Keywords
Energy efficiency
environmental sustainability
Energy security
Clean energy
Transition to green energy
How to Cite
Abstract
Purpose: To develop and validate a competitive intelligence framework that transforms renewable energy data into strategic decision-making tools for achieving Sustainable Development Goal 7 and creating sustainable competitive advantage.
Methodology/approach: The study follows the full competitive intelligence cycle and applies statistical analysis, content analysis, and econometric modeling (linear regression) to secondary data. Elasticity and correlation coefficients were calculated.
Originality/Relevance: The research introduces a novel competitive intelligence conceptual model that links raw renewable energy data directly to actionable intelligence, integrating smart grids, synchronization standards, and AI as strategic tools.
Key findings: Renewable energy significantly reduces CO₂ emissions and stimulates GDP growth, with differentiated elasticities by source (hydropower: 3.3758; solar: 0.2431). Main barriers remain high investment costs, infrastructure deficits, and regulatory constraints.
Theoretical/methodological contributions: The study proposes a replicable CI framework and evidence-based recommendations for policy and investment prioritization, advancing the integration of Competitive Intelligence into sustainable energy transition.
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