Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/116449
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Aeronautical and Aviation Engineering | - |
| dc.contributor | Department of Civil and Environmental Engineering | - |
| dc.creator | Liu, Q | - |
| dc.creator | Song, P | - |
| dc.creator | Li, F | - |
| dc.date.accessioned | 2025-12-30T05:22:53Z | - |
| dc.date.available | 2025-12-30T05:22:53Z | - |
| dc.identifier.issn | 2213-6657 | - |
| dc.identifier.uri | http://hdl.handle.net/10397/116449 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.subject | Aircraft damage | en_US |
| dc.subject | Flight phases | en_US |
| dc.subject | General aviation | en_US |
| dc.subject | Pilot injury severity | en_US |
| dc.subject | Random parameters bivariate probit model | en_US |
| dc.title | Exploring the dynamic determinants of general aviation accidents across flight phases and time : a random parameter bivariate probit approach with heterogeneity in means | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 47 | - |
| dc.identifier.doi | 10.1016/j.amar.2025.100386 | - |
| dcterms.abstract | General aviation experiences significant variation in accident characteristics across flight phases. This study seeks to investigate the phase transferability and temporal stability of determinants influencing general aviation accidents, using the U.S. data (2008–2019) from the National Transportation Safety Board. To achieve this, a random parameter bivariate approach with heterogeneity in means was employed, focusing on two binary outcomes: injury severity (fatal/severe vs. minor/none) and aircraft damage (destroyed vs. non-destroyed). Four flight phases were analyzed: departure, enroute, maneuvering, and arrival. The data were divided into three time periods, 2008–2011, 2012–2015, and 2016–2019, to assess the determinants’ temporal stability. Likelihood ratio tests revealed that pilot injury and aircraft damage risks exhibit phase non-transferability and temporal instability. Out-of-sample predictions indicated a steady rise in fatal or severe injury risk, while aircraft damage risk initially increased before declining over time. A significant positive correlation between pilot injury and aircraft damage was observed through model estimation. Key factors, including pilot, aircraft, flight, and environmental conditions, significantly influenced both outcomes. Moreover, factors such as decision-making errors, adverse physiological conditions, fixed landing gear, and visual meteorological conditions showed both phase transferability and temporal stability. However, most factors were phase- and period-specific. Based on these findings, targeted measures, such as pilot escape and survival training, as well as phase-specific, scenario-based training, are proposed to mitigate general aviation risks. | - |
| dcterms.accessRights | embargoed access | en_US |
| dcterms.bibliographicCitation | Analytic methods in accident research, 2025, v. 47, 100386 | - |
| dcterms.isPartOf | Analytic methods in accident research | - |
| dcterms.issued | 2025-09 | - |
| dc.identifier.scopus | 2-s2.0-105005853478 | - |
| dc.identifier.artn | 100386 | - |
| dc.description.validate | 202512 bcel | - |
| dc.description.oa | Not applicable | en_US |
| dc.identifier.SubFormID | G000645/2025-11 | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | The study is supported by Research Centre Data Science AI, the Hong Kong Polytechnic University (Grant : P0046166 ). In addition, special thanks to Dr. Wang Chenzhu for his valuable assistance in resolving the methodological issues. | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.date.embargo | 2027-09-30 | en_US |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
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