Abstract: The imbalance in salary structure is a key issue that constrains the vitality and innovation efficiency of university teachers. Focusing on the high-quality development of higher education, this study integrates entropy theory and elasticity theory to construct a quantitative analysis framework, diagnoses structural defects in the salary system, and proposes a systematic optimization path based on empirical evidence of incentive effects. The study constructs an entropy model and an imbalance index of salary structure through information entropy, establishes a fixed effects model combined with elasticity theory, and then constructs a multi-objective programming model and uses the NSGA-II algorithm to solve for the optimal structure. Panel data from 35 "Double First-Class" universities from 2018 to 2022 are empirically analyzed. The results show that the salary structure of the sample universities is moderately imbalanced, with an average imbalance index of 0.417, a relatively low proportion of basic salary, and insufficient long-term incentives. There are significant differences in the elasticity of various salary components, with long-term incentives exerting the greatest long-term elasticity on comprehensive performance. There is an inverted U-shaped relationship between the structural imbalance index and the scientific research output. After optimization, the salary structure can improve comprehensive performance by approximately 18.7%, and the structural imbalance index decreases to 0.286. The study concludes that the salary reform for university teachers needs to shift from “quantitative growth” to “structural optimization”. The proposed three-dimensional path of “benchmark guarantee, elastic incentives, and long-term development” can effectively correct the distortion of the salary structure and provide theoretical basis and decision-making reference for a new salary system.
Keywords: university teachers; salary structure; structural imbalance; entropy measurement; elasticity theory; multi-objective optimization
合肥工业大学学报自科版