Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13087/1401
Title: Analytic Hierarchy Process-Based Selection Method for Airline Pilot Candidates
Authors: Oktal, Hakan
Onrat, Atilla
Issue Date: 2020
Publisher: Taylor & Francis Inc
Abstract: Objective: In this study, a new selection method for airline pilot candidates is developed. Background: In a large majority of previous studies, parametric statistical classification methods have been commonly used for the pilot candidate selection process. These kind of methods require a representative sample with sufficient numbers of good and poor candidates to minimize the standard error associated with the regression weights and to ensure prediction accuracy. In this study, a new pilot candidate selection method has been developed, which can also be used in cases where there are not enough candidates or there is not a significant relationship between predictors. Method: The model was developed by using an analytic hierarchy process technique. A survey was conducted with airline pilots working at Turkish air carriers to determine the weights of the selection criteria considered in the model. The minimum success score of each criterion was obtained from the survey results. The analyzes are carried out using the Super Decisions program. Results: We found that the most important factor among the pilot candidate selection criteria is psychomotor coordination and operational abilities with a coefficient of 0.37306. Conclusion: The survey results revealed the importance of flight abilities and personality traits for pilots and it also found that lack of motivation is the most important problem among new airline pilots.
URI: https://doi.org/10.1080/24721840.2020.1816469
https://hdl.handle.net/20.500.13087/1401
ISSN: 2472-1832
2472-1840
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu

Show full item record

CORE Recommender

Page view(s)

18
checked on Oct 3, 2022

Google ScholarTM

Check

Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.