Bayesian networks for assessing the sustainability of the marine renewable energy sector in the blue economy of Spanish ports

Abstract

This research focuses on identifying key indicators for the sustainable development of the Marine Renewable Energy sector in the Blue Economy of Spanish ports, utilizing Bayesian networks to integrate economic, social, and environmental perspectives. The study also aims to develop a decision-support tool for strategic planning in ports. The methodology involves creating and analyzing a Bayesian model using data from 28 Spanish port authorities. The study includes selecting indicators, data preprocessing, and model construction to identify interrelations among sustainability variables. Key findings indicate that economic investment in port infrastructure, environmental characterization, and occupational safety are crucial factors for the sector's development. Bayesian networks enabled the representation of relationships among these indicators, highlighting the importance of a balanced approach between economic, social, and environmental sustainability. The study concludes that the sustainability of the Marine Renewable Energy sector depends on an effective integration of economic investments, environmental management, and occupational safety measures, supported by tools like Bayesian networks to optimize decision-making in the port sector.