Archetype-based analysis of single-pilot operations risk: Evidence from small jet incident and accident narratives

This study employs systems thinking and systems archetype modeling to identify systemic risk patterns inherent in single-pilot operations (SiPO) within commercial aviation. A rigorous qualitative classification of 279 aviation safety narratives (237 NASA Aviation Safety Reporting System (ASRS) incident reports and 42 small jets (SJ) accident investigations) was conducted by subject matter experts to uncover recurring feedback structures indicative of latent operational vulnerabilities. Analysis reveals a predominance of archetypes such as Drifting into Failure and Fixes That Fail in accident investigations, reflecting incremental procedural degradation and compensatory failures. Conversely, ASRS narratives exhibit early-stage systemic stress archetypes including Accidental Adversaries and Limits to Growth , evidencing cognitive overload and inter-organizational friction. These findings substantiate the imperative for system-aware Single Pilot Resource Management (SRM) frameworks embedding real-time monitoring and targeted interventions addressing emergent feedback loops. Contributions: (1) First expert archetype classification of 279 SiPO narratives, formalizing Drift; (2) Causal network; (3) SRM maturity model; (4) Safety Management System (SMS) integration; (5) Prospective complement to the Human Factors Analysis and Classification System (HFACS), the Functional Resonance Analysis Method (FRAM), and the Systems-Theoretic Accident Model and Processes (STAMP). The archetype classification offers a theoretically grounded prospective diagnostic instrument for SiPO risk identification, with potential utility in supporting regulatory certification processes and operational safety enhancement strategies. Given the modest accident subsample (n = 42), the prevalence estimates are reported with confidence intervals and treated as exploratory. The framework is presented as a structured analytical tool requiring independent empirical validation in large-scale commercial environments before its findings can be adopted as operational guidelines or incorporated into regulatory standards.