The impact of artificial intelligence on total factor productivity: empirical evidence from China’s manufacturing enterprises

被引:0
|
作者
Ke-Liang Wang
Ting-Ting Sun
Ru-Yu Xu
机构
[1] Ocean University of China,School of Economics
来源
关键词
Total factor productivity (TFP); Artificial intelligence (AI); Manufacturing enterprises; Transmission mechanism; Heterogeneity; Exogenous policy shock;
D O I
暂无
中图分类号
学科分类号
摘要
Using the panel data of 938 listed manufacturing companies in China from 2011 to 2020, this paper scientifically examines the impact of artificial intelligence (AI) on total factor productivity (TFP) of China’s manufacturing enterprises by using the fixed effect model, mediating effect model and difference-in-differences model. The results show that AI can significantly improve the TFP of China’s manufacturing enterprises, as confirmed by a series of robustness tests. Technological innovation, human capital optimization and market matching improvement have proved to be three important channels for AI to affect the TFP of China’s manufacturing enterprises. The impact of AI on TFP varies greatly among China’s manufacturing enterprises in different geographical locations, industry characteristics, ownership and life cycle stages. The findings of this paper can provide theoretical insights and empirical evidence at the micro enterprise level for policymakers to give full play to the role of AI in promoting the high-quality development of China's manufacturing industry.
引用
收藏
页码:1113 / 1146
页数:33
相关论文
共 50 条
  • [41] Impact of Industrial Intelligence on Total Factor Productivity
    An, Ke
    Shan, Yike
    Shi, Sheng
    SUSTAINABILITY, 2022, 14 (21)
  • [42] The impact of green total factor productivity on export product quality: evidence from china
    Feng, Wei
    Yuan, Hang
    Chen, Yanyi
    ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2024,
  • [43] The impact of environmental regulation on agricultural green total factor productivity: evidence from China
    Sun, Tian-Le
    Zhang, Yi-Cheng
    INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION, 2021, 70 (3-4) : 203 - 222
  • [44] Impact of industrial agglomeration on total factor productivity in the construction industry: evidence from China
    Wang, Yousong
    Yao, Yao
    Zhang, Yangbing
    Su, Boya
    Wu, Tongyuan
    CONSTRUCTION MANAGEMENT AND ECONOMICS, 2023, 41 (04) : 322 - 337
  • [45] The impact of holiday tourism development on tourism total factor productivity: Evidence from China
    Sun, Panpan
    Huang, Songshan
    Yap, Ghialy
    TOURISM MANAGEMENT PERSPECTIVES, 2022, 43
  • [46] IMPACT OF ENVIRONMENTAL REGULATION AND FDI ON GREEN TOTAL FACTOR PRODUCTIVITY: EVIDENCE FROM CHINA
    Xu Xiaofei
    Cui Yanjuan
    Zhong Yundi
    ENVIRONMENTAL ENGINEERING AND MANAGEMENT JOURNAL, 2021, 20 (02): : 177 - 184
  • [47] The Impact of Free-Trade Zones on Total Factor Productivity: Evidence from China
    Chen, Jun
    Yang, Bingyu
    Wu, Maoguo
    JOURNAL OF THE KNOWLEDGE ECONOMY, 2024, 15 (4) : 17649 - 17675
  • [48] The impact of forced mergers and acquisitions on banks' total factor productivity: empirical evidence from Malaysia
    Sufian, Fadzlan
    Habibullah, Muzafar Shah
    JOURNAL OF THE ASIA PACIFIC ECONOMY, 2014, 19 (01) : 151 - 185
  • [49] Influence of artificial intelligence applications on total factor productivity of enterprises-evidence from textual analysis of annual reports of Chinese-listed companies
    Zhong, Yilin
    Xu, Feng
    Zhang, Longpeng
    APPLIED ECONOMICS, 2024, 56 (43) : 5205 - 5223
  • [50] Artificial Intelligence and Food Processing Firms Productivity: Evidence from China
    Liu, Huanan
    Wang, Yan
    Yan, Zhoufu
    SUSTAINABILITY, 2024, 16 (14)