Research on the Evaluation of the Efficiency of High-quality Talent Training in “Double First-Class” Universities in Western China

Abstract This article uses Principal Component Analysis ( PCA ) – Data Envelopment Analysis ( DEA ) – Malmquist Total Factor Productivity (Malmquist) method to analyze the talent training efficiency of 9 “double first-class” universities in Western China. By constructing the evaluation index system and reducing the main factor analysis, the principal-component data is analyzed by DEA -Malmquist model again. The results show that: (1) since the implementation of the national “double first-class” plan, the talent training efficiency of the “double first-class” universities in Western China has been increasing year by year, with an average annual growth rate of 9.01%. (2) Scale reward analysis, the scale benefit of 3 universities is in the optimal state; the scale benefit of 3 universities is in the increasing state; and the other universities are decreasing after 2020. (3) The input redundancy of universities is mainly concentrated in the input of human resources, and mainly in 5 universities, indicating that 5 universities have not reached the ideal output, but the input redundancy rate is decreasing year by year. (4) Insufficient output is mainly concentrated in the output of high-quality and high-level talents and disciplines. Except for 3 universities, all 6 universities have different degrees of insufficient output; among them, one university has insufficient output of high-quality basic talents for 6 consecutive years, and one university has the same situation in 2022.