Green consumption behaviour among Generation Z college students in China: the moderating role of government support
YOUNG CONSUMERS(2023)
Abstract
PurposeGreen consumption behaviour (GCB) has been advocated to mitigate the environmental consequences of traditional consumption patterns. Besides the current circumstances, Generation Z college students are a sizable consumer group who are likely to be concerned about the future. Thus, this study aims to examine the factors affecting the college students' GCB and the moderating effect of government support to provide new evidence from college students in China. Design/methodology/approachIn addition to environmental knowledge and social media influence as the variables, government support was used as a moderator to develop the extended theory of planned behaviour (TPB) model. Purposive sampling was used to obtain 328 valid responses from Chinese college students. The collected data were analysed using partial least squares structural equation modelling. FindingsThe findings indicated that subjective norms, perceived behavioural control, environmental knowledge and social media influence substantially affect students' GCB. Notably, the moderation analysis suggested that government support greatly strengthens the relationship between subjective norms and social media influence on the GCB of Chinese college students. Practical implicationsThe study provides several significant practical implications as the findings could be referred by stakeholders, such as government and businesses entities, in formulating policies and strategies to encourage the consumers' GCB in mitigating ecological consequences. Originality/valueThe extended TPB model that integrated environmental knowledge and social media influence with the government support as the moderator contributes to the extant literature with the evidence derived from Generation Z in China.
MoreTranslated text
Key words
Green consumption behaviour,Theory of planned behaviour,Generation Z,Environmental knowledge,Government support
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined