Research on dynamic evaluation method of individual scientific impact under multiple key nodes

Abstract

Introduction. The purpose of this paper is to research an evaluation method for the development trend of the scientific impact of individual scientists before and after different key nodes in scientific careers. Method. This paper focuses on scientists at universities in Shanghai who obtained their first key programmes from the National Natural Science Foundation of China (NSFC) from 2011 to 2015. A two-node piecewise linear regression is used to divide the scientists’ individual academic trajectories. The Boston Consulting Group matrix (BCG-M) model is used to propose four types of talent. Analysis. The pr(y)-index is applied to evaluate the scientists’ impact. Several characteristics of the trajectory of the impact of individual scientists are defined by the change in the pr(y)-index growth rate. Results. The scientific impact of most scientists (66% and 62%) increased after they first obtained NSFC funding or their first key programme, respectively. The pr(y)-index of a 5-year time window is more sensitive to judge the of influence on scientific career. Conclusion. The two-node piecewise linear regression model successfully divided the academic trajectories of individual scientists into three stages。NSFC funding promotes academic influence. The talents are divided into star talent, focus talent, question talent and taurus talent.