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Emerging digital technologies generate persistent paradoxes: they enable trust and efficiency while constraining flexibility and control. Prior research explains adoption through drivers, barriers, or institutional alignment, treating innovation as a matter of fit between organizations and environments. This view overlooks how managers actively configure technologies to stabilize innovation under institutional complexity. This study reframes adoption as innovation stabilization and conceptualizes dynamic institutional fit as a mid-range configurational explanation of how paradoxical digital infrastructures become operationally viable and institutionally legitimate under institutional complexity. Using systematic evidence synthesis combined with set-theoretic qualitative comparative analysis (QCA), it examines 75 blockchain studies across manufacturing, finance, logistics, healthcare, and agriculture. The findings show that viable innovation does not stem from a single driver but from multiple equifinal combinations of design and governance choices across sectors. Four recurring design mechanisms are identified from cross-sector configurations and interpreted through paradox theory and institutional theory, namely, the selective prioritization of attributes, controlled autonomy, managed openness, and temporal sequencing. Sustainability considerations appear less recurrent than regulatory, efficiency, and capability conditions, suggesting a possible sequencing logic for further investigation. These results reframe innovation viability as an active configuration rather than a passive institutional alignment and show how similar outcomes arise through different sector-specific pathways. This study contributes a cross-sector configurational explanation of institutional viability under a paradox and provides structured guidance for managers and policymakers seeking to stabilize digital innovations in complex environments.
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Mattos et al. (2026) studied this question.
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