广州市居民工作日小汽车出行个体与社区双层影响机制

doi:10.11821/dlxb201708009

Abstract

Abstract:

The relationship between car travel and built environment is one of the hot issues in the urban studies. The existing researches mainly focus on the respective effects on car travel of individual demographic variables and built environment variables on car travel. Under the background of China's urban transformation and the social space differentiation, a growing number of scholars have examined the relationship between residents' demographics and their residential built environment. Quantifying the relative roles of the individual social attributes and the built environment in influencing car travel has a policy implication. This study applied a multilevel logit model which contains individual-level variables and neighbourhood-level variables to explore the impact on car use. It is concluded that urban residents' working-day car travel is influenced by multilevel variables associated to neighbourhood types. Most of the variation in the travel mode choice is caused by the difference among neighbourhoods. Travel mode choices have a strong neighbourhood contextual effect on car travel. As for the individual level, lower income and education level, collective unit profession, less minors in a family may help refrain the choice of automobile travel. As for the community level, improving bus stops density, building density, land mixing degree and commercial accessibility may help reduce car use ratio of working-day activities' travel. The mechanism of the relationship between two kinds of variables lies in the strength of market effect on urban residential space reconstruction. The residents who have similar social and economic attributes tend to choose the same type of neighbourhood, which has a similar built environment. These conclusions help us to have a better understanding of the mechanism behind the urban residents' working-day car travel and provide suggestions to alleviate the traffic problem by adjusting the multilevel variables in the similar type of community.

Key words: car travel, built environment, multilevel logit model, neighbourhood type, Guangzhou

Suhong ZHOU, Jiangyu SONG, Guangwen SONG. Examining the dual-levels impact of neighbourhood and individual variables on car use on weekdays in Guangzhou[J].Acta Geographica Sinica, 2017, 72(8): 1444-1457.

Figures/Tables 10

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References 38

[1]	Guangzhou Transport Planning Research Institute. Guangzhou Transport Development Annual Report 2013. 2013.
	[广州市交通规划研究所. 2013广州城市交通运行报告. 广州市交通规划研究院. 2013.]
[2]	Zhou Suhong, Yan Xiaopei.The relationship between urban structure and traffic demand in Guangzhou. Acta Geographica Sinica, 2005, 60(1): 130-141. doi: 10.3321/j.issn:0375-5444.2005.01.015
	[周素红, 闫小培. 广州城市空间结构与交通需求关系. 地理学报, 2005, 60(1): 130-141.] doi: 10.3321/j.issn:0375-5444.2005.01.015
[3]	Zhou Suhong, Yan Xiaopei.The impact of commuters' travel pattern on urban structure: A case study in some typical communities in Guangzhou. Acta Geographica Sinica, 2006, 61(2): 179-189. doi: 10.3321/j.issn:0375-5444.2006.02.007
	[周素红, 闫小培. 基于居民通勤行为分析的城市空间解读: 以广州市典型街区为案例. 地理学报, 2006, 61(2): 179-189.] doi: 10.3321/j.issn:0375-5444.2006.02.007
[4]	Chatman D G.How density and mixed uses at the workplace affect personal commercial travel and commute mode choice. Transportation Research Record: Journal of the Transportation Research Board, 2003,1831(1): 193-201. doi: 10.3141/1831-22
[5]	Wang D, Chai Y.The jobs-housing relationship and commuting in Beijing, China: The legacy of Danwei. Journal of Transport Geography, 2009, 17(1): 30-38. doi: 10.1016/j.jtrangeo.2008.04.005
[6]	Zhou Suhong, Yang Lijun.Study on the spatial characteristic of commuting in Guangzhou. Urban Transport of China, 2005, 3(1): 62-67. doi: 10.3969/j.issn.1672-5328.2005.01.015
	[周素红, 杨利军. 广州城市居民通勤空间特征研究. 城市交通, 2005, 3(1): 62-67.] doi: 10.3969/j.issn.1672-5328.2005.01.015
[7]	Sun Bindong, Pan Xin, Ning Yuemin.Analysis on influence of job-housing balance on commute travel in Shanghai. Urban Planning Forum, 2008 (1): 77-82. doi: 10.3969/j.issn.1000-3363.2008.01.012
	[孙斌栋, 潘鑫, 宁越敏. 上海市就业与居住空间均衡对交通出行的影响分析.城市规划学刊, 2008(1): 77-82.] doi: 10.3969/j.issn.1000-3363.2008.01.012
[8]	Cao Xinyu.Examining the relationship between neighborhood built environment and travel behavior: A review from the US perspective. Urban Planning International, 2015, 30(4): 46-52.
	[曹新宇. 社区建成环境和交通行为研究回顾与展望: 以美国为鉴. 国际城市规划, 2015, 30(4): 46-52.]
[9]	Sun Bindong, Dan Bo.Impact of urban built environment on residential choice of commuting mode: A case study of Shanghai. Acta Geographica Sinica, 2015, 70(10): 1664-1674. doi: 10.11821/dlxb201510010
	[孙斌栋, 但波. 上海城市建成环境对居民通勤方式选择的影响. 地理学报, 2015, 70(10): 1664-1674.] doi: 10.11821/dlxb201510010
[10]	Limtanakool N, Dijst M, Schwanen T.The influence of socioeconomic characteristics, land use and travel time considerations on mode choice for medium-and longer-distance trips. Journal of Transport Geography, 2006, 14(5): 327-341. doi: 10.1016/j.jtrangeo.2005.06.004
[11]	Zhou Suhong, Deng Lifang.Spatio-temporal pattern of residents' daily activities based on T-GIS: A case study in Guangzhou, China. Acta Geographica Sinica, 2010, 65(12): 1454-1463. doi: 10.11821/xb201012002
	[周素红, 邓丽芳. 基于T-GIS的广州市居民日常活动时空关系. 地理学报, 2010, 65(12): 1454-1463.] doi: 10.11821/xb201012002
[12]	Gu Jie, Zhou Suhong, Yan Xiaopei.The space-time paths of residential mobility in Guangzhou from a perspective of life course. Geographical Research, 2013, 32(1): 157-165. doi: 10.11821/yj2013010016
	[古杰, 周素红, 闫小培. 生命历程视角下的广州市居民居住迁移的时空路径. 地理研究, 2013, 32(1): 157-165.] doi: 10.11821/yj2013010016
[13]	Kwan M P.Gender and individual access to urban opportunities: A study using space-time measures. Professional Geographer, 1999, 51(2): 210-227. doi: 10.1111/0033-0124.00158
[14]	Chai Yanwei, Wen Guilan, Liu Zhilin.Feminist geographical research on the behavior spaces of female residents in Chinese cities. Human Geography, 2003, 18(4): 1-4. doi: 10.3969/j.issn.1003-2398.2003.04.001
	[柴彦威, 翁桂兰. 刘志林. 中国城市女性居民行为空间研究的女性主义视角. 人文地理, 2003, 18(4): 1-4.] doi: 10.3969/j.issn.1003-2398.2003.04.001
[15]	Shergold I, Lyons G, Hubers C.Future mobility in an ageing society: Where are we heading? Journal of Transport & Health, 2015, 2(1): 86-94. doi: 10.1016/j.jth.2014.10.005
[16]	Zhou S, Deng L, Kwan M P, et al.Social and spatial differentiation of high and low income groups' out-of-home activities in Guangzhou, China. Cities, 2015(45): 81-90. doi: 10.1016/j.cities.2015.03.002
[17]	Srinivasan S, Rogers P.Travel behavior of low-income residents: Studying two contrasting locations in the city of Chennai, India. Journal of Transport Geography, 2005, 13(3): 265-274. doi: 10.1016/j.jtrangeo.2004.07.008
[18]	De Jong G C. An indirect utility model of car ownership and private car use. European Economic Review, 1990, 34(5): 971-985. doi: 10.1016/0014-2921(90)90018-T
[19]	Gliebe J P, Koppelman F S.A model of joint activity participation between household members. Transportation, 2002, 29(1): 49-72. doi: 10.1023/A:1012995509777
[20]	Zhao P.The impact of the built environment on individual workers' commuting behavior in Beijing. International Journal of Sustainable Transportation, 2013, 7(5): 389-415. doi: 10.1080/15568318.2012.692173
[21]	Cervero R, Kockelman K.Travel demand and the 3Ds: density, diversity, and design. Transportation Research Part D: Transport and Environment, 1997, 2(3): 199-219. doi: 10.1016/S1361-9209(97)00009-6
[22]	Ewing R, Cervero R.Travel and the built environment: A meta-analysis. Journal of the American Planning Association, 2010, 76(3): 265-294. doi: 10.1080/01944361003766766
[23]	Frank L D, Engelke P, Schmid T.Health and community design: The impacts of the built environment on physical activity. Washington, DC: Island Press, 2003.
[24]	Cervero R.Mixed land-uses and commuting: Evidence from the American housing survey. Transportation Research Part A: Policy and Practice, 1996, 30(5): 361-377. doi: 10.1016/0965-8564(95)00033-X
[25]	Acker V V, Witlox F.Commuting trips within tours: How is commuting related to land use? Transportation, 2011, 38(3): 465-486. doi: 10.1007/s11116-010-9309-6
[26]	Zhang M.The role of land use in travel mode choice: Evidence from Boston and Hong Kong. Journal of the American Planning Association, 2004, 70(3): 344-360. doi: 10.1080/01944360408976383
[27]	Cao X, Fan Y.Exploring the influences of density on travel behavior using propensity score matching. Environment and Planning B: Planning and Design, 2012, 39(3): 459-470. doi: 10.1068/b36168
[28]	Wang D, Lin T.Residential self-selection, built environment, and travel behavior in the Chinese context. Journal of Transport and Land Use, 2014, 7(3): 5-14. doi: 10.5198/jtlu.v7i3.486
[29]	Naess P.Residential location, travel, and energy use in the Hangzhou metropolitan area. Journal of Transport and Land Use, 2010, 3(3): 27-59. doi: 10.5198/jtlu.v3i3.98
[30]	Wang D, Chai Y, Li F.Built environment diversities and activity-travel behavior variations in Beijing, China. Journal of Transport Geography, 2011,19(6): 1173-1186. doi: 10.1016/j.jtrangeo.2011.03.008
[31]	Chai Yanwei, Liu Zhilin, Li Zhengrong, et al.Time-space Structure of Chinese Cities. Beijing: Peking University Press, 2002: 1-3.
	[柴彦威, 刘志林, 李峥嵘, 等. 中国城市的时空间结构. 北京: 北京大学出版社, 2002: 1-3.]
[32]	Xu Xueqiang, Hu Huaying, Yeh A G O. A factorial ecological study of social spatial structure in Guangzhou. Acta Geographica Sinica, 1989, 44(4): 385-399.
	[许学强, 胡华颖, 叶嘉安. 广州市社会空间结构的因子生态分析. 地理学报, 1989, 44(4): 385-399.]
[33]	Zhou Chunshan, Luo Renze, Dai Dandan.Evolution and mechanism of the residential spatial structure from 2000 to 2010 in Guangzhou. Geographical Research, 2015, 34(6): 1109-1124. doi: 10.11821/dlyj201506010
	[周春山, 罗仁泽, 代丹丹. 2000-2010年广州市居住空间结构演变及机制分析. 地理研究, 2015, 34(6): 1109-1124.] doi: 10.11821/dlyj201506010
[34]	Tana, Chai Yanwei, Kwan M P. The relationship between the built environment and car travel distance on weekdays in Beijing. Acta Geographica Sinica, 2015, 70(10): 1675-1685. doi: 10.11821/dlxb201510011
	[塔娜, 柴彦威, 关美宝. 建成环境对北京市郊区居民工作日汽车出行的影响. 地理学报, 2015, 70(10): 1675-1685.] doi: 10.11821/dlxb201510011
[35]	Wang Fenglong, Wang Donggen.Characteristics and determinants of car use in Beijing. Acta Geographica Sinica, 2014,69(6): 771-781. doi: 10.11821/dlxb201406005
	[王丰龙, 王冬根. 北京市居民汽车使用的特征及其影响因素. 地理学报, 2014, 69(6): 771-781.] doi: 10.11821/dlxb201406005
[36]	Zhang Lei, Lei Li, Guo Boliang, et al.Applied Multilevel Data Analysis. Beijing: Educational Science Publishing House, 2003.
	[张雷, 雷雳, 郭伯良. 多层线性模型应用. 北京: 教育科学出版社, 2003.]
[37]	Xu Y, Wen M, Wang F.Multilevel built environment features and individual odds of overweight and obesity in Utah. Applied Geography, 2014, 60: 197-203. doi: 10.1016/j.apgeog.2014.10.006
[38]	Rajamani J, Bhat C R, Handy S, Knaap G and Song Y. Assessing impact of urban form measures on nonwork trip mode choice after controlling for demographic and level-of-service effects. Transportation Research Record, 2003(1831): 158-165. doi: 10.3141/1831-18

社区类型	特征	典型社区
旧城旧机关社区	旧城社区、旧机关人口和老龄非在业人口比例高	洪庆坊、三眼井、吉祥、小梅、泽德
商业社区	外来人口集中,城市商业从业人口及保障性住房集中	石溪、怡东、穗华、康乐中、王圣堂
高教育旧单位社区	旧单位社区、教育水平高	麓苑、中大、天河直街、广和
郊区社区	近郊住宅区、购房或自建住房集中	三堂、先锋、祈福新村、莲塘

变量		小汽车出行数	小汽车出行比例(%)
性别	男	248	14.55
性别	女	198	8.43
婚姻状况	已婚	411	11.77
婚姻状况	未婚	35	6.23
家庭未成年人个数	0	68	4.23
	1	281	13.44
	2	91	26.38
	3	6	46.15
个人月收入 (元)	1000以下	0	0
	1000~3999	263	9.25
	4000~7999	97	11.89
	8000以上	86	22.63
全样本		446	11.00

社区类型		容积率	人口密度(万人/km²)	用地混合度	商业可达性	公交站点密度(个/km²)	小汽车出行数(辆)	小汽车出行比例(%)
旧城旧机关社区	平均值	3.61	4.33	0.57	1.02	0.26	30	2.14
旧城旧机关社区	标准差	0.56	1.91	0.57	0.51	0.07	30	2.14
商业社区	平均值	2.31	2.91	0.60	0.77	0.18	10	1.27
商业社区	标准差	0.60	1.43	0.16	0.88	0.05	10	1.27
高教育旧单位社区	平均值	2.93	2.91	0.66	1.02	0.26	63	8.33
高教育旧单位社区	标准差	2.80	0.52	0.07	0.27	0.04	63	8.33
郊区社区	平均值	1.54	1.13	0.48	0.21	0.14	343	30.79
郊区社区	标准差	0.93	0.91	0.12	0.17	0.07	343	30.79

层次	类别	指标	定义	均值	标准差	样本数
		出行方式	非小汽车出行=0,小汽车出行=1	0.11	0.31	4055
个体层次	个人社会经济属性	性别	女=0,男=1	0.42	0.49	4055
		文化程度	不识字=1,初识字=2,小学=3,初中=4,高中=5,大专、大学本科=6,研究生以上=7	5.09	0.92	4055
		年龄	单位：岁	38.74	9.91	4055
		婚姻状况	未婚=0,已婚=1	0.86	0.35	4055
		在广州居住时间	单位：年	28.91	16.95	4055
		个人月收入水平	1000元以下=1,1000~3999元=2,4000~7999元=3,8000元以上=4	2.38	0.66	4055
		单位性质	机关=1,事业单位=2,国有企业=3,集体单位=4,股份制企业=5,港澳台及外商投资企业=6,私营企业=7,个体经济=8	5.81	2.12	4055
	家庭属性	全家广州居住人数	单位：个	3.28	1.06	4055
		全家未成年人数	单位：个	0.70	0.63	4055
		房屋建筑面积	单位：m²	73.23	45.72	4055
社区层次	建成环境	建筑密度	单位：%	26.78	12.33	18
		用地混合度		0.58	0.12	18
		POI密度	单位：个/km²	8.34	3.97	18
		商业可达性		2.09	1.27	18
		公交站点密度	单位：个/km²	0.21	0.08	18
	社区类型	旧城旧机关社区				5
		商业社区				5
		高教育旧单位社区				4
		郊区社区				4

层次	方差	ICC指数	卡方检验
个体层次	0.90	0.24	-
社区层次	2.90	0.76	1567.44^***

Examining the dual-levels impact of neighbourhood and individual variables on car use on weekdays in Guangzhou

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类别	变量	固定部分				随机部分
类别	变量	回归系数	OR值	T检验		方差成分	卡方检验
	截距	-5.20	0.01	-6.86^***		9.26	4686.81^***
基本状况	性别	0.21	1.23	0.52		3.76	66.84^***
	文化程度	0.61	1.84	1.86^*	1.49		110.16^***
	年龄	-0.06	0.94	-0.87	0.06		88.35^***
	婚姻状况	-0.88	0.42	-0.84	11.73		111.52^***
	在广州居住时间	0.03	1.03	1.00	0.01		132.98^***
	个人月收入水平	1.72	5.56	1.92^*	1.08		172.44^***
	单位性质	0.25	1.28	2.76^**	0.14		90.74^***
家庭状况	全家在广州居住人数	0.06	1.06	0.21		0.033	65.81^***
	全家未成年人数	1.19	3.28	2.97^***		0.16	108.34^***
	房屋建筑面积	0.02	1.02	3.04^***		0.00	157.92^***

预测变量		固定部分				随机部分
预测变量		回归系数		OR值	t值	方差	卡方值
截距		2.20	9.02	1.83^*		7.28	3021.42^***
建成环境	建筑密度	-0.03	0.97	-6.70^***
	用地混合度	-12.88	0.00	-5.15^***
	POI密度	0.52	1.68	5.60^***
	商业可达性	0.65	1.92	2.05^**
	公交站点密度	-20.3	0.00	-5.18^***

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