|ZHU Chen (University of Tokyo) / MOTOHASHI Kazuyuki (Faculty Fellow, RIETI)
|April 2022 22-E-030
|Research on innovation ecosystem formation processes
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This paper investigates the impact of government R&D spending on promoting technology convergence. We test the hypotheses that a government funding program has a positive effect on technology convergence and the effects are heterogenous on different participants (i.e., academic, and industrial inventors). To investigate this, our empirical test applies the Advanced Sequencing Technology Program (ASTP) as one example. We develop a novel dataset by linking the ASTP grantee information with the PATSTAT patent database. Based on this, we create inventor-level characteristics to implement propensity score matching, selecting an appropriate control group of inventors who are comparable to those enrolled in the ASTP. We then employ DiD models to evaluate the impact of the program on the matched sample. The results confirm that the program is a driving force of technology convergence. The findings also indicate that the program is more influential to industry inventors than to their academic counterparts. Additionally, we conceptualize a ‘leverage effect’ of the program and show it can attract many external industrial inventors. The work contributes to better understanding the role of a government-funded program in encouraging convergence and providing implications for developing convergence-related R&D programs in the future.
Published: Zhu, Chen, and Kazuyuki Motohashi, 2023. "Government R&D spending as a driving force of technology convergence: A case of study of the Advanced Sequencing Technology Program," Scientometrics, Volume 128, Issue 5 (2023), 3035–3065.