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Inter-Brain Synchrony in Open-Ended Collaborative Learning: An fNIRS-Hyperscanning Study
Published on: July 21, 2021
How similar should collaborators be in inter-organizational learning: Optimal cognitive proximity and knowledge
Yeokyung Hwang1,2, Junseok Hwang1,2, Junmin Lee3
1Technology Management, Economics, and Policy Program, Seoul National University, Seoul, South Korea.
Knowledge complexity impacts collaborative innovation differently. High complexity favors more partners for volume but hinders quality by weakening the link between proximity and innovation outcomes.
Area of Science:
- Innovation Studies
- Organizational Behavior
- Intellectual Property Management
Background:
- Effective knowledge exchange is vital for innovation in knowledge-intensive industries.
- The interplay between cognitive proximity and collaborative innovation, especially in complex knowledge environments, requires further investigation.
- Existing research suggests a non-linear, inverted U-shaped relationship between cognitive proximity and innovation, but the moderating role of knowledge complexity is unclear.
Purpose of the Study:
- To examine how knowledge complexity moderates the relationship between cognitive proximity and collaborative innovation.
- To differentiate the effects on collaboration volume versus collaboration quality.
- To provide insights into partner selection strategies in complex innovation ecosystems.
Main Methods:
- Analysis of over 650,000 U.S. biotechnology patents (1976-2024) from over 57,000 organizations.
- Measurement of cognitive proximity using CPC-based Jaccard similarity.
- Operationalization of knowledge complexity via a structural complexity framework based on knowledge combination networks.
- Application of negative binomial regressions to analyze the data.
Main Results:
- Knowledge complexity moderates the proximity-innovation relationship differently for collaboration volume and quality.
- For collaboration volume, increased complexity shifts the optimal proximity rightward and flattens the inverted U-curve.
- For collaboration quality, high complexity causes a leftward shift and a near-horizontal relationship, indicating a breakdown of the curvilinear effect.
Conclusions:
- Cognitive proximity influences partner selection and innovation realization through distinct mechanisms, particularly under high knowledge complexity.
- Absorptive capacity remains key in partnership decisions, but novelty generation disconnects from proximity effects as complexity rises.
- Knowledge complexity acts as a structural moderator, refining proximity theory and informing strategic partner selection in advanced innovation.
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