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Longitudinal analysis uncovers configurational pathways and spatial spillovers linking digital ecosystems to regional innovation across China, highlighting the need for tailored regional strategies.
Digital ecosystem configurations are significantly associated with regional high-quality innovation. Nevertheless, existing studies have not fully captured the temporal dynamics of digital ecosystem configurations, nor the spatial spillovers of digital dimensions. The underlying mechanism through which digitalisation promotes regional innovation remains unsystematically elaborated. Drawing on the technology–organisation–environment (TOE) framework, this study integrates complex adaptive systems theory and resource allocation theory. It employs panel data for 31 Chinese provinces from 2019 to 2024 and combines kernel density estimation, dynamic QCA, a two-way fixed-effects benchmark, and the spatial Durbin model. The findings show that digital talent and digital innovation satisfy the necessity criterion in the main specification and remain comparatively stable in some robustness tests; digital infrastructure is more sensitive to influential provinces; necessity classifications are also sensitive to calibration anchors. Four configurational pathways to high-quality innovation (H1–H4) and three configurational pathways for the absence of high-quality innovation (L1–L3) are identified. These innovation pathways show divergent temporal-evolution trajectories, with 2022 constituting a candidate descriptive inflexion point; various innovation configurations show notable spatial-differentiation features, and individual digital dimensions exhibit conditional and weight matrix-dependent spatial spillover associations. This paper refines the configurational mechanism linking digital ecosystems to regional high-quality innovation from a temporal perspective, while also providing a complementary analysis of individual dimensions’ spatial spillovers. The findings provide empirical evidence and practical guidance for local governments to formulate differentiated digital construction strategies suited to regional conditions and advance high-quality innovation development.
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Fang et al. (2026) studied this question.
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