Exploring the role of public risk perceptions on preferences for air quality improvement policies: An integrated choice and latent variable approach
Exploring the role of public risk perceptions on preferences for air quality improvement policies: An integrated choice and latent variable approach
复制标题
探索公众风险认知对空气质量改善政策偏好的作用：综合选择和潜变量方法
DOI：
10.1016/j.jclepro.2020.122379
复制
发表时间：
2020-10
影响因子：
11.1
通讯作者：
Lishan Xu
中科院分区：
文献类型：
--
作者：
Biqi Mao;Changlin Ao;Yang Cheng;Nan Jiang;Lishan Xu
评估公众对空气质量改善政策的偏好可以为空气污染可持续治理提供宝贵的见解，其中风险感知可以被视为偏好的关键决定因素。本研究的目的是通过选择实验探讨公众风险感知在改善空气质量偏好背景下的作用。提出了一个综合选择和潜变量模型，同时解释公众的空气污染的风险感知，通过观察社会经济特征，并探讨这些风险感知，在潜变量方面，链接到空气质量改善政策的公众偏好。结果表明，具有较高风险可接受性的个体比其他个体更不可能为空气质量改善做出贡献。相反，个人的风险感越高，他们就越愿意为空气质量改善政策买单。此外，研究结果还显示，风险感受与其前因变量：教育和收入呈正相关，风险可接受性与女性呈负相关。本文有助于设计社会最优的政策，以改善空气质量，因为它有助于探索公共决策背后的隐藏因素。
Assessing of public preferences for air quality improvement policies could provide valuable insights for air pollution sustainable governance, where risk perceptions can be regarded as a key determinant of preferences. The objective of this study is to explore the role of public risk perceptions in the context of improved air quality preferences though choice experiment. An integrated choice and latent variable model was proposed to simultaneously explain public risk perceptions of air pollution by observing socio-economic characteristics and to explore how these risk perceptions, in terms of latent variables, link to public preferences for air quality improvement policies. The results suggested that individuals with higher Risk acceptability were less likely than the others to contribute to air quality improvement. Conversely, the higher an individuals’ Risk feeling was, the more likely they were willing to pay for air quality improvement policies. In addition, the results also revealed a positive correlation between Risk feeling and its antecedents: education and income, as well as a negative correlation between Risk acceptability and women. This paper can help design socially optimal policies to improve air quality due to its contribution to exploring the hidden factors behind public decision-making.
登录
查看更多内容
影响因子：
5.9
作者：
Hess, Stephane;Beharry-Borg, Nesha
通讯作者：
Beharry-Borg, Nesha
影响因子：
9
作者：
Chin-Hsien Yu;Shih-Kai Huang;Ping Qin;Xiaolan Chen
通讯作者：
Chin-Hsien Yu;Shih-Kai Huang;Ping Qin;Xiaolan Chen
公众空气污染风险感知的空间分布：中国的一项全国性研究
影响因子：
9.8
作者：
Pu, Sisi;Shao, Zhijuan;Ma, Zongwei
通讯作者：
Ma, Zongwei
影响因子：
4.8
作者：
Hodgson, Antonia;Hitchings, Russell
通讯作者：
Hitchings, Russell
影响因子：
15.9
作者：
Lingling Wang;Tsunemi Watanabe
通讯作者：
Lingling Wang;Tsunemi Watanabe