文献类型：期刊文献

中文题名：北京居民生活满意度的多层级定序因变量模型分析

英文题名：Influencing Factors of Residents' Life Satisfaction:A Study Based on Ordered Category Response Multilevel Modelling in Beijing

作者：党云晓[1,2,3];余建辉[1,2];张文忠[1,2];李业锦[4];谌丽[5];湛东升[1,2]

第一作者：党云晓

机构：[1]中国科学院区域可持续发展分析与模拟重点实验室;[2]中国科学院地理科学与资源研究所;[3]中国科学院大学;[4]首都师范大学资源环境与旅游学院;[5]北京联合大学应用文理学院

第一机构：中国科学院区域可持续发展分析与模拟重点实验室,北京100101

年份：2016

卷号：36

期号：6

起止页码：829-836

中文期刊名：地理科学

外文期刊名：Scientia Geographica Sinica

收录：CSTPCD;;Scopus;北大核心:【北大核心2014】；CSCD:【CSCD2015_2016】；

基金：国家自然科学基金项目(41230632;41201169)资助~~

语种：中文

中文关键词：多层级模型;定序因变量;生活满意度;北京

外文关键词：life satisfaction; influencing factors; multilevel modelling; Beijing

摘要：传统经济学视角出发的个体生活满意度研究往往忽略了数据的嵌套性,多层级模型更适用于地理学中分析不同层级地理单元特征对个体生活满意度的影响。采用多层级定序因变量模型,以北京为例,研究居民生活满意度在城市内部街道和居住小区尺度内的异质性,并研究了高层级地理空间单元的属性特征对居民生活满意度的影响。结果表明,生活满意度在居住小区层级的异质性远高于街道层级,个体自身的社会经济属性对个体的生活满意度有显著影响,总的来说,高收入、老年人、北京户口居民的生活满意度更高。除个体属性特征以外,居住小区的类型是影响生活满意度的重要因素,商品房小区居民的满意度显著高于保障房和单位房小区居民。
Life satisfaction, a stable and long felling of life, denotes how well people thrive. In the last decade,scholars from different academic fields including psychology, sociology, geography, economy and so on have contributed a lot of research on the relevant topics. Besides, life satisfaction is also increasingly being seen as an essential element for the quality of urban development and government policy, therefore, followed by the scientific interests is the concern of administrative authorities who believe public policy should be about enhancing life satisfaction of the people. Although the highest rate of growth in GDP in Chinese urban, the economic growth did not promise an equal level of the improvement of residents＇ life satisfaction.According to the previous research, there is little study that focus on life satisfaction from the perspective of Human Geography in China, especially lack of research that the influence of geographical unit effect on residents＇ life satisfaction. Traditionally, single-level model was used in previous research to analyze the influence, which ignoring the similarity of individuals who living in same geographical unit and the clustering effect of groups.Worse still, single-level models do not fully exploit the hierarchical nature of geography data that are increasingly available and that can be utilized to provide more information about the role of geography at different spatial scales. In this aticle, we use ordered category response multilevel model to analyze that how the characteristics of sub-districts and community affect residents＇ life satisfaction. Based on large scale survey in 2013 in case of Beijing, several conclusions are drawn as follows： 1） There are life satisfaction heterogeneity both at sub-district and community level, and the heterogeneity at community level is bigger than sub-district level. 2）Individual attributes also affect subjective well-being（SWB）. In general, weak groups, such as low-income families, nonlocal hukou people and old people, are more likely be unsatisfied about their life. 3） Type of community has significant impact on life satisfaction. The closeness of community and high identity of residents in same community should largely responsible for this. Residents living in commercial housing are more likely feel satisfied about life than affordable housing and unit housing. Currently, diverse community is the inevitable choice for the rapid progress of urbanization as it provides more choices for urban families to access housing opportunities. However, community disparity also deeps residents＇ SWB gap, implying that it should be given due attention to promote living environment of affordable and unit housing, further improve residents＇ sense of well-being. Furthermore, in current metropolitan cities in China, it is the weak groups who are most unsatisfied about their life and always need help and concern from government most urgently. Because of institutional and economic factors, they are always excluded from the preferential policy provided to urban residents, and have few opportunities to access to good life in urban, especially for rural migrant workers.