基于三阶段DEA模型的中国工业企业创新效率评价

Evaluation of Industrial Enterprise's Innovation Efficiency in China Based on Three-stage DEA Model

为了消除环境变量和随机误差对创新效率值的影响,运用Fried等提出的三阶段DEA模型,对1998-2007年中国工业企业创新效率状况进行了实证分析,研究结果表明,中国工业企业创新效率确实受到经济发展水平、外资活动、政府扶持激励政策和市场结构等环境变量和随机因素的影响。在剔除环境和随机因素影响后,1998-2007年间中国各地区工业企业创新效率呈现出下降的趋势,其中,东部的上海、广东、海南和西部的青海四个地区比较稳定地处于前沿面相对效率位置,结合各地区创新效率与R&D投入水平,可以将我国各地区划分为相对效率高投入、相对效率低投入、高效率高投入、高效率低投入、低效率高投入和低效率低投入等六种模式,并根据各种模式有针对性地提出了相关对策建议。

In order to exclude the influence of environmental variables and random error on the innovation efficiency, this paper uses the three-stage DEA model that proposed by Fred etc. to investigate the industrial enterprise＇s innovation efficiency in China in 1998-2007. The results indicate, the industrial enterprise＇s innovation efficiency in China has been affected by environmental variables and random factors such as the economy development level, FDI, government inventive policies and market structure. After excluding the influence of environmental variables and random factors, the industrial enterprise＇s innovation efficiency in various provinces are decreasing in 1998-2007. the Shanghai, Guangdong, Hainan Province in East area and Qinghai Province in West area stay on the efficiency frontier steadily. Considering the industrial enterprise＇s innovation efficiency and R＆D input, the authors divide 30 provinces in China into six types： relative efficiency and high input, relative efficiency and low input, high efficiency and high input, high efficiency and low input, low efficiency and high input as well as low efficiency and low input, and put forward some countermeasures for the different types.