Study on the impact of industrial green development and technological innovation on employment structure DOI Creative Commons
Yue Li, Mingzhao Hu,

Lingdi Zhao

et al.

Frontiers in Earth Science, Journal Year: 2023, Volume and Issue: 11

Published: Feb. 2, 2023

Exploring the relationship between industrial green development, technological innovation, and employment structure, especially impact development innovation on is of enormous theoretical practical importance to achieve high-quality as well optimize structure China. Thirty Chinese provinces’ data from 2009 2019 adopted assess levels. Considering above, this research innovatively integrates into an analytical framework, empirically investigates effects two factors their interaction by adopting a two-way fixed model. The specific conclusions are presented follows. Firstly, China’s levels exhibit fluctuating rising time-series evolutionary feature have regional differences. Secondly, conducive optimizing structure. Thirdly, eastern northeastern areas’ optimization boosted development. However, corresponding regression coefficients in western central areas not significant. northeastern, eastern, encourages improvement. Instead, hampered region. An evolution positively affects relevant structures four regions. Specific results necessary significance realistic reference price for whether interplay affect

Language: Английский

AI capability and green innovation impact on sustainable performance: Moderating role of big data and knowledge management DOI
Hussam Al Halbusi, Khalid Ibrahim Al‐Sulaiti, Ali Abdallah Alalwan

et al.

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 210, P. 123897 - 123897

Published: Nov. 23, 2024

Language: Английский

Citations

8

Practice With Less AI Makes Perfect: Partially Automated AI During Training Leads to Better Worker Motivation, Engagement, and Skill Acquisition DOI Creative Commons
Mario Passalacqua, Robert Pellerin, Esma Yahia

et al.

International Journal of Human-Computer Interaction, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 21

Published: March 3, 2024

The increased prevalence of human-AI collaboration is reshaping the manufacturing sector, fundamentally changing nature human work and training needs. While high automation improves performance when functioning correctly, it can lead to problematic (e.g., defect detection accuracy, response time) operators are required intervene assume manual control decision-making responsibilities. As AI capability reaches higher levels human–AI becomes ubiquitous, addressing these issues crucial. Proper worker training, focusing on skill-based, cognitive, affective outcomes, nurturing motivation engagement, be a mitigation strategy. However, most research in has prioritized effectiveness technology for rather than how design influences key success longevity. current study explored workers using an system affected their motivation, skill acquisition. Specifically, we manipulated level decision selection used 102 participants quality task. Findings indicated that fully automated negatively impacted perceived autonomy, self-determined behavioral task acquisition during training. Conversely, partially AI-enhanced enabling better adapt failure by developing necessary skills. results suggest involving as aid selector, yields more positive outcomes. This approach ensures aspect not overlooked, maintaining balance between technological advancement development, engagement. These findings applied enhance real-world practices designing programs develop operators' technical, methodological, personal skills, though companies may face challenges allocating substantial resources redevelopment continuously adapting keep pace with evolving technology.

Language: Английский

Citations

7

Strategic Load Management: Enhancing Eco-Efficiency in Mining Operations Through Automated Technologies DOI Creative Commons
Ali Akbar Firoozi,

Magdeline Tshambane,

Ali Asghar Firoozi

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 102890 - 102890

Published: Sept. 1, 2024

Language: Английский

Citations

7

Are our values becoming more fit for artificial intelligence society? A longitudinal study of occupational values and occupational susceptibility to technological substitution DOI Creative Commons
Johnny Långstedt, Jonas Spohr, Magnus Hellström

et al.

Technology in Society, Journal Year: 2023, Volume and Issue: 72, P. 102205 - 102205

Published: Jan. 27, 2023

Advanced technologies are changing our working life in unpredictable ways. Consequently, a fear of technologically induced mass unemployment has re-emerged. The increased precarity associated with the technological substitution work could lead to regression towards materialist values that more accepting authoritarianism and xenophobia. Crucially, these less skills demanded future work, which tends be depicted as demanding higher levels innovation, creative social post-materialist values. Current research thus far overlooked cultural aspects large-scale this study illuminates. We investigate how relationship between occupational automatability developed 2002 2018 Europe. results demonstrate have been rather stable throughout period. Occupational not becoming or fit for artificial intelligence society would expected if context becomes increasingly precarious innovation-driven. paper demonstrates adaptation type yet occurred.

Language: Английский

Citations

13

Study on the impact of industrial green development and technological innovation on employment structure DOI Creative Commons
Yue Li, Mingzhao Hu,

Lingdi Zhao

et al.

Frontiers in Earth Science, Journal Year: 2023, Volume and Issue: 11

Published: Feb. 2, 2023

Exploring the relationship between industrial green development, technological innovation, and employment structure, especially impact development innovation on is of enormous theoretical practical importance to achieve high-quality as well optimize structure China. Thirty Chinese provinces’ data from 2009 2019 adopted assess levels. Considering above, this research innovatively integrates into an analytical framework, empirically investigates effects two factors their interaction by adopting a two-way fixed model. The specific conclusions are presented follows. Firstly, China’s levels exhibit fluctuating rising time-series evolutionary feature have regional differences. Secondly, conducive optimizing structure. Thirdly, eastern northeastern areas’ optimization boosted development. However, corresponding regression coefficients in western central areas not significant. northeastern, eastern, encourages improvement. Instead, hampered region. An evolution positively affects relevant structures four regions. Specific results necessary significance realistic reference price for whether interplay affect

Language: Английский

Citations

13