Published at : 01 Dec 2025
Volume : IJtech
Vol 16, No 6 (2025)
DOI : https://doi.org/10.14716/ijtech.v16i6.7815
| Yuri Chernenko | Department of Doctoral Studies, International University of Business and Law |
| Olena Borodina | Faculty of Management, Public Administration and Marketing, Kyiv University of Market Relations |
This study aims to develop and validate the MuSyRI early-warning index for critical e-government infrastructure. This study introduces the Multi-Domain Synergistic Resilience Index (MuSyRI), a bounded [0–1] metric that identifies nonlinear, compound risks across operational, financial, regulatory, and cyber domains in critical e-government infrastructure. MuSyRI explicitly integrates domain-specific resilience factors to modulate synergy-driven escalation. A multiple-case study of four anonymised organizations – a housing-services agency, a specialized construction firm, a water-tech startup, and a partially state-owned energy – water utility – validates MuSyRI. ERP-BPMS logs are converted into fuzzy sub-indices and aggregated via a Cascading Amplification Function (CAF) to capture concurrent moderate hazards and offset by a resilience term. Parameters were calibrated using Delphi panels, genetic algorithms, and expert elicitation. MuSyRI detects overlapping medium-level risks 1–4 weeks earlier than standard additive approaches. Early synergy alerts enabled proactive interventions, reducing housing-service disruptions by 8%–12% and boosting pilot adoption in the water-tech case by 12%–15%. Resilience offset curtails overestimation and preserves policymakers’ and managers’ interpretability. Unlike linear or unbounded fuzzy methods, MuSyRI formally integrates a nonlinear synergy function with domain-specific resilience into one bounded index. Consequently, it offers an actionable early warning framework for multi-domain oversight, resource prioritization, and digital governance reforms in e-government ecosystems.
Critical infrastructure; E-government; Multi-domain risk; MuSyRI; Synergy-based index
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