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Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors
Abstract
This paper analyzes the impact of artificial intelligence (AI) on technological innovation through logic reasoning and empirical modeling. Based on the industrial robot data provided by the International Federation of Robotics (IFR) and the panel data of China's 14 manufacturing sectors from 2008 to 2017, this paper empirically analyzes the impact of AI on technological innovation. Our analysis shows that the mechanism of how AI affects technological innovation is that the former promotes technological innovation through accelerating knowledge creation and technology spillover, improving learning and absorptive capacities, while increasing R&D and talent investment. Our empirical results indicate that under the condition of controlling intensity of R&D investment, FDI, ownership structure, technical imitation, AI significantly promotes technological innovation. And the impact of AI on technological innovation experiences sector heterogeneity: AI has more significant impact on the technological innovation of low-tech sectors. The higher the level of AI, the greater its impact on technological innovation. Based on our established conclusions, we provide corresponding suggestions and recommendations for managerial decision-making.
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“AI adoption requires the firm's ability to screen the regulatory environment to check whether the AI method applied complies with the latest government regulations.”
From Artificial intelligence in innovation management: A review of innovation capabilities and a taxonomy of AI applications (2025) · cites this paper as Liu et al. (2020)
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Explanation in artificial intelligence: Insights from the social sciences
Miller, T. (2019) · Artificial Intelligence · doi:10.1016/j.artint.2018.07.007 · Cited by 5,302
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., et al. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.002 · Cited by 4,611
Artificial Intelligence, Automation and Work
Acemoglu, D., & Restrepo, P. (2018) · doi:10.3386/w24196 · Cited by 962
Industrial artificial intelligence for industry 4.0-based manufacturing systems
Lee, J., Davari, H., Singh, J., & Pandhare, V. (2018) · Manufacturing Letters · doi:10.1016/j.mfglet.2018.09.002 · Cited by 870
Rulers of the world, unite! The challenges and opportunities of artificial intelligence
Kaplan, A., & Haenlein, M. (2020) · Business Horizons · doi:10.1016/j.bushor.2019.09.003 · Cited by 718
Cited by
Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.120420 · Cited by 910
Sjödin, D., Parida, V., Palmié, M., & Wincent, J. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2021.05.009 · Cited by 584
Denicolai, S., Zucchella, A., & Magnani, G. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120650 · Cited by 503
Artificial intelligence and industrial innovation: Evidence from German firm-level data
Rammer, C., Fernández, G. P., & Czarnitzki, D. (2022) · Research Policy · doi:10.1016/j.respol.2022.104555 · Cited by 489
Perifanis, N.-A., & Kitsios, F. (2023) · Information · doi:10.3390/info14020085 · Cited by 407
Metadata
- Authors
- Liu, J., Chang, H., Forrest, J. Y.-L., & Yang, B.
- Venue
- Technological Forecasting and Social Change
- Publisher
- Elsevier BV
- Published
- 2020-09
- Volume
- 158
- Pages
- 120142
- ISSN
- 0040-1625 (ISSN-L)
- OpenAlex
- W3036506385
- Cited by
- 695
- References
- 5
- FWCI
- 37.62
- Type
- journal article
- Language
- en
- Open access
- closed
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- Liu, J., Chang, H., Forrest, J. Y.-L., & Yang, B. (2020). Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors. Technological Forecasting and Social Change. https://doi.org/10.1016/j.techfore.2020.120142
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