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Relationships between consecutive long-term and mid-term mobility decisions over the life course: a bayesian network approach

Relationships between consecutive long-term and mid-term mobility decisions over the life course: a bayesian network approach

Wang, Bobin ORCID: 0000-0003-4437-2490, Rasouli, Soora, Timmermans, Harry and Shao, Chunfu (2018) Relationships between consecutive long-term and mid-term mobility decisions over the life course: a bayesian network approach. Transportation Research Record: Journal of the Transportation Research Board, 2672 (47). pp. 159-170. ISSN 0361-1981 (Print), 2169-4052 (Online) (doi:https://doi.org/10.1177/0361198118777604)

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Abstract

Long-term and mid-term mobility decision processes in different life trajectories generate complex dynamics, in which consecutive life events are interrelated and time dependent. This study uses the Bayesian network approach to study the dynamic relationships among residential events, household structure events, employment/education events, and car ownership events. Using retrospective data obtained from a web-based survey in Beijing, China, first structure learning is used to discover the direct and indirect relationships between these mobility decisions. Parameter learning is then applied to describe the conditional probabilities and predict the direct and indirect effects of actions and policies in the resulting network. The results confirm the interdependencies between these long-term and mid-term mobility decisions, and evidence the reactive and proactive behavior of individuals and households in the context of various life events over the course of their lives. In this regard, it is important to note that an increase in household size has a contemporaneous effect on car acquisition in the future; while residential events have a synergic relationship with employment/education events. Moreover, if people’s residential location or workplace/study location will move from an urban district to a suburban or outer suburban district, it has both lagged and concurrent effects on car acquisition.

Item Type: Article
Uncontrolled Keywords: long-term and mid-term mobility, life events, life trajectory, bayesian network approach
Subjects: H Social Sciences > H Social Sciences (General)
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of Systems Management & Strategy
Faculty of Business > Networks and Urban Systems Centre (NUSC)
Faculty of Business > Networks and Urban Systems Centre (NUSC) > Connected Cities Research Group
Last Modified: 21 May 2020 16:57
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: REF 4
URI: http://gala.gre.ac.uk/id/eprint/28204

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