Geo-spatial analysis of activity spaces in a TOD environment – Tracking impacts of rail transport policy using kernel density estimation

Activity spaces are dynamic, “people-based” accessibility measures that can be used to analyse spatial arrangements of travel. This paper reports on activity spaces in context of transport policy aimed at changing travel behaviour by offering alternative transport options and new urban services within transit-oriented developments (TOD) environments. Specifically, we explore associations between TOD and activity spaces to derive visually easy comprehensible indicators, assisting practitioners and policy makers in determining decision-making effectiveness. We analyse results from household travel diaries collected within three unique TOD precincts in Perth, Western Australia situated alongside a 72km new metro-rail link, pre- and postopening, to identify impacts of the major transport intervention on travel. While activity spaces have increasingly been applied as metrics for assessing the extent of urban space used by households for satisfying their daily activity needs, their application to explore potential changes in built environment induced travel behaviour is a novel feature of this research. We employ herein kernel density estimation, which has great flexibility and superior visualisation capabilities in representing activity spaces, to longitudinally track travel behaviour changes. We also expand on previous investigation that considered discrete origin-destination trip data, by applying kernel density estimation to data including generated route information. Our findings suggest benefits of activity space analysis in investigating past transport infrastructure decisions and associated implications, promising a potential improvement for development of new policies and strategies in the transport sector

The loneliness of the hybrid worker

Unprecedented levels of hybrid work seem likely to persist beyond the pandemic conditions that revolutionized employers' attitudes toward flexible working arrangements. Even as offices have reopened, many employees are loath to give up the benefits of working from home at least some of the time. But some two years into what has been an unplanned global experiment in remote work, the costs of that approach are coming into sharper focus. While employees appreciate saving time, shedding the stress of commuting, and having more flexibility to balance work and personal demands, remote work has downsides that go beyond domestic distractions and blurred work-life boundaries. In particular, the quality, frequency, and nature of interactions change when colleagues are physically remote and there is less dynamic, spontaneous communication. Here, Knight et al discuss the differences of employee' experiences working at home versus in the company workplace and indicates that in-office interactions--especially with colleagues--can indeed improve employees' job satisfaction and reduce their feelings of loneliness, even when working at home

Autonomous Vehicles Down Under: An Empirical Investigation of Consumer Sentiment

Of the many issues surrounding the potential introduction of Autonomous Vehicles (AVs), consumer response remains unclear. The current paper presents an empirical investigation of consumer sentiment towards AVs based on an online survey of 455 Australian adults. Market segmentation procedures are used to cluster participants according to their attitudes and concerns towards AVs with clusters then profiled according to demographics, personality traits and contextual/situational factors. Results suggest unsurprisingly that attitudes and concerns are a useful predictor of the likelihood of purchasing an AV. More favourable attitudes towards AVs are associated with younger, male respondents, those who drive less currently and those more open to sharing their car. More negative attitudes prevail with older, female respondents, those who drive more, and those less open to sharing their car. Results have important implications for policy-makers and researchers alike

The influence of work–family conflict and enhancement on the wellbeing of the self-employed and their spouses : a dyadic analysis

This study examines the effect of work–family conflict (WFC) and work–family enhancement (WFE) on the wellbeing of the self-employed and their spouses. Adopting a dyadic perspective, our analysis focuses on three dimensions of wellbeing: physical health, mental health and life satisfaction. Using the Spillover and Crossover Model as theoretical framework and the Actor–Partner Interdependence Model as an estimation technique, we investigate how work–family conflict and enhancement among the self-employed and their spouses were associated to their individual and mutual wellbeing. The analysis revealed a strong actor and partner effect, such that one’s own perception of WFC undermined the wellbeing for both the self-employed and their spouses. Further, WFE was associated with an improvement in wellbeing, mainly for the self-employed, and not their spouses. The results partially supported the ‘crossover hypothesis’, suggesting that launching a new business is a stressful endeavour at the dyadic level of the self-employed and their spouses

Using brand knowledge to predict beer brand preference and loyalty for samples of new frequent users in Perth and Beijing

This study tests a model of Brand Knowledge and Brand Equity of brands of beer on new and frequent users in two populations that differ in their stage of the beer product life cycle and culture. Using Multiple Logistic Regression (MLR) and Binomial Logistic Regression (BLR), models based on the respondents\u27 Brand Knowledge are able to correctly identify Chinese respondents&rsquo; preferred brand of beer 56% of the time, while correctly identifying 77% of respondents in an Australian sample when three top brands are tested. The model could further identify 67% of those that stay or switch in both the Australian and the Chinese samples.<br /

Measuring the Accessibility of Public Transport: A Critical Comparison Between Methods in Helsinki

This research compares two location-based methods of evaluating public transport accessibility and applies them in Helsinki. After discussing a series of methodological aspects, the authors calculate the Structural Accessibility Layer (SAL) public transport indicator and the Public Transport and Walking Accessibility Index (PTWAI) for a grid with 8,325 zones, comparable in size to the smallest census unit. Both methods are operational for urban planners and policy makers interested in a relatively straightforward way of quantifying the accessibility of sustainable transport modes such as public transport. The results display similar accessibility patterns when moving from larger to smaller isochrones (60 to 38 min). However, the findings are inconclusive between SAL and PTWAI: SAL (38 min) displays good accessibility by public transport (more than 94 % of the population living within two-thirds of the metropolitan area has very high and high access to public transport), but PTWAI indicates that 35 % of the population, primarily households with children (43 %), experience low and very low access. The contrasting results are mainly due to the derivation of the two indicators and have considerable implications for policy making. The findings of this research imply that PTWAI is preferable to planning assessments regarding public transport, given its relatively richer content. However, for multi-mode-based accessibility categorization, SAL appears more appropriate. It is the analyst’s role to understand the objective and contents of each index and choose the tool fit for their purpose. Then, a judgement should be made on the trade-off between the detail of the measures and results and the computational burden. Given the sensitivity of the models to various input parameters and assumptions, cross-validation and replication are key for ascertaining the credibility and usefulness of the models. Document type: Articl

Essentials of Business Statistics: communicating with numbers

Essentials of Business Statistics is designed for a new generation of students. This text sparks student interest and bridges the gap between how statistics is taught and how practitioners think about and apply statistical methods. Designed for a one-semester course, the emphasis is on communicating with numbers as opposed to just number crunching. Throughout the text, students are exposed to statistical information using real life examples. The focus is on writing and communicating results rather than merely the process of getting to the correct answer. This unique approach helps present the subject matter in a straightforward and relevant manner. As a result, students learn how to take data, apply it, and convey the results in a meaningful way

CIAM: A data-driven approach for classifying long-term engagement of public transport riders at multiple temporal scales

Many human activities, including daily travel, show a mix of stable, intermittent and changing patterns in demand by individuals over time. However, the lack of continuous, long-term, passenger-linked data for public transport (PT) journeys means that we do not know how passenger ridership evolves in real-world networks. This paper proposes the CIAM model for classifying long-term passenger engagement with PT. CIAM is a data-driven model combining year-on-year churn (C), monthly intensity (I), annual (A) and multi-year (M) engagement. Parameter search algorithms are used to ensure that the learned features are distinctive and robust. We evaluated CIAM using a 5-year dataset from a PT network with over 300 million journeys. CIAM identified distinct patterns of long-term ridership at multiple time scales. Although the total number of annual journeys was relatively stable over the five years, we found long-term differences between passenger subgroups. Churn of passengers was a major factor in ridership with only 55% of passengers retained from year to year. Patterns of annual engagement are often intermittent, so short-term snapshots of a few weeks are typically not good indicators for longer term engagement. Only 27% of high-frequency, full-fare riders still have the same level of engagement four years later, compared with 55% who continue high-frequency engagement after only one year

Assessing the accessibility of activity centres and their prioritisation: a case study for Perth Metropolitan Area

The primary objective of this study was to ascertain, through analysis of accessibility and development potential, which activity centres should be prioritised to support decentralisation of jobs, encourage better integration of transport and land use and ultimately aid the evaluation of a more compact, consolidation and connected city. In doing so, this study evaluated and compared the existing accessibility of different geographic units across the city, including the 34 activity centres identified by the Government of Australia, by the two most frequently use transport modes, namely – public transport and car. The analysis of this study has two parts. Firstly, an isochrone-based measure of accessibility was used for an accessibility modelling across the Perth Metropolitan Area in Western Australia. Secondly, using six node-place based indicators, this paper also endeavoured to prioritise the geographic units that are already better served by public transport, as indicated by the accessibility analysis. Multi-criteria weighed scoring method was applied to calculate a score out of 100 for each of the geographic units. The results of this analysis could help to identify activity centre(s) and other areas in Perth, if any, with higher potentials of being a Transit Oriented Development (TOD) supportive activity centre