Navigating the Future of the Aviation Market: Machine Learning-Based Intention and Attitude Analysis

Abstract

In the current technological era, artificial intelligence (AI) is transforming various aspects of the aviation industry, with the use of chatbots to enhance customer service. Although prior research discusses the application of self-service technologies, there is a lack of studies investigating the factors influencing the attitudes and intentions toward AI chatbots among aviation sector consumers. Furthermore, the majority of studies examining intention and attitude rely solely on technology acceptance models, often overlooking the potential of advanced machine learning algorithms for deeper analysis and predictive accuracy. Accordingly, the present study strives to analyze the intention and attitude toward the use of AI chatbots through machine learning algorithms. For this purpose, three hundred and seventeen respondents provided self-reported data that was analyzed using machine learning algorithms, after cleaning the data the final total number has been decreased to 298 which we have used to train our models. The results showed that both perceived ease of use and perceived usefulness significantly influenced one’s attitude and intention to use AI chatbots. These findings pave the way for future research on exploring the application of machine learning algorithms for a more precise analysis of attitude and intention.