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中国城市流动人口居留意愿影响因素的空间分异特征
Spatial variation of the determinants of China's urban floating population's settlement intention

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古恒宇 1,2   孟鑫 1,3   沈体雁 1 *   崔娜娜 4  
文摘 流动人口居留意愿的影响因素往往存在显著的空间分异特征,然而既有研究对此关注较少。基于2015年中国流动人口动态监测数据,运用半参数地理加权回归(SGWR)模型,结合k均值聚类法,对中国城市流动人口居留意愿影响因素的空间分异特征展开研究。结论如下: ①流动人口居留意愿主要受流动人口群体自身特征的影响,受流入地的影响相对较弱;②社会经济因素与流动人口居留意愿的关系紧密,人口、家庭及流动特征因素同样产生影响,收入、婚姻、跨省流动等因素对流动人口居留意愿产生抑制作用,而住房支出、参保率、子女个数等因素则产生促进作用;③各影响因素总体上呈现带状的空间分异模式,可概括为“E-W”“N-S” “NE-SW”“SE-NW”4种。民族、家庭等因素的正向影响自北向南递减,参保率、未婚率、二产就业等因素的影响自西北向东南递减,子女个数及人均GDP的影响自东北向西南递减。东部经济较发达地区高收入流动人口的居留意愿相对更弱,华南地区住房支出较高的流动人口居留意愿相对更强。④全国可划分为四大影响区,其中,华北地区、华中地区、华东地区受多因素共同影响;西北地区及部分西南地区主要受人口及社会因素的影响;东北三省及内蒙古东部地区主要受经济及家庭因素的影响;华南地区及部分中、东、西南部地区,除住房支出外,受大部分因素的影响相对最小。最后,本文对中国流动人口的服务与管理提出相应建议。
其他语种文摘 It is demonstrated that the determinants of China's urban floating population's settlement intention are different among geographic units, which seems to be ignored by previous researches. Based on the data from the 2015 national migrant population dynamic monitoring survey (CMDS) and related statistics, this article uses the Semiparametric Geographically Weighted Regression (SGWR) model and k-means cluster method to examine the spatial variation of the factors influencing floating population's settlement intention in 282 prefecture-and provincial-level cites of China. Results provide the following conclusions. (1) The settlement intention of urban floating population is mainly influenced by the floating population characteristics instead of the destination characteristics. (2) Social and economic factors are closely related to the floating population's settlement intention. Meanwhile, the demographic, family and mobility factors exert a significant impact on such an intention. To be specific, there exists an inhibitory effect on floating population's settlement intention in factors such as income, marriage, and cross provincial mobility. However, housing expenditure, participation rate, number of children and other factors can effectively contribute to such intention. (3) Zonal spatial differentiation patterns of the influencing factors' coefficients are illustrated by the SGWR model, which can be further divided into four categories ("E-W", "NS", "NE-SW" and "SE-NW"): The positive influences of ethnic and family factors are decreasing from the northern to southern regions, while the influence of employment ratio in the secondary industry is declining from the northwest to the southeast regions, and the impacts of factors such as the number of children and per capita GDP are diminishing from the northeast to the southwest regions. In eastern developed areas, the settlement intention of floating population with higher income is comparatively lower, while migrants with higher housing expenditure in southern China have a stronger intention to settle down. (4) Four influencing zones are detected by the k-means method: Floating population's settlement intention in North China, Central China and East China is significantly affected by multiple factors; In the northwest region and part of the southwest region, migrants' settlement intention is mainly influenced by demographic and social factors; The northeast region and the eastern part of Inner Mongolia's floating population's willingness to stay is mainly related to economic and family factors; Apart from housing expenditure, coefficients of other factors are relatively small in southern China and part of the central, eastern and southwestern regions. Additionally, this paper puts forward some suggestions on the service and management of the floating population in China.
来源 地理学报 ,2020,75(2):240-254 【核心库】
DOI 10.11821/dlxb202002003
关键词 流动人口居留意愿 ; 影响因素 ; 空间分异 ; 半参数地理加权回归 ; 中国
地址

1. 北京大学政府管理学院, 北京, 100871  

2. 芝加哥大学空间数据科学中心, 美国, 芝加哥, 60637  

3. 华润(深圳)有限公司, 深圳, 518000  

4. 北京交通大学建筑与艺术学院, 北京, 100044

语种 中文
文献类型 研究性论文
ISSN 0375-5444
基金 国家社会科学基金重大项目 ;  国家自然科学基金项目 ;  国家留学基金委公派联合培养博士研究生项目
文献收藏号 CSCD:6711147

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引证文献 37

1 古恒宇 东北三省流动人口居留意愿的空间差异及影响因素 地理科学,2020,40(2):261-269
CSCD被引 11

2 沈体雁 北京市二手住宅价格影响机制--基于多尺度地理加权回归模型(MGWR)的研究 经济地理,2020,40(3):75-83
CSCD被引 87

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