Author
Listed:
- Xiaojing Lv
- Gui Zhang
- Jiqing Liu
- Jiayu Li
- Wen-Tsao Pan
Abstract
The digitalization of the automobile industry must depend on the information technology industry. The coupling development of the two creates conditions for the realization of industry 4.0 and intelligent manufacturing. The purpose of this paper is to make an empirical study on the possibility of coupling and the coupling degree, correlation degree, and innovation ability of China’s automobile industry and information technology industry. This paper takes the intelligent manufacturing of the automobile industry as the research object. According to the current situation of China’s automobile industry, this paper uses data to analyze and predict the development level of China’s automobile industry and the gap with the foreign automobile industry. Firstly, it summarizes and analyzes the development of China’s automobile industry and information technology industry. Then, the gray correlation analysis method is used to explore the factors affecting the innovation of China’s automobile industry. It is found that the relationship between capital investment and innovation is the most significant in “industrial innovation investment.†Finally, the coupling development model of the automobile industry and information technology industry is established, and the coupling degree of the two is analyzed by using the analytic hierarchy process and the Delphi method. The research of this paper mainly focuses on the automobile industry. Under the wave of internet, other industries such as the commerce and service industry also have a strong coupling relationship with the information technology industry, which will provide a new research direction for the follow-up research of experts and scholars.
Suggested Citation
Xiaojing Lv & Gui Zhang & Jiqing Liu & Jiayu Li & Wen-Tsao Pan, 2022.
"The Innovation Ecological Model of Chinese Automotive Industry Based on Artificial Intelligence and Big Data Technology,"
Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, July.
Handle:
RePEc:hin:jnlmpe:4328187
DOI: 10.1155/2022/4328187
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