Research on the Evaluation of Scientific Research Efficiency and Its Influencing Factors in Chinese Universities: An Empirical Study Based on DEA and Tobit Model

Yang Luo^*Ziting Jian

• Catholic University of Korea, Seoul, Republic of Korea

Objective: This study evaluates the scientific research efficiency of Chinese universities and analyzes its influencing factors using a two-stage approach combining Data Envelopment Analysis (DEA) and a Tobit regression model. Methodology: An input-output framework for research performance is constructed using university-level data (e.g. R and D expenditures, research staff, project counts as inputs; publications, patents, and academic awards as outputs). DEA is first employed to compute efficiency scores for a sample of universities, and then a Tobit regression is applied to identify how various factors (such as funding sources, human resource allocation, and collaboration activities) affect these efficiency scores. Results: The DEA results show that the overall research efficiency of Chinese universities is moderate, with relatively few institutions achieving DEA efficiency (score = 1) and many operating below the frontier. There are notable differences by region and university type: on average, "Project 985" universities (top-tier research universities) exhibit higher efficiency than "Project 211" universities and other general universities, and institutions in eastern coastal regions tend to outperform those in central and western regions. The Tobit regression reveals that government R and D funding and the number of research projects have positive impacts on efficiency (p ¡ 0.05), whereas excessive industry-sponsored research funding correlates with lower efficiency (p ¡ 0.05). The size of research human resources shows no significant effect, suggesting diminishing returns to simply adding more researchers. Significance: These findings indicate that while Chinese universities have expanded their research inputs and outputs rapidly in recent years, efficiency in converting resources to results remains suboptimal. Policy implications include the need to optimize resource allocation, strengthen research management, and create incentives for efficient research practices. This study contributes to the literature by providing an up-to-date empirical assessment of research efficiency in Chinese higher education and offering insights for improving research productivity through targeted reforms.