Develops a self-organizing governance approach to enhance digital government resilience and adaptability.
As digital government systems evolve, increasing complexity in information interactions has challenged traditional hierarchical governance models, which often struggle in dynamic and cross-sectoral contexts. This study aims to identify the structural patterns of government information interaction and to develop a testable adaptive governance approach that supports sustainable digital government evolution. Drawing on IT alignment theory and complex network analysis, this study reconceptualizes digital government as a complex adaptive system and reveals the heavy-tailed distribution, structural stability, and self-organizing tendencies of government information networks. Building on these findings, the study develops and operationalizes a self-organizing adaptive governance framework—featuring fractal design, dynamic alignment, and layered modular coordination—into 11 governance rules. By shifting the focus from static alignment to adaptive structural coordination, this research advances a new pathway for the sustainable and resilient evolution of digital government systems.
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Guo et al. (2026) studied this question.
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