 Breakdowns in team resilience during aircraft landing due to mental model disconnects as identified through machine learningHsueh-Yi Lai Reliability Engineering and System Safety, 2023, vol. 237, issue C Abstract: Landing system in aviation is a representative sociotechnical system; such systems often require seamless teamwork among experts. Resilience is critical for the ability of a team to adapt to sudden changes, overcome challenges, and return to normalcy. However, team heterogeneity can result in cognitive misalignment, known as mental model disconnects (MMDs). MMDs can cause interaction conflcits, which compromise team resilience. This study aimed to use machine learning to identify breakdowns in team resilience during aircraft landing. The results showed that the MMDs in the terminal area had the greatest influence on missed approaches; in particular, the late intervention of air traffic controllers’ (ATCOs) in an improper landing state was the major breakdown identified. This result highlights the importance of ATCO initiative in preventing landing incidents. The mechanism was determined to be ineffective information dissemination in nonroutine scenarios, which unravels the necessity for improving future information systems. Keywords: Team resilience; Mental model disconnects; Landing system; Information transparency (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:237:y:2023:i:c:s0951832023002703 DOI: 10.1016/j.ress.2023.109356 Access Statistics for this article Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares More articles in Reliability Engineering and System Safety from Elsevier |
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