Large-scale, publicly funded research and development (R&D) programs are implemented to accelerate state-of-the-art science, technology, and innovation applications that are expected to solve various societal problems. The present study aims to build on the body of theory on the mechanisms that promote or impede the creation of intellectual property in such programs. Using a mixed methods approach and combining quantitative network analysis and qualitative semistructured interviews, we conducted a case study to investigate best practices in terms of intellectual property creation in a Japanese governmental research and development program. The results of the network analysis showed that the core/periphery structure in the co-inventor network of patents and joint application by a university and a startup promoted intellectual property creation. The results of the interview confirmed the significance of a reciprocal mindset, which the researchers in academia could acquire through collaboration with a startup. These results suggest that a knowledge logistics system for agile intellectual property management can be established by learning to acquire tacit knowledge on social implementation. Furthermore, we focus on the principal–agent relationship between knowledge producers and knowledge consumers as a factor that impedes the creation of intellectual property. We also discuss adverse selection and moral hazards caused by information asymmetry between knowledge producers and knowledge consumers and how to deal with them.
Intellectual Property Management in Publicly Funded R&D Program and Projects: Optimizing Principal–Agent Relationship through Transdisciplinary Approach
