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成都市生活垃圾分类支付意愿及影响因素的问卷调查分析
引用本文:郭卫广,雍毅,吴怡,侯江,刘恒博.成都市生活垃圾分类支付意愿及影响因素的问卷调查分析[J].环境保护科学,2021,47(1):15-20.
作者姓名:郭卫广  雍毅  吴怡  侯江  刘恒博
作者单位:四川省生态环境科学研究院,四川 成都 610041
基金项目:四川省科技计划资助(2019YFS0058)、科技厅常规项目(油气开采含油污泥焚烧渣安全利用体系研究)。
摘    要:为了为成都市垃圾分类政策制定提供科学依据,文章基于问卷调研,运用条件价值评估法结合二元Logistic回归模型、多元线性回归模型,分析了成都市居民对城市生活垃圾分类的支付意愿(WTP)及其影响因素。调研发现:问卷填报者中95.3%的人支持强制垃圾分类,但仅21.0%人深入掌握垃圾分类知识;造成成都市垃圾分类失效的原因,73.8%的人认为政策不到位,需要采取强制监管措施,67.6%的人认为垃圾分类桶等基础硬件设施建设不到位,69.2%的人认为居民自身环保意识差,需要加强环保宣传教育。成都市居民生活垃圾治理的WTP金额为12.65元/月/户。年龄、有无住房、户口类型和月收入4个因素对支付额度有显著影响。

关 键 词:生活垃圾分类  支付意愿  问卷调查  多元线性回归模型  成都市

Questionnaire Investigation on the Willingness to Pay for the Garbage Classification in Chengdu and Its Influencing Factors
GUO Weiguang,YONG Yi,WU Yi,HOU Jiang,LIU Hengbo.Questionnaire Investigation on the Willingness to Pay for the Garbage Classification in Chengdu and Its Influencing Factors[J].Environmental Protection Science,2021,47(1):15-20.
Authors:GUO Weiguang  YONG Yi  WU Yi  HOU Jiang  LIU Hengbo
Institution:(Sichuan Academy of Ecological and Environmental Sciences,Chengdu 610041,China)
Abstract:To provide a scientific basis for Chengdu garbage classification policy,based on the questionnaire survey,this paper analyzed the willingness to pay(WTP)and its influencing factors by the contingent valuation method combined with the binary logistic regression model as well as the multivariate linear regression model.The results showed that 95.3%of respondents supported the mandatory garbage classification.However,only 21.0%of them understood the knowledge of garbage classification.The reasons resulting in the failure of garbage classification in Chengdu were considered as following.The policy was invalid and the mandatory measures were necessary(73.8%),the construction of the infrastructure such as garbage bins was not enough(67.6%),the awareness of environmental protection of the residents was poor and the publicity needed to be enhanced(69.2%).The WTP amount for the resident garbage treatment was 12.65 yuan per month in Chengdu.The factors,such as the age,housing,the household type and the income significantly affected the payment.
Keywords:Garbage Classification  Willingness to Pay  Questionnaire Investigation  Multivariate Linear Regression Model  Chengdu
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