What factors predict the type of person who is willing to fly in an autonomous commercial airplane?. (March 2019)

• Record Type: Journal Article
• Authors: Rice, Stephen; Winter, Scott R.; Mehta, Rian; Ragbir, Nadine K.
• Is Part Of: Journal of air transport management. Volume 75(2019)
• Page Start: 131
• Page End: 138
• Publication Date: 2019-03
• Subjects: Autonomous aircraft -- Willingness to fly -- Regression -- Model fit -- Consumer perceptions; Airlines -- Management -- Periodicals; Aeronautics, Commercial -- Management -- Periodicals; 387.7068
• DOI: 10.1016/j.jairtraman.2018.12.008
• Languages: English
• ISSNs: 0969-6997

Abstract

Abstract: There has been much discussion and research lately highlighting autonomous commercial flight, with most of the focus on engineering design and legal issues. Some prior research has shown that many people are generally not willing to fly in fully autonomous aircraft; however, there is a significant proportion of society that is willing to use these types of airplanes. It is critical for the aviation industry to be able to identify these individuals as they will likely be the early adopters. The current study was designed with the purpose of determining what factors predict the type of person who would be willing to fly in fully autonomous commercial airplanes. We provided a hypothetical scenario to 1042 potential passengers from the United States and asked them to rate their willingness to fly in that situation. We also collected demographic data, along with ratings of various scales to determine what predictors were significant in a regression model. In Stage 1, we built the model from a dataset of 522 participants and determined that the significant factors were familiarity with autonomous flight, fun factor, general wariness of new technology, happiness, fear, age, and educational level. This model accounted for 85.9% of the variance in the data. In Stage 2, we tested the model with 520 participants and found excellent model fit. We discuss the practical and theoretical implications of these findings. Highlights: Examined predictors of passenger's willingness to fly in autonomous aircraft. In two stages, developed the regression equation and conducted model fit. Findings indicate model explains over 85% of the variance. Identified seven significant predictors of passenger willingness to fly.