Provincial Data-Factor Allocation Capacity in China: A Supply–Circulation–Utilization Framework for Measuring Balance, Bottlenecks, and Distributional Dynamics

Data-factor allocation involves interrelated supply, circulation, and utilization functions, yet existing provincial assessments often emphasize aggregate development rather than internal system configuration. Using 18 indicators for 30 Chinese provinces from 2012 to 2023, this study develops a systems-oriented measurement framework that distinguishes overall attainment, subsystem balance, and relative bottlenecks. Entropy weighting and arithmetic–geometric aggregation are combined with regional inequality decomposition and distributional dynamics analysis. The results show that mean balance-adjusted capacity increased from 0.0449 in 2012 to 0.2125 in 2023, while subsystem balance evolved non-monotonically and showed no sustained improvement after 2018. Under the baseline measurement specification, the predominant relative bottleneck shifted from circulation in 2012 to utilization in 2023, with each identified as the weakest subsystem in 23 provinces. Net between-region differences accounted for an average of 69.34% of total inequality, while annual development-state transitions exhibited substantial persistence. These findings highlight the diagnostic value of examining internal functional configurations alongside aggregate capacity and provide a proxy-based framework for differentiated provincial assessment.