Big Data Innovative Development Experiments, Sci-Technology Finance Ecology, and the Chinese Path to Sustainable Modernization—A Quasi-Natural Experiment Based on SDID and DML

Modernization in developing countries such as China has long been unsustainable. As a result, China has set the goal of achieving sustainable modernization characterized by harmony between humanity and nature. Against this backdrop, in this study, we apply spatial difference-in-differences (SDID) and double machine learning (DML) models using panel data from 30 provincial-level regions in China from 2009 to 2021. We examine the impacts of the National Big Data Comprehensive Pilot Zone policy and sci-technology financial ecology on the Chinese Path to Sustainable Modernization. The results show that big data pilot zones significantly enhance modernization and generate positive spatial spillover effects through demonstration and diffusion. Sci-technology financial ecology improves sustainable modernization and amplifies the role played by pilot zones. Heterogeneity tests reveal stronger effects in eastern provinces and in areas implementing urban–rural integration or green finance reforms. The results of the mechanism analysis show that big data innovation promotes modernization by strengthening sci-technology financial ecology, raising government attention, fostering inclusive intelligence development, enhancing green innovation efficiency, and upgrading industrial structures.