Environmental concern among Chinese youth: the roles of knowledge and cultural bias

Abstract

This article uses Cultural Theory (CT) to complement the Knowledge Deficit Model (KDM) in explaining the environmental concern of Chinese youth. We use a large-scale nationwide sample and adopt multiple multi-level models. We find that the effect of knowledge varies with measurements of knowledge and environmental concern. Youth whose cultural orientation is dominated by egalitarianism are most concerned, followed by those for whom hierarchy is dominant, while those for whom individualism and fatalism are dominant are least concerned. As expected, egalitarianism increases environmental concern while fatalism decreases it, and hierarchism also increases national concern. But, contrary to expectations, individualism has no effect on either and hierarchism does not increase personal concern. We suggest how to educate culturally diverse youth about environmental risk. As one of the first efforts to operationalize CT for survey research in China, this article also suggests how to improve measurement of CT there.

Supplemental data for this article is available online at https://doi.org/10.1080/13504622.2022.2033705 .

Keywords:

• Environment
• China
• youth
• knowledge
• culture
• cultural theory
• grid-group cultural theory

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The datasets generated during and/or analyzed during this study are available from the corresponding author on reasonable request.

Notes

1 If, for example, the respondent is clearly more positive about hierarchy (scoring 1.4) and slightly more positive about egalitarianism (1.2) than the average respondent, and simultaneously, is slightly below the average for individualism (−0.2), and far below the average for fatalism (−1.5), this respondent will be categorized as one for whom hierarchy is dominant.

2 The Cronbach’s alpha for the egalitarian, hierarchical, individualist, and fatalist indices are 0.10, 0.05, 0.04, and 0.17, respectively.

3 Multi-level modelling should be used when the data is nested or grouped (Nezlek 2008). While a low or zero intra class correlation (ICC) – meaning that there is no (or very little) between-group variance in the dependent measure – may exist in multilevel data, the nested structure of the data cannot be ignored because a low ICC does not mean that the relationship between this measure and another measure is the same across all groups or that the relationships between or among all the variables do not vary across groups.

4 Dominant egalitarianism is left out of our models to prevent multicollinearity.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China10.13039/501100001809 [Grant No. 71974203]; National Natural Science Foundation of China10.13039/501100001809 [Grant No. 72104039]; National Natural Science Foundation of China10.13039/501100001809 [Grant No. 72074224]; Humanity and Social Science Youth Foundation of Ministry of Education of China10.13039/501100017630 (Grant No. 21XJC810001); Innovation and Talent Base for Income Distribution and Public Finance [Grant No. B20084]; Chinese Postdoctoral Science Foundation (Grant No. 2021M700615), and Chongqing University Fundamental Research Funds for the Central Universities [Grant No. 2021CD8KXYGG006].