The level of data element utilization in the integration of the digital and real economies drives AI technological innovation

Chenjie Liu

doi:10.63313/EBM.9174

Authors

Chenjie Liu Foshan University, Foshan, China Author

DOI:

https://doi.org/10.63313/EBM.9174

Keywords:

Data elements, Artificial intelligence innovation, Integration of the digital and real economies, Total factor productivity

Abstract

Using a sample of Chinese A-share listed companies in core digital economy industries from 2015 to 2024, this study examines how data element utilization drives AI technological innovation. Employing a panel fixed‑effects regression model, we find that the level of data factor utilization has a significant positive impact on AI patent output. This effect is more pronounced in firms with low total factor productivity (TFP), exhibiting a "contrarian" catch‑up characteristic. The conclusions remain robust after substituting different TFP measurement methods. This study reveals the unique mechanism through which data elements enable late‑entrant firms to catch up technologically, providing empirical evidence for deepening data element market reforms.

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