Organizations increasingly operate under persistent digital technological turbulence, where traditional capability-outcome explanations offer limited insight into how they sustain decision-making under continuous perturbation. This study addresses this gap by reconceptualizing organizational digital resilience as decision continuity, a second-order system property reflecting the capacity to maintain recursive decision processes. By shifting from linear causality to systemic self-regulation, the study aims to provide a theoretically grounded explanation of how organizations remain viable in digitally mediated environments characterized by complexity, uncertainty and rapid technological change.
Drawing on second-order cybernetics and systems theory, digital ambidexterity and digital agility are interpreted as mechanisms of structural coupling and temporal regulation, respectively, while digital technological turbulence is conceptualized as environmental perturbation. Survey data were collected from 311 managers in digitally intensive organizations. Partial least squares structural equation modelling (PLS-SEM) was employed as an observational analytical device to examine relational patterns among constructs, with parameters interpreted as indicators of structural alignment rather than causal effects.
The results reveal stable and statistically significant relational patterns among constructs. Digital ambidexterity is strongly associated with digital agility (ß = 0.471, p < 0.001) and organizational digital resilience (ß = 0.502, p < 0.001), while digital agility also shows a positive association with resilience (ß = 0.228, p < 0.01). The model explains 40.4% of variance in agility (R2 = 0.404) and 48.5% in resilience (R2 = 0.485). These patterns support the interpretation of resilience as an emergent property of aligned structural and temporal regulation under turbulence.
This study advances digital resilience research by introducing a second-order cybernetic perspective that reframes resilience as a process of recursive self-regulation rather than a capability-driven outcome. Methodologically, it demonstrates the use of PLS-SEM as a non-causal observational tool. The findings offer a novel systemic lens for understanding organizational viability and contribute to ongoing debates on complexity, digital transformation and systems thinking.
