Intellectual Capital for Monitoring Technology Transfer Maturity in National Innovation Systems

Abstract

This paper proposes a methodological framework for restructuring the innovation indicator system used to monitor Brazilian Scientific, Technological and Innovation Institutions (ICTs) through the lens of Intellectual Capital (IC). Traditional metrics of technology transfer, such as patent counts and licensing revenues, often suffer from an outcome bias, providing only a partial representation of innovation performance while overlooking the institutional capacities and organisational routines that enable knowledge generation and transfer. To address this limitation, the study reorganises 77 original metrics into the three core dimensions of Intellectual Capital: Human Capital, Structural Capital and Relational Capital. These dimensions underpin a causal analytical model linking intangible assets to innovation capacity, technology transfer processes and economic impact. Rather than relying on isolated outputs, the framework emphasises the role of systemic capabilities in shaping innovation performance. It further incorporates Absorptive Capacity (ACAP) as a contextual and mediating analytical dimension, enabling the assessment of institutional readiness to assimilate and exploit externally generated knowledge within the broader set of structural and relational conditions shaping transfer effectiveness. The methodology advances beyond descriptive measurement by establishing analytical relationships between indicators and by proposing a synthetic Technology Transfer Maturity Index (TTMI), designed to identify structural bottlenecks and institutional maturity profiles through cluster analysis. This approach enables policymakers to move from static reporting to a more structured interpretation of how knowledge is produced, mobilised and converted into value. The framework has been developed and submitted to a working group coordinated by the Brazilian Ministry of Science, Technology and Innovation (MCTI), which received it favourably as a basis for reconsidering the national data collection system for ICTs. By transforming fragmented metrics into structured analytical insights, the proposed approach provides a scalable model for national monitoring and evidence-based policy design. The study contributes to the Intellectual Capital and knowledge management literature by demonstrating how IC-based analytical structures can enhance the interpretation of innovation performance in complex national innovation systems.