人工智能技术应用、吸收能力与企业创新绩效——高管团队异质性的调节效应

Artificial Intelligence Application, Absorptive Capacity, and Enterprise Innovation Performance: The Moderating Effect of TMT Heterogeneity

摘要:

随着人工智能技术不断嵌入企业的生产经营过程，如何实现人工智能技术应用向企业创新绩效的有效转化，成为亟待研究的重要问题。现有研究较多关注人工智能技术应用对企业创新的直接影响，对于技术应用如何转化为创新产出的组织能力机制，以及企业内部治理情境如何影响这一转化过程，仍有进一步深化空间。本文基于资源基础观与吸收能力理论，选取2008—2023年中国A股上市公司样本，实证考察人工智能技术应用影响企业创新绩效的作用机制与内部治理边界。研究发现：(1)人工智能技术应用能够显著提升企业创新绩效，该赋能效应具有滞后性与跨期持续性；(2)吸收能力发挥部分中介效应，表明人工智能技术应用能够通过增强企业知识吸收与转化能力进一步促进创新产出；(3)高管团队异质性负向调节人工智能技术应用对吸收能力的促进作用，表明团队成员差异可能增加知识整合与协调成本，从而制约人工智能技术应用向组织能力的有效转化；(4)异质性分析表明，人工智能技术应用的创新促进作用在中西部企业和高技术行业中更为明显。本文从组织能力转化和内部治理情境两个维度深化了人工智能技术应用创新效应的研究，为理解人工智能技术如何转化为企业创新优势及其差异化作用提供了新的经验证据。

Abstract:

As AI technology is increasingly embedded in the production and operation processes of enterprises, how to achieve the effective transformation of AI technology application into enterprise innovation performance has become an important issue that urgently needs to be addressed. Existing studies mainly focus on the direct effects of AI technology application on enterprise innovation. However, the organizational capability mechanism through which technology application is transformed into innovation output, and the way the internal governance context affects this transformation process, still need to be further explored. Based on the resource-based view and absorptive capacity theory, a sample of Chinese A-share listed firms from 2008 to 2023 was selected, and the mechanism and internal governance boundaries through which AI technology application affects enterprise innovation performance were empirically examined. The results show that: (1) AI technology application can significantly improve enterprise innovation performance, and this enabling effect is characterized by lag and cross-period persistence; (2) absorptive capacity plays a partial mediating role, indicating that AI technology application can further promote innovation output by enhancing enterprises'' knowledge absorption and transformation capabilities; (3) TMT heterogeneity negatively moderates the promoting effect of AI technology application on absorptive capacity, indicating that differences among team members may increase the costs of knowledge integration and coordination, thereby constraining the effective transformation of AI technology application into organizational capabilities; (4) heterogeneity analysis show that the innovation-promoting effect of AI technology application is more pronounced in central and western region enterprises and high-tech industries. This study deepens the research on the innovation effects of AI technology application from the two dimensions of organizational capability transformation and internal governance context, and provides new empirical evidence for understanding how AI technology is transformed into enterprise innovation advantages and its differentiated effects.