Spatio-Temporal Characteristics and Influencing Mechanisms of China’s Digital Rural Development: A Panel Data Analysis Across 31 Provinces

To advance human society towards a fully inclusive and accessible digital future, it is essential to foster the comprehensive and balanced development of digital villages, thereby addressing rural residents’ aspirations for a digitally enriched life. This study systematically investigates the spatiotemporal differentiation patterns and spatial spillover effects of China’s Digital Rural Development (DRD). Utilizing panel data from 31 provinces in China from 2013 to 2022, we construct a comprehensive evaluation framework covering digital infrastructure, economic digitization, governance digitization, and life digitization. The empirical analysis integrates entropy weighting, Dagum Gini coefficient decomposition, Moran’s I index, and spatial Durbin models. The findings indicate that China’s DRD has exhibited sustained overall improvement, progressing through three distinct phases: slow growth, rapid advancement, and fluctuating ascent. Significant regional disparities persist, with eastern regions consistently outperforming central, western, and northeastern areas. Inter-regional differences constitute the primary source of overall variation, and this gap has progressively widened over time. Spatially, DRD demonstrates a significant positive agglomeration effect alongside a negative spatial spillover effect (ρ = −1.3209), suggesting that advancements in neighboring regions may inhibit local development progress. Mechanism analysis identifies technological innovation, rural population size, and age structure as key local determinants, whereas industrial upgrading generates significant positive spillover effects on surrounding regions. Based on these results, at the same time, in order to ensure the sustainable development of DRD, we propose the following policy recommendations: implement regionally differentiated interventions, enhance the alignment of core local drivers, establish interregional coordination mechanisms, and develop dynamic monitoring and adjustment systems. These measures are expected to promote more balanced urban–rural and regional development, offering empirical evidence and policy insights for other developing countries pursuing similar pathways of rural digital transformation.