The Impact of Fractal Characteristics of Knowledge Networks on Innovation Performance
Bibliographic Data
| ID | 19450212 |
|---|---|
| Authors | Runhui Lin (0009-0008-8922-2991, Nankai University), Meichen Chen (Meichen Chen (corresponding author), Business School, Nankai University, Tianjin, China., corresponding author), Qian Wang (0000-0002-8601-749X, Nankai University) |
| Year | 2026 |
| Volume | 31 |
| Issue | 1 |
| Pages | 139-156 |
| Publication date | 2026-03-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Science Technology and Society (JOURNAL) |
| Journal identifiers | ISSN: 0971-7218 • E-ISSN: 0973-0796 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/09717218251397458 |
| OpenAlex | W4417186390 |
| Language | EN |
| References cited | 25 |
Knowledge innovation increasingly relies on complex network structures, and network research has provided many insights for innovation. However, in the field of innovation management, current research on the impact of knowledge networks on innovation performance mainly focuses on static local characteristics of networks, neglecting their global structural features. Based on an exploration of the fractal characteristics of knowledge networks, this study constructs a theoretical model linking the fractal characteristics of enterprise knowledge networks to innovation performance. Additionally, it investigates the moderating role of the quantity of knowledge elements in the relationship between the fractal dimensions of knowledge networks and innovation performance. Hypotheses are tested using patent data submitted by Huawei in China between 1995 and 2021. The results show that small-scale fractal dimensions have a significantly negative effect on innovation performance, while large-scale fractal dimensions have a positive effect on innovation performance. Moreover, an increase in the quantity of knowledge elements weakens these effects
Artificial neural network · Fractal · Fractal analysis · Innovation Management · Knowledge economy · Complex Systems and Time Series Analysis · Innovation and Knowledge Management · University-Industry-Government Innovation Models
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Knowledge-relatedness in firm technological diversification
Knowledge Networks, Collaboration Networks, and Exploratory Innovation
Technology as a complex adaptive system
Recombinant Growth
A Penny for Your Quotes
Ambidextrous Organizations
Recombinant Uncertainty in Technological Search
Exploitative and exploratory innovations in knowledge network and collaboration network
Network structure and the diffusion of knowledge
Knowledge of the Firm, Combinative Capabilities, and the Replication of Technology
Exploration and Exploitation in Organizational Learning
Collaboration and Creativity
| Highly cited | No |
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