Analyzing the Complexity of Sustainable Development Goals and Indicators

Understanding the complex interrelations among Sustainable Development Goals (SDGs) and targets is crucial for achieving social, environmental, and economic advances, as these interconnections provide a valuable framework for the development of strategies to coordinate progress. The interconnections can also be used to determine the ways in which SDG targets and goals may influence each other. Various previous studies have examined correlation-based or causal relationships between SDG targets, a systematic analysis of the strongest connections among SDG indicators across countries, especially interactions involving SDG 9, remains unexplored, offering opportunities for evidence-based insights into sustainable industrial development. In this study, we use United Nations SDG indicator data, which are collected for monitoring of progress with respect to specific SDG targets, selecting indicators that are associated with various SDG targets and goals from European countries. To analyze the complexities of these data, we apply a mutual-information-based network inference method and construct a robust network that shows distinct clusters of indicators spanning multiple SDGs, emphasizing the interconnected nature of sustainable development efforts and the unique dimensions represented by each cluster. In addition, analysis of the hub nodes (defined as key indicators) within the network highlights the crucial roles of social, economic, and environmental factors in driving progress toward different SDG objectives. Finally, an analysis focused on indicators of SDG 9 (industry, innovation, and infrastructure) and their interactions with other SDG indicators emphasizes the multifaceted influences involved and the need for coordinated actions crucial for value creation, sustainable industrialization, and smart manufacturing. Our analyses demonstrate the complex relationships among SDGs and show potential for broader applications, including comparative regional analyses and use in corporate sustainability strategies.