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008 | 210412b ||||| |||| 00| 0 eng d | ||
100 |
_aDang, Yunxiao _945756 |
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245 | _aResidential environment and subjective well-being in Beijing: A fine-grained spatial scale analysis using a bivariate response binomial multilevel model | ||
260 |
_bSage, _c2019. |
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300 | _aVol 46, Issue 4, 2019,(648-667 p.) | ||
520 | _aExisting literature has examined the determinants of subjective well-being in China from the social, economic and psychological perspectives. Very few studies explore the impacts of residential environment on subjective well-being. Drawing on a large scale questionnaire survey in Beijing, this paper investigates the role of residential environment by decomposing the variations of subjective well-being at fine-grained spatial scales, i.e. district and neighbourhood levels. A bivariate response binomial multilevel model is employed to assess the relative importance of geographical contexts and individual characteristics, in particular, the household registration (hukou) status, in influencing subjective well-being. The results show significant heterogeneities in subjective well-being among districts and neighbourhoods. Neighbourhood types are significantly correlated with subjective well-being, with residents in commercial housing neighbourhoods reporting higher levels of subjective well-being than those in work-unit and affordable housing neighbourhoods. However, the impacts of neighbourhood types are not uniformly experienced by people with different hukou status. Migrants tend to express lower levels of subjective well-being than local residents. Such disparities are more pronounced in urban villages compared with other neighbourhoods. | ||
650 |
_aSubjective well-being, _942420 |
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650 |
_aresidential environment, _945757 |
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650 |
_aneighbourhood types, _942205 |
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650 |
_a hukou status, _945758 |
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650 |
_amultilevel model _940110 |
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700 |
_aDong, Guanpeng _933784 |
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700 |
_aChen, Yu _932054 |
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700 |
_aJones, Kelvyn _945759 |
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700 |
_aZhang, Wenzhong _945760 |
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773 | 0 |
_011590 _915512 _dSage 2019. _t Environment and Planning B: Urban Analytics and City Science |
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942 |
_2ddc _cART |