Patterns of knowledge diffusion and knowledge recombination

• Applicant: Professorin Dr. Karin Hoisl
• Subject Area: Management and Marketing
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 503159030

Although the existing literature has considerably improved our understanding of knowledge recombination and diffusion, the two concepts generally exist in parallel literature and have not yet been meaningfully integrated. As a result, the boundaries of the concepts in relation to each other have not been (sufficiently) elaborated. Integration of the two concepts is necessary because knowledge diffusion and knowledge recombination, although different concepts, are mutually dependent. Knowledge must be created (potentially through the recombination of existing knowledge components) before it can be disseminated, and knowledge recombination is impossible if individuals are not aware of the required knowledge components. However, the interdependencies cannot be studied without clear definitional boundaries. The empirical literature also lacks measures to delineate the two concepts; both are still mostly operationalized by patent or publication citation frequencies.A clear definitional delimitation and separate measurement of the two concepts is further important for the successful management of invention and possibly even innovation processes. Only if the separate effects of recombination and diffusion on the value of an invention are clearly identified can the underlying processes be understood and managed. Since existing research does not consider recombination and diffusion separately and does not address the chicken-and-egg problem inherent in the two concepts, we can so far only assume what isolated effect knowledge diffusion and recombination have on the economic value of an invention.To help close these gaps, there are three goals of this project. First, we will clearly distinguish the concepts of knowledge diffusion and knowledge recombination theoretically and investigate their mutual dependencies. Second, we will build knowledge diffusion and knowledge recombination measures using patent indicators and probabilistic topic modeling and trace knowledge diffusion and knowledge recombination patterns in robotics and polymers (to a execute treatment-control design) based on patent data. Third, we will analyze how knowledge diffusion and knowledge recombination patterns impact the economic value of inventions by comparing these patterns prior to and after an exogenous shock, i.e., the Fukushima Daiichi nuclear disaster in Japan in March 2011.

• DFG Programme: Research Grants
• International Connection: Japan
• Co-Investigator: Professor Dr. Dietmar Harhoff
• Cooperation Partner: Professor Sadao Nagaoka