北京郊区居民日常生活方式的行为测度与空间—行为互动

doi:10.11821/dlxb201508007

摘要/Abstract

摘要：

郊区化及其对居民日常生活的影响成为近年来城市研究的重要议题。时空行为研究认为推动日常生活方式的郊区化是解决郊区化过程中出现的社会与空间问题的根本措施。从日常生活方式的角度出发,需要利用多维度时空行为指标刻画群体的生活方式类型以分析郊区居民的空间—行为互动机制。本文采用活动空间和出行频率指标构建个体日常生活方式的行为测度方法,并基于2012年在北京上地—清河地区进行的GPS调查数据将郊区居民划分为“空间排斥”、“本地化”、“郊区性”、“两极化”、“城市依赖”五种日常生活方式类型。研究发现不同日常生活方式群体在活动分布、活动频率和交通方式上存在差异;并通过多项logistic模型分析郊区化对于个体日常生活方式的影响,发现工作日居民的日常生活方式受到性别、收入、年龄和工作时长等社会经济属性的影响。同时郊区设施配置直接影响着居民对郊区空间的利用程度,土地混合利用、商业设施密度提高更有可能实现日常生活的郊区化。日常生活方式的行为测度方法有助于分析郊区居民日常行为的复杂性,为理解郊区化提供了独特的视角,为构建城市研究的空间—行为互动理论提供了有力的支持。

关键词: 郊区化, 日常生活方式, 活动空间, 空间—行为互动, 北京

Abstract:

Rapid suburbanization in China is dramatically reshaping the daily life of suburban residents. Characterized by fragmentation, increasing car ownership and job-housing separation, suburbanization is changing the way residents use urban space. In China, long-distance commuting, traffic congestion, spatial mismatch and the low quality of life emerging in the progress of residential suburbanization have caused widespread concerns. Suburbanization of residents' daily life is believed to be a solution to the socio-spatial issues in suburbs. Therefore, scholars have argued that there is an urgent need to introduce behavioral perspectives to the study of suburbanization. This approach will enhance our understanding of the process and the mechanism of suburbanization from the perspective of an individual’s daily life. The important step in this study is to portray the nature of the daily lifestyle in the suburbs. Along with the trend toward behavioral perspectives in human geography, space-time behavior has become an important perspective for the study of urban space. Activity space and travel behavior often serve as important indicators of individual behavior in urban and geographic studies. This study focuses on daily activity-travel behavior, introduces the concept of lifestyle, and brings forward a concept of daily lifestyle based on a combined measure of activity space and trip frequency. The daily lifestyle of suburban residents can be classified into five categories: localization, spatial exclusion, suburbanism, polarization, and city dependence, according to the size of the activity space and the trip frequency. Based on a GPS-facilitated activity-travel survey dataset collected in the Shangdi-Qinghe area in Beijing in 2012, this paper compares the differences in activity-travel behavior among five daily lifestyle groups. The study finds that there are intergroup differences in the spatial distribution of activities, activity participation and modal split among these five lifestyle groups. Furthermore, this paper analyzes the impact of suburbanization on daily lifestyle by examining the relationship between daily lifestyle and built environment while controlling socio-demographic factors using a multinomial logistic model. Women and older people are more likely to be in the categories of localization and spatial exclusion. Low-income people have the higher possibility to be spatially excluded. These outcomes indicate that traditionally disadvantaged groups could be trapped in suburban areas, raising definite concerns for their daily life in suburban areas. Factors associated with the built environment primarily impact the localization lifestyle. Mixed land use in danwei and higher retail density contribute to the concentration of activity space in suburbs, as well as more active travel. The concept of daily lifestyle provides an effective and reasonable way to understand complicated activity-travel behavior of suburban residents. The paper offers a special perspective on understanding suburbanization and the interaction between urban space and individual behavior.

Key words: suburbanization, daily lifestyle, activity space, space-behavior interaction, Beijing

塔娜, 柴彦威, 关美宝. 北京郊区居民日常生活方式的行为测度与空间—行为互动[J]. 地理学报, 2015, 70(8): 1271-1280.

Tana, Yanwei CHAI, Mei-Po KWAN. Suburbanization, daily lifestyle and space-behavior interaction in Beijing[J]. Acta Geographica Sinica, 2015, 70(8): 1271-1280.

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变量		样本数	频率
性别	男性	140	47.78%
	女性	153	52.22%
年龄		36.17
户口	非北京户口	39	13.31%
	北京户口	254	86.69%
个人月收入	低于2000元	32	10.92%
	2001~6000元	180	61.43%
	6001元以上	81	27.65%
教育程度	高中及以下	42	14.33%
	大专或大学	199	67.92%
	研究生及以上	52	17.75%
住房产权	自有住房	254	86.69%
	租住住房	39	13.31%
汽车所有权	有小汽车	185	63.14%
	无小汽车	108	36.86%
家庭规模	1	5	1.71%
	2	68	23.21%
	3	141	48.12%
	4+	79	26.96%

日常生活方式	活动空间	出行频率	样本数
空间排斥	小于等于25%	少于等于平均值	37(12.9%)
本地化	小于等于25%	多于平均值	35(12.2%)
郊区性	大于25%小于等于75%		142(49.7%)
两极化	大于75%	少于等于平均值	28(9.8%)
城市依赖	大于75%	多于平均值	44(15.4%)

	工作活动	休闲娱乐	购物活动	外出就餐
空间排斥	1.22	0.19	0.06	0.47
本地化	1.79	0.24	0.11	0.48
郊区性	1.50	0.21	0.08	0.65
两极化	1.29	0.15	0.03	0.51
城市依赖	1.63	0.22	0.07	0.68

	非机动车出行距离	公交出行距离	小汽车出行距离
空间排斥	3.73	1.04	1.57
本地化	5.04	1.63	1.80
郊区性	2.76	9.62	8.49
两极化	1.34	18.42	16.83
城市依赖	2.91	11.54	28.06

变量	变量类别	备注
1.个人社会经济属性
性别	虚拟变量	1=女性,0=男性
年龄	连续变量
个人收入	连续变量
教育程度	连续变量
户口	虚拟变量	1=北京户口,0=非北京户口
工作时间	连续变量
2.家庭社会经济属性
家庭规模	连续变量
住房产权	虚拟变量	1=自有住房,0=租住住房
汽车所有权	虚拟变量	1=有小汽车,0=无小汽车
3.建成环境属性
休闲设施密度	连续变量	以家为中心500m范围内休闲设施密度
零售商业密度	连续变量	以家为中心500m范围内零售商业设施密度
距离地铁站的距离	连续变量	家与最近的地铁站的直线距离
单位社区	虚拟变量
商品房社区	虚拟变量
保障房社区	虚拟变量
混合社区	参照变量