## 4 Empirical Research
### Clusters Identification Results Analysis  
In Figure 7, the technology distribution of the clusters was further analyzed based on the correlation between the clusters labeled with blue nodes and technology labeled with green nodes. It can be seen that the distribution of different clusters shows a core-periphery network structure. The center is the Yangtze River Delta cluster of c1, the Pearl River Delta cluster of c2, and the Beijing-Tianjin-Hebei cluster of c3. The technology clusters between the abovementioned locations are relatively close to each other, with stronger technological complementarity. In contrast, other clusters tend to be in the peripheral structure and only involve individual technology nodes, mainly because of the smaller technological distance and higher technological overlap among the enterprises within the cluster. For example, the Wuhan cluster, located in central China and designated as Cluster No. 6, primarily revolves around two technologies: organic display (T80) and display (T72). These technologies are characterized as flexible display technologies, suggesting that the cluster predominantly focuses on a single technology and lacks significant industrial competitiveness. By considering the core-periphery network structure, it becomes evident that the MDBSCAN-based algorithm can effectively identify clusters that exhibit greater technological complementarity, a capability that is not achievable with the current DBSCAN algorithm.  
The identification of development patterns in the target clusters can be facilitated by the examination of patent texts alongside econometric data, as demonstrated in Figure 8. By distinguishing the number of patents associated with various applicant nodes within the cluster, it becomes apparent that the Pearl River Delta cluster conforms to the typical Marshall-type industrial cluster model. This model is characterized by a predominance of SMEs, a pronounced specialization in specific fields, a significant complementarity of technological capabilities among enterprises, and a notable level of industrial competitiveness. On the other hand, the Yangtze River Delta cluster exhibits a combination of a government-led industrial cluster model and Marshall-type industrial clusters. This hybrid configuration involves a greater presence of institutions, which are represented by red dots, alongside a higher proportion of SMEs. The Beijing-Tianjin-Hebei cluster is mainly a mixture of  
Figure 7: Technology distribution of clusters.  
the hub-and-spoke industry cluster model and the government-led industry cluster model. Apart from the large number of universities and research institutes in the cluster, there is a clear distinction in the hierarchy due to significant differences in technological expertise among applicants, where the node diameter represents the number of patent applications by the applicants. As typical satellite platform-type industrial clusters (shown in Figure 8), c27, c28, c35, and c42 are established in areas at a certain distance from large clusters, and the spatial distance can ensure the realization of resource sharing while reducing the operating costs. It is also another advantage of industrial cluster identification based on patent big data.