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Evaluation of the impact of moral dissonance-based low-carbon interventions on consumer behavior

认知失调 干预(咨询) 消费(社会学) 道德 心理干预 消费者行为 心理学 比例(比率) 社会心理学 环境经济学 营销 经济 业务 政治学 法学 社会学 地理 社会科学 地图学 精神科
作者
Li Xue,Chaoran Li,Endi Cai,W. Wan,Shuo Wei,Zhuo Yu,Hejun Xu
出处
期刊:Journal of Cleaner Production [Elsevier BV]
卷期号:425: 138947-138947 被引量:1
标识
DOI:10.1016/j.jclepro.2023.138947
摘要

With the ever-changing scientific and technological progress and improving human living standards, people's consumption levels are also steadily increasing. However, the consumption behavior of consumers has brought a significant impact on the earth's environment. For this reason, some governments or organizations are constantly calling for environmentally friendly consumption behaviors, trying to change people's consumption habits through a series of intervention measures. However, researchers can hardly track each consumer's behavioral changes and inner thoughts in real-time, so it is challenging to quantify the effect of intervention measures. This study considers three factors: consumer behavior, morality and self-esteem, and intervention measures to estimate the carbon emissions caused by consumption behavior. Firstly, the carbon emissions are estimated through the existing behavior of consumers. Secondly, the morality and self-esteem of the respondents are evaluated through the process of moral dissonance and the self-esteem scale. And then we investigate the change of consumers' carbon emissions under the intervention measures. Finally, the adjusted final result is given by combining morality and self-esteem. Through a series of surveys on 354 respondents, this study estimated that their average annual carbon emissions without intervention were 5.3 tons, and their average yearly carbon emissions after intervention were 4.365 tons. After considering the intervention of moral disorder and self-esteem, the average annual carbon emission is 4.691 tons. From the results, this study explains why some measures are not as effective as expected and, at the same time, provides a new research method for quantifying the effect of intervention measures.
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