Abstract
This study advances the discourse on Demand Response adaptation in developing economies by introducing a novel Socio-Technical Adaptive Framework for Demand Response (STAF-DR), which integrates mobile-based platforms, decentralized energy systems, and policy reforms with a unique emphasis on behavioral economics and institutional capacity building. Unlike prior reviews, we systematically analyze causal mechanisms behind DR success or failure across 15 case studies (2010–2025) using a mixed-methods approach, combining quantitative meta-analysis of peak load reductions (5–15 %) with qualitative institutional diagnostics. Our framework identifies three original levers for scalability: (1) contextualized technology bundling (e.g., hybrid SMS/solar-microgrid DR in Kenya achieving 18 % higher participation than standalone solutions), (2) policy sequencing tailored to regulatory maturity (e.g., Ghana's phased TOU rollout reducing implementation costs by 30 %), and (3) community trust metrics that predict DR adoption (R2 = 0.72 in rural India). The study provides new empirical evidence on DR's role in mitigating renewable intermittency, demonstrating that mobile-DR can reduce solar curtailment by 12 % in South Africa, compared to 5 % for smart meters. We provide actionable insights for policymakers through a risk-weighted decision matrix, addressing gaps in longitudinal impact assessment and rural DR scalability.
