Abstract

It was examined how barriers to renewable energy adoption in low-income communities influenced uptake rates, integrating socio-economic variables and technology adoption theory. Using cross-sectional survey data from diverse low-income households, logistic regression assessed the influence of income, education, access to micro-credit, perceived complexity, and institutional support on renewable energy adoption. Results indicated that higher income, greater educational attainment, access to micro-credit, and stronger institutional support were positively associated with adoption, while perceived complexity significantly reduced adoption likelihood. The model demonstrated good fit and discriminative ability. These findings suggest that financial constraints, informational deficits, and weak institutional environments jointly impede renewable energy adoption. Policies aimed at enhancing credit access, increasing energy literacy, simplifying technology, and strengthening governance could promote equitable energy transitions. The study contributes to literature by quantifying barriers using robust statistical methods, providing actionable insights for policymakers and development practitioners focused on sustainable energy access in resource-poor settings.