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YAO Shu-jun, XU Jun-bao, SUN Tie-dan. Research on the Mechanism of Data Element Utilization in Promoting the Development of New Quality Productivity in EnterprisesJ. Journal of Xihua University (Philosophy & Social Sciences) , 2026, 45(1): 94-107. DOI: 10.12189/j.issn.1672-8505.2026.01.009
Citation: YAO Shu-jun, XU Jun-bao, SUN Tie-dan. Research on the Mechanism of Data Element Utilization in Promoting the Development of New Quality Productivity in EnterprisesJ. Journal of Xihua University (Philosophy & Social Sciences) , 2026, 45(1): 94-107. DOI: 10.12189/j.issn.1672-8505.2026.01.009

Research on the Mechanism of Data Element Utilization in Promoting the Development of New Quality Productivity in Enterprises

  • New quality productivity provides vital support for innovation in science and technology, industrial upgrading, development models, institutional reform, and talent cultivation, and it is also key to enhancing China's international competitiveness. Using data from Chinese A-share listed companies between 2012 and 2022, this paper investigates the impact of data element utilization on new quality productivity, as well as the roles of the three ESG dimensions and management gradient in this relationship. The results show that higher levels of data element utilization significantly promote the development of new quality productivity in enterprises. Mechanism analysis indicates that environmental management and corporate social responsibility exert positive mediating effects, whereas internal corporate governance has a negative mediating effect. The management age structure has a significant moderating effect on the relationship between data utilization and new quality productivity. In addition, comprehensive pilot zones for cross-border e-commerce significantly accelerate the development of new quality productivity. Heterogeneity analysis reveals that the positive impact of data element utilization is stronger in state-owned enterprises, non-heavily polluting enterprises, and non-asset-intensive enterprises. These findings provide theoretical implications for optimizing the institutional environment of enterprise data utilization and for promoting the development of new quality productivity.
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