Towards low-carbon development: The role of industrial robots in decarbonization in Chinese cities

Yu, Lingzheng; Wang, Yao; Wei, Xiahai; Zeng, Chenyu

doi:10.1016/j.jenvman.2023.117216

Cited by 48 publications

(15 citation statements)

References 42 publications

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“…with a higher level of industrial intelligence is also in line with China's development reality(Yu et al, 2023). The eastern region has more comparative advantages, like superior geographical location and economic foundation, which make the eastern region outperform other regions in terms of technological development, and so forth.…”

mentioning

confidence: 73%

“…Figure 5 illustrates that the industrial intelligence level of each region has improved from 2006 to 2019, generally, and regions with higher levels of industrial intelligence have lower CEI, especially in the eastern regions like Beijing, Guangdong, Jiangsu, and so forth. Meanwhile, the development of the eastern region and some central regions, such as Hunan and Hubei, with a higher level of industrial intelligence is also in line with China's development reality (Yu et al, 2023). The eastern region has more comparative advantages, like superior geographical location and economic foundation, which make the eastern region outperform other regions in terms of technological development, and so forth.…”

Section: Methodology and Datamentioning

confidence: 98%

“…Research on industrial intelligence is currently in the emerging development stage, and there is no unified measurement standard. The mainstream methods for measuring industrial intelligence include indicator system construction (Sun & Hou, 2019; Wang, Jiang, & Dong, 2022), the number of production robots (Liu et al, 2022), or per capita robot stock or per unit GDP robot installation (Li et al, 2022; Yu et al, 2023).…”

Section: Methodology and Datamentioning

confidence: 99%

“…Liu et al (2022) and Li et al (2022), based on data from Chinese cities and 35 countries, respectively, point out that robotic inputs can effectively reduce carbon emissions in production and that there is significant industrial heterogeneity. Yu et al (2023) further find that the role of industrial robots in urban decarbonization shows heterogeneous characteristics in terms of city scale, manufacturing development, and low‐carbon pilots and state that the use of robots reduces carbon emissions mainly via improving energy efficiency and green technology efficiency. In contrast, Luan et al (2022) state that industrial robots will stimulate energy consumption and then exacerbate air pollution, which presents a noticeable industrial heterogeneity despite the fact that robotic applications can enhance productivity and energy efficiency.…”

Section: Literature Review and Theoretical Analysismentioning

confidence: 99%

“…The significance of INT is unchanged in both estimation methods, which reconfirms the robustness of our findings.Then, we adopt two-stage least squares (2SLS) to estimate the original model by lagging independent variables one period as its instrumental variables (IV), and the results are shown in columns(3) and (4) of Table5. What's more, referring toAcemoglu and Restrepo (2020),Wang, Jiang, andYu et al (2023),…”

mentioning

confidence: 99%

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Towards low‐carbon sustainable development under Industry 4.0: The influence of industrial intelligence on China's carbon mitigation

Tian

Qin

Cheng

et al. 2023

Sustainable Development

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Global climate change is becoming an increasingly serious issue. China, the largest carbon emitter, has a long way towards its sustainable development goals (SDGs) and take on its carbon reduction responsibility, especially in the industrial sector. In this vein, industrial intelligence, a key driver in the “Industry 4.0 era”, offers an opportunity in this carbon reduction campaign. This paper seeks to examine the influences of industrial intelligence on carbon emissions, their heterogeneous characteristics and transmission mechanisms, and the moderating role of human capital. Therefore, we properly probed theoretical aspects, and then we used China's provincial data from 2006 to 2019 and a number of tests, namely the fixed effect model, the two‐stage test, and the moderating effect model, to test the relevant assumptions. We first unfolded that industrial intelligence can significantly mitigate carbon emissions. Specifically, the heterogeneous analysis found that carbon reduction efforts are more pronounced in China's central and western regions and resource‐based regions. We further highlight the mechanism identification, which reveals that industrial structure upgrading and technological innovation are the main channels for industrial intelligence to abate CO2 emissions. Importantly, we pinpoint the role of human capital, which positively moderates the relationship between industrial intelligence and carbon emissions and can well amplify the industrial structure effect of industrial intelligence. These results are conducive to accurately assessing the environmental benefits of industrial intelligence and providing policy enlightenment for China to alleviate carbon emissions, and they will also offer a reference for other developing countries to learn from.

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mentioning

confidence: 73%

Section: Methodology and Datamentioning

confidence: 98%

Section: Methodology and Datamentioning

confidence: 99%

Section: Literature Review and Theoretical Analysismentioning

confidence: 99%

mentioning

confidence: 99%

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Towards low‐carbon sustainable development under Industry 4.0: The influence of industrial intelligence on China's carbon mitigation

Tian

Qin

Cheng

et al. 2023

Sustainable Development

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show abstract

Skin‐Inspired Bimodal Receptors for Object Recognition and Temperature Sensing Simulation

Chen,

Liu,

Shi

et al. 2024

Adv Funct Materials

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Skin contacts with objects with different thermal conductivity and tactile perception will produce different temperature and tactile sensations. Here, an innovative creation is presented known as the BB‐Skin, a highly realistic bionic bimodal electronic skin, meticulously designed to mirror the thermal sensitivity and tactile perception found in human skin. This technology allows for precise object recognition and offers remote temperature sensing feedback. The BB‐Skin comprises temperature sensing, heating, and tribo‐electrode modules. Through the utilization of machine learning algorithms that measure the thermal conductivity and electronegativity of materials, a bimodal bionic robot object recognition system is developed, achieving an impressive accuracy rate exceeding 98.11%. The bimodal nature of the system, based on different types of electrical signals that operate independently, significantly enhances the reliability of the device. Moreover, harnessing the inherent capabilities of the BB‐Skin, a novel remote temperature sensing and feedback system is successfully implemented. This system adeptly replicates the temperature perception when remotely touching objects and provides users with feedback through gloves embedded with heating and cooling modules.

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Industrial clusters and carbon emission reduction: evidence from China

Liu,

Wu,

Zhu

2024

Ann Reg Sci

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Towards low-carbon development: The role of industrial robots in decarbonization in Chinese cities

Cited by 48 publications

References 42 publications

Towards low‐carbon sustainable development under Industry 4.0: The influence of industrial intelligence on China's carbon mitigation

Towards low‐carbon sustainable development under Industry 4.0: The influence of industrial intelligence on China's carbon mitigation

Skin‐Inspired Bimodal Receptors for Object Recognition and Temperature Sensing Simulation

Industrial clusters and carbon emission reduction: evidence from China

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