Northern Lights: Prospecting Efficiency in Europe’s Renewable Energy Sector
Yen-Hsing Hung, Fu-Chiang Yang- Process Chemistry and Technology
- Chemical Engineering (miscellaneous)
- Bioengineering
Northern European nations are at the forefront of renewable energy adoption but face challenges in optimizing energy conversion efficiency. There is a lack of detailed understanding of how behavioral factors affect the efficiency of renewable energy conversion in these countries. This study aims to evaluate and compare the renewable energy conversion efficiency of Northern European countries, intending to inform strategic policy making and identify best practices for technology deployment in the renewable energy sector. Employing a Data Envelopment Analysis (DEA) model, the study integrates behavioral economic parameters—specifically, the aversion loss and gain significance coefficients—to assess the efficiency of renewable energy conversion, accounting for psychological factors in decision making. A comprehensive sensitivity analysis was conducted, varying the gain significance coefficient while maintaining the aversion loss coefficient at constant levels. This experiment was designed to observe the impact of behavioral parameters on the efficiency ranking of each country. The analysis revealed that Latvia consistently ranked highest in efficiency, irrespective of the gain significance valuation, whereas Iceland consistently ranked lowest. Other countries demonstrated varying efficiency rankings with changes in gain significance, indicating different behavioral economic influences on their renewable energy sectors. Theoretically, the study enhances the DEA framework by integrating behavioral economics, offering a more holistic view of efficiency in renewable energy. Practically, it provides a benchmarking perspective that can guide policy and investment in renewable energy, with sensitivity analysis underscoring the importance of considering behavioral factors. The research offers a practical tool for policymakers and energy stakeholders to align renewable energy strategies with behavioral incentives, aiming to improve the adoption and effectiveness of these initiatives.