Mapping Innovation Networks: A Network-Based Approach to Actor Heterogeneity in National Innovation Systems

TL;DR

This paper introduces a network-based method using economic complexity theory to map and analyze the heterogeneity and structure of innovation actors within national innovation systems, demonstrated on Korean data.

Contribution

It presents a novel capability-based network approach that captures actor heterogeneity and structural complexity beyond traditional typologies.

Findings

Identifies a stratified system of actors with varying diversification levels.

Reveals assortative and hierarchical structures in the innovation network.

Demonstrates the method's scalability and applicability to national data.

Abstract

The Triple Helix model has provided a foundational framework for analyzing National Innovation Systems by highlighting the roles of universities, industries, and government research institutes. However, increasing heterogeneity within these actor groups limits the explanatory power of typological approaches. This study introduces a capability-based network methodology that maps the structural relationships among innovation actors based on the similarity of their research and development (R&D) capabilities. Drawing on Economic Complexity Theory, we measure each actor's revealed comparative advantage (RCA) across scientific and technological fields and construct an R&D Actor Space - a proximity-based network that reflects the relational configuration of innovation capacities. Applying this method to Korean R&D data, we uncover a stratified system in which central, highly diversified universities coexist with more specialized firms and government institutes. Network analysis reveals assortative and unequal structures, and hierarchical clustering further highlights layered subgroupings. By moving beyond categorical classification, this capability-based network approach provides a scalable and generalizable tool for analyzing structural complexity within national innovation systems.