‘Buzz-and-Pipeline’ Dynamics in AI Innovation Network: A Case Study of Zhangjiang National Innovation Demonstration Zone, Shanghai - Yuanyuan Wan; Gang Zeng; Jiawei Wang; Lin Zou (Land)
The success of a cluster depends on the interplay between intra- and inter-regional collaboration, while empirical research on the mechanisms through which intra- and inter-regional collaborations trigger cluster growth is rarely focused. Based on the local buzz–global pipelines framework and incorporating an evolutionary perspective, we explore how intra- and inter-regional innovation networks can be integrated to drive the growth of emerging industries. We draw on Zhangjiang, China’s most advanced AI industry cluster, using social network analysis and qualitative methods, combining patent data with semi-structured interviews. The results indicate that with the return of multinational corporations and the limitation of Western technology, universities have become the primary source of AI innovation in Zhangjiang. The government has played a pivotal role in propelling the accelerated growth of China’s AI industry, particularly through the backing of pioneering AI private enterprises and the calibration of the potential inefficiencies associated with a state-led model with the dynamism of market forces. The ‘Buzz-and-pipeline’ dynamics in the AI innovation network are shaped by four processes: local networking, market demand, resource integration, and policy synergy. This underscores the intricate interconnections between the national and local scales in AI innovation networks.