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This study introduces a survey instrument to collect retrospective life-course events, focusing on residential relocation, and it utilizes the survey to evaluate determinants of residential mobility. The survey consists of seven modules collecting information about household structure and household demographics, latest residential relocation, current and previous home, employment, education, vehicle ownership, and travel behavior. The time window of the life-course calendar in the survey is customized according to the latest residential relocation as an anchor point to assist with memory recollection and balance the required input from participants. The survey is used to collect data from a sample of 514 respondents in Sydney, Australia, and another sample of 404 respondents in Chicago, Illinois, in the US. The Cox proportional hazard model is used to analyze residential mobility. The results show primary school commencement is a salient determinant of residential relocation, but its impact is significantly higher in Chicago compared to Sydney. [ABSTRACT FROM AUTHOR]

The dynamics of household behavior regarding home and occupation relocation is a critical consideration in multiple fields, including transport planning, as it influences the majority of daily trips and urban congestion patterns. While a causal dependence between home and occupation relocation has been widely investigated, the simultaneous dependence of relocation durations has not. Here, households' residential and workplace relocation durations are simultaneously modeled using Bayesian, copula-based, multivariate, parametric survival analysis. Three copula formulations are compared. Nested and independent model structures are proposed for modeling occupation durations in households with more than one employed member. A comprehensive, retrospectively revealed, life-course dataset with a focus on the homeownership, occupation, education, and vehicle ownership statuses of households was collected from Chicago, USA, and Sydney, Australia. The impacts of sociodemographic, home, and occupational attributes were mostly consistent in both cities, demonstrating similarities in the behaviors of their metropolitan residents. The results reveal that, contrary to expectations, home and workplace relocation durations are not necessarily strongly correlated. This result prompts many valuable research directions in this field. • A simultaneous model of residential and workplace relocation durations, comparison of multiple copula dependence structures. • Nested and multiplication job duration dependence structures used to model households with more than one employed member. • Survival models considering dynamic variables including economic and demographic, housing, intra-household decision-making. • A Bayesian method is utilized for the parameter estimation. • A case study on the data of two cities in Australia and the US (Sydney and Chicago cities). [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]