Management Science · 2025 · Lynn Wu、Bowen Lou、Lorin M. Hitt
中文摘要
我们考察AI分析在促进已完成IPO的企业创新方面的作用。利用1000多家上市公司的专利数据，我们发现，与未获得AI分析能力的同类企业相比，在IPO后获得AI分析能力的企业其创新质量下降幅度更小。当仅考虑机器学习能力时，这一效应更大。此外，我们发现这种持续的创新率主要由将现有技术组合为新技术的创新的持续开发所驱动——这是一种尤其受分析技术支持的创新形式。通过考察阻碍IPO后创新的三种主要机制，我们发现AI分析能够缓解满足短期财务目标和披露要求的压力。然而，它在应对管理者激励方面的作用有限。对于产品周期较长的企业，披露效应相对于短周期企业被削弱得更明显。总体而言，我们的结果表明了将技术视为创新关键投入要素加以考察的重要性。我们表明，AI分析部署的增加可能减轻IPO所承受的部分创新损失，并且投资者和管理者可以通过将IPO过程中获得的资金用于获取AI分析能力，从而潜在地缓解IPO后创新产出的下降。
Abstract
We examine the role of AI analytics in facilitating innovation in firms that have gone through IPO. Using patent data on over 1,000 publicly traded firms, we find that firms acquiring AI analytics capability post-IPO experience less of a decline in innovation quality compared with similar firms that have not acquired that capability. This effect is greater when only machine learning capabilities are considered. Moreover, we find this sustained rate of innovation is driven principally by the continued development of innovations that combine existing technologies into new ones—a form of innovation that is especially well supported by analytics. By examining three main mechanisms that hampered post-IPO innovation, we find that AI analytics can ameliorate the pressure to meet short-term financial goals and disclosure requirements. However, it has limited effect in addressing managerial incentives. For firms with long product cycles, the disclosure effect is reduced to a greater extent than it is for those with short cycles. Overall, our results show the importance of examining technology as a critical input factor in innovation. We show that the increased deployment of AI analytics may reduce some of the innovative penalties suffered by IPOs and that investors and managers can potentially mitigate post-IPO reductions in innovative output by directing capital acquired in the IPO process to the acquisition of AI analytics capabilities.