Sustainable energy technology adoption for a low-carbon future: A global meta-analysis of psychological determinants

Sustainable energy technologies are essential to achieving global climate goals, yet adoption rates remain below the levels required to realise net-zero emissions. To clarify which psychological factors can accelerate or hinder uptake, we performed the most comprehensive quantitative synthesis of psychological determinants of sustainable energy-technology adoption to date. We synthesised 1341 zero-order correlations from 206 peer-reviewed studies (138,874 participants in total) across 35 countries. The summary of results for 57 constructs shows that, among the most frequently studied variables, personal norms, attitudes, and perceived behavioural control have the strongest positive associations with sustainable energy-technology adoption outcomes, whereas perceived monetary costs and perceived risk emerge as relevant barriers. For most constructs, psychological predictors have slightly stronger effects on adoption intentions than on actual adoption; however, medium-to-large associations with behaviour indicate that the same determinants are ultimately important for action. Over time, both the positive influence of environmental concern and the negative influence of perceived monetary cost have increased, while the influence of other constructs has remained stable. In addition, the magnitude of the key psychological predictors appears largely consistent across world regions and technology categories. Our findings indicate that, beyond price-based instruments, policies that reinforce moral and social norms, foster supportive attitudes, and strengthen perceived control can further accelerate uptake. By capturing key drivers and barriers at scale, this meta-analysis refines explanations for the adoption of sustainable energy technologies and provides an evidence base for more targeted interventions. • Personal norms, attitudes, and behavioural control predict adoption the strongest. • Most predictors exhibit consistent effects across diverse sustainable technologies. • Adoption predictors are largely stable across regions, with only minor variation. • Intentions and behaviour align closely and predictors have similarly sized effects. • Most predictors remain stable over time, reflecting enduring influences.