy testing, the estimated models are transformed into linked logit models to also allow for important policy measures such as accessibility and commodity generation influences such as population and employment to be estimated. The proposed model has been implemented to generate the amount of commodity of each type produced and consumed in each state of Australia with illustrations of how the production and/or consumption of one commodity triggers the production and/or consumption of other commodities. The study also demonstrates the differential impacts of changes in demographics or employment growth on the consumption and/production of different commodities. When built into an integrated transport and land use model system that accommodates both passenger and freight activity, and includes models that account for spatial dependency (which is not a requirement of the macro level commodity generation stage), this freight generation capability contribute to the way in which freight movements influence and hence impact on the performance of the entire transport network, for both passenger and freight. [ABSTRACT FROM AUTHOR]