Drivers of artificial intelligence innovation in manufacturing clusters
Insights from cellular automata simulations
Bibliographic Data
| ID | 22230641 |
|---|---|
| Authors | Juan Yu (0000-0002-0553-0196, Guangdong University of Technology, corresponding author), Weihong Xie (0009-0000-8688-182X, Guangdong University of Technology), Xiuyi Zhao (Guangdong University of Technology), Zhongshun Li (Guangdong University of Technology), Liang Guo (0000-0003-2111-0631, Guangdong University of Technology) |
| Year | 2025 |
| Volume | 12 |
| Issue | 1 |
| Publication date | 2025-07-05 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Humanities and Social Sciences Communications (JOURNAL) |
| Journal identifiers | ISSN: 2662-9992 • E-ISSN: 2662-9992 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1057/s41599-025-05386-7 |
| OpenAlex | W4412049873 |
| Language | EN |
| Citations received | 2 |
| References cited | 60 |
With the rapid development of the global economy and artificial intelligence (AI) technologies, AI-driven innovation has become a key driver of economic growth in manufacturing clusters. This study investigates the main drivers of AI innovation in manufacturing clusters through the lens of evolutionary economic geography theory. Three primary driving factors are identified: cluster resources, cluster networks, and cluster environments. An evolutionary model based on Cellular Automata (CA) is developed to quantitatively analyze their influence, followed by simulation experiments. The results show a positive correlation between these factors and the evolution of AI innovation within industrial clusters. Further case studies of AI-enabled manufacturing clusters, including Zhongguancun, Shenzhen, and Bangalore, substantiate these findings. The study highlights the critical role of resource endowments, AI-driven inter-firm collaboration, and supportive policy frameworks in fostering AI innovation. The findings provide a deeper understanding of clustered innovation ecosystems and the theoretical foundations of collective learning and competitive advantage in the AI era. This research also has broad implications, particularly for interdisciplinary studies in digital humanities, complex network analysis, and the socioeconomic impact of AI-driven technological transformation
Cellular automaton · Cellular manufacturing · Manufacturing engineering · Cellular Automata and Applications · Computer Science · Engineering · Artificial Intelligence
Interfirm Collaboration Networks
Sustainability innovations and firm competitiveness
Knowledge, Clusters, and Competitive Advantage
Artificial intelligence, firm growth, and product innovation
Exploring the multifaceted impacts of artificial intelligence on public organizations, business, and society
Deconstruction of green product innovation drivers for regional export-oriented industrial enterprises in China
Artificial intelligence, big data, algorithms and Industry 4.0 in firms and clusters
Clustering as an organizational response to capital market inefficiency
Path dependence and regional economic evolution
Deconstructing clusters
| Unique citing works | 2 |
|---|---|
| Citations per year | 2 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |