| “双一流”目标下一流大学科研效率评价 |
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| 引用本文： | 李康,范跃进.“双一流”目标下一流大学科研效率评价[J].科研管理,2022,43(9):41-47. |
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| 作者姓名： | 李康 范跃进 |
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| 作者单位： | 青岛大学商学院，山东 青岛266071 |
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| 基金项目： | 国家社会科学基金项目：“进一步开放背景下推进事业单位管办评分离改革研究：以高校改革为例”（18BZZ099，2018.01—2020.12）；山东省社科规划研究项目：“‘双一流’建设背景下山东省属高校管理团队建设路径探索”（19CJYJ12，2019.03—2021.03）。 |
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| 摘 要： | “双一流”建设是我国高等教育强国建设的战略安排，是我国高等教育发展的必由之路。“双一流”建设之一流大学建设高校，是高等教育强国建设的“领头雁”，研究一流大学建设高校科研创新效率，加快提升科学研究水平具有重大现实意义。本文以一流大学高校为研究对象，构建了突出科研产出质量和服务的综合效率评价指标体系，在传统DEA模型基础上运用随机前沿分析理论，通过三阶段DEA模型方法测度一流大学建设高校的科研效率，并进一步分析环境因素对科研效率的影响差异。研究结果表明：（1）环境变量和随机误差是影响一流大学科研效率的重要因素，我国一流大学整体科研效率存在虚高现象，剔除环境因素后样本高校综合效率和纯技术效率均值都明显下降。（2）地区经济水平、居民受教育程度和政府扶持力度对各个高校科研效率存在差异性影响，并据此将高校分为稳定型、发展型和改进型三类。（3）一流大学建设高校科研效率存在分化倾向，规模收益递减现象突出，其科研效率提升的关键是缩减规模、完善内部治理结构、优化资源配置，持续深化科研体系改革。
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| 关 键 词： | 一流大学 科研效率 指标体系 三阶段DEA模型 |
| 收稿时间： | 2019-09-25 |
| 修稿时间： | 2020-04-01 |
An evaluation of the scientific research efficiency of first-class universities under the goal of construction of "double first-class university" |
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| Li Kang,Fan Yuejin.An evaluation of the scientific research efficiency of first-class universities under the goal of construction of "double first-class university"[J].Science Research Management,2022,43(9):41-47. |
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| Authors: | Li Kang Fan Yuejin |
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| Institution: | School of Business, Qingdao University, Qingdao 266071, Shandong, China; |
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| Abstract: | The "double first-class university" construction indicates the direction for the development of higher education in China, and it is a systematic project of China′s higher education reform. In October 2015, the State Council proposed a three-step strategy for the construction of world-class universities. By the middle of 21st century the number and capability of first-class universities ranks among the best in the world and make China an international higher education power. In September 2017, the Ministry of Education, Ministry of Finance, and National Development and Reform Commission jointly announced the list of first-class universities, and 42 universities have been officially confirmed as world-class universities. These universities are the "leading goose" for China to enter the forefront of world-class universities. It occupies a large amount of high-quality education resources. A series of issues such as whether it can be used efficiently and how the resources can be used are urgently needed to be solved. In the meantime, the evaluation of scientific research efficiency is also needed to optimize the allocation of higher education resources and improve scientific research in universities.
Date envelopment analysis (DEA) is a non-parametric mathematical programming method used to evaluate the relative effectiveness of the similar unit. This method was proposed by the famous American operations researcher A. Charnes and W. W. Cooper in 1978. Professor Levin introduced DEA model into the field of education to measure the technical efficiency of educational production. After that, more and more scholars began to use DEA to discuss the efficiency of higher education. However, when applying DEA model to study the efficiency of higher education, most of them ignore the influence of external environment on the efficiency of decision-making unit, and generally characterize the efficiency difference caused by environment factors as the difference of management efficiency.
This study builds a scientific research efficiency evaluation index system for the first-class universities. Drawing on the ranking of the world′s top four world universities, the index system highlights the quality and service of scientific research output, and try to fully and objectively evaluated the scientific research input and output of universities. Since traditional DEA models cannot distinguish among management inefficiency, environmental impact and statistical noise, to make up this deficiency, we use three-stage DEA model based on stochastic frontier analysis to evaluate the research efficiency of universities which is affected by environment. This paper also deeply explores the impact of environmental variables such as regional economy, residents′ education level and government support on the research efficiency of universities. The study results show that:
(1) The scientific research efficiency of the sample universities is relatively high without considering the environmental factors and random disturbance, but the scientific research efficiency declines significantly after eliminating environmental factors. Specifically, the mean comprehensive efficiency decreased from 0.92 to 0.89, the average pure technical efficiency decreased from 0.97 to 0.93. Compared with the first stage, the number of DEA effective universities decreased from 19 to 18, and in the third stage, Fudan University, Nanjing University and Shandong University changed from non-DEA to DEA effective, as for the Ocean University of China, South China University of Technology, Chongqing University and Northwest A& F university, the status appears totally converse outcome.
(2) Environmental factors, such as regional economic level, residents′ education and local government′s support, play an important role in influencing the research efficiency of first-class universities, but have different impacts on different universities, therefore we can divide universities into three categories. The first type is stable universities, and there are 15 universities that are effective in the first and third stages of DEA calculation, which means environmental factors have no impact on these universities, and effective management keeps their scientific research efficiency at a high level. The second type is development universities, and there are 7 universities that have been proved to have improved their scientific research efficiency after eliminating the influence of environmental factors. For this type of colleges, the government should give appropriate policy preference to curb the negative effects, which are caused by regional economic, cultural and policy differences, so as to provide better external conditions for these universities to promote the efficiency of scientific research. The third type is retrograde universities, and there are 10 universities belong to this category, including China Agricultural University, Tianjin University and Jilin University, etc. The research efficiency of these universities in the third stage is significantly lower than that in the first stage. For this type of universities, it′s necessary to strength the management ability of university manages and construct a reasonable evaluation model in order to reduce their management inefficiency.
(3) The scale returns of non-DEA effective universities are generally decreasing. Among the 14 non-DEA effective universities, only Ocean University of China and Chongqing University have increasing returns to scale, while the other 12 universities have decreasing returns to scale. Obviously, the scale of first-class universities has exceeded the most appropriate level, and it′s impossible to improve the scientific research efficiency by expending the scale of universities. Without the improvement of management efficiency, it′s inevitable that the "double first-class university" construction cannot be sustainable simply relying on the increase of investment.
To achieve the goal of "double first-class university" construction, first-class universities should transform from the extensive development to the intensive development, and from the expansion of scale to the improvement of quality and efficiency. On the one hand, the government and social organization is supposed to take great measures in leading the public opinion to make a correct evaluation. Government departments, evaluation agencies and various higher education associations should pay more attention to the quality and efficiency of scientific research achievements, and establish an external environment in which universities focus on improving the quality and efficiency of scientific research. On the other hand, colleges and universities should deepen the reform of scientific research system, optimize the allocation of scientific research resources, and strengthen the internal supervision and management mechanism for scientific research quality. |
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| Keywords: | first-class universities scientific research efficiency index system three-stage DEA model |
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