The Evaluation of the Relative Efficiency of Higher Education Talents Training Based on Data Envelopment Analysis Model

This study evaluates the relative efficiency of talent training in eight distinct Chinese universities from 2018 to 2022 using the data envelopment analysis (DEA) model. An integrated index system covering human resources, material resources, financial inputs, and outputs related to personnel training quality, scientific research achievements, and social service contributions was developed. Both constant-returns-to-scale and variable-returns-to-scale models were applied via DEAP2.1 software to calculate efficiency scores, followed by projection analysis to identify inefficiencies and explore influencing factors. Results show that 50% of institutions achieved optimal comprehensive efficiency, while others faced issues like decreasing returns to scale. Key influences on efficiency included rational allocation of educational funds, faculty research levels, and university-industry collaboration intensity. This study provides a foundation for optimizing resource allocation and improving training quality, serving as a reference for policy makers.