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Shared Micromobility systems in urban regions hold the potential to reduce private vehicle usage and boost public transport patronage. To effectively achieve these goals, a comprehensive approach to integrating micromobility and public transport is essential. This study introduces a novel modelling framework to elicit travellers' preferences towards the features of integrated shared micromoiblity and public transport systems. The data is obtained from a stated preference survey involving 250 residents in Canberra, Australia. Respondents' mode choice behaviour and their propensity to switch from their current mode of transport to an integrated system are collected and modelled using a hierarchical latent class approach to account for taste heterogeneity and attribute non-attendance. The results show higher propensity of mode shift is associated with young age, high educational attainment, high scooter ownership and low car ownership. On average, respondents in this study express a willingness to pay of $0.55 for an integrated payment option. These results provide valuable insight into the integrated urban transport systems. [ABSTRACT FROM AUTHOR]

• This study examined the impact of communication channels on AV consideration. • Men are more likely to belong to segments with higher AV consideration. • Social media sentiment has the largest positive effect on AV consideration for 90% percent. • Family members, men, and contacts with fulltime job and college education are trusted more. • Interactions with social contacts on social media increases the trust. The emerging technology of autonomous vehicles (AVs) is envisaged to substantially alter transport systems and travel behaviour. However, this impact is conditional on the level and rate of AV market penetration. This study examines consumers' consideration to adopt AVs, with a particular focus on the impact of informational cues from different communication channels. Data for our analysis is collected through an online survey conducted in December 2019, and our sample comprises 862 residents from Sydney, Australia. The survey asks respondents about their social networks, and their use of different mass and social media platforms. Respondents are subsequently presented a discrete choice experiment where we systematically vary informational cues about AVs from each of these communication channels, and respondents are asked to indicate their willingness to consider AVs under each scenario. This data is used to develop a latent class choice model of AV consideration as a function of the informational cues received from different communication channels. Our model also considers the level of trust that respondents associate with their social contacts when modelling the effect of word-of-mouth from these social contacts. The results reveal eleven segments in the sample that differ from one another in terms of sociodemographic attributes, evaluation of social contact trust, and the relative importance they attach to different communication channels. The findings show social media sentiment has the highest effect on AV consideration for 90 per cent of the sample. Also 3.8 per cent of the sample never consider adopting AVs, regardless of the informational cues. [ABSTRACT FROM AUTHOR]

Understanding households' behaviour in residential relocation timing is of great importance in the field of transport engineering and economics. This research aims to develop a residential relocation model by considering the potential dynamic impacts of other households' decisions and variables, including economic and demographic attributes, housing features, intra-household decision-making structures, travel mode choice, and other life-course attributes. A multivariate parametric survival model with both fixed and time-varying covariates is developed. To the best of the authors' knowledge, this study is the first paper in the literature of residential relocation timing to propose the use of a Bayesian model in contrast to the widely used classic frequentist approach and have conducted a discussion on its advantages. An emerging residential relocation dataset collected for two cities in Australia and the USA (Sydney and Chicago cities) has been used, which covers residence, vehicle ownership, occupation, education, economic and demographic attributes of respondents. A comprehensive comparison between the results of two cities and a comparison between two Bayesian and frequentist approaches are made. This study confirms the impact of life-course variables, intra-household decision-making behaviours, and sociodemographic attributes on home mobility. According to the model outputs, the accelerating or decelerating impact of explanatory variables on the relocation timing has been almost the same in the two cities. The Bayesian model was confirmed to have some advantages over the frequentist model, including being straightforward to interpret, availability of making inferences on the results, and ease of handling complex models, and optimisation convergence complexities. • A model of residential relocation timing with dynamic variables. • Variables including demographic, housing, intra-household decision-making, travel mode choice, and life-course attributes. • A multivariate survival model with both fixed and time-varying covariates is utilised. • A Bayesian approach compared to the classic frequentist approach. • A case study on the data of two cities in Australia and USA (Sydney and Chicago cities) is run. [ABSTRACT FROM AUTHOR]