详情
The Impact of Digital Transformation on Enterprises’ Total Factor Productivity: Matching and Learning Mechanism
This research study primarily examines the digital transformation’s internal mechanism promoting enterprises’ total factor productivity (TFP) based on the matching and learning mechanism. Afterward, this research article empirically examines the digital transformation’s influential mechanism on enterprises’ TFP, using the Chinese listed companies’ data on the “A” stock market for the time period ranging from 2007 to 2019. The major study findings are as follows: (1) the improvement of the digital transformation significantly increases enterprises’ TFP. The proposed conclusion remains robust after a series of robustness- and the endogeneity test. (2) Furthermore, mechanism analysis reveals that digital transformation effectively enhances enterprises’ TFP by eliminating resource misallocation in the industry. In addition to this, digital transformation relies on the mechanism of “learning by doing” to promote the technological innovation’s spillover effect; hence, effectively enhancing enterprises’ TFP. (3) Heterogeneity analysis demonstrates that the digital transformation’s impact on enterprises’ TFP is heterogeneous in the context of enterprise size, enterprise type, and enterprise ownership. Lastly, this study puts forward that government bodies should intensify the construction and investment in digital infrastructure, promote a series of institutional reforms, and support digital technological R&D practices.