Attitudes toward climate change to demand-driven energy mitigation: A machine-learning approach

Promoting mitigation behaviors among the public is a fundamental step in addressing climate change, yet such efforts have achieved uneven success across demographic groups. This paper surveys the literature on the relationship between personal attitudes toward climate change and mitigation behaviors, with a particular focus on demand-side energy consumption reductions. An interpretative framework for understanding the key drivers of and barriers to common mitigation strategies is provided. Applying a machine-learning approach to survey data from 23 European countries to disentangle the relative importance of attitudinal predictors, the analysis finds that perceived personal responsibility for climate change is the single most powerful predictor of energy-conscious behavior. This paper thus offers a useful guide to understanding successful approaches to incentivizing climate-friendly action within this regional context.