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首页> 外文期刊>Journal of Air Transport Management >What factors predict the type of person who is willing to fly in an autonomous commercial airplane?
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What factors predict the type of person who is willing to fly in an autonomous commercial airplane?

机译:哪些因素可以预测愿意乘坐自动驾驶商用飞机的人的类型?

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摘要

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.
机译:最近有很多讨论和研究突出了自主商业飞行,其中大部分集中在工程设计和法律问题上。先前的一些研究表明,许多人通常不愿意驾驶全自动飞机。但是,社会上有很大一部分愿意使用这些类型的飞机。对于航空业来说,能够识别这些人至关重要,因为他们很可能是早期采用者。当前的研究旨在确定哪些因素可以预测愿意驾驶全自动民航飞机的人的类型。我们为1042名来自美国的潜在乘客提供了一个假设的情景,并要求他们对在这种情况下的飞行意愿进行评分。我们还收集了人口统计数据以及各种规模的评级,以确定在回归模型中哪些预测指标是重要的。在第1阶段,我们从522名参与者的数据集中建立了模型,并确定了重要因素是对自动驾驶的熟悉程度,娱乐因素,对新技术的普遍警惕,幸福感,恐惧感,年龄和教育程度。该模型占数据差异的85.9%。在阶段2中,我们用520名参与者测试了该模型,并发现了出色的模型拟合度。我们讨论了这些发现的实践和理论意义。

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