Chatbots for Travelers: Comparative User Experience Analysis of Air Travel Meta-search Engines


  • Fernando Travieso, Postdoctoral Researcher, Department of Interaction Science, Sungkyunkwan University, Republic of Korea


This paper investigates user experience (UX) from chatbots used for air travel fare aggregators such as Kayak, Hipmunk, and Skyscanner. These virtual stores are fare aggregators of airlines competing with dynamic offers in the industry of civil air transportation. Since its inception, the marketers of these digital companies have made an effort to increase the user experience and to allure users to buy online. This research aims to provide both theoretical and empirical analysis of the impact of chatbots on their user experience for buying flight tickets online. It examines the effect of incipient inclusion of AI chatbots in social media channels to entice online consumers.

By applying the unified theory of acceptance and use of technology (UTAUT), this research takes a technology acceptance perspective to comparatively analyze consumer behavior when users search for flights by means of a web search engine, a corporate website of an airline, and a travel AI chatbot on social media. In addition, formal measures including usability and user experiences are used to evaluate the persuasiveness and effect of each interface.

This study uses an experiment and pre-experiment and post experiment surveys. The data from a survey of online consumers are used to empirically test the proposed research model.

Confirmatory factor analysis (CFA) is performed to examine the reliability and validity of the measurement model, and the structural equation modeling (SEM) technique is used to evaluate the causal model. The implications of the research model for both developers and marketers are also discussed.

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