Digital risk matrix and safety management workflow for airport infrastructure in developing countries: a data-driven prioritization approach

This paper presents a digital risk assessment and safety management workflow for airport infrastructure in developing countries, designed to operate under limited and heterogeneous safety data. The proposed approach combines hazard identification, exposure-normalized probability estimation, severity scoring, and automated prioritization using a numerical risk index <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:mi>R</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>i</mml:mi> </mml:mrow> </mml:msub> <mml:mo>=</mml:mo> <mml:msub> <mml:mrow> <mml:mi>P</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>i</mml:mi> </mml:mrow> </mml:msub> <mml:mo>×</mml:mo> <mml:msub> <mml:mrow> <mml:mi>S</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>i</mml:mi> </mml:mrow> </mml:msub> </mml:math> . Probability is derived from event frequency normalized by an exposure metric (flight hours or aircraft movements), while severity is assigned using a predefined five-level consequence scale aligned with SMS practice. The workflow is implemented as a lightweight digital tool that standardizes event records, applies scoring rules, generates risk matrices/heatmaps, and automatically produces a risk register with mitigation actions for key airport asset classes. A case study illustrates how national safety records can be transformed into ranked risk priorities under data scarcity. The contribution is a reproducible scoring framework with transparent thresholds and a practical digital reporting format that improves traceability and decision-making in Safety Management Systems.