scholarly journals Research on Regional Differences and Influencing Factors of Chinese Industrial Green Technology Innovation Efficiency Based on Dagum Gini Coefficient Decomposition

Land ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 122
Author(s):  
Liyuan Zhang ◽  
Xiang Ma ◽  
Young-Seok Ock ◽  
Lingli Qing
Keyword(s):  
Gini Coefficient ◽  
Regional Differences ◽  
Technology Innovation ◽  
Influencing Factor ◽  
Growth Period ◽  
Spillover Effects ◽  
Development Trend ◽  
Green Technology ◽  
Government Support ◽  
Eastern Region

Industrial green technology innovation has become an important content in achieving high-quality economic growth and comprehensively practicing the new development concept in the new era. This paper measures the efficiency of industrial green technology innovation and regional differences based on Chinese provincial panel data from 2005 to 2018, using a combination of the super efficiency slacks-based measure (SBM) model for considering undesirable outputs and the Dagum Gini coefficient method, and discusses and analyses the factors influencing industrial green technology innovation efficiency by constructing a spatial econometric model. The results show that: firstly, industrial green technology innovation efficiency in China shows a relatively stable development trend, going through three stages: “stationary period”, “recession period” and “growth period”. However, the efficiency gap between different regions is obvious, specifically in the eastern > central > western regions of China, and the industrial green technology efficiency innovation in the central and western regions is lower than the national average. Secondly, regional differences in the efficiency of industrial green technology innovation in China are evident but tend to narrow overall, with the main reason for the overall difference being regional differences. In terms of intra-regional variation, variation within the eastern region is relatively stable, variation within the central region is relatively low and shows an inverted ‘U’ shaped trend, and variation within the western region is high and shows a fluctuating downward trend. Thirdly, the firm size, government support, openness to the outside world, environmental regulations and education levels contribute to the efficiency of industrial green technology innovation. In addition, the industrial structure hinders the efficiency of industrial green technology innovation, and each influencing factor has different degrees of spatial spillover effects.

scholarly journals Research on Regional Differences and Influencing Factors of Chinese Industrial Green Technology Innovation Efficiency Based on Dagum Gini Coefficient Decomposition

2021 ◽  
Author(s):  
Liyuan Zhang ◽  
Pengzhen Liu ◽  
Heather Tarbert ◽  
Qingyu Bu
Keyword(s):  
Gini Coefficient ◽  
Regional Differences ◽  
Technology Innovation ◽  
Influencing Factor ◽  
Growth Period ◽  
Spillover Effects ◽  
Development Trend ◽  
Green Technology ◽  
Government Support ◽  
Eastern Region

Industrial green technology innovation has become an important content in achieving high-quality economic growth and comprehensively practicing the new development concept in the new era. This paper measures the efficiency of industrial green technology innovation and regional differences based on Chinese provincial panel data from 2005 to 2018, using a combination of the super-efficient SBM model for considering undesirable outputs and the Dagum Gini coefficient method, and discusses and analyses the factors influencing of the industrial green technology innovation efficiency by constructing a spatial econometric model. The results show that: firstly, the industrial green technology innovation efficiency in China shows a relatively stable development trend, going through three stages: " stationary period", " recession period " and "growth period ". However, the efficiency gap between different regions is obvious, specifically in the eastern > central > western regions of China, and the industrial green technology efficiency innovation in the central and western regions is lower than the national average. Secondly, regional differences in the efficiency of industrial green technology innovation in China are evident but tend to narrow overall, with the main reason for the overall difference being regional differences. In terms of intra-regional variation, variation within the eastern region is relatively stable, variation within the central region is relatively low and shows an inverted 'U' shaped trend, and variation within the western region is high and shows a fluctuating downward trend. Thirdly, the firm size, government support, openness to the outside world, environmental regulations and education levels contribute to the efficiency of industrial green technology innovation. In addition, the industrial structure hinders the efficiency of industrial green technology innovation, and each influencing factor has different degrees of spatial spillover effects.

scholarly journals Factors affecting enterprise level green innovation efficiency in the digital economy era – Evidence from listed paper enterprises in China

BioResources ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. 7648-7670
Author(s):  
Zhengxia He ◽  
Wenqi Lu ◽  
Guihong Hua ◽  
Jianming Wang
Keyword(s):  
Technology Innovation ◽  
Positive Impact ◽  
Innovation System ◽  
Inhibitory Effect ◽  
Digital Economy ◽  
Green Technology ◽  
Government Support ◽  
Media Report ◽  
Factors Affecting ◽  
Public Media

The Guidelines on Building a Market-Oriented Green Technology Innovation System, which was released by China in 2019, has become a powerful signal to guide the development of green technology innovation (GTI). In the current digital strategy of China, the public media has become a key factor for promoting the transparency of enterprise environmental information. This paper measures the GTI efficiency of the listed paper enterprises in China as well as incorporating media attention into the research framework to explore the influencing factors of GTI of the listed paper enterprises in China during the digital economy era. The results showed that a positive media report had a positive impact on GTI and has become a new driving factor in promoting sustainable production in the digital era. Government support and openness also have a positive impact on GTI. However, negative media reports, environmental regulations, and technological innovation abilities have an inhibitory effect on the GTI efficiency of paper making enterprises.

scholarly journals Assessing Regional Differences in Green Innovation Efficiency of Industrial Enterprises in China

2019 ◽  
Vol 16 (6) ◽  
pp. 940 ◽  
Author(s):  
Jun-liang Du ◽  
Yong Liu ◽  
Wei-xue Diao
Keyword(s):  
Economic Growth ◽  
Value Chain ◽  
Regional Differences ◽  
Technology Innovation ◽  
Indicator System ◽  
Green Technology ◽  
Green Innovation ◽  
High Quality ◽  
Two Stage ◽  
Industrial Enterprises

Green technology innovation is an important means to break out of the constraints of resources and the environment, enhance the competitiveness of enterprises, and achieve the upgrading of industrial structures, and promote high-quality economic growth. In order to realize the overall improvement of the green technology innovation capability of Chinese enterprises, it is necessary to measure the efficiency of industrial enterprises’ green technology innovation and explore their regional differences. In this paper, from the perspective of a two-stage innovation value chain, by introducing the industrial carbon emissions per unit of Gross Domestic Product (GDP) and the “three wastes” pollutants into the research framework of green technology innovation efficiency, we established a novel green innovation efficiency evaluation indicator system for industrial enterprises. Furthermore, we used a two-stage network DEA with shared input to measure the efficiency of regional enterprises’ green technology innovation and explored the regional differences in industrial enterprises’ green technology R&D and the efficiency of green technology achievement transformation. Finally, we provide some suggestions for improving China’s industrial enterprises’ green innovation efficiency, so that they can ameliorate the significant regional imbalances and differences and realize high-quality economic growth.

Whether green technology innovation is conducive to haze emission reduction: Empirical evidence from China

2021 ◽  
Author(s):  
Ming Yi ◽  
Ying Lu ◽  
Le Wen ◽  
Ying Luo ◽  
Shujing Xu ◽  
...  
Keyword(s):  
Spatial Correlation ◽  
Foreign Investment ◽  
Industrial Structure ◽  
Technology Innovation ◽  
Collaborative Governance ◽  
Spillover Effects ◽  
Green Technology ◽  
Haze Pollution ◽  
The Impact ◽  
Negative Spillover

Abstract With the acceleration of industrialization, haze pollution has become a severe environmental pollution problem, and green technology innovation is one feasible way to alleviate it. Based on the PM2.5 concentration data of 30 provinces in mainland China from 2011 to 2017, we use a spatial panel model to investigate the spatial characteristics of haze pollution and examine the impact of green technology innovation on it. Results show that haze pollution has spatial correlation and a time lag. Its spatial correlation is associated with geographical distance as well as the compound influence of distance and economic development. Green technology innovation and foreign investment have inhibitory and negative spillover effects on haze pollution. Industrial structure and energy consumption structure play a partial intermediary role between green technology innovation and haze pollution, and the former has a significant negative spillover, while the latter has a positive effect. To reduce haze pollution, China should improve the level of green technology innovation, use foreign investment wisely, and enhance policy support and guidance. It should also promote the rationalization of industrial structure, optimize energy structure and implement energy substitution. Finally, it is crucial that it should strengthen regional collaborative governance and build a multi-agent governance system.

scholarly journals Efficiency Evaluation of Green Technology Innovation of China’s Industrial Enterprises Based on SBM Model and EBM Model

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Wei Chen ◽  
Liying Pan ◽  
Chaoran Lin ◽  
Mengqi Zhao ◽  
Tan Li ◽  
...  
Keyword(s):  
Coming Out ◽  
Value Chain ◽  
Technology Innovation ◽  
Proper Time ◽  
Green Technology ◽  
Ecological Environment ◽  
Eastern Region ◽  
Network Dea ◽  
Industrial Enterprises ◽  
Sbm Model

The industrial revolution has brought a leap in productivity; however, some severe ecological environment and resource problems are coming out with the development of industrialization. To achieve sustainable development of social economy, green technology innovation emerges in response to the proper time and conditions. In this context, the correct approach to measure the efficiency of green technology innovation in China’s industrial enterprises is an important research topic. Based on existing studies, this paper divides innovation activities into two stages based on the innovation value chain and constructs a two-stage evaluation index system including all kinds of undesirable outputs transferred from negative externalities of the ecological environment. To evaluate green technology innovation efficiency, SBM and EBM network DEA models are applied to conduct empirical analysis from the perspective of time and space. This paper also calculates the efficiency values based on the SBM model and the EBM model, respectively, and compares the differences between them. The results show that the efficiency value of the achievement transformation stage is significantly higher than that of technology development stage; there are noticeable gaps in the efficiency of green technology innovation between different regions of China. Besides, the eastern region has a better performance in green technology innovation than the western region and Qinghai has the best green technology innovation performance. Combining the empirical results, the corresponding policy recommendations are put forward.

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