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Spatiotemporal evolution and configuration pathways of digital-intelligent regional innovation ecosystem sustainability: Evidence from China based on symbiosis theory

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  • Deng, Qinwen

Abstract

Amid the global wave of digital and intelligent transformation, Digital-Intelligent Regional Innovation Ecosystem Sustainability (DIRGIES) has become vital for promoting innovation, enhancing resilience, and overcoming growth bottlenecks. Grounded in symbiosis theory, this study develops a five-dimensional evaluation framework, which includes units, matrix, community, network, and environment. By integrating the CRITIC-TOPSIS method, spatial econometrics, and dynamic QCA, it systematically examines the spatiotemporal evolution and configuration pathways of DIRGIES across Chinese provinces from 2011 to 2023. The findings reveal that DIRGIES in China exhibit a spatial divergence pattern characterized by strong performance in the eastern region and weaker performance in the west; however, with the widespread adoption of digital technologies and deepening policy coordination, spatial dependence has weakened and network-based collaboration has intensified. Dynamic QCA identifies four configurations associated with high DIRGIES and four associated with low DIRGIES, highlighting the complex, nonlinear, and synergistic causal mechanisms among multiple factors. Digital-intelligent technologies significantly enhance system resilience by reconfiguring resource allocation, optimizing network structures, and strengthening environmental adaptability. Based on these insights, this study proposes a stratified, differentiated, and dynamically adaptive policy framework that provides a theoretical foundation and practical guidance for differentiated regional governance.

Suggested Citation

  • Deng, Qinwen, 2026. "Spatiotemporal evolution and configuration pathways of digital-intelligent regional innovation ecosystem sustainability: Evidence from China based on symbiosis theory," Technology in Society, Elsevier, vol. 85(C).
  • Handle: RePEc:eee:teinso:v:85:y:2026:i:c:s0160791x25003343
    DOI: 10.1016/j.techsoc.2025.103144
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