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

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.

How Does the Digital Economy Affect the Domestic Value-Added Rate of Chinese Exports?

The digital economy continuously injects new momentum into the traditional economy and has become an important driving force for national economic development. Against this backdrop and using input-output data from the WIOD from 2002 to 2014, this paper empirically analyzes the impact of the development of the digital economy on the domestic value-added rate of Chinese manufacturing industry exports and the mechanism underlying this relationship. The results show that (1) digital economic input significantly promotes growth in the domestic value-added rate of manufacturing industry exports, (2) digital economic input mainly increases the domestic value-added rate of intermediate-product exports, (3) digital input has a significant positive impact on the capital-intensive and knowledge-intensive manufacturing industries, and (4) technological progress and cost reduction are important mechanisms through which the digital economy promotes the domestic value-added rate of exports.

The Role of Value Appropriation Capability of Chinese Multinationals in Operating Cross-Border Business Models

In an ever increasingly competitive and unstable global market, multinational corporations (MNCs) are greatly pressurised to use inherent capacities and develop effective cross-border business models (CBMs) that can transform value into the desired outcome. Amid high uncertainties, MNCs are required to develop some critical capabilities to operate CBMs to the best of their ability. More specifically, it is vital for MNCs to have a unique capability that enables them to more effectively synergise with these commonly recognised capabilities (e.g., technological innovation capabilities (TIC) and marketing capability (MC) alongside the global value chain (GVC)) to sustain balance among and gain profits with stakeholders. From the literature review, we first identified value appropriation capability (VAC) as one of the most important capabilities and thereby developed three hypotheses. Based on the hypotheses, we investigated how VAC efficiently moderates MNCs’ capabilities to appositely operate CBMs. Then, empirical panel data between 2011 and 2019 in the Chinese manufacturing industry were used to examine the hypotheses. The results reveal that VAC, TIC and MC positively impact MNC performance. Moreover, VAC–TIC interaction significantly improves MNC performance, and VAC–MC interaction positively improves MNC performance. Our findings provide novel insights into the CBM literature by examining the importance of VAC for operating CBMs alongside its multifaceted effects on MNC performance, especially in times of uncertainty.

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

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.

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

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.

Value Investing: Evidence from Listed Companies in Chinese Manufacturing Industry

Value investing methods have been broadly researched and applied to various atmosphere of security analysis. It mainly deals with the identification of value securities for possible buy and hold or resale. For further analysis, statistical technique is utilized to inspect the extent and characters of value investing theory in Chinese manufacturing industry. This paper intends to reveal the interactions among returns on investment (ROI) as well as other accounting information filed within financial reports, and also testing the degree of the interaction on returns on investment in China’s manufacturing industry.