Strategic assessment of investment opportunities for pay-as-you-go solar in off-grid communities: An artificial intelligence-driven multi-facet fuzzy entropy optimization approach

Access to reliable and affordable energy remains a major challenge in off-grid communities, where energy poverty continues to hinder social and economic development. In this context, pay-as-you-go (PAYG) solar investments have emerged as a promising strategy to expand sustainable energy access and support the achievement of SDG 7. However, the strategic criteria that maximize the effectiveness of PAYG solar investments and guide optimal implementation have not been systematically defined in the literature. This study aims to address this gap by developing an integrated, parameter-driven artificial intelligence (AI)-based decision support framework grounded in multi-facet fuzzy entropy optimization. The proposed framework enhances the strategic planning process by quantifying decision-makers’ linguistic uncertainties and multi-dimensional behavioral patterns through dynamic multi-way fuzzy sets—contributing a novel fuzzy modeling approach to the field. Furthermore, the model employs a dynamic influence propagation mechanism with entropy optimization to estimate the relative importance of investment criteria, capturing both temporal and structural interactions to minimize information loss. The findings highlight that customer creditworthiness and lifetime value represent the most influential factors for effective investment strategies. At the strategic level, PAYG solar initiatives integrating electric vehicle infrastructure and locally franchised delivery models are identified as high-priority pathways to strengthen energy access, long-term system sustainability, and investment resilience in developing economies.