data assets and green transformation

This study employs a panel dataset of Chinese A-share listed companies from 2012 to 2024, using text analysis and the entropy weight method to construct measurement indicators for data assetization and CGT, and empirically examines the impact of data assetization on CGT and its underlying mechanisms. Results show that data assetization significantly promotes CGT, with internally used data assets serving as the core driver. Grounded in Schumpeter’s theory of innovation and Porter’s innovation-driven hypothesis, the mediating mechanism test confirms that data assetization enhances enterprise innovation capability, thereby stimulating the technological, scale, and management effects to promote CGT. The moderating effect test reveals that excessively stringent government environmental regulation may attenuate this positive effect. Threshold analysis uncovers a dual-threshold effect contingent on the scale of enterprise assets: the promoting effect becomes statistically significant only when asset size surpasses the higher threshold of 24.077. Further analysis confirms that the synergy between data assetization and CGT exerts a significant positive impact on corporate value.