As an intellectual property product that is highly farmer-friendly, geographical indication (GI) products have always garnered significant attention. In recent years, research on how GI products promote agricultural development has been increasing, yet the academic community remains divided on this issue. On one hand, some studies point out that GI products can drive agricultural development; on the other hand, other studies suggest that the impact of GI products is not significant or varies. Meta-analysis is a method that leverages statistical techniques to integrate the findings of multiple studies with a common research objective, addressing controversial issues and arriving at generalizable conclusions. Therefore, to more precisely uncover the intrinsic relationship between GI products and agricultural development and to delve deeper into the root causes of the aforementioned discrepancies, this study employed a meta-analytic approach. We extracted 478 correlation coefficients (r) as effect sizes from 82 empirical articles worldwide. Using these coefficients, we calculated the overall effect size and moderating effects of GI products on promoting agricultural development. Research indicates that GI products exert a positive influence on agricultural development. There is a low positive correlation between the two (r = 0.197). Further analysis reveals that various factors at the sample, data, literature, and methodology levels all impact the outcomes of GI products’ promotion of agricultural development. Research has shown that, in pursuit of sustainable agricultural development goals, it is further recommended that governments should accord high priority to the cultivation and development of GI products. This is aimed at providing practical insights to facilitate the sustainable advancement of GI products and bolster agricultural competitiveness.

In the contemporary economic landscape shaped by globalization and digital transformation, patent-intensive industries have emerged as critical engines for enhancing national competitiveness. This study analyzed 98,464 collaborative patent application records (2012–2023) from listed companies in patent-intensive sectors, sourced from the China National Intellectual Property Administration (CNIPA) database. Through kernel density estimation, social network analysis, and community detection techniques, we examined the evolutionary trajectories of innovation networks and spatial patterns within these industrial clusters. Our findings indicate a notable spatial agglomeration trend in patent-intensive industries, exhibiting a prominent “core-periphery” structural feature. The core nodes of this cluster network closely align with economically developed regions, and the network structure has gradually shifted from a triangular framework supported by Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta to a diversified multilateral framework. Moreover, the community structure of the collaborative network within China’s patent-intensive industrial clusters exhibits distinct characteristics driven by technological relevance and strategic synergy, rather than strictly adhering to the principle of geographical proximity. These discoveries not only enrich the application of innovation network theory in the specific context of China, but also provide valuable guidance for cluster enterprises in selecting partners and achieving collaborative innovation.