Jialu Qian, Xiaolin Chu
Against the backdrop of the digital economy driving high-quality economic development, the convergence of data factor agglomeration and enterprise new quality productivity has emerged as a critical pathway for transforming growth models and shifting development drivers. Taking the National Big Data Comprehensive Pilot Zone (NBDCPZ) as a quasi-natural experiment and using a panel dataset of Chinese A-share listed companies from 2010 to 2023, this paper employs a difference-in-differences (DID) framework combined with a mediation effect model to empirically examine the impact, transmission mechanisms, and heterogeneity of data factor agglomeration on enterprise new quality productivity. Robustness tests are also conducted to verify the reliability of the findings. The results indicate that data factor agglomeration significantly enhances enterprise new quality productivity, and this finding passes robustness tests across multiple specifications. Digital transformation, R&D innovation, and talent agglomeration are identified as the three core transmission pathways through which data factor agglomeration affects new quality productivity. Heterogeneity analysis further reveals that the positive effect is more pronounced in non-state-owned enterprises, firms aged over 20 years, and enterprises located in eastern China. These findings contribute to the theoretical foundations of data factors and new quality productivity, and provide empirical evidence for the design of NBDCPZ policy and the advancement of enterprise new quality productivity.