Work

From Segmentation to Strategy: Identifying Population Segments and Regional Patterns of Environmental Behaviour to Enhance Policy Transfer

Year: 2025
Type: preprint
Study design: Observational Study
Abstract: Energy, transport, and food sectors contribute substantially to climate change and are key areas where behaviour change can have the greatest impact. International policy learning and transfer are central to government approaches in these sectors. However, policies often show limited effectiveness when applied in varied contexts, likely due to assumptions of population homogeneity and over-reliance on socio-demographic characteristics. Using Multilevel Latent Class Analyses (MLCA) on over 17,000 respondents across 61 regions in nine OECD countries, we found that the majority fell into population segments with the least sustainable behaviours across the three sectors, and that socio-demographic characteristics failed to predict segment membership consistently. Individuals engaging in sustainable behaviours in one sector were more likely to do so in others, and unsustainable behaviours had similar positive associations across sectors, suggesting coordinated cross-sector interventions are crucial. Regional distribution of population segments typically grouped geographically by country, underscoring the importance of contextual influences. However, we identified significant within-country variations in regional distributions, with some regions showing substantially different proportions of people in sustainable segments than neighbouring regions under identical national policies, showing the importance of regional context. Moving beyond traditional ad-hoc policy transfer approaches, we present a systematic framework for identifying evidence-based transfer opportunities, showing policymakers not only who needs interventions but where successful patterns emerge and which contexts appear to enable sustainable behaviours. These findings provide actionable insights for the international policy community seeking to accelerate behavioural change at the scale and speed required for climate mitigation.
Language: English
Open Access status: gold
OpenAlex ID: W4414512011
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