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Predicting the intentions to use chatbots for travel and tourism

Author

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  • Santiago Melián-González
  • Desiderio Gutiérrez-Taño
  • Jacques Bulchand-Gidumal

Abstract

As with other businesses, tourist companies are taking advantage of modern technologies. Chatbots are a recent technology that hotels, travel agencies, and airline companies are adopting. Despite this industry-wide implementation, there is no evidence about the factors that explain why consumers are willing to interact with chatbots. This work proposes a model to explain chatbot usage intention. The model and its hypotheses were tested by structural equations with the PLS technique. The study was conducted on a sample of 476 individuals who had travelled on vacation in the previous 12 months. The study reveals that the intentions behind using chatbots are directly influenced by the following factors: the chatbots’ expected performance, the habit of using chatbots, the hedonic component in using them, the predisposition to using self-service technologies, the social influences, and the fact that the chatbot behaves like a human. The inconvenience and problems related to communicating with the chatbot were found to have a negative influence. Lastly, the possibility that chatbots could replace jobs had a surprisingly positive influence, and not a negative one.

Suggested Citation

  • Santiago Melián-González & Desiderio Gutiérrez-Taño & Jacques Bulchand-Gidumal, 2021. "Predicting the intentions to use chatbots for travel and tourism," Current Issues in Tourism, Taylor & Francis Journals, vol. 24(2), pages 192-210, January.
    • Handle: RePEc:taf:rcitxx:v:24:y:2021:i:2:p:192-210
    DOI: 10.1080/13683500.2019.1706457
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    Citations

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    Cited by:

    1. Taoufiq Dadouch & Bouchra Bennani & Malika Haoucha, 2023. "Consumer Acceptance of Mobile Shopping Apps, From Basic Apps to AI-Conversational Apps: A Literature Review," Post-Print hal-04194657, HAL.
    2. Singh, Pratibha & Sharma, Mahak & Daim, Tugrul, 2024. "Envisaging AR travel revolution for visiting heritage sites: A mixed-method approach," Technology in Society, Elsevier, vol. 76(C).
    3. Jan, Ihsan Ullah & Ji, Seonggoo & Kim, Changju, 2023. "What (de) motivates customers to use AI-powered conversational agents for shopping? The extended behavioral reasoning perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    4. Mariani, Marcello M. & Hashemi, Novin & Wirtz, Jochen, 2023. "Artificial intelligence empowered conversational agents: A systematic literature review and research agenda," Journal of Business Research, Elsevier, vol. 161(C).
    5. Ma, Xiaoyue & Huo, Yudi, 2023. "Are users willing to embrace ChatGPT? Exploring the factors on the acceptance of chatbots from the perspective of AIDUA framework," Technology in Society, Elsevier, vol. 75(C).
    6. Kamoonpuri, Sana Zehra & Sengar, Anita, 2023. "Hi, May AI help you? An analysis of the barriers impeding the implementation and use of artificial intelligence-enabled virtual assistants in retail," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    7. Mengjun Li & Ayoung Suh, 2022. "Anthropomorphism in AI-enabled technology: A literature review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2245-2275, December.
    8. Li, Tian-Ge & Zhang, Chu-Bing & Chang, Ying & Zheng, Wei, 2024. "The impact of AI identity disclosure on consumer unethical behavior: A social judgment perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    9. Mark Anthony Camilleri & Ciro Troise, 2023. "Live support by chatbots with artificial intelligence: A future research agenda," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 61-80, March.

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