Author Information

Joel SamuFollow

Is this project an undergraduate, graduate, or faculty project?

Graduate

Project Type

individual

Campus

Daytona Beach

Authors' Class Standing

Joel Samu, Graduate Teaching Assistant

Lead Presenter's Name

Joel Samu

Lead Presenter's College

DB College of Aviation

Faculty Mentor Name

Dr. Jennifer Thropp

Abstract

Aviation safety is paramount, and the concern for risk-taking remains persistent in the industry, especially among pilots with a high propensity for such behavior. The research objective is to explore established and novel factors that predict risk propensity among general aviation pilots in the United States. Sample data will be gathered from local Experimental Aircraft Association chapters in Central Florida and Embry Riddle Aeronautical University campus in Daytona Beach. The study involves developing a statistical prediction model to forecast pilots’ risk propensity, followed by model fit testing using additional sampling to validate the predicted model. The research aims to identify the factors that impact pilots’ decision-making and aid the industry in developing intervention programs for pilot risk management. The study explores several risk-propensity predictors, including self-efficacy, locus of control, pilots’ mental health, and hazardous events. The model prediction and cross-validation approach aim to increase the rigor and generalizability of the findings, contributing to a better understanding of risk-taking propensity among GA pilots and ultimately improving aviation safety.

Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?

Yes, Spark Grant

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Risk-Taking Propensity Among General Aviation Pilots

Aviation safety is paramount, and the concern for risk-taking remains persistent in the industry, especially among pilots with a high propensity for such behavior. The research objective is to explore established and novel factors that predict risk propensity among general aviation pilots in the United States. Sample data will be gathered from local Experimental Aircraft Association chapters in Central Florida and Embry Riddle Aeronautical University campus in Daytona Beach. The study involves developing a statistical prediction model to forecast pilots’ risk propensity, followed by model fit testing using additional sampling to validate the predicted model. The research aims to identify the factors that impact pilots’ decision-making and aid the industry in developing intervention programs for pilot risk management. The study explores several risk-propensity predictors, including self-efficacy, locus of control, pilots’ mental health, and hazardous events. The model prediction and cross-validation approach aim to increase the rigor and generalizability of the findings, contributing to a better understanding of risk-taking propensity among GA pilots and ultimately improving aviation safety.

 

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