The rapid development of the digital economy has driven the digital transformation of public services. However, in China, particularly in peripheral counties, there exists a spatial–temporal mismatch between the digital economy and public services. This article focuses on counties in Shaanxi Province and employs Point of Interest data from Gaode Map spanning from 2012 to 2022. Using methods such as kernel density estimation, nearest neighbor index, and Ripley’s K function, it analyzes the spatial–temporal distribution patterns of digital economy and public service facilities, identifying cold and hot spots as well as types of mismatch. Additionally, the article applies a geographic and temporal weighted regression model to explore the influencing factors of mismatch and their spatial characteristics across social, economic, financial, natural, and industrial dimensions. The results indicate a concentration of facilities in the Central Shaanxi region, while southern and northern Shaanxi counties remain underdeveloped. The authors recommend that the government increase targeted investments in weaker regions to enhance infrastructure, particularly in healthcare and education. Furthermore, tailored measures should be implemented based on the specific mismatch types and characteristics of different counties, employing fiscal support, industrial optimization, and technological innovation to promote high-quality development of facilities and facilitate coordinated adaptation between the digital economy and public services. This article provides empirical evidence from the perspective of Chinese counties to enhance spatial adaptation of facilities and offers valuable insights for policy governance in other developing countries.
Huang et al. (Wed,) studied this question.