The Sustainable Development Goals (SDGs) adopted by the United Nations in 2015 represent the current perceptions of humans regarding understanding and monitoring development. Achieving all 17 goals simultaneously is unrealistic. Considering the interconnected nature of SDGs, identifying their critical dimensions, goals, indicators, and mutual relationships is necessary. In addition, with increasing reservations about the sustainability of SDGs, it is crucial to explore consistency across different dimensions to ensure policy coherence in maximizing synergies and minimizing trade-offs. Our study employed multiple factor analysis (MFA) and hierarchical clustering on principal components (HCPC) to investigate these issues and analyze the results based on the public value (PV) theory. The results indicated that the Human Development Index (HDI) and gross domestic product per capita (GDPP) constitute the first principal component (PC) and are determinants in differentiating country clusters. However, they contradict environmental indicators such as CO2 emissions per capita and ecological footprint gha per person (EFP) and have low synergy with the Happy Planet Index (HPI). Additionally, the relationships between income level, inequality, and environmental quality correspond to a combined Kuznets curve and an environmental Kuznets curve (EKC). Moreover, governance capacity has become increasingly crucial in sustainable development, particularly in the capability to prioritize different PVs in a timely and strategic manner. Finally, despite the novelty of EFP and HPI, they cannot reveal the entire development story. SDGs require embracing more such indicators to enrich the value bases of development and achieve a sustainable future.
Copyright: © 2024 Wang, Chen. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.