Abstract: With the rapid development of the digital economy, computing infrastructure has become a critical strategic resource, essential for technological innovation and digital transformation. This paper examines provincial-level computing infrastructure in China by constructing a multidimensional evaluation indicator system based on the principles of innovation, coordination, green development, openness, and sharing. Using the entropy weight method, spatial autocorrelation analysis, spatial Markov chain, and Spatial Durbin Model, it examines the spatial spillover effects and driving factors. The results show that overall development levels have improved, though growth has slowed; regional disparities have narrowed, and spatial patterns display a“higher in the east and south, lower in the west and north”trend, with declining spatial correlations over time. Provinces generally exhibit stable upward trends, but spatial lag effects differ across regions. Such key drivers as population size, technological progress, investment intensity, and economic development level positively influence development. The Spatial Durbin Model reveals that neighboring regions’ population structure, technological advancement, and industrial structure generate significant spatial spillover effects. These findings provide valuable policy insights for promoting coordinated and high-quality computing infrastructure development and advancing the digital transformation of China’s economy and society.

Key words: Arithmetic infrastructure, High-quality development, Spatial spillover effects, Spatial Markov chains, Spatial Durbin model