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Chatbots in Airport Customer Service—Exploring Use Cases and Technology Acceptance

Author

Listed:
  • Isabel Auer

    (Department Management, Communication & IT, MCI|The Entrepreneurial School, Universitätsstrasse 15, 6020 Innsbruck, Austria)

  • Stephan Schlögl

    (Department Management, Communication & IT, MCI|The Entrepreneurial School, Universitätsstrasse 15, 6020 Innsbruck, Austria)

  • Gundula Glowka

    (Department Management, Communication & IT, MCI|The Entrepreneurial School, Universitätsstrasse 15, 6020 Innsbruck, Austria)

Abstract

Throughout the last decade, chatbots have gained widespread adoption across various industries, including healthcare, education, business, e-commerce, and entertainment. These types of artificial, usually cloud-based, agents have also been used in airport customer service, although there has been limited research concerning travelers’ perspectives on this rather techno-centric approach to handling inquiries. Consequently, the goal of the presented study was to tackle this research gap and explore potential use cases for chatbots at airports, as well as investigate travelers’ acceptance of said technology. We employed an extended version of the Technology Acceptance Model considering Perceived Usefulness , Perceived Ease of Use , Trust , and Perceived Enjoyment as predictors of Behavioral Intention , with Affinity for Technology as a potential moderator. A total of n = 191 travelers completed our survey. The results show that Perceived Usefulness , Trust , Perceived Ease of Use , and Perceived Enjoyment positively correlate with the Behavioral Intention to use a chatbot for airport customer service inquiries, with Perceived Usefulness showing the highest impact. Travelers’ Affinity for Technology , on the other hand, does not seem to have any significant effect.

Suggested Citation

  • Isabel Auer & Stephan Schlögl & Gundula Glowka, 2024. "Chatbots in Airport Customer Service—Exploring Use Cases and Technology Acceptance," Future Internet, MDPI, vol. 16(5), pages 1-19, May.
    • Handle: RePEc:gam:jftint:v:16:y:2024:i:5:p:175-:d:1396905
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    References listed on IDEAS

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    1. Martin Adam & Michael Wessel & Alexander Benlian, 2021. "AI-based chatbots in customer service and their effects on user compliance," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 427-445, June.
    2. Fernandes, Teresa & Oliveira, Elisabete, 2021. "Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption," Journal of Business Research, Elsevier, vol. 122(C), pages 180-191.
    3. Astrid Dickinger & Mitra Arami & David Meyer, 2008. "The role of perceived enjoyment and social norm in the adoption of technology with network externalities," European Journal of Information Systems, Taylor & Francis Journals, vol. 17(1), pages 4-11, February.
    4. Sheehan, Ben & Jin, Hyun Seung & Gottlieb, Udo, 2020. "Customer service chatbots: Anthropomorphism and adoption," Journal of Business Research, Elsevier, vol. 115(C), pages 14-24.
    5. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
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