Earlier studies on the innovation process in the high-tech manufacturing industry failed to take environmental pollution into account, making it difficult to estimate green innovation efficiency in the industry. From a perspective of innovation value chain, this paper decomposes green innovation process in the high-tech manufacturing industry into two stages: R&D stage and achievement transformation stage; a network DEA approach considering undesirable outputs is utilized to estimate the green innovation efficiency in China’s high-tech manufacturing industry. Compared with the method of conventional innovation efficiency without considering environmental pollution, the estimation method for green innovation efficiency can not only avoid bias of estimation results of provinces producing low pollution emissions like Inner Mongolia and Hainan but also reflect the volatility in efficiency of the high-tech manufacturing industry before and after the implementation of the environmental law.

The sustainable development of China’s high-tech manufacturing (HTM) sector is restricted by dependence on technology introduction and foreign direct investment (FDI), low input-output efficiency, and environmental pollution. This study aimed to examine the roles of technology introduction and FDI in improving the technical efficiency of Chinese HTM from an environmental perspective. By integrating stochastic frontier analysis (SFA) and projection pursuit (PP) based on the real-coded accelerated genetic algorithm (RAGA), this study constructed a RAGA-PP-SFA model that considers undesirable outputs. This model includes various outputs, including environmental pollution, in the production function to improve estimation accuracy. Moreover, to verify the robustness of the estimation results, the results were provided when environmental pollutants were taken as input factors. The results showed that technology introduction could significantly promote HTM’s technical efficiency, while FDI had no significant positive effect. By comparing the estimated results with those that did not consider environmental pollution, this study not only reveals different roles of technology introduction and FDI in improving HTM’s technical efficiency but also confirms that ignoring environmental pollution will overestimate their roles (especially the role of FDI) in such improvement.

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Innovation inertia often blocks new innovation mode to form after enterprises' succeeding in innovation, which depress the ability enterprises' adapting to changes of market. In this article author analyzes the causes of formation of innovation inertia, and puts forward countermeasure restraining innovation inertia using systemic theories for reference, creating the simulating model by the methods of systems archetype and level variables and rate variables fundamental in-tree modeling of System Dynamics, which is used to test the effect of countermeasures for restraining the innovation inertia.