王佰川, 杜创. 人工智能技术创新扩散的特征、影响因素及政府作用研究——基于A股上市公司数据[J]. 北京工业大学学报(社会科学版), 2022, 22(3): 142-158. DOI: 10.12120/bjutskxb202203142
    引用本文: 王佰川, 杜创. 人工智能技术创新扩散的特征、影响因素及政府作用研究——基于A股上市公司数据[J]. 北京工业大学学报(社会科学版), 2022, 22(3): 142-158. DOI: 10.12120/bjutskxb202203142
    WANG Baichuan, DU Chuang. Research on the Characteristics, Influencing Factors and Government Role in Artificial Intelligence Technology Innovation Diffusion: Based on the Data of A-Share Listed Companies[J]. JOURNAL OF BEIJING UNIVERSITY OF TECHNOLOGY(SOCIAL SCIENCES EDITION), 2022, 22(3): 142-158. DOI: 10.12120/bjutskxb202203142
    Citation: WANG Baichuan, DU Chuang. Research on the Characteristics, Influencing Factors and Government Role in Artificial Intelligence Technology Innovation Diffusion: Based on the Data of A-Share Listed Companies[J]. JOURNAL OF BEIJING UNIVERSITY OF TECHNOLOGY(SOCIAL SCIENCES EDITION), 2022, 22(3): 142-158. DOI: 10.12120/bjutskxb202203142

    人工智能技术创新扩散的特征、影响因素及政府作用研究——基于A股上市公司数据

    Research on the Characteristics, Influencing Factors and Government Role in Artificial Intelligence Technology Innovation Diffusion: Based on the Data of A-Share Listed Companies

    • 摘要: 基于中国A股上市公司年报文本数据,借助机器学习技术识别出人工智能上市公司名单,揭示了中国人工智能技术创新扩散的总体特征:(1)中国人工智能技术创新扩散在2016、2017年出现增长拐点;(2)中国人工智能技术应用存在头部效应,智能安防成为应用最热的行业。基于此总体特征,从微观视角分析了人工智能技术创新扩散的影响因素,并构造2015—2019年的面板数据研究,面板Probit模型的实证分析表明,企业规模对创新扩散的影响呈倒U型;企业研发能力未表现出显著影响;竞争性市场结构、政府补贴可以促进创新扩散。人工智能技术具有网络外部性,相关产业政策的正向作用机制在于降低技术转换成本、推动上市公司整体形成新的市场预期,使技术应用走向正反馈循环。当前,中国经济进入高质量发展阶段,人工智能相关政策有必要实现从产业政策为主向竞争政策为主的转变,充分发挥市场在资源配置中的决定性作用。

       

      Abstract: Based on the annual reports of Chinese A-share listed companies, this paper uses machine learning technology to identify the list of AI listed companies, and reveals the general characteristics of China′ s AI innovation diffusion: (1) The diffusion of AI technology innovation in China showed an inflection point in 2016 and 2017; (2) There is head effect in the application of AI technology in China, and intelligent security has become the most popular industry. Secondly, this paper analyzes the factors influencing the diffusion of AI technology. Then the paper constructs the panel data from 2015 to 2019, and makes empirical analysis using the panel probit model. The results show that the impact of firm size on innovation diffusion is inverted U-shaped. Firm′s R & D capability has no significant effect. Competitive market structure and government subsidy can promote innovation diffusion. AI technology has network externalities. The positive mechanism of government subsidies and other relevant policies lies in reducing firm′s technology conversion costs, promoting listed companies to form new market expectations, and leading to a positive feedback cycle of technology application. As China′s economy enters a stage of high-quality development, it is necessary for policies related to AI to shift from industrial policy to competition policy, and give full play to the decisive role of the market in resource allocation.

       

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