How does industrial intelligence affect capacity utilization?—Analysis based on green development perspective

Yang, Yuan; Yu, Liuming; Kumar, Sanjay; Zhang, Yi

doi:10.3389/fenvs.2022.1006630

Cited by 7 publications

(3 citation statements)

References 44 publications

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“…Therefore, the application of industrial robots can alter the structural elements of an industry and affect the technological complexity of enterprises. This paper defines the factor structure (Element) as the ratio of fixed assets to the number of employees employed, drawing from Yuan et al (2022) [41].…”

Section: Element Structurementioning

confidence: 99%

Disruptive Displacement: The Impacts of Industrial Robots on the Energy Industry’s International Division of Labor from a Technological Complexity View

Zhang

Peng

2023

Energies

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In light of the growing economic uncertainties worldwide, the use of industrial robots has emerged as a significant opportunity for improving the production efficiency and the international division of labor in China’s energy industry. This study employed a two-way fixed-effect model utilizing data from 31 Chinese provinces between 2011 and 2019 to investigate the impact of industrial robots on the energy industry’s participation in the international division of labor. The results of the study indicated that the widespread application of industrial robots can boost the international division of labor status of China’s energy sector. This conclusion remains robust even after addressing the potential endogeneity issues and conducting a range of sensitivity tests. Furthermore, our findings suggest that the regions that possess abundant energy resources or exhibit a lower carbon intensity are more likely to leverage the use of industrial robots to increase the technological sophistication and enhance their participation in the international division of labor. The application of industrial robots in the energy industry can enhance the international division of labor through two distinct channels: optimizing the factor structure and reducing the export costs. Our findings have important policy implications for ensuring energy security and improving the energy industry’s participation in the international division of labor.

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Section: Element Structurementioning

confidence: 99%

Disruptive Displacement: The Impacts of Industrial Robots on the Energy Industry’s International Division of Labor from a Technological Complexity View

Zhang

Peng

2023

Energies

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“…In addition, other influence paths have been mentioned in some literatures. For example, the application of artificial intelligence can also enable the upgrading of the manufacturing value chain by improving the total factor productivity of enterprises, reducing export costs and increasing the types of domestic intermediate goods [56,57] . In 2023, Lu Yue et al gave a more comprehensive answer through empirical research: artificial intelligence can not only promote the deepening of GVC network in various countries, but also extend the length of GVC, and promote countries to climb upstream of GVC [58] .…”

Section: Enabling Manufacturing To Upgrade the Global Value Chain Thr...mentioning

confidence: 99%

A review of research on global value chain upgrading of manufacturing enabled by digital economy

2023

FSST

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The digital economy based on a new generation of digital technology has become a new driving force for the transformation and upgrading of the manufacturing industry, but the existing research is relatively lagging behind and difficult to effectively guide China to get rid of the low-end lock in the manufacturing industry. This paper focuses on how the digital economy upgrades the global value chains of manufacturing industry at the enterprise and industrial levels, and reviews the upgrading of the value chain of manufacturing industry enabled by the digital economy from four aspects: digital infrastructure, digital technology, manufacturing digitization and digital service industry. It is found that there are many research perspectives, methods and fruitful results on this topic. However, it has not formed a systematic theoretical system. It is hoped that more studies in the future can focus on the measurement of digital economy and value chain upgrading, so as to have more accurate and unified indicators to measure the empowerment of digital economy to manufacturing value chains, and include more new categories in digital economy into the analytical framework.

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“…Wu et al [3]constructed an industrial intelligence system from three aspects to explore the relationship between industrial intelligence and energy intensity in China from 2006 to 2018. Yuan et al [4] used a fixed effects model and data from the International Federation of Robotics (IFR) and Chinese A-share listed companies from 2011 to 2019 to empirically analyze the impact of industrial intelligence on enterprise capacity utilization. Wang et al [5] used the super efficiency SBM model of unexpected output to measure the efficiency of high-quality industrial development in China, analyzed the spatiotemporal evolution and heterogeneity of industrial high-quality development efficiency, and constructed a panel multiple regression model to analyze the driving effect of its influencing factors on the high-quality industrial development in China.…”

Section: Introductionmentioning

confidence: 99%

Research on Inclusive Green Growth Based on SD-based Industrial Intelligence

2023

IJBMET

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Since the reform and opening up, along with the policy dividend, China's economy has developed rapidly. However, in recent years, with the change of international environment and the adjustment of domestic economic structure, economic development has entered a stage of low-speed growth, mainly manifested in the decline of population, the decline of marginal return on capital and the severe situation of energy and environment, the pressure of energy conservation and emission reduction has been increasing, and the urban-rural income gap has aroused social concern. It shows that the factor-driven economic growth model can no longer meet the requirements of high-quality economic development, and the inclusive green growth model that takes into account green, inclusive and growth provides an opportunity to solve these problems. In this paper, the causal loop diagram and system dynamics flow diagram of dynamic evolution are constructed, and the system dynamics method is used to sort out the dynamic complexity of inclusive green growth and the multi-order nonlinear multi-factor system, and the systematic dynamic model is simulated by different scenario schemes.

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How does industrial intelligence affect capacity utilization?—Analysis based on green development perspective

Cited by 7 publications

References 44 publications

Disruptive Displacement: The Impacts of Industrial Robots on the Energy Industry’s International Division of Labor from a Technological Complexity View

Disruptive Displacement: The Impacts of Industrial Robots on the Energy Industry’s International Division of Labor from a Technological Complexity View

A review of research on global value chain upgrading of manufacturing enabled by digital economy

Research on Inclusive Green Growth Based on SD-based Industrial Intelligence

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