social_science3 papersavg year 2026weak evidence

The interaction between AI-driven innovation and public–private-university collaborations

Research gap analysis derived from 3 social_science papers in our local library.

The gap

The paper identifies a gap in the existing literature on the interaction between AI-driven innovation and public–private-university collaborations. The study highlights the need for a comprehensive and interdisciplinary overview of the stat

Evidence profile

Sourced from the future work and stated research gap of the source papers, classified as general, drawn from work published between 2025 and 2026, spanning 2 journals. Those papers have been cited 79 times in total.

Research trend

Established — well-defined area with open sub-problems.

Supporting evidence — 3 representative gaps

  • Spatiotemporal evolution of innovation collaboration networks in China’s AI medical device industry: implications for public health governance (2026) · Frontiers in Public Health · cited 6× · doi

    3.1 Basic attributes of the innovation network From an overall network-scale perspective, the technological innovation network for the AI medical device industry in the YRD has shown a continuous expansion trend across the four time periods (Table 1). For the external collaborative network, local network, and two-layer network, both the number of nodes and the number of edges steadily increase. This indicates that a growing number of urban entities are engaging in AI medical device innovation and that col- laborative innovation between cities is steadily increasing. Specifically, the two-layer network showed the most significant growth trend, with nodes increasing from 40 in Phase I to 123 in Phase IV, and the number of edges increasing from 68 to 360. This indicates that as more cities outside the region are incorporated into the cooperation frame- work, innovation resources in the YRD are gradually transcending regional boundaries, evolving from internal regional concentration to cross-regional diffusion. Notably, the growth rate of nodes in the external collaborative network has consistently outpaced that of the TABLE 1 Network characteristics of urban innovation networks from a national-to-local perspective.

    generalfuture work
    Keywords: network innovation number nodes increasing regional perspective medical device trend external collaborative local layer edges
  • Innovation networks in the advanced medical equipment industry: supporting regional digital health systems from a local–national perspective (2025) · Frontiers in Public Health · cited 73× · doi

    Figure  2 shows that, from a local perspective, the intensity of collaborative innovation among cities within the YRD in the advanced medical equipment and device manufacturing industry has grown continuously, with increasingly close connections. Consistent with the national trend, the second level occurs in Phase III and the first level in Phase IV, and shows a radiation from the core city to other cities. Moreover, the first and second levels are mostly found among close TABLE 2 Types of industry-university-research collaboration in the innovation network from a national perspective.

    generalfuture work
    Keywords: shows perspective innovation among cities industry close national second level phase first local intensity collaborative
  • Artificial intelligence as a catalyst for sustainable urban transformation through the triple helix (2026) · Smart Construction and Sustainable Cities · doi

    The paper identifies a gap in the existing literature on the interaction between AI-driven innovation and public–private-university collaborations. The study highlights the need for a comprehensive and interdisciplinary overview of the state of AI-enabled Triple Helix collaboration in urban settings. The analysis emphasizes the importance of addressing the inequitable distribution of technology infrastructure and AI capabilities throughout regions and socioeconomic groups.

    generalstated research gapevidence 5/5
    Keywords: paper identifies gap existing literature interaction between ai-driven

Questions about this gap

The paper identifies a gap in the existing literature on the interaction between AI-driven innovation and public–private-university collaborations. The study highlights the need fo… This is supported by 3 representative gap statements extracted from 3 papers, rated weak evidence.

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