Date of Award
Doctor of Philosophy in Aviation Sciences
The purpose of the study was to develop a statistical model representing predictors to anticipate pilots’ likelihood to quit flying in Part 121 Commercial Aviation. The study was primarily focused on the current Part 121 pilots in the United States. The study was designed with a correlational methodology and multiple linear regression was employed as the statistical procedure to analyze the data collected from diverse sources. The sample of the study consists of 163 participants (33 females), and all of them currently working for either major or regional airline in the United States respectively. Simultaneous regression strategy was used to regress all 22 predictors with the outcome variables to generate significant results. The predictors were age, experience in flight hours, education, gender, race/ethnicity, organizational culture, workload, type of airline, current role, job satisfaction, months to upgrade from first officer to captain, years of service employed at current airline, total years of service as an Airline Transport Pilot, salary, marital status, level of spousal income, time away from spouse, number of dependent children, gender discrimination, sexual harassment, medical certification, and fatigue. The outcome variable was pilots’ likelihood to quit flying in Part 121 commercial aviation. Due to the presence of missing data points, multiple imputation was employed as the missing data handling procedure to generate complete datasets. The results of this study suggested that job satisfaction, annual salary before taxes, married vs cohabiting comparison, and medical certification significantly predict pilots’ likelihood to quit flying in Part 121 commercial aviation. Further information on limitations, recommendations for practice, and future research recommendations were addressed.
Tamilselvan, Gajapriya, "Pilots’ Likelihood to Quit Flying in Part 121 Commercial Aviation" (2018). Theses and Dissertations. 42.