A fuzzy multi-criteria decision-making framework for assessing the impact of multi-agent technology in preventing the probabilities of airplane crashing

Purpose The increasing complexity of air transportation highlights the need for advanced technologies to enhance aviation safety. But implementing these technologies to control airplane safety is a big challenge for the aviation industry. To overcome this, current research aims to investigate the potential of Multi-Agent Technology (MAT) in addressing key factors contributing to airplane crashes. Design/methodology/approach A comprehensive literature review led to the identification of six major crash-related factors and 30 control variables relevant to MAT. A hybrid fuzzy multi-criteria decision-making (MCDM) approach was applied: Fuzzy AHP ranked the factors and variables; Fuzzy TOPSIS validated the rankings; and Fuzzy DEMATEL assessed the interrelationships among them. Findings The analysis identified “Flight Crew Support” as the most influential factor in preventing airplane crashes, with the “Intelligent Decision-Making System” emerging as the top-ranked MAT-based variable. Fuzzy DEMATEL revealed that both “Flight Crew Support” and “Aircraft Design & Production Systems” have strong causal impacts, acting as key drivers within the aviation safety framework. Prioritizing these areas enables the aviation sector to leverage MAT for more effective crash prevention and enhanced operational safety. Practical implications These insights enable aviation stakeholders to prioritize investments and policies focused on high-impact areas, especially in training and real-time crew support systems. Originality/value This research presents a novel integration of MAT and fuzzy MCDM techniques to inform aviation safety strategies through a data-driven framework.