000			02298nab a2200229 4500
999			_c11598 _d11598
003			OSt
005			20210331164531.0
007			cr aa aaaaa
008			210331b ||||| |||| 00| 0 eng d
100			_aRashidi, Taha H _945615
245			_aCompeting survival analysis for housing relocation behaviour and risk aversion in a resilient housing market
300			_aVol 46, Issue 1, 2019,(122-142 p.)
520			_aResidential relocation decision making is a complicated process, and modelling this complex course of actions requires careful scrutinisation of different aspects. The relocation decision comprises several different decisions, including the reason for the relocation, relocation timing, and attributes of the desired residence. Among these decisions needing to be taken, the reason for relocation and its timing are decided earlier than others. Depending on the variant reasons and motivations for relocating, its timing may be accelerated or decelerated. Relocation usually occurs because of a multiplicity of reasons, which necessitates using a multivariate model for relocation decision making that is jointly modelled with the timing decision. A competing accelerated failure model to jointly formulate these decisions. The housing search literature emphasizes on the importance of considering financial risk acceptance level of decision makers in residential relocation decision models. Therefore, a binary logit model is used to model whether the decision maker is financially risk averse or not. This paper used longitudinal data collected in Australia from the Household, Income, and Labour Dynamics in Australia Survey. Further, the impact of group decision making on residential relocation is captured in this paper through the information provided in Household, Income, and Labour Dynamics in Australia Survey regarding the manner in which decisions are made within households.
650			_aCompeting hazard model, _945616
650			_a financial risk aversion, _945617
650			_a land use, _945618
650			_aresidential relocation _945619
700			_aGhasri, Milad _945620
773	0		_011590 _915512 _dSage 2019. _t Environment and Planning B: Urban Analytics and City Science
856			_uhttps://doi.org/10.1177/2399808317703381
942			_2ddc _cART