基于叙述性偏好法的城市居住环境质量评价方法研究

doi:10.13249/j.cnki.sgs.2013.01.8

Abstract

Abstract:

Quality of Residential Environment (QRE) is becoming an important goal of modern society. With the rapid advancement of urbanization in China, many issues are emerging in fields of the society, space, security and so on. Urban residents have been increasingly concerned about the QRE that reflects their actual living conditions. As a result, urban planners have been studying the evaluation of QRE in terms of residential environment since the 1980s. A variety of evaluation methods have been explored, among which economic models have been increasingly used for QRE evaluation in recent years. The purpose of this study is to build a system for evaluating residential environment of Chinese cities, by exploring the mechanisms of the elements influencing the quality of residential environment. Stated preference method (SP), a mature approach in the areas of environmental impact assessment, is used to estimate the influence based on the data of residents’ choices from the virtual urban environments composed of elements that considered important for defining quality of residential environment. Yangpu District of Shanghai was taken as the example. Firstly, a pilot survey was implemented, which asks the residents to choose the elements influencing the quality of residential environment most. A system of residential environment evaluation is proposed, focusing on 3 indexes including convenience, comfort and security. Each index includes 4 sub-indexes. Secondly, residents’ preference data were obtained through SP surveys. Then the evaluation functions taking into account convenience, comfort and security of living environment were estimated based on discrete choice models. At last the results of the SP survey and modeling were validated with a comparative analysis on separate elements’ impact on QRE. The validation results show that the models of the convenience, comfort and the comprehensive elements were well fitted, while the model of the security fitted relatively poorly. The case study in Yangpu District shows that elements of convenience and comfort have more influences on QRE evaluation than elements of security. To maintain certain QRE, more improvements of other elements are needed for compensating the ambient noise and security elements’ decline. It is also found that people who are low-educated, female, old, with low income are more sensitive to the basic elements that affect their daily lives. When the level of basic elements decline, residents need more compensation from other elements to keep up their QRE level.

Key words: Stated preference method, Quality of Residential Environment (QRE), Shanghai

CLC Number:

K901.8

Qian ZHAO, De WANG, Wei ZHU. Quality of Urban Residential Environment Based on Stated Preference Methods[J].SCIENTIA GEOGRAPHICA SINICA, 2013, 33(1): 8-8.

Figures/Tables 4

Table 1

Table 2

Table 3

Fig.1

References 32

[1]	朱锡金. 居住环境的构成与质量评价[J].城市规划汇刊,1980,(4):37~48.
[2]	陈青慧,徐培玮.城市生活居住环境质量评价方法初探[J].城市规划,1987,(5):52~58.
[3]	宁越敏,查志强.大都市人居环境评价和优化研究——以上海市为例[J].城市规划,1999,(6):15~20.
[4]	陈浮. 城市人居环境与满意度评价研究[J].城市规划,2000,(7):25~27.
[5]	巩如英,王飞,王颖,等.济南市城市居住区外部环境空间的评价[J].林业调查规划,2008,33(1):137~141.
[6]	李卓,陈鸿,刘宏斌,等.我国城市人居环境及其评价指标体系研究——以西安市人居环境评价为例[C] .//中国环境保护优秀论文精选.北京: 中国环境科学出版社,2006:523~528.
[7]	K Doi, M Kii, H Nakanishi.An integrated evaluation method of accessibility, quality of life, and social interaction[J]. Environment and Planning B: Planning and esign,2008,35(6):1098~1116.
[8]	浅见泰司. 居住环境评价方法与理论[M]. 高晓路,张文忠,等译.北京:清华大学出版社,2006.
[9]	罗志军. 城市居住环境质量综合评价研究[J].高等函授学报(自然科学),2001,14(2):36~40.
[10]	徐磊青,杨公侠.上海居住环境评价研究[J].同济大学学报(自然科学),1996,24(5):546~551.
[11]	M Bonaiuto, A Aiello, M Perugini, et al.Multidimensional perception of residential environment quality and neighbourhood attachment in the urban environment[J]. Environ. Psycho,1999,19(4): 331-352.
[12]	张文忠. 城市内部居住环境评价的指标体系和方法[J].地理科学,2007,27(1):17~23.
[13]	吴文钰. 城市便利性、生活质量与城市发展:综述及启示[J]. 城市规划学刊,2010,(4):71-75.
[14]	Irene van Kamp, Kees Leidelmeijer, Gooitske Marsman, Augustinus de Hollander. Urban environmental quality and human well-being Towards a conceptual framework and demarcation of concepts; a literature study[J]. Landscape and Urban Planning,2003, (65): 5-18.
[15]	A Cicerchia.Indicators for the measurement of the quality of urban life—what is the appropriate territorial dimension?[J]. Soc. Indicators Res, 1996,39(3):321-358.
[16]	杨雁翔,连晓霞.联合分析研究文献综述[J].现代农业,2010,(5):198~199.
[17]	Peter C Boxall, Wiktor L Adamowicz, Joffre Swait, et al.A comparison of stated preference methods for environmental valuation[J].Ecological Economics, 1996,18(3):243-253.
[18]	王利敏. SP 调查在离散选择模型中的应用[D]. 苏州:苏州大学,2010.
[19]	加知範康,加藤博和,林良嗣.汎用空間データを用いて居住環境レベルの空間分布をQOL指標で評価するシステムの開発[J].日本都市計画学会,都市計画論文,2008,43(3):19~24.
[20]	戸川卓哉. 環境·経済·社会のトリプル·ボトムラインに基づく都市持続性評価システム-都市域集約政策への適用- [D]. 名古屋:名古屋大学,2010.
[21]	森田紘圭. 既存空間データに基づく地区レベルでの居住環境評価を可能とするシステム開発[D].名古屋:名古屋大学,2008.
[22]	钱欣,王德,马力.街头公园改造的收益评价——CVM价值评估法在城市规划中的应用[J]. 城市规划学刊, 2010,(3):41~50.
[23]	Knight Robert L, D Mark Menchik. Conjoint preference estimation for residential land use policy evaluation[R]. Santa Monica, CA: RAND Corporation, 1974.
[24]	van Poll Ricvan. The perceived quality of the urban residential environment: a multi-attribute evaluation[D]. Groningen: Rijksuniversiteit Groningen, 1997.
[25]	张茵,蔡运龙.条件估值法评估环境资源价值的研究进展[J].北京大学学报(自然科学版),2005,41(2):317~328.
[26]	Eric Molin, Harmen Oppewal, Harry Timmermans.Predicting consumer response to new housing: a stated choice experiment[J].Journal of Housing and the Built Environment, 1996,11(3):297-311.
[27]	Bruce Walker, Alex Marsh, Mark Wardman, et al.Modelling tenants’ choices in the public rented sector——a stated preference approach[J].Urban Studies, 2002,39(4):665-688.
[28]	Wang Dong-gen, Li Si-ming.Socio-economic differentials and stated housing preferences in Guangzhou, China[J]. Habitat International, 2006,(30):305-326.
[29]	Jordan Louvière, Harry Timmermans.Stated preference and choice models applied to recreation research: A review[J].Leisure Sciences: An Interdisciplinary Journal,1990,12(1):9-32.
[30]	N A Powea, G D Garrodb,P L McMahon. Mixing methods within stated preference environmental valuation: choice experiments and post-questionnaire qualitative analysis[J].Ecological Economics,2005,52(4):513-526.
[31]	Helena Nordh, Chaham Alalouch, Terry Hartig.Assessing restorative components of small urban parks using conjoint methodology[J].Urban Forestry and Urban Greening,2011,10(2):95-103.
[32]	刘佳燕. 面向当前社会需求发展趋势的规划方法[J]. 城市规划学刊,2006,(4): 35~40.

生活质量评价要素		属性水平
分类		属性
便利性	轨道站距离	步行5 min、步行15 min、步行30 min
	市级医院距离	步行5 min、公交15 min、公交30 min
	中小学距离	步行5 min、步行15 min、步行30 min
	商业地距离	步行5 min、公交15 min、公交30 min
舒适性	住房面积	40 m²、80 m²、120 m²
	公园距离	步行5 min、步行15 min、步行30 min
	健身场距离	步行5 min、步行15 min、步行30 min
	交通噪音	嘈杂
	交通噪音	安静
安全性	交通事故概率	2件/a及以下
	交通事故概率	2件/a以上
	空气污染（尾气）	交通性道路密度低
	空气污染（尾气）	交通性道路密度高
	火灾事故概率	棚户简屋、工厂区
	火灾事故概率	其他区域
	犯罪率	抢盗事件3件/a及以下
	犯罪率	抢盗事件3件/a以上

便利性	居住地A	居住地B	C
轨道站距离	5 min	30 min	都不满意
市级医院距离	公交15 min	公交15 min
中小学距离	15 min	5 min
商业地距离	公交15 min	5 min
舒适性	居住地A	居住地B	C
住房面积	80 m²	40 m²	都不满意
公园距离	5 min	5 min
健身场距离	15 min	30 min
交通噪音	嘈杂	安静
安全性	居住地A	居住地B	C
交通事故概率	低	高	都不满意
空气污染（尾气）	严重	不严重
火灾事故概率	高	低
犯罪率	低	低
居住环境质量	居住地A	居住地B	C
市级医院距离	公交30 min	公交15 min	都不满意
公园距离	5 min	15 min
空气污染（尾气）	高	低

居住环境指标		分类模型	总模型
居住环境指标		系数	系数
便利性	地铁站距离	-0.0370^***	-0.0246^*
	医院距离	-0.0043^***	-0.0029
	中小学距离	-0.0375^***	-0.0249^*
	商业地距离	-0.0037^***	-0.0025^*
	McFadden’s LRI	0.2344	-
舒适性	住房面积	0.0106^***	0.0068^*
	公园距离	-0.0122^*	-0.0078
	健身场距离	-0.0084^*	-0.0054^*
	交通噪音	-1.395^***	-0.8947^***
	McFadden’s LRI	0.2518	-
安全性	交通事故概率	-0.6946^***	-1.2887^***
	尾气污染程度	-0.7478^***	-1.3874^***
	火灾概率	-0.5728^***	-1.0627^***
	犯罪率	-1.0683^***	-1.982^***
	McFadden’s LRI	0.0947	0.1801

Quality of Urban Residential Environment Based on Stated Preference Methods

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