Hospitality and tourism experience in metaverse: an examination of users’ behavior, motivations, and preferences

ABSTRACT

The rise of the metaverse presents an outlook for revitalizing the hospitality and tourism industry and garnering recognition across professional spheres. This study explores the motivations and preferences of users engaging in hospitality and tourism using 5W1H analysis, which stands for five Ws (what, who, when, where, and why) and one H (how). This comprehensive examination sheds light on the evolution and potential advantages of hospitality and tourism and offers insights for future progress. The study reveals that users are primarily driven by their anticipated experiences when participating in hospitality and tourism. Additionally, time- and cost-saving benefits, along with opportunities to discover destinations, play an important role in attracting hospitality and tourism users. Compared to traditional metaverse hospitality and tourism, metaverse hospitality and tourism offer greater flexibility in terms of timing, location, and companionship. However, the two are not in opposition; they complement each other and can develop together.

摘要

元宇宙的兴起为振兴酒店业和旅游业以及获得专业领域的认可提供了前景. 本研究使用5W1H分析探讨了用户从事酒店和旅游业的动机和偏好,5W1H代表五个W(什么、谁、何时、何地和为什么)和一个H (如何). 这项全面的研究揭示了酒店业和旅游业的演变和潜在优势, 并为未来的发展提供了见解. 研究表明, 用户在参与酒店和旅游时, 主要受其预期体验的驱动. 此外, 节省时间和成本的好处, 以及发现目的地的机会, 在吸引酒店和旅游用户方面发挥着重要作用. 与传统的元宇宙酒店和旅游相比, 元宇宙酒店与旅游在时间、地点和陪伴方面提供了更大的灵活性. 然而, 这两者并不对立 ; 它们相辅相成, 可以共同发展.

KEYWORDS:

• Metaverse
• metaverse tourism
• 5W1H
• exploratory study
• digital technology

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Informed consent

All participants gave their informed consent for inclusion before participating in the study.

Additional information

Funding

This work was supported by Institute of Information and communications Technology Planning and Evaluation (IITP) grant funded by the Korean Government (MSIT) (No.2020–0-01373, Artificial Intelligence Graduate School Program (Hanyang University)) and the research fund of Hanyang University (HY-202100000670057).