Determinants of Renewable Energy Adoption
Summary
The adoption of renewable energy arises from a confluence of economic, political, technological and social factors. Economic growth and per capita income determine a society’s capacity to invest in clean technologies and absorb transition costs. Access to finance, often measured through foreign direct investment and the development of financial markets, lowers capital barriers and accelerates deployment. Political commitment and regulatory frameworks, including the stringency of environmental policies and the stability of governance structures, shape market signals and investor confidence. Technological innovation, reflected in research and development intensity and infrastructure readiness, influences the cost and performance of renewable resources. Societal attitudes and public support foster demand, while geographical resource endowments and grid integration capacity determine the feasibility of specific technologies. Together, these interlinked determinants guide policy choices, direct private-sector engagement and frame global efforts towards a sustainable energy transition.
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Determinants of Renewable Energy Adoption publication trend
The graph below shows the total number of articles in determinants of renewable energy adoption across all publications each year (not limited to Nature Index journals).
Technical terms
Gross Domestic Product (GDP) per capita: The average economic output per person, indicating national wealth and capacity for investment in energy infrastructure.
Foreign Direct Investment (FDI): Cross-border capital flows by firms or individuals to establish or expand business operations, reducing financing costs for renewable projects.
Total Factor Productivity (TFP): A measure of overall efficiency in converting labour and capital into economic output, reflecting technological progress.
Geopolitical risk: Political uncertainties and events, such as conflicts or regulatory shifts, that can influence investor confidence and energy investment decisions.
Panel data modelling: Statistical techniques analysing data collected over time for multiple entities, enabling the study of dynamic relationships across countries or regions.
References
- Towards a gradual transition to renewable energies in Tunisia: Do foreign direct investments and information and communication technologies matter?. Energy Nexus (2023).
- Determinants of renewable energy consumption in agrarian Sub-Sahara African economies. Energy, Ecology and Environment (2022).
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