How to become the chosen one in the artificial intelligence market: the evidence from China

被引:3
|
作者
Li, Jizhen [1 ]
Liu, Zixu [1 ]
Zhou, Jianghua [2 ]
机构
[1] Tsinghua Univ, Res Ctr Competit Dynam & Innovat Strategy, Sch Econ & Management, Beijing 100084, Peoples R China
[2] Beijing Normal Univ, Business Sch, Beijing 100875, Peoples R China
基金
中国国家自然科学基金;
关键词
artificial intelligence market; small and medium-sized enterprises; SMEs; innovation performance; social investment; institutional intermediaries; public funding; Innofund; signalling effects; China; RESEARCH-AND-DEVELOPMENT; DEVELOPMENT SUBSIDIES; ENTREPRENEURIAL FIRMS; PUBLIC SUPPORT; POLITICAL TIES; INNOVATION; PERFORMANCE; INVESTMENT; STRATEGIES; LEGITIMACY;
D O I
10.1504/IJTM.2020.112122
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This study aims to explore how firms' innovation performance is related to their possibility of receiving public support, and the boundary conditions of this relationship. Specifically, we focus on the firms in the Chinese artificial intelligence (AI) market, and study a specific public support, namely, Innofund. The results suggest that a firm's innovation performance has an inverted U-shaped effect on its probability of receiving Innofund. The effect, moreover, is moderated by whether a firm has received social investment, that is, the relationship between innovation performance and the probability of receiving funding is flattened by the receipt of social investment. Besides, a firm's ties to institutional intermediaries further strengthen the moderating effect of social investment. The findings carry implications for future research and technology policy.
引用
收藏
页码:8 / 24
页数:17
相关论文
共 50 条
  • [41] From anomaly detection to time series forecasting: How artificial intelligence changes the energy market
    Wilsdorf, André
    BWK- Energie-Fachmagazin, 2019, 71 (7-8): : 24 - 26
  • [42] The impact of artificial intelligence on energy environmental performance: Empirical evidence from cities in China
    Guo, Qingbin
    Peng, Yanqing
    Luo, Kang
    ENERGY ECONOMICS, 2025, 141
  • [43] Artificial intelligence empowers enterprise innovation: evidence from China's industrial enterprises
    Han, Feng
    Mao, Xin
    APPLIED ECONOMICS, 2024, 56 (57) : 7971 - 7986
  • [44] Do Artificial Intelligence applications affect firm stock liquidity? Evidence from China
    Zhong, Yilin
    Zhong, Junhao
    Yang, Tianjian
    Han, Minghui
    Zhang, Qinghua
    APPLIED ECONOMICS LETTERS, 2025, 32 (02) : 204 - 209
  • [45] Artificial Intelligence and Street Space Optimization in Green Cities: New Evidence from China
    Liu, Yuwei
    Qin, Shan
    Li, Jiamin
    Jin, Ting
    SUSTAINABILITY, 2023, 15 (23)
  • [46] Unveiling the role of artificial intelligence in influencing enterprise environmental performance: Evidence from China
    Cheng, Kai
    Jin, Zhuiqiao
    Wu, Guo
    JOURNAL OF CLEANER PRODUCTION, 2024, 440
  • [47] Impact of population aging on food security in the context of artificial intelligence: Evidence from China
    Lee, Chien-Chiang
    Yan, Jingyang
    Wang, Fuhao
    TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2024, 199
  • [48] Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China
    Liu, Jun
    Qian, Yu
    Yang, Yuanjun
    Yang, Zhidan
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (04)
  • [49] Does artificial intelligence reduce corporate energy consumption? New evidence from China
    Fu, Yunyun
    Shen, Yongchang
    Song, Malin
    Wang, Weiyu
    ECONOMIC ANALYSIS AND POLICY, 2024, 83 : 548 - 561
  • [50] Artificial intelligence against the first wave of COVID-19: evidence from China
    Wang, Ting
    Zhang, Yi
    Liu, Chun
    Zhou, Zhongliang
    BMC HEALTH SERVICES RESEARCH, 2022, 22 (01)