Digital–intelligent systemic innovation for sustainable development: Mechanisms and boundary conditions
The intersection between digitalization and intelligent technology is transforming the dynamics of systemic innovation. However, how this intersection affects systemic innovation toward sustainability, and the boundary conditions that influence innovation effectiveness, remain poorly theorized. This research proposes a causal analytic model that includes both a ternary coupling system and boundary conditions. A multiple-case comparative analysis used four cases representing different developmental phases: Germany’s Energiewende, Hangzhou City Brain in China, the Kenya Agricultural Observatory Platform digital agriculture platform, and the Advanced Metering Infrastructure project under the Asian Development Bank Second Distribution Enhancement Investment Program in Pakistan. These cases included different innovation patterns, ranging from successful integration, dysfunctional operation, and later correction at the technology-content level to large disruptions and restarts at the institutional level. The results suggest that the convergence of digital and intelligent factors has shifted the linkage among technological, institutional, and market aspects from a reactive state to resonant synchronization through real-time feedback and adaptive optimization. Composite coupling strength was associated with differences in innovation cycle length across the four cases, though the small sample did not support inference of a specific numerical threshold. The priority order of boundary conditions differed across the four cases, with technological feasibility as the binding constraint in the German and Hangzhou cases and institutional adequacy together with capital availability in the Kenyan and Pakistani cases. Comparing the negative cases shows that regardless of where the failures arise, either on the technology-content level or the institutional level, the process of innovation can be turned around as long as the critical flaw is discovered and dealt with. However, both repairs observed here relied on substantial external support. This study lays the foundation for further research to develop a theoretical framework for system innovation in the era of digital intelligence and provides an analytical tool for prioritizing sustainable development policies.
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