This study demonstrates the impact of fractal dimensions on innovation performance in knowledge networks, suggesting management strategies for optimization.
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.
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Lin et al. (2025) studied this question.
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