A Five-Stage DEA Model for Technological Innovation Efficiency of China's Strategic Emerging Industries, Considering Environmental Factors and Statistical Errors

The development of strategic emerging industries is important for China's Economic structure optimization and low-carbon economy. The purpose of this paper is to scientifically evaluate the technological innovation efficiency of strategic emerging industries. A five-stage data envelopment analysis (DEA) model was proposed. The model combines the super slack-based-measure (SBM)-Tobit-Super SBM and bootstrap DEA, improving the classical DEA model as well as the popular four-stage DEA model method. The purpose of this study is to design a scientific and accurate method to evaluate the efficiency of technological innovation, considering the impact of environmental factors and statistical errors on the efficiency value. Input indicators were considered from the perspectives of capital, labour, and land, and output indicators were considered from the perspectives of science, technology, and the economy. Environmental factors such as regional economic level, labour market, and financial support were excluded. The empirical results show that: (1) the five-stage DEA model eliminates environmental interference and avoids the impact of statistical noise to reduce outliers; (2) after eliminating environmental interference and statistical noise, the technological innovation efficiency of strategic emerging industries in the Eastern, Central, and Western regions of China show a "U-shaped" fluctuation, with the highest in the Eastern region (0.57), followed by the Western region (0.56), and the Central region (0.53); and (3) environmental factors have a significant impact on the innovation activities of China's strategic emerging industries.