A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Adopting a random forest approach to model household residential relocation behavior
Abstract Although many studies have investigated the impact of residential relocation on travel behaviors, few studies examine how influencing factors affect residential relocation behavior. Using data from 903 families who have moved in Beijing (China), this study builds a random forest model to evaluate the relative importance and impact ways of the built environment, commuting distance, housing price, living area, and household socio-economic and demographic attributes on the residential relocation behavior of families with commuting workers or students. The results show that the built environment has the greatest influence on the relocation behavior, followed by housing price, commuting distance, socio-economic and demographic attributes, and the living area. In addition, this study finds that the effects of the built environment, commuting distance, and housing price on relocation behavior are nonlinear and have thresholds. This study can help urban planners and managers to quantitatively understand the impact of influencing factors on residential relocation behavior and provide reference values for planners and real estate development companies to plan and develop related land reasonably.
Highlights The relative importance of impact factors on the relocation behavior are analyzed. The nonlinear and threshold effects on the relocation behavior are explored. Reference values of each planning index for the residential land are proposed.
Adopting a random forest approach to model household residential relocation behavior
Abstract Although many studies have investigated the impact of residential relocation on travel behaviors, few studies examine how influencing factors affect residential relocation behavior. Using data from 903 families who have moved in Beijing (China), this study builds a random forest model to evaluate the relative importance and impact ways of the built environment, commuting distance, housing price, living area, and household socio-economic and demographic attributes on the residential relocation behavior of families with commuting workers or students. The results show that the built environment has the greatest influence on the relocation behavior, followed by housing price, commuting distance, socio-economic and demographic attributes, and the living area. In addition, this study finds that the effects of the built environment, commuting distance, and housing price on relocation behavior are nonlinear and have thresholds. This study can help urban planners and managers to quantitatively understand the impact of influencing factors on residential relocation behavior and provide reference values for planners and real estate development companies to plan and develop related land reasonably.
Highlights The relative importance of impact factors on the relocation behavior are analyzed. The nonlinear and threshold effects on the relocation behavior are explored. Reference values of each planning index for the residential land are proposed.
Adopting a random forest approach to model household residential relocation behavior
Xue, Fei (author) / Yao, Enjian (author)
Cities ; 125
2022-01-29
Article (Journal)
Electronic Resource
English
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