Exploring City-Level Scholar Funding Service Impact: A Data-Driven Decision-Making System based on Difference-in-Differences Method

Numerous cities offer a diverse array of funding services to scholars. This study introduces data-driven methodologies to investigate the effects of city-level funding initiatives on annual publication counts and annual cumulative impact factors-two metrics of academic impact. We build a local dataset according to scholars' information from the Scopus database and design a complex network-based Difference-in-Differences (DID) methodology. In addition, we utilize data from the Clarivate's Journal Citation Reports to measure academic achievements and influence. A novel aspect of our research is the data-based scholar-journal publication network construction, which aids in the meticulous selection of a control group, enhancing the robustness and efficiency of our research. Our results demonstrate that the city-level funding service significantly improves the academic output of distinguished scholars. Notably, the study uncovers a temporal lag in the impact of funding on academic output, typically ranging from one to two years. Further analysis reveals that the effectiveness of the project in enhancing scholars' academic impact varies among individuals. Based on these findings, recommendations for the rational adjustment of funding and evaluation criteria for the funding support service are proposed. This paper underscores the importance of a data-driven approach in policy design and assessment, particularly in the realm of academic funding services.