Exploring the subject heterogeneity of scientific research projects funding-example of the Chinese natural science foundation

Abstract

In the increasingly competitive landscape of science and technology funding, understanding the heterogeneous factors and outcomes in funding allocation is crucial. This study proposes a research framework of subject heterogeneity to explore how the individual and combined characteristics of scholars and research topics impact funding acquisition, intensity, and performance. We use the case of the National Natural Science Foundation of China (NSFC) funding for artificial intelligence projects from 2009 to 2018 to empirically validate our framework. The findings reveal that scholars affiliated with high-level institutions, who focus on specialized areas and produce high-quality representative work, are more likely to secure funding. Unexpectedly, funding incentives did not significantly alter scholars' enthusiasm for pursuing popular topics. Moreover, the results indicate that funding has a more substantial impact on cultivating scholars than on advancing new research topics, particularly in the short term. Expanding the scope of funding proves to be more effective in enhancing research performance than merely increasing funding intensity. These insights provide valuable guidance for researchers in topic selection and submission strategies, as well as for policymakers aiming to optimize the management of competitive scientific projects.