摘要
利用2021年9月至12月的手机信令数据、POI及网络数据等多源数据,以前人对北京城市职住空间研究的结论为参照系,对空间错位指数进行测度与比较,并利用地理探测器方法,分析挖掘居住和工作在北京中心城区出生于1995-2010年的“Z世代”群体居住—就业空间的职住特征及其影响因素。结果表明:1)北京“Z世代”的居住空间和就业空间总体呈现多集聚小组团的特点,且与北京城市居住—就业中心的总格局基本一致,但空间错位指数要高于全年龄段;2)所在地区的生活设施配置、交通条件是影响“Z世代”对居住地和工作地选择的主要因素,房价也是影响居住地选择的重要因素;3)“Z世代”的职住空间选择影响因子均存在交互作用,表现为双因子增强和非线性增强,说明居住地和工作地选择受到多个条件的协同作用。
By using multi-source data such as mobile signaling data from September to December 2021,POI data,open source data on the internet,and the previous research conclusions on Beijing’s job-housing space as a reference frame,this paper measured and compared the spatial displacement index.What’s more,by using the method of Geo-detector,the occupational and residential characteristics and influencing factors of the“Generation Z”population born from 1995 to 2010 living and working in the central urban area of Beijing were analyzed and excavated.The results show that:1)The residential and employment spaces of“Generation Z”in Beijing generally exhibit the characteristics of multi clusters,and are basically consistent with the overall pattern of urban residential-employment centers in Beijing,but the spatial dislocation index is higher than that of all age groups;2)It was found that the configuration of living facilities and transportation conditions in the region are the main factors affecting the choice of residence and work place for“Generation Z”,and housing prices are also important factors affecting the choice of residence place;3)It was found that the influencing factors of occupational and residential space selection in“Generation Z”all have interactive effects,manifested as dual factor enhancement and non-linear enhancement,indicating that the selection of residence and workplace is influenced by multiple conditions in synergy.
作者
张彭飞
张景秋
ZHANG Pengfei;ZHANG Jingqiu(College of Applied Arts and Science,Beijing Union University,Beijing 100191,China)
出处
《北京联合大学学报》
2024年第1期47-56,共10页
Journal of Beijing Union University
基金
国家自然科学基金项目(41771187)。
关键词
多源数据
职住空间
Z世代
空间错位
地理探测器
multi-source data
job-housing space
Generation Z
spatial dislocation
Geo-detector