Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Business
Evidence-Based Managerial Decision-Making With Machine Learning: The Case Of Bayesian Inference In Aviation Incidents, Aaron Glassman, Burak Cankaya, Kazim Topuz, Dursun Delen
Evidence-Based Managerial Decision-Making With Machine Learning: The Case Of Bayesian Inference In Aviation Incidents, Aaron Glassman, Burak Cankaya, Kazim Topuz, Dursun Delen
Publications
Understanding the factors behind aviation incidents is essential, not only because of the lethality of the accidents but also the incidents’ direct and indirect economic impact. Even minor incidents trigger significant economic damage and create disruptions to aviation operations. It is crucial to investigate these incidents to understand the underlying reasons and hence, reduce the risk associated with physical and financial safety in a precarious industry like aviation. The findings may provide decision-makers with a causally accurate means of investigating the topic while untangling the difficulties concerning the statistical associations and causal effects. This research aims to identify the significant …
Business Inferences And Risk Modeling With Machine Learning; The Case Of Aviation Incidents, Burak Cankaya, Kazim Topuz, Aaron M. Glassman
Business Inferences And Risk Modeling With Machine Learning; The Case Of Aviation Incidents, Burak Cankaya, Kazim Topuz, Aaron M. Glassman
Publications
Machine learning becomes truly valuable only when decision-makers begin to depend on it to optimize decisions. Instilling trust in machine learning is critical for businesses in their efforts to interpret and get insights into data, and to make their analytical choices accessible and subject to accountability. In the field of aviation, the innovative application of machine learning and analytics can facilitate an understanding of the risk of accidents and other incidents. These occur infrequently, generally in an irregular, unpredictable manner, and cause significant disruptions, and hence, they are classified as "high-impact, low-probability" (HILP) events. Aviation incident reports are inspected by …