Adoption of low-carbon behaviors and carbon emission reduction potential among rural residents: A case of Qingshan village, China - Peng, Yijing; Wang, Xinxin; Chen, Kevin Z. (CGIAR System Organization, 2025)
Rural households constitute a crucial but understudied frontier in the decarbonization pathway in China; nevertheless, a sustained cognition-action gap still hinders the implementation of environmental awareness into behavioral adoption. This study overcomes this difficulty by combining the Attitude-Behavior-Context (ABC) model and scenario-based emission simulation. Drawing on survey data from 739 households in Qingshan Village, a village designated as a provincial pilot for low-carbon development in Zhejiang Province, this study examined the relationship between village governance perception and digital literacy and how they influence low-carbon behaviors. The results identify that the governance perception does not have a direct effect on behavior; instead, its effect goes through the mediation of the low-carbon awareness. Digital literacy is a critical moderator that has been found to amplify the conversion of governance signals into environmental cognition. Heterogeneity analysis shows a key strategic difference: the link between governance-cognition-behavior is statistically significant only for behaviors that are efficiency-oriented, requiring considerable investments, not for low-cost habitual ones. Scenario simulations also reveal a mismatch in adoption and the potential emission reductions that might have been achieved, with a high adoption of habitual behavior with limited emission reduction potential and low levels of adoption of efficiency-based behaviors with high emission reduction potential in dietary transition and energy substitution. Routine practices spread through social norms, but high-impact efficiency behaviors require trustworthy governance and digital empowerment. The research attests to the need for differentiated policy portfolios that go beyond awareness campaigns for all and aim at more specific interventions on cognitive and structural factors that affect high-potential rural low-carbon transitions, to provide a precise leverage point to improve the climate effectiveness of rural environmental programmes.