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Tourists’ Willingness to Adopt AI in Hospitality—Assumption of Sustainability in Developing Countries

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Listed:
  • Tamara Gajić

    (Geographical Institute “Jovan Cvijić”, Serbian Academy of Sciences and Arts, 11000 Belgrade, Serbia
    Faculty of Hotel Management and Tourism, University of Kragujevac, 36210 Vrnjačka Banja, Serbia)

  • Alireza Ranjbaran

    (Faculty of Management, University of Tehran, Tehran 1411713114, Iran)

  • Dragan Vukolić

    (Faculty of Hotel Management and Tourism, University of Kragujevac, 36210 Vrnjačka Banja, Serbia
    Faculty of Tourism and Hotel Management, University of Business Studies, 78000 Banja Luka, Bosnia and Herzegovina)

  • Jovan Bugarčić

    (Faculty of Hotel Management and Tourism, University of Kragujevac, 36210 Vrnjačka Banja, Serbia)

  • Ana Spasojević

    (Faculty of Economics, University of Kragujevac, 34000 Kragujevac, Serbia)

  • Jelena Đorđević Boljanović

    (Faculty of Organizational Studies EDUKA, University Business Academy, 11000 Belgrade, Serbia)

  • Duško Vujačić

    (Faculty of Tourism and Hospitality, University of Montenegro, 85330 Kotor, Montenegro)

  • Marija Mandarić

    (Faculty of Hotel Management and Tourism, University of Kragujevac, 36210 Vrnjačka Banja, Serbia)

  • Marija Kostić

    (Faculty of Hotel Management and Tourism, University of Kragujevac, 36210 Vrnjačka Banja, Serbia)

  • Dejan Sekulić

    (Faculty of Hotel Management and Tourism, University of Kragujevac, 36210 Vrnjačka Banja, Serbia)

  • Marina Bugarčić

    (Faculty of Civil Engineering, University Union—Nikola Tesla, 11000 Belgrade, Serbia)

  • Bojana D. Drašković

    (Faculty of Civil Engineering, University Union—Nikola Tesla, 11000 Belgrade, Serbia)

  • Sandra R. Rakić

    (Faculty of Entrepreneurial Business and Real Estate Management, University Union—Nikola Tesla, 11000 Belgrade, Serbia)

Abstract

This study explores the impact of artificial intelligence (AI) on customer perceptions and behavior in restaurants, airline companies, and hotel sectors within the hospitality industry of Iran. The primary objective is to analyze how AI affects customer trust, brand engagement, electronic word-of-mouth (eWOM), and tourists’ readiness to use AI technologies. Using a comparative analysis approach and surveys, this research tests hypotheses about the effects of artificial intelligence on various dimensions of customer interaction. The findings highlight significant relationships between the quality of artificial intelligence and customer engagement metrics, such as trust and brand loyalty, which are crucial for understanding and predicting customer behavior in response to technological advancements. This study lays the groundwork for theoretical assumptions about sustainability in these sectors in developing countries, providing a basis for future empirical research that could validate these assumptions and explore broader implications of AI integration in enhancing sustainable practices within the hospitality industry.

Suggested Citation

  • Tamara Gajić & Alireza Ranjbaran & Dragan Vukolić & Jovan Bugarčić & Ana Spasojević & Jelena Đorđević Boljanović & Duško Vujačić & Marija Mandarić & Marija Kostić & Dejan Sekulić & Marina Bugarčić & B, 2024. "Tourists’ Willingness to Adopt AI in Hospitality—Assumption of Sustainability in Developing Countries," Sustainability, MDPI, vol. 16(9), pages 1-25, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:9:p:3663-:d:1384003
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    References listed on IDEAS

    as
    1. Kichan Nam & Christopher S. Dutt & Prakash Chathoth & Abdelkader Daghfous & M. Sajid Khan, 2021. "The adoption of artificial intelligence and robotics in the hotel industry: prospects and challenges," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 553-574, September.
    2. Hadigheh Morabi Jouybari & Amir Ghorbani & Hossein Mousazadeh & Azadeh Golafshan & Farahnaz Akbarzadeh Almani & Dávid Lóránt Dénes & Ritter Krisztián, 2023. "Smartphones as a Platform for Tourism Management Dynamics during Pandemics: A Case Study of the Shiraz Metropolis, Iran," Sustainability, MDPI, vol. 15(5), pages 1-17, February.
    3. Xiaoyuan Wu & Shiva Hashemi & Yiyue Yao & Shaian Kiumarsi & Danping Liu & Jinquan Tang, 2023. "How Do Tourism Stakeholders Support Sustainable Tourism Development: The Case of Iran," Sustainability, MDPI, vol. 15(9), pages 1-19, May.
    4. Jang, SooCheong (Shawn) & Namkung, Young, 2009. "Perceived quality, emotions, and behavioral intentions: Application of an extended Mehrabian-Russell model to restaurants," Journal of Business Research, Elsevier, vol. 62(4), pages 451-460, April.
    5. Jinde Jiang, 2022. "The role of natural soundscape in nature-based tourism experience: an extension of the stimulus–organism–response model," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(5), pages 707-726, March.
    6. Zhong, Lina & Verma, Rohit & Wei, Wenqi & Morrsion, Alastair M. & Yang, Liyu, 2022. "Multi-stakeholder perspectives on the impacts of service robots in urban hotel rooms," Technology in Society, Elsevier, vol. 68(C).
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