Study on the Spatial Effects and Micro-Level Transmission Mechanisms of Digital Economy Empowering Innovation Performance in Manufacturing

Xiaofei Li; Wenxuan Li; Keqing Li; Kaiwen Tan; Huajia Shi

doi:10.54691/f8cn9p46

Authors

Xiaofei Li
Wenxuan Li
Keqing Li
Kaiwen Tan
Huajia Shi

DOI:

https://doi.org/10.54691/f8cn9p46

Keywords:

Digital Economy; Innovation Performance; Structural Equation Modeling (SEM); Spatial Durbin Model (SDM).

Abstract

The deep integration of the digital economy and the manufacturing sector constitutes a critical pathway for fostering industrial innovation and high-quality development. Utilizing panel data from 11 provinces within the Yangtze River Economic Belt (2015–2023), this study employs the Spatial Durbin Model (SDM) and Structural Equation Modeling (SEM) to investigate the transmission mechanisms and spatial spillover effects of the digital economy on manufacturing innovation performance. The findings indicate that: (1) The digital economy acts as a significant driver of manufacturing innovation performance, with a total effect coefficient of 1.327. The decomposition of this impact-61.8% direct and 38.2% indirect-highlights a dual-drive characteristic involving both technological empowerment and institutional optimization. (2) The innovation-promoting effect exhibits spatial correlation; specifically, while the digital economy exerts a slight direct inhibitory effect locally, it generates significant positive spatial spillovers to neighboring regions, suggesting a potential "siphon effect" arising from inter-regional factor competition. (3) The transmission pathways display significant threshold characteristics. The mediating mechanisms are fully activated only after the digital economy surpasses a specific developmental threshold, implying that the empowerment effect is contingent upon the maturity of the digital ecosystem. This study provides theoretical foundations and policy insights for implementing differentiated digital development strategies, constructing cross-regional innovation collaborative systems, and advancing the deep fusion of digital technology and manufacturing.

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References

[1] Hong, Y., & Ren, B. (2023). Connotation and Pathways of Deep Integration of Digital Economy and Real Economy. China Industrial Economics, (2), 5-16. (in Chinese)

[2] Dai, X., & Yang, S. (2022). Digital Empowerment, Source of Digital Input and Green Transformation of Manufacturing Industry. China Industrial Economics, (9), 83-101. (in Chinese)

[3] Shi, B., & Chang, Q. (2024). Effects and Mechanisms of Enterprise Digital Transformation Empowering Green Innovation. Economic Management Journal, 46(11), 67-88. (in Chinese)

[4] Zhou, Y., & Chen, M. (2025). Spatial Correlation Effects and Influencing Factors of Digital Economy Development in China's Regions. Economic Theory and Business Management, 45(2), 96-117. (in Chinese)

[5] Chao, X., Zhou, W., & Liu, Y. (2024). Industrial Internet and Total Factor Productivity of Manufacturing Enterprises. Economic Management Journal, 46(7), 5-19. (in Chinese)

[6] Yang, Z., & Yuan, Z. (2025). Digital Innovation Network Embedding and Key Core Technology Breakthroughs. China Industrial Economics, (5), 156-173. (in Chinese)

[7] Tang, Y., Wang, Y., & Tang, C. (2022). Digital Economy, Market Structure and Innovation Performance. China Industrial Economics, (10), 62-80. (in Chinese)

[8] Dou, J., Wang, G., & Ma, R. (2023). Impact of Digital Economy Development on Urban Collaborative Innovation: A Perspective Based on Spatial Spillover Effects. Economic Management Journal, 45(7), 56-75. (in Chinese)