From Decisions to Systemic Risk: A Conceptual Multi-Method Framework for Aviation Maintenance Safety Policy Analysis

Abstract

Aviation maintenance operates within a complex socio-technical system in which safety emerges from interactions among technical systems, human operators, maintenance organizations, and regulatory structures. Despite growing research interest, existing studies remain fragmented across the micro, meso, and macro levels of analysis, limiting the ability to explain how decentralized decision-making under economic pressure translates into system-level safety outcomes and how policies can effectively intervene in this process. This study identifies this gap through a systematic literature review of 29 peer-reviewed studies, which reveals structural and methodological fragmentation in current approaches. The review shows that aviation maintenance decision-making is inherently multi-level, characterized by decentralized interactions, boundedly rational behavior, and delayed system-level feedback. Existing methodologies address these dimensions selectively rather than in combination. To overcome this limitation, the paper proposes a conceptual multi-method framework that integrates Agent-Based Modeling (ABM) to map micro-level behavioral dynamics and then links them to System Dynamics (SD) to model macro-level system feedback. The combined framework enables analysis of how operational decisions propagate into long-term safety risks. By providing a unified representation of cross-level interactions, the framework establishes a foundation for simulation-based evaluation of aviation maintenance safety policies under economic constraints.