Skip to main content
SpringerLink
Log in

Digital Frontiers: Gen-Z’s Adventure Tourism in the Metaverse

  • Conference paper
  • First Online:
Proceedings of World Conference on Information Systems for Business Management (ISBM 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 834))

Included in the following conference series:

Abstract

Revolutionizing the digital landscape, metaverse technology creates immersive virtual environments that captivate users’ senses and redefine their experiences. This study investigates the adoption of metaverse adventure tours among Gen-Z. Primary data has been collected through surveys from a sample of 465 Gen-Z participants. The findings suggest that Gen-Z finds metaverse adventure tours easy to use, thanks to user-friendly interfaces and intuitive controls. Their adoption is primarily driven by hedonic motivation, seeking unique and thrilling experiences. However, factors such as social influence, facilitating conditions, habit, trust, and personal innovativeness, have limited influence on their decision to engage in metaverse adventure tours. Study has theoretical as well as practical implications. The study highlights the importance of designing immersive, user-friendly metaverse platforms that emphasize hedonic experiences and foster social interactions. Future research directions include exploring other demographic groups, investigating sustainability aspects, cross-cultural influences, and integrating physical and virtual adventure tourism experiences.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Hanji S, Hanji S (2023) Towards performance overview of mini batch K-means and K-means: case of four-wheeler market segmentation. In: Senjyu T, So-In C, Joshi A (eds) Smart trends in computing and communications. SMART 2023. Lecture notes in networks and systems, vol 645. Springer, Singapore. https://doi.org/10.1007/978-981-99-0769-4_70

  2. Kodabagi MM, Hanji SS, Hanji SV (2014) Application of enhanced clustering technique using similarity measure for market segmentation. Comput Sci Inf Technol 15

    Google Scholar 

  3. Petit O, Velasco C, Spence C (2019) Digital sensory marketing: integrating new technologies into multisensory online experience. J Interact Mark 45:42–61

    Article  Google Scholar 

  4. Dwivedi YK, Hughes L, Baabdullah AM, Ribeiro Navarrete S, Giannakis M, Al-Debei MM, Wamba SF (2022) Metaverse beyond the hype: multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int J Inf Manag 66:102542

    Article  Google Scholar 

  5. Ball M (2022) The metaverse: and how it will revolutionize everything. Liveright Publishing

    Google Scholar 

  6. Gupta OJ, Yadav S, Srivastava MK, Darda P, Mishra V (2023) Understanding the intention to use metaverse in healthcare utilizing a mix method approach. Int J Healthcare Manag 1–12

    Google Scholar 

  7. Sowmya G, Chakraborty D, Polisetty A, Khorana S, Buhalis D (2023) Use of metaverse in socializing: application of the big five personality traits framework. Psychol Mark

    Google Scholar 

  8. Almarzouqi A, Aburayya A, Salloum SA (2022) Prediction of user’s intention to use metaverse system in medical education: a hybrid SEM-ML learning approach. IEEE Access 10:43421–43434

    Article  Google Scholar 

  9. Yang F, Ren L, Gu C (2022) A study of college students’ intention to use metaverse technology for basketball learning based on UTAUT2. Heliyon 8(9)

    Google Scholar 

  10. McKinsey & Company (2022) Value creation in the metaverse. https://www.mckinsey.com/business-functions/growth-marketing-and-sales/our-insights/value-creation-in-the-metaverse

  11. Buhalis D, Lin MS, Leung D (2023) Metaverse as a driver for customer experience and value co-creation: implications for hospitality and tourism management and marketing. Int J Contemp Hospitality Manag 35

    Google Scholar 

  12. Buhalis D (2020) Technology in tourism-from information communication technologies to eTourism and smart tourism towards ambient intelligence tourism: a perspective article. Tour Rev 75(1):267–272

    Article  Google Scholar 

  13. Yovcheva Z, Buhalis D, Gatzidis C, van Elzakker CPJM (2014) Empirical evaluation of smartphone augmented reality browsers in an urban tourism destination context. Int J Mobile Human Comput Interac 6(2):10–31

    Article  Google Scholar 

  14. Buckley R (2006) Adventure tourism. Cabi

    Google Scholar 

  15. Janowski I, Gardiner S, Kwek A (2021) Dimensions of adventure tourism. Tour Manag Perspect 37:100776

    Google Scholar 

  16. Weber K (2001) Outdoor adventure tourism: a review of research approaches. Ann Tour Res 28(2):360–377

    Article  Google Scholar 

  17. Wirtz J, Zeithaml V (2018) Cost-effective service excellence. J Acad Mark Sci 46(1):59–80

    Article  Google Scholar 

  18. Dwivedi YK, Hughes L, Wang Y, Alalwan AA, Ahn SJ, Balakrishnan J et al (2023) Metaverse marketing: how the metaverse will shape the future of consumer research and practice. Psychol Market 40(4):750–776

    Google Scholar 

  19. Buhalis D, Volchek K (2021) Bridging marketing theory and big data analytics: the taxonomy of marketing attribution. Int J Inf Manag 56:102253

    Article  Google Scholar 

  20. Venkatesh V, Thong JYL, Xu X (2012) Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q 36(1):157–178

    Google Scholar 

  21. Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Q 425–478

    Google Scholar 

  22. Trapero H, Ilao J, Lacaza R (2020) An integrated theory for chatbot use in air travel: questionnaire development and validation. In: 2020 IEEE region 10 conference (TENCON), Nov 2020. IEEE, pp 652–657

    Google Scholar 

  23. Hanji SV, Navalgund N, Ingalagi S, Desai S, Hanji SS (2023) Adoption of AI chatbots in travel and tourism services. In: Yang X-S et al (eds) Proceedings of eighth international congress on information and communication technology, ICICT 2023. Lecture notes in networks and systems, vol 696. Springer, Singapore. https://doi.org/10.1007/978-981-99-3236-8_57

  24. Alalwan AA, Dwivedi YK, Rana NP (2017) Factors influencing adoption of mobile banking by Jordanian bank customers: extending UTAUT2 with trust. Int J Inf Manag 37(3):99–110

    Article  Google Scholar 

  25. Gupta A, Dogra N, George B (2018) What determines tourist adoption of smartphone apps? An analysis based on the UTAUT-2 framework. J Hosp Tour Technol 9(1):50–64

    Google Scholar 

  26. Hanji SV, Hungund S, Blagov E, Desai S, Hanji SS (2023) Examining the factors influencing diffusion and adoption of AI chatbots in tourism and travel industry. In: International working conference on transfer and diffusion of IT. Springer Nature Switzerland, Cham, pp 150–160

    Google Scholar 

  27. Pitardi V, Marriott HR (2021) Alexa, she’s not human but… Unveiling the drivers of consumers’ trust in voice-based artificial intelligence. Psychol Mark 38(4):626–642

    Article  Google Scholar 

  28. de Blanes Sebastián MG, Guede JRS, Antonovica A (2022) Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants. Front Psychol

    Google Scholar 

  29. Hanji SV, Hungund S, Hanji SS, Desai S, Tapashetti RB (2023) Augmented reality immersion in cultural heritage sites: analyzing adoption intentions. In: International working conference on transfer and diffusion of IT. Springer Nature Switzerland, Cham, pp 81–91

    Google Scholar 

  30. Chandra S, Srivastava SC, Theng YL (2010) Evaluating the role of trust in consumer adoption of mobile payment systems: an empirical analysis. Commun Assoc Inf Syst 27(1):561–588

    Google Scholar 

  31. Agarwal R, Prasad J (1998) A conceptual and operational definition of personal innovativeness in the domain of information technology. Inf Syst Res 9:204–215. https://doi.org/10.1287/isre.9.2.204

    Article  Google Scholar 

  32. Thakur R, Srivastava M (2014) Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Res 24. https://doi.org/10.1108/IntR-12-2012-0244

  33. Limayem M, Hirt SG, Cheung CM (2007) How habit limits the predictive power of intention: the case of information systems continuance. MIS Q 705–737

    Google Scholar 

  34. Nunnally JC (1978) An overview of psychological measurement. In: Clinical diagnosis of mental disorders, pp 97–146

    Google Scholar 

  35. Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50

    Article  Google Scholar 

  36. Navalgund NR, Hanji S, Mahantshetti S, Nulkar G, Kadadevar Math RS, Aranganathan P (2023) Family business in futuristic times: marketing focus in family run restaurants in post covid times. J Mines Met & Fuels 71(2)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. KLE Technological University, Dr. MSSCET, Belagavi, Karnataka, India

    Sanjay Hanji & Savita S. Hanji

  2. KLS Institute of Management Education and Research, Belagavi, Karnataka, India

    Sumanth Desai

  3. KLE Technological University, Hubli, Karnataka, India

    Nagaraj Navalgund

  4. Basaveshwar Engineering College, Bagalkot, Karnataka, India

    Rajeshwari B. Tapashetti

Authors
  1. Sanjay Hanji
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sumanth Desai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Savita S. Hanji
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nagaraj Navalgund
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rajeshwari B. Tapashetti
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sanjay Hanji .

Editor information

Editors and Affiliations

  1. University of Cantabria, Santander, Spain

    Andres Iglesias

  2. University of Aizu, Fukushima, Japan

    Jungpil Shin

  3. Knowledge Chamber of Commerce and Industry, Ahmedabad, Gujarat, India

    Bharat Patel

  4. Global Knowledge Research Foundation, Ahmedabad, Gujarat, India

    Amit Joshi

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Hanji, S., Desai, S., Hanji, S.S., Navalgund, N., Tapashetti, R.B. (2024). Digital Frontiers: Gen-Z’s Adventure Tourism in the Metaverse. In: Iglesias, A., Shin, J., Patel, B., Joshi, A. (eds) Proceedings of World Conference on Information Systems for Business Management. ISBM 2023. Lecture Notes in Networks and Systems, vol 834. Springer, Singapore. https://doi.org/10.1007/978-981-99-8349-0_38

Download citation

Publish with us

Policies and ethics

Search

Navigation