scholarly journals Analysis on the Upgrading and Development of Chinese Manufacturing Industry Based on Green Technology Innovation

Author(s):  
Liang Shen ◽  
Runjie Fan ◽  
Yuyan Wang ◽  
Zhaoqing Yu ◽  
Rongyun Tang

Since environmental problems are becoming increasingly prominent, macro policies and social development have placed higher requirements on manufacturing enterprises to promote green transformation and upgrading (GTU) in China. Considering that different manufacturing enterprises choose different green technology innovation levels for GTU under environmental regulation, a game model between manufacturing enterprises and the government is constructed. The relationship between the green technology innovation level (GTIL) and the environmental regulation intensity is analyzed. Through numerical examples, the influences of environmental regulation and consumer preference on system decisions are further examined. Moreover, an econometric model is constructed to explore the influence that the environmental regulation exerts on the GTIL using panel data from the Chinese manufacturing industry. Our results show that the increase in environmental regulation intensity contributes to improving GTIL and promoting the GTU of manufacturing enterprises. Furthermore, as the environmental regulation is enhanced, the sales price decreases, benefiting consumers. Consumers’ preference for high-GTIL products is conducive to GTU under environmental regulation. Empirical analysis shows that there is a U-shaped relationship between environmental regulation and the GTIL. Only when the intensity reaches a threshold can the environmental regulation be beneficial to improve the GTIL and promote the GTU of Chinese manufacturing enterprises.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xiangyu Jiang ◽  
Gu-Hong Lin ◽  
Jui-Chan Huang ◽  
I-Hsiang Hu ◽  
Yen-Chun Chiu

The powerful advanced manufacturing industry is the most powerful driving force for economic development and growth, and it is also the main source of environmental pollution. Artificial intelligence and blockchain technology are recognized as a breakthrough technology that can be widely used, changing the way the entire society and economy operate. The main constraints affecting the sustainable development of the manufacturing industry are ecological deterioration and resource shortage, but the development of artificial intelligence and blockchain technology provides new ideas for solving manufacturing problems. Based on this, this paper proposes a research on the sustainable development performance of green manufacturing technology innovation based on artificial intelligence and blockchain technology. This paper deeply grasps the essence and connotation of artificial intelligence and blockchain technology, analyzes its specific application form and research background, searches for the effective effect of manufacturing technology innovation and green manufacturing performance path, and clarifies the mechanism between the two. All measurement items in the questionnaire used in this article use Likert5 scale and use 1–5 options to indicate the degree of conformity with the actual situation of the enterprise. The results show that the average green manufacturing capacity of each measurement item is between 3.18∼3.97, indicating that the company's green manufacturing capacity is relatively high. Among them, the ability of green technology innovation is relatively high, indicating that most companies have noticed that the improvement of the ability of green technology innovation plays a vital role in the future sustainable development of enterprises. Moreover, more and more companies are paying attention to the latest applications of blockchain technology, which can effectively promote the development of enterprises.


2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Tuochen Li ◽  
Lei Liang ◽  
Dongri Han

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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