Strategic Intelligence and Digital Transformation in Energy Economics: Pathways to Renewable Energy Expansion and ESG-Aligned Sustainability - Alrawahna, Ammar Salamh; Khasawneh, Ohoud; Alma’abreh, Sajeda; Khtatbeh, Mohamed Mahmoud (International Journal of Energy Economics and Policy, 2026)
The digital transformation is gradually transforming the energy systems by transforming the manner in which information is generated, processed and incorporated in strategic decision-making. In the third world, but where energy transformation is limited by institutional weakness, skills and capabilities, and governance issues, the degree to which digitalization positively contributes to renewable energy growth and plausible environmental, social, and governance (ESG) performance is lopsided. This is a review that incorporates interdisciplinary studies in the fields of energy economics, information systems, sustainability management, and human resource management to understand how the digital transformation affects the renewable energy consumption and the sustainability of ESG outcomes through the intermediation of strategic intelligence and human resource sustainability. The synthesis shows that the generation of transition value on the basis of digital technologies is not achieved by means of data accumulation but organizational capabilities that allow performing higher level analytics, future planning, and staff adaptation. It also demonstrates the existence of nonlinear impacts, gaps in governance, and risks of greenwashing that may deter the sustainability results without the devising supplementary human and institutional abilities. Elaborating on these insights, the paper constructs an integrative framework and a collection of propositions on the ways in which digital transformation, strategic intelligence and sustainable human resource management mutually contribute to the energy and ESG outcomes in developing economies. The review ends with the description of the managerial and policy implications and priority directions to be taken in further empirical research.