This study offers a RAGA-PP-SFA model to measure green technology’s innovation efficiency in the high-end manufacturing industry. The study’s aim is to solve the shortcomings of traditional SFA methods that are unable to improve multi-output efficiency. The RAGA-PP-SFA model presented here is based on the multi-emission and multi-output characteristics of high-end manufacturing innovation activities. Using panel data from 2010 to 2015 on China's high-end manufacturing industry and considering factors such as environmental regulation, government subsidy, and market maturity, this paper empirically examines and compares the efficiency of green technology innovation versus traditional technology innovation, as well as regional heterogeneity in China's high-end manufacturing industry. The study ultimately found a low level of green technology innovation efficiency in China’s high-end manufacturing industry. However, an overall rising trend shows that the green development of China's high-end manufacturing industry has achieved remarkable results. Green technology innovation efficiency in high-end manufacturing industries across various regions was generally lower than the efficiency of traditional technology innovation. Both types of efficiency showed a pattern of “high in the east and low in the middle and in the west”. High-high efficiency is primarily found in the east, whereas the west is characterized by low-low efficiency. There are significant differences between regions, pointing to an equal rate of development. Government subsidies and enterprise scale had a significant negative impact on green technology innovation efficiency in regional high-end manufacturing industries, while market maturity and industrial agglomeration had a significant positive impact. Based on the study’s findings, environmental regulation and openness to the outside world play insignificant roles in green technology innovation efficiency.

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Green total factor productivity is not merely an inevitable choice to continuously increase the quality of China's economy, but also a booming demand to promote global development. With the fast development of the new generation information technology represented by world comprehensive web technology, Internet growth may well play a more crucial role in enhancing green total factor productivity in China. Based on 2009-2017 China's inter-provincial panel data, this article uses the threshold regression model and fixed-effect model to empirically investigate the influence intensity and internal mechanism of green total factor productivity in areas affected by the Internet development. We ultimately come to the following conclusions. First, there is a digital divide between the regions of China. Second, many factors such as Internet development, human capital, urbanization, energy efficiency, and external dependence all exert a positive influence on China's green total factor productivity. At the same time, government intervention is not conducive to green total factor productivity. Third, the influence of Internet growth on China's green total factor productivity is non-linear, based on the significant double threshold effect of human capital. As the level of human capital continues to exceed the threshold value, the effect of Internet expansion on the green total factor productivity of China has undergone a structural change. The result has changed from a weak negative influence to a positive one, and the significance is increasing. To advance the smart, green, and coordinated development among regions, it is necessary to bring "Internet +" into full play in promoting China's green total factor productivity, strengthen the deep integration of Internet development and industrial development, and improve the level of clean production utilizing network information.

Climate change poses unprecedented challenges for humanity. Reducing carbon intensity is an inevitable choice for tackling climate change and promoting sustainable development. China has made some emission reduction commitments in the international community to promote the decoupling of China’s economic development from carbon emissions. The realization of the industrial structure from the “single-wheel drive” of the manufacturing to the “two-wheel drive” economic development model of the service industry and the manufacturing has become a key measure to achieve China’s economic intensive development. According to resource misallocation situation in different regions, this paper explored the impact of the collaborative agglomeration between producer services and manufacturing (hereinafter referred to as industrial co-agglomeration) on carbon intensity. The research results show that the carbon intensity is decreasing year by year, and the degree of intensification of China’s economic growth continues to increase. Moreover, the effect of industrial co-agglomeration to promote carbon emission reduction is significantly limited by the degree of misallocated resources, and there is a double threshold effect. Specifically, in areas where resource allocation is reasonable, industrial co-agglomeration can produce significant agglomeration effects and promote carbon intensity reduction. Once the degree of misallocated resources exceeds a threshold level, the agglomeration effect will turn into a crowding effect, resulting in an inability to reduce carbon intensity. We comprehensively analyzed the driving factors for reducing carbon intensity and proposed policy pathways for achieving China’s carbon intensity target.

Facing the pressures of international carbon emission reduction, the transformation into a low-carbon economy has become a common issue of all countries. The core of developing a low-carbon economy is to increase carbon productivity, which can be measured as the economic benefits of unit carbon emissions. Therefore, using province-level panel data in China from 2009 to 2017, we analyze the carbon productivity level of each region, and empirically investigate the threshold effect of clean energy development on carbon productivity under different technological innovation levels. The results show that the carbon productivity is rising, and China’s economic development pattern has been shifting towards low-carbon and sustainable development. Furthermore, the driving force of clean energy development on carbon productivity is not monotonously increasing (decreasing) but is a “double threshold effect” of technological innovation capability. Finally, based on the research conclusions and realistic requirements of China’s low-carbon economic transformation, this paper proposes improving carbon productivity from the aspects of innovation capability improvement and institutional guarantee.