scholarly journals Research on Industry Difference and Convergence of Green Innovation Efficiency of Manufacturing Industry in China Based on Super-SBM and Convergence Models

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yongcan Yan ◽  
Jian Li ◽  
Yi Xu
Keyword(s):  
Manufacturing Industry ◽  
Variable Density ◽  
Manufacturing Industries ◽  
Policy Implications ◽  
Green Innovation ◽  
Time Dimension ◽  
Technology Industry ◽  
Evolution Characteristics ◽  
Chinese Manufacturing Industry ◽  
Convergence Trend

To accurately grasp the current situation of green innovation efficiency in the manufacturing industry in China, this paper analyzes the differences and convergence characteristics of green innovation efficiency in various industries. Based on the panel data of 29 manufacturing industries in China from 2010 to 2019, the super-slack-based measure (Super-SBM) model measures the green innovation efficiency of manufacturing industries whose evolution characteristics are classified and analyzed from the perspective of technical demand. The Dagum Gini coefficient decomposition method indicates the source of industry differences in green innovation efficiency of the manufacturing industry in China with its convergence characteristics analyzed from the time dimension by constructing σ and β convergence models. The results reveal the improvement of green innovation efficiency of the Chinese manufacturing industry with obvious distinctions among different sectors and the industries with high green innovation efficiency, mostly high-end technology ones. The narrowing overall difference of green innovation efficiency in the manufacturing industry is accompanied by the lowest contribution rate of super-variable density, with the disparities between groups being the main source. It also shows the fluctuation of the intermittent σ convergence characteristics of the national manufacturing industry as a whole and low-end and high-end technology industry groups. However, the entire manufacturing industry and the three groups witness the absolute β convergence trend, with an ununiform convergence rate. The research will provide a reference for further upgrading the efficiency of green innovation in the industry and help to achieve the goals of carbon emission reduction and neutrality with the policy implications for promoting high-quality development of the manufacturing industry.

scholarly journals Impact of Global Value Chains on Export Technology Content of China’s Manufacturing Industry

2020 ◽  
Vol 12 (1) ◽  
pp. 432 ◽  
Author(s):  
Jing Peng ◽  
Yabin Zhang
Keyword(s):  
Production Process ◽  
Manufacturing Industry ◽  
Home Country ◽  
Developed Countries ◽  
Global Value Chains ◽  
Manufacturing Industries ◽  
Value Chains ◽  
Intermediate Inputs ◽  
Domestic Technology ◽  
Chinese Manufacturing Industry

With the deepening development of global value chains (GVC), a large number of foreign intermediate inputs have been integrated in the products production process of one country, thus the technology content of export products may not completely come from the home country. According to the new measurement based on production process, this paper calculates the domestic technology content of China’s manufacturing industry from 2000 to 2014 by using the data of World Input–Output Database (WIOD). Furthermore, it has an empirical analysis of the effect of GVC position on domestic technology content using the panel data of China’s 18 manufacturing industries. The results showed that: the technology content of the China’s manufacturing exports are increasing, and the domestic technology content grows faster than overall technology content, which indicats that China’s manufacturing industry has been upgraded and optimized in a certain way; However, there is still a certain gap between China’s manufacturing technology content and the corresponding indicators of major developed countries; And the upgrading of GVC position of Chinese manufacturing industry can significantly improve the domestic technology content of manufacturing exports.

scholarly journals Analysis of the agglomeration of Chinese manufacturing industries and its effect on economic growth in different regions after entering the new normal

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Fangxu Ren
Keyword(s):  
Economic Growth ◽  
Manufacturing Industry ◽  
Manufacturing Industries ◽  
Regional Economic Growth ◽  
Industrial Agglomeration ◽  
Regional Economic ◽  
New Normal ◽  
Financial Expenditure ◽  
Stage System ◽  
Chinese Manufacturing Industry

Abstract Entering the new normal of economy symbolises the innovation of growth mode and continuous optimisation and upgradation of economic structure. Using EG index, this paper measures the agglomeration degree of 31 provinces and cities and 31 manufacturing industries in China from 2012 to 2016; the results show that under the new normal, the degree of industrial agglomeration in China's manufacturing industry remains basically stable, but the overall situation is still in a state of moderate agglomeration, the regions with higher degree of concentration continue to present the pattern of ‘one pole, two domains’. To further reveal the relationship between the concentration of Chinese manufacturing industry and regional economic growth, the GMM method of dynamic panel two-stage system was used, and the results showed that industrial agglomeration and economic growth do not have simple linear relationship, but inverted U-type relationship. There was a dynamic continuation effect of regional economic growth, and external factors such as fixed asset investment and government financial expenditure can promote regional industrial economic growth. Finally, the enlightenment of the complete article is given.

scholarly journals Mechanisms of Environmental Regulation’s Impact on Green Technological Progress—Evidence from China’s Manufacturing Sector

2021 ◽  
Vol 13 (4) ◽  
pp. 1600
Author(s):  
Weijiang Liu ◽  
Mingze Du ◽  
Yuxin Bai
Keyword(s):  
Sustainable Development ◽  
Energy Consumption ◽  
Technological Change ◽  
Environmental Protection ◽  
Technological Progress ◽  
Manufacturing Industry ◽  
Manufacturing Sector ◽  
The Sustainable Development ◽  
Biased Technological Change ◽  
Chinese Manufacturing Industry

As the world’s largest developing country, and as the home to many of the world’s factories, China plays a crucial role in the sustainable development of the world economy regarding environmental protection, energy conservation, and emission reduction issues. Based on the data from 2003–2015, this paper examined the green total factor productivity and the technological progress in the Chinese manufacturing industry. A slack-based measure (SBM) Malmquist productivity index was used to measure the bias of technological change (BTC), input-biased technological change (IBTC), and output-biased technological change (OBTC) by decomposing the technological progress. It also investigated the mechanism of environmental regulation, property right structure, enterprise-scale, energy consumption structure, and other factors on China’s technological progress bias. The empirical results showed the following: (1) there was a bias of technological progress in the Chinese manufacturing industry during the research period; (2) although China’s manufacturing industry’s output tended to become greener, it was still characterized by a preference for overall CO2 output; and (3) the impact of environmental regulations on the Chinese manufacturing industry’s technological progress had a significant threshold effect. The flexible control of environmental regulatory strength will benefit the Chinese manufacturing industry’s technological development. (4) R&D investment, export delivery value, and structure of energy consumption significantly contributed to promoting technological progress. This study provides further insight into the sustainable development of China’s manufacturing sector to promote green-biased technological progress and to achieve the dual goal of environmental protection and healthy economic growth.

scholarly journals Effects of Institutions on Spatial Patterns of Manufacturing Industries and Policy Implications in Metropolitan Areas: A Case Study of Wuhan, China

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 710
Author(s):  
Min Zhou ◽  
Man Yuan ◽  
Yaping Huang ◽  
Kaixuan Lin
Keyword(s):  
Spatial Patterns ◽  
Policy Development ◽  
Manufacturing Industries ◽  
Policy Implications ◽  
Land Policy ◽  
Spatial Transformation ◽  
Development Zone ◽  
Analysis Technique ◽  
Spatial System ◽  
Big Cities

Manufacturing space is a spatial system that combines the interaction between capital and institutions at the enterprise, industry, and spatial levels. It is also an important functional type that promotes the spatial evolution of big cities. Most studies focus on the effects of a single institutional type on the manufacturing space of big cities and lack systematic and complete exploration of the institutional mechanism. Current empirical research on typical industrial cities in China is insufficient. This study uses a GIS spatial analysis technique and a Poisson regression model to analyze the mechanism by which institutions have influenced the spatial patterns of manufacturing industries in the Wuhan metropolitan area since the 1990s. The results show that land policy, development zone policy, urban planning, transportation strategy, and eco-environmental policy all have a significant impact on the restructuring process and distribution pattern of the manufacturing industries through incentives and constraints. This study expands our understanding of the influence mechanism of manufacturing spatial patterns and proposes spatial guiding strategies and policy implications for the spatial transformation of urban manufacturing.

scholarly journals Using a Novel Grey DANP Model to Identify Interactions between Manufacturing and Logistics Industries in China

2018 ◽  
Vol 10 (10) ◽  
pp. 3456 ◽  
Author(s):  
Peng Jiang ◽  
Yi-Chung Hu ◽  
Ghi-Feng Yen ◽  
Hang Jiang ◽  
Yu-Jing Chiu
Keyword(s):  
Manufacturing Industry ◽  
Multiple Criteria Decision Making ◽  
Value Added ◽  
Manufacturing Industries ◽  
Direct Influence ◽  
Key Factors ◽  
Logistics Industry ◽  
Influence Matrix ◽  
Factors Affecting ◽  
Two Factors

As a crucial part of producer services, the logistics industry is highly dependent on the manufacturing industry. In general, the interactive development of the logistics and manufacturing industries is essential. Due to the existence of a certain degree of interdependence between any two factors, interaction between the two industries has produced a basis for measurement; identifying the key factors affecting the interaction between the manufacturing and logistics industries is a kind of decision problem in the field of multiple criteria decision making (MCDM). A hybrid MCDM method, DEMATEL-based ANP (DANP) is appropriate to solve this problem. However, DANP uses a direct influence matrix, which involves pairwise comparisons that may be more or less influenced by the respondents. Therefore, we propose a decision model, Grey DANP, which can automatically generate the direct influence matrix. Statistical data for the logistics and manufacturing industries in the China Statistical Yearbook (2006–2015) were used to identify the key factors for interaction between these two industries. The results showed that the key logistics criteria for interaction development are the total number of employees in the transport business, the volume of goods, and the total length of routes. The key manufacturing criteria for interaction development are the gross domestic product and the value added. Therefore, stakeholders should increase the number of employees in the transport industry and freight volumes. Also, the investment in infrastructure should be increased.

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