Data-driven coordination and optimization of the digital economy and urban–rural integration

Fostering the coordinated development of the digital economy (DE) and urban–rural integration (URI) is considered a critical pathway to achieving sustainable growth. In this paper, we present a data-driven method for measuring, identifying, and testing the coupling coordination degree between DE and URI (DE–URI CCD). First, relevant data on DE and URI were collected, and an evaluation index system was established. Subsequently, the Technique for Order of Preference by Similarity to Ideal Solution method was applied to measure development levels, and the CCD model was used to assess their coordination. Meanwhile, the Dagum Gini coefficient was applied to identify regional differences, and the convergence model was employed to verify the convergence characteristics of the levels. Using 2013–2022 panel data from 30 Chinese provinces and cities, the findings show that (1) DE–URI CCD is rising in China with significant variations across regions; (2) inter-regional differences are the primary source of regional CCD disparities; and (3) economic development level and education level of labor force have varied impacts on CCD, exhibiting significant regional heterogeneities. To address these challenges, we propose a multi-level “National–Regional–Provincial” collaborative strategy, emphasizing the need for tailored policies that account for regional specificities. This research not only enriches the theoretical and methodological foundations of sustainable regional development but also provides actionable insights for policymakers aiming to bridge the urban–rural divide in the digital era. By aligning with the United Nations Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities), this work underscores the importance of integrating digital innovation with inclusive development frameworks.