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Understanding the Determinants of Adoption and Intention to Recommend AI Technology in Travel and Transportation

Author

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  • Gonçalo Baptista

    (Nova Information Management School, Universidade Nova de Lisboa, Campolide Campus, 1099-085 Lisbon, Portugal)

  • Antonio Pereira

    (Porto Business School (CPBS), Universidade Católica Porto, 4169-005 Porto, Portugal)

Abstract

The travel and transportation sectors continuously fight to stay up to date with new advancements in technology. Disruptive technologies, such as Artificial Intelligence (AI), are being used to develop businesses, enhance economic growth, revolutionize existing industries, create new opportunities, and increase productivity and efficiency. Notwithstanding the several advantages that this technology may bring, there is still little research on AI use in the travel and transportation sectors. This research contributes to this still understudied field to fill a gap in the literature by putting out a novel, thorough, and as far as we know not yet tested until now theoretical model, designed with the combination of the outcome of a literature meta-analysis study with Travel Experience and the Intention to Recommend technology constructs. A quantitative investigation using an online questionnaire was administered through social media and reached a total of 100 European participants. Structural equation modelling (SEM) was employed to test the suggested model empirically. The findings highlight that the user’s attitude towards AI is strongly influenced by Performance Expectancy and that the Intention to Use this technology is significantly influenced by Initial Trust and Attitude. Theoretical and practical contributions, limitations, and future areas of research are discussed.

Suggested Citation

  • Gonçalo Baptista & Antonio Pereira, 2025. "Understanding the Determinants of Adoption and Intention to Recommend AI Technology in Travel and Transportation," Tourism and Hospitality, MDPI, vol. 6(2), pages 1-23, March.
    • Handle: RePEc:gam:jtourh:v:6:y:2025:i:2:p:54-:d:1619938
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    References listed on IDEAS

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    4. Yu Wang & Shanyong Wang & Jing Wang & Jiuchang Wei & Chenglin Wang, 2020. "An empirical study of consumers’ intention to use ride-sharing services: using an extended technology acceptance model," Transportation, Springer, vol. 47(1), pages 397-415, February.
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