人工智能应用如何赋能企业投资效率——基于资源配置效率和投资决策质量的视角

How Can Artificial Intelligence Applications Empower Corporate Investment Efficiency —From the Perspectives of Resource Allocation Efficiency and Investment Decision-Making Quality

中文关键词:  人工智能应用  企业投资效率  资源配置效率  投资决策质量  大数据战略

英文关键词:artificial intelligence applications  corporate investment efficiency  resource allocation efficiency  investment decision-making quality  big data strategy

中文摘要:

      人工智能是推动产业变革、赋能新质生产力发展的新动能,其以强大的数据获取、分析和预测能力,正在改变企业传统的投资模式。利用2010—2022年中国沪深A股上市公司数据,从资源协同和决策支持双重维度,实证检验了人工智能应用对企业投资效率的影响及作用机制。研究发现,人工智能应用对企业投资效率的提高起到了促进作用,既抑制了企业过度投资,又改善了企业投资不足。人工智能应用通过提升资源配置效率、改善投资决策质量,促进了企业投资效率的提高。大数据战略在人工智能应用与企业投资效率的关系中发挥了正向调节作用。异质性分析表明,在人工智能应用程度高、员工技术能力强、管理层对经济政策不确定性的感知程度低和处于成熟期的企业中,人工智能应用对企业投资效率提高的促进作用更加显著。因此,应大力推动人工智能在企业的应用,强化人工智能应用的资源整合和决策支持能力,促进人工智能与实体经济的深度融合。

英文摘要:

      Artificial intelligence (AI) is a new driver that promotes industrial transformation and empowers the development of new quality productive forces. Leveraging its advanced capabilities in data acquisition, analysis, and prediction, AI is reshaping traditional investment models of firms. Using data from China's A-share listed firms in Shanghai and Shenzhen stock exchanges from 2010 to 2022, this study empirically examines the impact of AI applications on corporate investment efficiency through the dual lenses of resource allocation and decision-making, and its underlying mechanisms. The results demonstrate that AI applications significantly enhance corporate investment efficiency, suppressing both overinvestment and underinvestment. This enhancement is achieved primarily through two mechanisms:enhanced resource allocation efficiency and improved investment decision-making quality. Furthermore, a company's big data strategy positively moderates the relationship between AI applications and corporate investment efficiency. Heterogeneity analysis reveals that the positive effects of AI applications are more pronounced in firms with higher levels of applications, stronger technical competencies among employees, and lower awareness of economic policy uncertainty among managers, and those in the mature phase of AI applications. These findings underscore the importance of accelerating AI applications in firms, strengthening AI's capacity for resource integration and strategic decision support, and advancing the deep integration of AI with the real economy. 