居住自选择视角下城市建成环境对通勤模式选择的影响——以兰州市主城区为例

doi:10.12118/j.issn.1000－6060.2023.074

摘要/Abstract

摘要：

交通方式选择研究对于城市高效、可持续和安全的交通规划至关重要。以兰州市主城区为例，基于分布式认知理论，采用调查问卷数据、路网数据、POI数据，通过结构方程模型探讨居住自选择效应影响下非随机异质性的建成环境对通勤模式选择的影响。结果表明：（1）居民根据自身社会经济属性及态度偏好选择不同建成环境特征的住宅小区，继而形成特定的通勤模式，说明居住自选择存在偏好异质性，居住自选择效应存在。（2）在规避居住自选择效应后，建成环境依然对通勤模式选择具有显著影响。具体来讲，人口密度、路网密度及停车位数量直接影响通勤模式选择，路网密度、公交站点可达性、地铁站点可达性及停车位数量通过中介变量通勤距离与小汽车拥有间接影响通勤模式选择。（3）高人口密度、密路网与高可达性的建成环境通过提高道路网络的连通性、步行与公共交通的连接性进一步推动积极通勤模式与公共交通通勤模式选择，引导居民向积极通勤模式为主导的出行结构转变。

关键词: 建成环境, 通勤模式, 居住自选择, 结构方程模型, 兰州市

Abstract:

Research on travel mode choice is essential for efficient, sustainable, and safe urban traffic planning. This study selected the main urban area of Lanzhou City, Gansu Province, China as the study area, and based on the distributed cognitive theory, questionnaire data, road network data, and Point of Interest (POI) data. The structural equation model was used to explore the impact of nonrandom heterogeneity of the built environment on selecting the commuting mode under the influence of the residential self-selection effect. The study found that: (1) Residents chose residential quarters with different built-environment characteristics according to their socioeconomic attributes and attitude preferences. Subsequently, they formed a specific commuting pattern, indicating preference heterogeneity in residential self-selection and the existence of the residential self-selection effect. (2) The built environment continued to have a considerable impact on the choice of commuting mode even after avoiding the self-selection effect of residence. Specifically, population density, road network density, and the number of parking spaces directly affected the choice of commuting mode. Road network density, bus station accessibility, subway station accessibility, and the number of parking spaces indirectly influenced the choice of commuting mode through mediating variables, such as commuting distance and car ownership. (3) High-population density, dense road network, and high-accessibility of the built environment increased the active and public transportation commuting modes. This was achieved by improving the connectivity of road networks, connection between walking and public transit, and pedestrian-friendly environment and by guiding residents to a shift in the travel structure, led by active commuting patterns.

Key words: built environment, commuting mode choices, residential self-selection, structural equation model (SEM), Lanzhou City

郭燕, 张志斌, 陈龙, 马晓敏, 赵学伟. 居住自选择视角下城市建成环境对通勤模式选择的影响——以兰州市主城区为例[J]. 干旱区地理, 2024, 47(2): 307-318.

GUO Yan, ZHANG Zhibin, CHEN Long, MA Xiaomin, ZHAO Xuewei. Impact of urban built environment on commuting mode choices from the residential self-selection perspective[J]. Arid Land Geography, 2024, 47(2): 307-318.

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变量	变量符号	样本量	变量描述	变量	变量符号	样本量	变量描述
性别	GENDER	1384	虚拟	家庭规模	HS	1384	等级
男		722（52.16%）	0	单身		115（8.31%）	1
女		662（47.84%）	1	两口人		151（10.91%）	2
年龄（岁）	AGE	1384	等级	三口人		239（17.27%）	3
18~30岁		151（10.91%）	1	四口人		520（37.57%）	4
31~40岁		625（45.16%）	2	五口人		319（23.05%）	5
41~50岁		235（16.98%）	3	六口人		40（2.89%）	6
51~60岁		231（16.69%）	4	学历	EDU	1384	等级
60岁及以上		142（10.26%）	5	高中/中专及以下		657（47.47%）	0
户籍	HR	1384	虚拟	本科/大专及以上		727（52.53%）	1
外地		1000（72.25%）	0	家庭人均月收入/元	INCOME	1384	等级
本地		384（27.75%）	1	≤2000		102（7.37%）	1
小汽车拥有	CAR	1384	虚拟	2001~4000		291（21.03%）	2
否		556（40.17%）	0	4001~6000		440（31.79%）	3
是		828（59.83%）	1	6001~8000		261（18.86%）	4
房屋产权	HPR	1384	虚拟	8001~10000		151（10.91%）	5
非自有产权		213（15.39%）	0	>10000		139（10.04%）	6
自有产权		1171（84.61%）	1

维度	观察变量	变量符号	处理过程	均值	标准差
密度	人口密度/人·m^-2	RD	基于七普对Worldpop人口栅格数据修正，计算15 min出行范围内单位面积栅格人口数据	0.25	0.22
密度	公共服务设施密度/个·m^-2	PD	15 min出行范围内教育服务、交通设施、娱乐设施、餐饮购物、生活服务POI点数量/面积	0.01	0.07
多样性	土地利用混合度	LUM	15 min出行范围内各类POI点熵值数表示，取值范围0~1^[10]	0.79	0.07
道路设计	路网密度/km·km^-2	RND	15 min出行范围内道路长度/面积	0.22	0.17
道路设计	交叉口比重/个·km^-2	CD	15 min出行范围内交叉口数量/面积	0.11	0.14
可达性	公交站可达性	BSI	基于步行指数测算15 min出行范围内样本点至公交站点的路径距离，再根据距离衰减规律对路径距离的长短赋值	0.97	0.11
可达性	地铁站可达性	MSI	基于步行指数测算15 min出行范围内样本点至地铁站点的路径距离，再根据距离衰减规律对路径距离的长短赋值	0.24	0.35
目的地距离	距公共广场中心距离/km	DTC	居住点到主要公共广场西关什字的路径距离	0.35	0.25
	停车位数量	PARK	15 min出行范围内停车位数量	0.04	0.11

机动化出行方式	最终能源消耗/L·100^-1km,KWh·km^-1	容量/人	一次能源消耗/MJ·Pkm^-1	碳排放因子/g·Pkm^-1
小汽车	11.00	1.30	0.84	233.10
公交车	35.00	40.00	0.35	26.00
班车/楼巴	30.00	44.00	0.27	20.30
地铁	5.00	216.00	0.26	20.90
摩托车/电动车	1.50	1.20	0.70	50.00

适配度指数	注释	参考值	模型结果
绝对适配度指数
χ²	卡方值		194.358
GFI	拟合优度指标	>0.90	0.978
AGFI	调整后适度匹配指数	>0.90	0.949
RMR	残差均方和平方根	<0.05	0.022
RMSEA	渐进均方和平方根	<0.05	0.025
增值适配度指数
NFI	规准适配指数	>0.90	0.953
IFI	增值适配指数	>0.90	0.986
TLI（NNFI）	非规准适配指数	>0.90	0.968
CFI	比较适配指数	>0.90	0.985
简约适配度指数
PGFI	省检拟合优度指数	>0.5	0.415
PNFI	省检规准适配指数	>0.5	0.438
NC（χ²自由度比值），CMIN/DF	卡方自由度比值	1~3	1.408

外生变量	内生变量
外生变量	GENDER	AGE	HS	EDU	HR	HPR	INCOME	AP1	AP2	AP3	AP4	AP5
RD	-	0.132^***	-	-	-	-	-	-	0.043	-	-	0.048
PD	-	-	-	-	-	-	-	-	0.050	-	-	-
LUM	-	-	-	-	-	0.046^*	0.099^***	-	0.055^**	-	0.002	-
RND	0.066^**	0.115^***	-	-	-	-	-	-	0.038^*	0.072^**	0.017	-
CD	0.043	0.090^**	-	-0.077^***	-	-	-	-	-	0.124^***	-	-
BSI	-	0.005	-0.057^**	-	-	-	-	0.079^*	-0.053	0.064^**	-	-
MSI	-	-	-	-	0.057	-	-0.085^**	-	-	-	-	-
DTC	0.062^*	-0.071^**	-	-	0.077^**	-	-0.073^**	-	-	-	0.059^*	-
PARK	-	-0.054	-0.102^***	-	-	0.066^*	0.077^**	-	0.061	-	-	0.071^*
TD	0.078^**	-0.075^*	-	0.100^**	-0.049	0.191^***	-	0.042	-	-	-	-
CAR	0.092^**	-0.044	0.136^***	0.137^***	0.041	0.144^***	0.253^***	-0.008	-	-	-	0.062^*
CM	-0.072^**	-0.102^***	-0.030	-0.067^*	0.003	0.063^*	0.130^***	-0.029	-0.036^*	-0.071^**	-0.032	0.021^*