Institute of Geography, Heidelberg University, Heidelberg, Germany.
Institute of Management, Shanghai University of Engineering Science, Shanghai, China.
PLoS One. 2021 Dec 16;16(12):e0261343. doi: 10.1371/journal.pone.0261343. eCollection 2021.
Universities are important sources of knowledge and key members of the regional innovation system. The key problem in Chinese universities is the low efficiency of the scientific and technological (S&T) transformation, which limits the promotion of regional innovation and economic development. This article proposes the three-stage efficiency analytical framework, which regards it as a complex and interactive process. Avoiding the problem of considering the input and output of university S&T transformation as a "black box" and neglecting the links among different transformation stages. The super efficiency network SBM model is applied to the heterogeneous region of the Yangtze River Economic Belt. Empirical research proves that university S&T transformation has not been effectively improved and the scientific resources invested in universities have not been efficiently utilized in recent years. Generally, Despite the correlation between regional economy and transformation efficiency, the exclusive increase in resources is not enough. Regional openness and the quality of research talents are key factors for the application of technological innovation and technology marketization. Universities should not only pursue the number of research outputs but pay more attention to high-quality knowledge production to overcome difficulties in research achievements transformation.
大学是知识的重要来源，也是区域创新系统的重要成员。中国大学的关键问题是科技（S&T）转化效率低下，这限制了区域创新和经济发展的推进。本文提出了三阶段效率分析框架，将其视为一个复杂和互动的过程。避免了将大学 S&T 转化的投入和产出视为“黑箱”，忽视了不同转化阶段之间联系的问题。超效率网络 SBM 模型应用于长江经济带的异质区域。实证研究证明，近年来，大学 S&T 转化并没有得到有效提高，投入大学的科学资源也没有得到有效利用。总的来说，尽管区域经济与转化效率之间存在相关性，但仅增加资源是不够的。区域开放性和研究人才的质量是技术创新和技术市场化应用的关键因素。大学不仅要追求研究成果的数量，还要更加注重高质量的知识生产，以克服研究成果转化的困难。
