详细信息
Artificial intelligence investment, executive digital background, and stock price synchronization
文献类型:期刊文献
英文题名:Artificial intelligence investment, executive digital background, and stock price synchronization
作者:Zheng, Kai[1];Ruan, Yongping[1];He, Yanan[2]
机构:[1]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]Shanghai Lixin Univ Accounting & Finance, Sch Accounting, Shanghai 201620, Peoples R China
年份:2025
卷号:86
外文期刊名:FINANCE RESEARCH LETTERS
收录:;WOS:【SSCI(收录号:WOS:001614862800006)】;
基金:The Impact of Digital Technology on Auditors' Behavioral Decisions: An Experimental Study Based on Psychology and Behavior (Project No. 2022ZJB002) of the 2022 Shanghai Philosophy and Social Science Planning Project of China.
语种:英文
外文关键词:AI investment; Executives' digital backgrounds; Stock price synchronicity; Manufacturing industry
摘要:In the context of the accelerated development of the digital economy, investment in artificial intelligence (AI) has become an important force in promoting information governance and strategic transformation within enterprises. Based on data from publicly listed manufacturing companies in China from 2010 to 2023, this paper systematically examines the impact of AI investment on stock price synchronicity and further analyzes the moderating effect of executives' digital backgrounds and the heterogeneous effects of enterprise characteristics. Empirical results indicate that AI investment significantly reduces stock price synchronicity. Results of the moderating effect suggest that executives' digital backgrounds influence the impact of AI investment on stock price synchronicity. Heterogeneity tests reveal that the negative effect of AI investment on stock price synchronicity is more pronounced in small and medium-sized enterprises, as well as in technology-intensive and asset-intensive industries, while it is not significant in large enterprises and labor-intensive industries. The conclusions of this study provide empirical evidence and management insights for manufacturing enterprises to optimize their AI investment strategies, enhance the structure of their executive teams, and improve the quality of information disclosure.
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