Staging digital capability activation for innovation resilience: a dynamic capability perspective on sequencing AI, big data, IoT and blockchain

Purpose This paper aims to investigate how innovation ecosystems should sequence digital technologies – artificial intelligence (AI) and big data, Internet of Things (IoT) and blockchain – across crisis phases to build resilience. Grounded in the dynamic capability view, this paper develops and tests a Staged Digital Capability Activation Model (SDCAM) that links technologies to sensing, seizing and reconfiguring capabilities and to resilience outcomes, and presents a phase-gated roadmap for managers and policymakers. Design/methodology/approach A repeated cross-sectional survey of 1,500 firm-year observations (2014–2023) is analysed using covariance-based SEM (maximum likelihood, 5,000 bootstraps). This paper reports global fit, R², Q² and f²; tests capability-mediated effects; establishes measurement invariance; conducts multi-group comparisons by phase, sector and region; and performs robustness checks with post-stratification weighting. Findings are associational. Findings AI/big data strengthens sensing, IoT strengthens seizing and blockchain strengthens reconfiguring; these capabilities map to adaptability, operational recovery and sustained innovation, respectively. Proper sequencing improves resilience indirectly via capabilities. Cost and skills constraints weaken activation; cybersecurity is not a binding constraint. Cross-context heterogeneity is modest but meaningful. Research limitations/implications The design uses repeated cross-sections with retrospective timing anchors, limiting causal inference. Future work should use panel/event-study designs, combine surveys with operational trace data and extend the framework to additional technologies (e.g. digital twins, 5G). This paper provides validity and invariance evidence and encourages sector-specific replications. Practical implications A phase-gated roadmap is provided: pre-shock – build analytics for sensing; shock – deploy IoT for visibility and rapid response; recovery – use blockchain for traceability and reconfiguration; implement via triggers, readiness gates, staged roll-outs, targeted upskilling and ecosystem partnerships to overcome cost/skills constraints. Social implications Clarifying when to activate specific digital capabilities supports continuity of essential services, faster recovery and more inclusive innovation during shocks. Policy guidance includes skills programmes, interoperability standards, baseline cyber controls and de-risked financing to lower barriers for SMEs and public agencies. Originality/value This paper formalises temporal sequencing in the dynamic capability view, showing that the order and timing of AI/big data, IoT and blockchain activation matter as much as adoption. This paper offers predictive, prescriptive guidance (SDCAM plus roadmap) with rigorous SEM evidence, bridging theory and implementation for recurrent disruptions.