Three-stage super-efficiency DEA models based on the cooperative game and its application on the R&D green innovation of the Chinese high-tech industry. (June 2021) - Chen, Xiaoqing; Liu, Xinwang; Gong, Zaiwu; Xie, Jiangtao
Highlights: Cooperative game is introduced into network DEA models to depict the internal complex relationships. In this three-stage framework, shared inputs and undesirable outputs are considered. Super-efficiency is applied for further differentiation and ranking of the multiple efficient DMUs. Tobit model is used to investigate the factors associated with low efficiency. Abstract: In this paper, the R&D green innovation of the Chinese high-tech industry can be regarded as a system of three consequent stages. Firstly, considering the existence of multiple effective decision-making units at the same time, a three-stage super-efficiency DEA model is proposed. Secondly, considering the "internal relationships" and "the distribution structure of initial inputs and undesirable outputs", the above model is extended into a three-stage super-efficiency DEA model with a cooperative game based on shared inputs and undesirable outputs. Thirdly, to effectively obtain the unique optimal efficiency of each stage, an efficiency decomposition approach is proposed. Finally, an empirical example is conducted to evaluate the overall efficiency and the individual efficiency of R&D green innovation. Sensitivity analysis is conducted to analyze the reasonable allocation information of initial inputs. Furthermore, the Tobit model is adopted to analyze the main influencing factors of R&D green innovation. The empirical results show that: (1) Overall efficiency of the R&D green innovation is low and there exists much space for improvement. (2) Provincial development is uneven, and there are obvious differences in efficiency among the three stages within each province. (3) Technology market development, the degree of dependence on foreign trade, the degree of industrial structure, foreign direct investments have significant effects on the R&D green innovation; while government funding and R&D investment intensity have not produced obvious effects on the R&D green innovation.