摘要
采用超效率DEA法测度泛珠九省在2007—2016年的产学研协同创新效率,并采用Malmquist指数法考察效率的动态变动情况,最后采用Tobit模型验证协同创新效率的关键性影响因素。研究表明,泛珠九省的创新效率总体上趋于改善但也存在短期波动,其中贵州、海南两省的协同创新效率相对最低,而广东省的协同创新效率是泛珠三角区域中最高的。技术进步对协同创新效率的作用最明显,技术效率变动的贡献度却较小,这说明从管理和制度改善方面挖掘效益尚存在较大的空间。高校参与合作及转移知识的能力、企业吸收及应用知识的能力、政府及金融机构的支持程度、产学研合作关系对协同创新效率的改进都具有显著的正向影响,其中政府及金融机构支持的作用最为明显,而地区经济发展程度的影响则不显著。
The super-efficiency DEA method was used to measure the efficiency of industry-university-research synergy innovation in the nine provinces of the Pan-Pearl River Delta from 2007 to 2016,and the Malmquist index method was used to investigate the efficiency dynamic changes.The Tobit model was used to verify the key effect factors to the synergy innovation efficiency.The results show that the innovation efficiency of the nine provinces tends to improve on the whole but there are also short-term fluctuations.Among them,the synergy innovation efficiency of Guizhou and Hainan province is relatively the lowest,while the synergy innovation efficiency of Guangdong Province is the highest in the Pan-Pearl River Delta region.The effect of technology progress on the efficiency of synergy innovation is the most obvious,while the contribution of changes in technology efficiency is relatively small.The result shows that there is still a lot of room for digging benefits from the management and system improvement.The“ability of universities to participate in cooperation and transfer knowledge”,“the ability of enterprises to absorb and apply knowledge”,“the degree of support from the government and financial institutions”,and“the cooperation relationship of industry-university-research”have a significant positive impact on the improvement of synergy innovation efficiency,and the role of government and financial institution support is the most obvious,while the influence of regional economic development is not significant.
作者
贺灵
蒋晨帆
易秋平
HE Ling;JIANG Chen-fan;YI Qiu-ping(Business School,Hunan University of Science and Technology,Xiangtan Hunan 411201,China)
出处
《科技和产业》
2021年第8期1-7,共7页
Science Technology and Industry
基金
湖南省哲学社会科学基金资助项目(18JD30)
湖南省教育厅科学研究项目(17C0668)。
