Driving enterprise new quality productivity: The role of big data tax collection

Abstract

The application of big data in tax administration has emerged as a crucial catalyst for technological advancements in enterprises, promoting sustained growth and significantly enhancing the development of new quality productivity. This research uses a difference-in-difference (DID) model, anchored by the ‘Golden Tax Phase III’ project as a natural experiment benchmark, to empirically investigates how big data tax administration influences enterprise new quality productivity and uncovers the pathways through which these effects manifest. The findings indicate that the implementation of big data tax management, exemplified by the ‘Golden Tax Phase III’ project, significantly boosts enterprise new quality productivity, particularly by enhancing innovation capacity and output value. Notably, this impact is especially pronounced in technology-intensive and environmentally friendly enterprises, with the western region experiencing the strongest positive effects compared to the eastern and central regions. Furthermore, the mediation effect model provides further insights, revealing that big data tax administration indirectly strengthens enterprise new quality productivity by improving total factor productivity, increasing investment levels, and accelerating technological progress. By integrating theoretical foundations with empirical evidence, this research sheds light on the economic benefits of big data tax administration. It also offers strategic recommendations aimed at fostering digital economic innovation, improving new quality productivity, and driving the ongoing reform of regulatory systems.