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.

了解家庭搬迁时机的行为在交通工程和经济学领域具有重要意义。本研究旨在通过考虑其他家庭决策和变量的潜在动态影响来开发住宅搬迁模型，包括经济和人口属性、住房特征、家庭内部决策结构、出行方式选择和其他生命历程属性。 . 开发了具有固定和时变协变量的多变量参数生存模型。据作者所知，本研究是住宅搬迁时间文献中第一篇提出使用贝叶斯模型与广泛使用的经典频率论方法形成对比的论文，并对其优势进行了讨论。使用了为澳大利亚和美国的两个城市（悉尼和芝加哥城市）收集的新兴住宅搬迁数据集，其中涵盖了受访者的住宅、车辆所有权、职业、教育、经济和人口统计属性。对两个城市的结果进行了综合比较，并对两种贝叶斯和频率论方法进行了比较。本研究证实了生命历程变量、家庭内部决策行为和社会人口统计属性对家庭流动性的影响。根据模型输出，解释变量对搬迁时机的加速或减速影响在两个城市中几乎相同。贝叶斯模型被证实比频率论模型有一些优势，包括直接解释，