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| Research on Regional Green Innovation Efficiency Evaluation and Intelligent Diagnosis based on Three-stage Malmquist-PNN |
| Xu Xueguo,Zhou Yanfei |
| (School of Management, Shanghai University, Shanghai 200444，China) |
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Abstract This paper applies three-stage Malmquist index to measure the green innovation efficiency of eight comprehensive economic zones excluding external environment and random interference factors. The probability neural network (PNN) is used to conduct intelligent diagnosis of green innovation efficiency. The results show that: ①The green innovation efficiency of the eight comprehensive economic zones shows the fluctuation trend of "decline-rise-decline-rise". It is mainly determined by technological progress, while the low technology efficiency is caused by the decline of scale efficiency. ②After eliminating the interference of external environment and random factors, Malmquist index of each region decreases. The green innovation efficiency in the first stage is overestimated, which is due to the overestimation of technical efficiency. Among them, the rankings of northwest and middle reaches of the Yellow River are quite different from that of the first stage, while the rankings of other regions remain unchanged. ③Accelerating the development of technology market and optimizing industrial structure contribute to the growth of green innovation efficiency, while the level of economic development, economic openness and environmental regulation have no significant impact on green innovation efficiency. ④According to the results of intelligent diagnosis, the eight comprehensive economic zones are divided into three categories: the areas of total efficiency, the areas of pure technology inefficiency and the areas of scale inefficiency.
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Received: 15 October 2020
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