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Values lie at the heart of an individual's belief system, serving as prototypes from which attitudes and behaviors are subsequently manufactured. Attitudes and behaviors may evolve over time, but values represent a set of more enduring beliefs. This study examines the influence of values on travel mode choice behavior. It is argued that personal values influence individual attitudes towards different alternative attributes, which in turn impact modal choices. Using data from a sample of 519 German commuters drawn from a consumer panel, the study estimates an integrated choice and latent variable model of travel mode choice that allows for hierarchical relationships between the latent variables and flexible substitution patterns across the modal alternatives. Results from the empirical application support the value-attitude-behavior hierarchical model of cognition, and provide insights to planners and policy-makers on how better to sell public transit as a means of travel.Electronic supplementary material The online version of this article (

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This research investigates patterns and dynamics of population, migration and economic change in Australian regional urban centres 2011–2016 through the changing economic profile and performance of Australia’s regional urban centres and assesses how demographic and migration patterns are shaping and responding to economic change.The contribution of regional urban centres to Australia’s economic and population growth has been a topic of growing policy interest in the past two decades, as a result of rapid growth in the major cities and concerns for parts of regional Australia that have experienced population decline. Associated with these trends is the distribution of economic activity and employment—particularly as traditional regional strengths such as agriculture, manufacturing and mining have declined as sources of employment in recent decades.This analysis identifies three significant trends: larger and metropolitan-proximate regional urban centres are generally increasing in population more rapidly than other regional urban centres; coastal urban centres have experienced faster population growth rates than inland urban centres; and population losses tend to be concentrated in inland, smaller, remote and often resource-reliant towns.

Background/objectives An element of obesity prevention is increasing total physical activity energy expenditure. However, this approach does not incorporate the balance of various movement behaviors-physical activity, sedentary behaviors and sleep-across domains of the day. We aimed to identify time-use profiles over work and leisure, termed 'movement behavior profiles' and to investigate their association with obesity. Subjects/methods Eight-hundred-and-seven workers completed (a) thigh accelerometry and diaries to determine their 24-h composition of behaviors (sedentary and standing, light physical activity and moderate-to-vigorous physical activity at work and leisure, and time in bed) and (b) obesity measurements. Movement behavior profiles were determined using latent profile analyses of isometric log-ratios of the 24-h composition, and labeled according to animal movement behavior traits. Linear models were applied to determine the association between profiles and obesity. Results Four profiles were identified, labeled as "Chimpanzees" (n = 226), "Lions" (n = 179), "Ants" (n = 244), and "Koalas" (n = 158). "Chimpanzees" work time was evenly distributed between behaviors while their leisure time was predominantly active. Compared to Chimpanzees, "Lions" were more active at work and sedentary during leisure and spent more time in bed; "Ants" were more active at work and during leisure; "Koalas" were more sedentary at work and leisure and spent similar time in bed. With "Chimpanzees" as reference, "Lions" had least favorable obesity indicators: +2.0 (95% confidence interval [CI] 0.6, 3.4) %body fat, +4.3 cm (1.4, 7.3) waist circumference and +1.0 (2.0, 0.0) Body Mass Index (BMI), followed by "Koalas" +2.0 (0.4, 3.7) %body fat, +3.1 cm (0.1, 6.0) waist circumference, and +0.8 (−0.30, 1.94) BMI. No significant differences were found between "Chimpanzees" and "Ants". Conclusions Movement behavior profiles across work and leisure time-use compositions are associated with obesity. Achieving adequate balance between work and leisure movement behaviors should be further investigated as a potential obesity prevention strategy.

This study proposes a mixed logit model with multivariate nonparametric finite mixture distributions. The support of the distribution is specified as a high-dimensional grid over the coefficient space, with equal or unequal intervals between successive points along the same dimension; the location of each point on the grid and the probability mass at that point are model parameters that need to be estimated. The framework does not require the analyst to specify the shape of the distribution prior to model estimation, but can approximate any multivariate probability distribution function to any arbitrary degree of accuracy. The grid with unequal intervals, in particular, offers greater flexibility than existing multivariate nonparametric specifications, while requiring the estimation of a small number of additional parameters. An expectation maximization algorithm is developed for the estimation of these models. Multiple synthetic datasets and a case study on travel mode choice behavior are used to demonstrate the value of the model framework and estimation algorithm. Compared to extant models that incorporate random taste heterogeneity through continuous mixture distributions, the proposed model provides better out-of-sample predictive ability. Findings reveal significant differences in willingness to pay measures between the proposed model and extant specifications. The case study further demonstrates the ability of the proposed model to endogenously recover patterns of attribute non-attendance and choice set formation.3

While it is increasingly popular to broadcast information regarding environmental impact, little is known regarding the effects that this information has on human behavior. This research aims to provide insight into whether, and to what extent, presenting environmental attributes of transport alternatives influences individual transport decisions. We designed and conducted three experiments in which subjects (UC Berkeley undergraduates) were presented with hypothetical scenarios of transport decisions, including auto purchase choice, mode choice, and route choice. We analyzed their decisions via a choice model to determine how they value reducing their emissions relative to other attributes. We found that our subjects are willing to adjust their behavior to reduce emissions, exhibiting an average willingness to pay for emissions reduction, or value of green (VoG), of 15 cents per pound of CO 2 saved. Despite concern that people cannot meaningfully process quantities of CO 2 , we found evidence to the contrary in our subject pool in that the estimated VoG was consistent across context (the wide range of transport decisions that we presented) and presentation (e.g., whether the information was presented in tons or pounds, or whether a social reference point of the emissions of an average person was provided). We also found significant heterogeneity in VoG, with most of the respondents valuing green somewhere between 0 and 70 cents per pound and with women, on average, willing to pay 7 cents more per saved pound than men. While the findings are encouraging, further work is required to determine whether they hold outside of a lab environment and with a more representative pool of subjects.

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