The Impact of Data Element Agglomeration on Inclusive Green Development: Evidence from Threshold and Spatial Spillover Effects

As a production factor, data plays an increasingly important role in sustainable development. Using panel data from 31 Chinese provinces (2011–2023) and employing fixed-effects, panel threshold, and spatial Durbin models, this study examines the impact of data element agglomeration on inclusive green development. The results reveal four main findings. First, data element agglomeration significantly improves inclusive green development, though this positive effect stems primarily from economic growth and social inclusion rather than direct environmental gains. Second, industrial structure upgrading and green technology innovation function as underlying mechanisms, but exhibit suppression effects—their indirect contributions are negative, reflecting short-term adjustment costs and institutional frictions. Third, fiscal support intensity exhibits a nonlinear moderating effect with diminishing returns. Fourth, the effect is more pronounced in coastal provinces, regions with stringent environmental regulation, and the pre-2020 period, and generates significant spatial spillovers to neighboring regions. These findings highlight the conditional nature of data-driven green development and offer insights for designing context-sensitive data policies.