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Abstract Large-scale research infrastructures (LSRIs) are widely acknowledged as a crucial instrument for venturing into the uncharted territories of science and technology, as well as contributing to the well-being of society. However, only a limited number of literature have scrutinized the impact of LSRIs, founded upon a causal inference framework. Moreover, the function of LSRIs in the advancement of innovation at the regional level remains inadequately identified. Drawing on the resource-based view, this study develops a conceptual framework that links the scientific effect of LSRIs to innovation resources in order to assess their impact on knowledge innovation (KI). Taking China’s National Supercomputing Center (NSC) as a case, three major mechanism hypotheses are proposed for the impact of NSC on KI, including basic effect, network effect, and technology effect. Using panel data from 283 cities in China from 2000 to 2020, we employ a spatial difference-in-differences estimation model to examine the impact of NSC on KI. The research finds that: (1) The construction of NSC stimulates KI in local and surrounding areas. (2) The main mechanisms by which NSC promotes KI include the increase in fiscal investment and talents in science, the improvement of digital infrastructure, as well as the enhancement of urban network centrality and innovation efficiency. (3) Geographical proximity, cooperation proximity, and digitization proximity constitute the main channels of policy spillover. (4) NSC has not shown significant promotion of regional innovation convergence, and its radiation influence needs further improvement. (5) The knowledge innovation effects of NSCs manifest heterogeneity based on the distinct knowledge orientation and innovation environment, with this impact being notably pronounced in application innovation-oriented cities such as Shenzhen. The results of this study reveal the positive yet limited impact of NSC on KI and provide a reference for other economies in the areas of LSRIs, digital infrastructure, and the formulation of place-based innovation policy.
Yang et al. (Thu,) studied this question.