Digital Transformation as a Moderator of Institutional Quality, Economic Development, and Social Factors in Renewable Energy Adoption: Evidence From Major Economies (1999–2023)

ABSTRACT A limited understanding of the role of digital transformation as a moderator in the interaction of institutional quality, economic development, and renewable energy adoption in major economies has significantly held back the progress of sustainable energy transitions. This research focuses on the direct and moderated effects of institutional quality, economic development, urbanization, energy imports dependency, and environmental policy stringency on renewable energy adoption, theoretically grounded in the extension of institutional theory and the resource‐based view. The study utilizes Pooled Mean Group Autoregressive Distributed Lag (PMG‐ARDL) and Fully Modified Ordinary Least Squares (FMOLS) techniques on a balanced panel of 15 major economies (1999–2023), with data drawn from the World Development Indicators and Worldwide Governance Indicators. The results reveal that institutional quality is a major factor in the increase of renewable energy adoption ( β = 12.678, p < 0.001), and the relationship between them is moderated positively by digital transformation ( β = 0.150, p < 0.001). In addition, economic development ( β = 2.434, p = 0.005) and urbanization ( β = 1.473, p < 0.001) are also responsible for the increase in adoption; however, the short‐run urban effects are negative. Moreover, energy imports dependency ( β = 0.077, p < 0.001) and environmental policy stringency ( β = 0.617, p = 0.006) are the factors that lead to a further advancement of the transitions, while digital tools are the enablers of these effects. The results depict that digital infrastructure enables the effectiveness of governance and economic capacity. Such findings can be applied to theoretical frameworks that explain the role of digital transformation as a strategic enabler and enable purposeful policy focus. The scope of generalizability is hindered by data limitations including the heterogeneity of the region. Future research could contemplate analyzing the subnational processes or AI possibilities in energy systems.