Abstract: The effective allocation and utilization of research funding serve as a fundamental driver of scientific and technological innovation in universities and constitute a critical domain in the reform of national science and technology governance systems. In recent years, Chinese universities have made significant advancements in strengthening research funding management. However, existing assessment frameworks lack a rigorous, quantitative approach to evaluating university research funding management capabilities, and there remains an absence of in-depth and precise evaluations of research funding output performance. To address these deficiencies, this study constructs a two-stage entropy-based analytical framework to quantitatively assess the efficiency and effectiveness of university research funding utilization. In the first stage, leveraging the classical entropy model, we quantify the entropy value of research funding management and introduce the "negative entropy force" metric to systematically evaluate research funding management capability. In the second stage, the "negative entropy force" metric is further integrated into a regression model to establish the relationship between research funding management capabilities and multidimensional research output indicators, thereby enabling a comprehensive assessment of research funding utilization performance. This systematic research framework facilitates the identification of underlying inefficiencies in university research funding allocation and utilization, offering data-driven insights and strategic recommendations to inform policy optimization and enhance the overall effectiveness of research funding governance in Chinese universities.