New research published in Frontiers of Engineering Management reveals how collaboration patterns within innovation communities shape corporate innovation output, providing strategic guidance for firms seeking competitive advantage in technology-driven markets. The study, which analyzed 22 years of patent and network data from the global 3D printing industry, demonstrates that a firm's innovation performance is strongly influenced by how it is embedded in innovation communities.
Researchers from Beijing University of Posts and Telecommunications, Tsinghua University, and the Higher School of Economics in Russia examined collaboration networks based on co-patenting activities using rolling five-year windows, identifying innovation communities through Louvain topological clustering. The study analyzed data from 6,109 organizations over more than two decades, constructing global collaboration networks to understand how network structure drives innovation outcomes.
The research distinguishes between two types of embeddedness: within-community embeddedness representing ties to peers inside the same community, and cross-community embeddedness reflecting ties that bridge multiple communities. Both relational and structural dimensions were evaluated, with innovation performance measured by annual firm-level patent counts. Negative binomial regression models reveal that both embeddedness types significantly enhance innovation output.
Within-community connections provide trusted access to shared knowledge, allowing faster resource integration and reducing coordination costs, while cross-community ties offer diverse expertise and non-redundant information that broaden innovation perspectives. The complete research findings are available at https://doi.org/10.1007/s42524-025-4188-x.
Crucially, the study identifies collaboration complementarity as playing a contingency role—enhancing the returns of within-community ties while reducing the benefits of cross-community connections when complementarity is high. When complementarity is high, firms gain more from within-community relational embeddedness, while the innovation benefits of cross-community collaboration weaken due to integration complexity and resource absorption costs.
"Our results highlight that innovation is not only about forming partnerships, but about forming the right partnerships in the right network positions," the authors stated. "Dense internal ties accelerate trust and knowledge transfer, while cross-community ties introduce novel perspectives. Yet, high complementarity does not always guarantee more innovation—it amplifies internal collaboration benefits but increases coordination costs across communities."
These findings clarify why previous research reported inconsistent results regarding the relationship between network embeddedness and innovation performance. The study provides new evidence for how network structure drives innovation outcomes and reconciles contradictory findings in past literature by highlighting the importance of balancing local cohesion and external openness for innovation growth.
For business leaders, this research offers strategic guidance for managing collaboration portfolios. Companies embedded deeply in innovation communities may strengthen internal ties to leverage complementarities while selectively bridging external communities to maintain diversity of ideas. The analytical framework is applicable to emerging domains such as AI, new materials, and biomanufacturing, suggesting that optimizing embeddedness and collaboration patterns can accelerate technological progress across multiple industries.
Policymakers can use these insights to guide industrial cluster development, promote cross-sector collaboration, and design incentive mechanisms for innovation-driven industries. As digitalization and globalization accelerate knowledge exchange across firms, understanding how to structure collaboration within open innovation ecosystems becomes increasingly critical for maintaining competitive advantage in global markets.
