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• W2895796229 abstract "Current deteriorating air quality has become a severe threat for human health in the past several years in China. However, the insufficient understanding of public pro-environmental intentions and behaviors has become a barrier to implementing appropriate regulations for air quality improvement. This study aimed to seek the determinants of residents' intentions to improve air quality by using the extended Theory of Planned Behavior method. A survey that included 625 respondents from six urban cities (Beijing, Guangzhou, Hangzhou, Nanjing, Chongqing, and Kunming) was conducted to measure the intention to act by using the willingness to pay (WTP) monetary scale. The results showed that: (1) the mean WTP was 821 RMB per household per year, which accounted for 1.93% of the annual income; and the highest WTP (917 RMB) and most positive attitudes were observed for the respondents in Hangzhou; (2) the introduction of environmental concern and sense of duty can improve the predictive utility of the original TPB model (from 29% to 62%); (3) subjective norms, attitude and environmental awareness were the major influencing factors in predicting intention; (4) residents in the five advanced cities (Beijing, Guangzhou, Hangzhou, Nanjing, Chongqing) had stronger complaints, environmental knowledge, attitudes, subjective norms, perceived control and sense of duty for paying for air quality improvement than those in Kunming city; (5) the respondents who presented a greater likelihood of showing a higher WTP included males, middle-aged men, highly educated people, high-income earners, and people who spent longer amounts of time outdoors. The results could also provide policymakers with insights into residents’ internal thinking and motivations toward air pollution prevention." @default.
• W2895796229 created "2018-10-26" @default.
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• W2895796229 date "2019-02-01" @default.
• W2895796229 modified "2023-10-18" @default.
• W2895796229 title "Influential factors of public intention to improve the air quality in China" @default.
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• W2895796229 doi "https://doi.org/10.1016/j.jclepro.2018.10.192" @default.
• W2895796229 hasPublicationYear "2019" @default.
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