Application of artificial intelligence in efficiency measurement

Abstract

This study evaluates the efficiency of OECD countries in achieving 14th Sustainable Development Goal - "Life underwater". Using a comprehensive model that integrates data analysis, Data Envelopment Analysis (DEA) models, and Artificial Neural Networks (ANN), the research focuses on marine resource management, specifically analyzing the impact of support to the fisheries sector on environmental indicators. The results reveal significant variations in efficiency between OECD countries, with Sweden systematically occupying the lowest position. Correlation analysis identifies support for sectoral services as crucial, suggesting that reducing support to the fisheries sector could increase the efficiency of marine conservation. The integrated DEA-ANN approach provides a customizable framework for assessing marine sustainability, offering valuable information for policymakers and stakeholders. Future research should extend the analysis to more countries, refine the model based on regional characteristics, and explore temporal dynamics for a comprehensive understanding of 14th SDG implementation.

Date of Award	12 Jul 2024
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Aydin Teymourifar (Supervisor)