Evaluation of Innovation Efficiency and Innovation Mode of Patent-Intensive Industries

Jianyun Cao
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Abstract

Existing researches by Chinese researchers on the innovation performance of patent-intensive industries usually use the amount of patent grants, Innovation performance is not fully reflected in the relationship between innovation input and innovation output. This paper aims to open the “black box” of the innovation process and divides the innovation process into R&D process and the process of scientific output converted into economic output with the intention of providing a better understanding of the important role of patents in the development of industries and ideas for the formulation of industrial policies by focusing on the innovation performance and innovation mode of patent-intensive industries during 2004–2016 using DEA method. Results show that the innovation efficiency of Guangdong's patent-intensive industries is very low with an average level of 0.477 in the R&D stage and 0.361 in the stage of technological achievement transformation, which is highly related to the government-led mode of technological innovation, due to the non-optimal allocation and inefficient management of innovative resources, government-led technological innovation always leads to low quality of technological innovations. In addition, there are great differences in the innovation modes of patent-intensive industries. Therefore, it is necessary for the government to take the differences among different industrial innovation modes into account when formulating industrial and technological policies to improve innovation performance.
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专利密集型产业创新效率与创新模式评价
国内学者对专利密集型产业创新绩效的现有研究多采用专利授权额作为衡量指标,创新绩效在创新投入与创新产出之间的关系上没有得到充分体现。本文以2004-2016年专利密集型产业的创新绩效和创新模式为研究重点,运用DEA方法,打开创新过程的“黑箱”,将创新过程分为研发过程和科技产出转化为经济产出的过程,旨在更好地理解专利在产业发展中的重要作用,为产业政策的制定提供思路。结果表明,广东省专利密集型产业的创新效率非常低,研发阶段的平均效率为0.477,技术成果转化阶段的平均效率为0.361,这与政府主导的技术创新模式高度相关,由于创新资源的非优化配置和低效管理,政府主导的技术创新往往导致技术创新质量低下。此外,专利密集型产业的创新模式也存在较大差异。因此,政府在制定产业和技术政策时,有必要考虑不同产业创新模式之间的差异,以提高创新绩效。
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