Analysis reveals digital transformation enhances production efficiency in high-tech enterprises, suggesting significant policy implications.
Enterprise digital transformation is critical for enterprises to remain competitive in the fast-paced business environment. To explore the impact mechanisms of enterprise digital transformation on industrial structural adjustment, this paper analyzed data from 3,608 publicly listed enterprises in China from 2007 to 2020. A baseline panel model, a widely used statistical approach that is simple yet maintains generality, was adopted to analyze the data. The indicators for industrial structural adjustment, including production efficiency, production investment, and the efficiency-investment interaction, were considered dependent variables in the model. Nine control variables related to the degree of digital transformation, industry and enterprise attributes, policy, and macroeconomic conditions were then analyzed. The results show that the effective promotion of industrial structural adjustments occurs through the implementation of digital transformation. This positive impact primarily results from its ability to enhance enterprise production efficiency, rather than attracting increased production investment. High-tech enterprises are the initial adopters of digital transformation, and they, in turn, encourage its adoption among other enterprises, including traditional manufacturing enterprises. Additionally, we have observed that well-designed digital transformation-related policies can significantly expedite the digital transformation process for enterprises and contribute to industrial structural adjustments. Lastly, specific digital technologies such as artificial intelligence, cloud computing, and big data play a crucial role in supporting industrial structural adjustments. These findings contribute to a deeper theoretical understanding of digital transformation’s role in industrial structural adjustments and carry significant policy implications.
No takes yet. Share an insight, caveat, or question.
Guo-xia et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: