Investigation on the management of college performance pay with linear programming and mathematical statistics

Abstract

The performance-related pay system in colleges and universities is one of the hot spots in the reform of the wage system in colleges and universities in recent years. It is an important measure to improve the quality of education and teaching in colleges and universities and the construction of talent teams. However, there are many problems in the performance-related pay system of colleges and universities, such as unreasonable evaluation indicators, unfair weight distribution, etc., which makes it difficult to accurately reflect the work performance of teachers and staff in the measurement of performance-related pay. Based on this background and trend, this paper conducted an in-depth discussion on the salary system in China’s colleges and universities, and used the support vector regression algorithm to study the performance-based salary management of colleges and universities based on linear programming and mathematical statistics. The research showed that with other conditions remaining unchanged, the proportions of primary, intermediate, deputy and senior high school students who were dissatisfied with the system of performance-based pay in colleges and universities were 82%, 57%, 46%, and 9%, respectively. After applying linear programming and mathematical statistics, the proportions of elementary, intermediate, sub-high and ortho-high became 1%, 2%, 5% and 7% respectively. The decline of the first three was particularly obvious, and the teachers with positive high school also dropped by 2%, indicating that linear programming and mathematical statistics were beneficial to the management of performance wages in colleges and universities.