Data-Driven Assessment of Regional Sustainable Development in China: A Hybrid Comparative Method

As the 2030 Sustainable Development Agenda nears, research efforts have focused on evaluating sustainable development from a macro perspective. However, this macroscale assessment might be influenced by regional variations. Additionally, previous studies have tended to overemphasize quantitative evaluations. To address these shortcomings, this study applies regional sustainable development theory to structure an assessment framework by proposing a hybrid method that combines qualitative and quantitative assessments. The proposed hybrid method includes K-nearest neighbors, hierarchical clustering, a reliability test, and a decision-making trial and evaluation laboratory. It makes three significant contributions: (1) The complex causal interrelationships that are revealed strengthen the theoretical foundation and enhance the understanding of regional sustainable development; (2) the proposed hybrid method considers quantitative and qualitative factors simultaneously, resulting in a comprehensive evaluation; and (3) the simple visual assessment offers clear guidance for resource allocation adjustments. The assessment results reveal that the government prioritizes eco-coordination over the opinions of experts on cultural-environmental livability. On this basis, compared with the 292.64% variation in infrastructure support across regions, eco-innovation exhibits the least variation of 50.00%. The results also suggest that the provinces in Central China have a higher level of consensus in terms of pursuing regional sustainable development.