融入就业者感知的职住关系影响因素差异性研究——以乌鲁木齐市为例

doi:10.12118/j.issn.1000-6060.2025.825

Abstract

Abstract:

The urban jobs-housing relationship, which directly impacts commuters’ costs and quality of life, is a crucial indicator of high-quality urban development. In-depth analysis of its underlying mechanisms provides a scientific basis for the optimization of urban spatial structure and enhancing resident welfare. Taking Urumqi of Xinjiang, China, as a case study, drawing on data from a 2024 questionnaire survey data and on Baidu heat maps, this study employs the jobs-housing deviation index to classify types of jobs-housing relationships. Using multinomial logistic regression and spatial lag models, it investigates the differential influencing mechanisms across area types. The findings show that: (1) Urban jobs-housing relationships are categorized into three types: jobs-housing balance, housing-led imbalance, and employment-led imbalance. The central urban area of Urumqi is predominantly characterized by a jobs-housing balance, with areas having employment-led imbalance outnumbering those having housing-led imbalance. The spatial distribution pattern is closely correlated with industrial agglomeration and transportation layouts. (2) Individual characteristics, the objective built environment, and subjective perceptions all had significant influence on the jobs-housing relationship. Regarding individual characteristics, travel mode, educational attainment, and occupation type are common influencing factors. In particular, age, household annual income, and number of household members are critical factors in employment-led imbalance areas; gender and occupation impact housing-led imbalance areas; while household registration and age predominantly affect jobs-housing balance areas. The objective built environment influences the functional bias of the streets: medical facilities and BRT stations promote employment functions, while schools foster residential functions. Subjective perceptions significantly affect the commuting behavior of workers in balanced areas, while workers in both types of imbalanced areas mitigate the negative effects of spatial mismatch through behavioral adjustments.

Key words: jobs-housing balance, commuting time, multinomial logistics regression, Urumqi City

ZHOU Yuntian, DU Hongru, Ranna HAZIHAN, GUO Jiali. Differential analysis of influencing factors in jobs-housing relationships incorporating workers’ perception: A case of Urumqi City[J].Arid Land Geography, 2026, 49(9): 1901-1913.

Figures/Tables 10

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References 33

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数据类型	数据处理
百度热力图	2024年5—6月以1 h为最小单位的研究区内工作日热力图数据。在ArcGIS Pro平台上，通过核密度分析，获取各时段的热力图栅格数据
百度POI	2024年研究区内商业、餐饮、交通、游憩、教育、医疗6类设施POI数据，共85210个点，用于分析客观建成环境对职住平衡的影响
高德路网	2024年研究区内涵盖主干道、次干道、支路等各级道路网络数据。运用ArcGIS Pro网络分析工具提取道路交叉口节点，以街道为单元计算交叉口密度，衡量路网连通性对职住空间分布的影响
调查问卷	2024年城市居民社会满意度调查中18~60岁之间的就业者进行问卷统计。调查时间为2024年5—8月，由各街道办事处组织开展。经数据清洗与编码筛选，得到有效问卷25234份，有效率为81.3%。对问卷中主观感知类变量进行信度效度检验，Cronbach’s α系数为0.818，KMO值为0.783，Bartlett球形检验显著（P<0.01），信度效度良好，可用于后续分析

模型	-2对数似然值	似然比检验
模型	-2对数似然值	卡方	自由度	显著性
就业主导失衡型街道	5687.421	822.711	120	0.000
职住平衡型街道	34435.466	4274.519	120	0.000
居住主导失衡型街道	7113.865	892.208	120	0.000

因子	变量	系数
公共服务设施	医疗设施密度	0.014^***
	商业零售设施密度	0.001^***
	学校密度	-0.124^***
	餐饮服务设施密度	-0.001
交通可达性	道路交叉口密度	-0.007
	公交站点密度	0.031
	BRT站点密度	0.175^***

模型	-2对数似然值	似然比检验
模型	-2对数似然值	卡方	自由度	显著性
就业主导失衡型街道	1458.912	241.922	56	0.000
职住平衡型街道	3435.711	1470.769	56	0.000
居住主导失衡型街道	1733.541	283.585	56	0.000

因子	变量	15~29 min	30~44 min	45~59 min	大于60 min
您认为城市就业者的通勤距离远吗?	很近	-0.498^***	-0.635^***	-0.463^***	-0.523^***
	比较近	-0.181^***	-0.223^***	-0.286^***	-0.315^***
	比较远	0.033	0.345^***	0.850^***	1.016^***
	很远	-0.126	0.114	0.717^***	1.492^***
您认为城市平时道路通畅吗?	非常拥堵	0.146	0.281^**	0.477^***	0.675^***
	比较拥堵	0.180^**	0.400^***	0.310^***	0.429^***
	比较通畅	0.116	-0.058	-0.042	-0.190
	很通畅	-0.142	-0.173	-0.434^***	-0.485^***
您认为公共交通站点设置是否方便?	很不方便	0.162	0.168	0.010	0.457^**
	不太方便	0.228^**	0.062	0.141	0.192
	比较方便	0.108	0.062	0.000	-0.140
	很方便	-0.038	-0.003	-0.192	-0.136
您认为当前街区的商业类型?	较差，种类单一，无法满足生活购物需求	-0.101	-0.133	0.021	-0.126
您认为当前街区的商业类型?	较多，种类齐全，完全满足生活购物需求	-0.164^***	-0.138^***	-0.190^***	-0.162^**

Differential analysis of influencing factors in jobs-housing relationships incorporating workers’ perception: A case of Urumqi City

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