Exploring human-machine collaboration in metaverse communities: utilitarian vs. hedonic dimensions in enhancing user immersion
• Human-machine collaboration enhances user immersion in metaverse communities. • Product focus declines over time, while service focus increases among users. • Experienced users prioritize service aspects, while novices focus more on products. • Service focus positively correlates with user engagement and forum resonance. • Text mining and machine learning methods quantify metaverse user experience. This study explores the role of human–machine collaboration in shaping user immersion within metaverse communities, focusing on the shift between utilitarian and hedonic orientation. Using a large-scale dataset from Meta’s metaverse community forum, we employed text mining and machine learning techniques to quantify the utilitarian and hedonic dimensions within user disclosure. The findings identified specific areas under each dimension and revealed that both dimensions contribute meaningfully to immersion, but their emphasis varies across user experience levels and over time. Specifically, hedonic dimensions become more dominant among experienced users and over the product lifecycle, while utilitarian considerations are more salient for new users. Furthermore, the study identified a positive relationship between hedonic experiences and evoking resonance on the forum. The paper discusses the implications of understanding utilitarian and hedonic dimensions related to enhancing consumers’ immersion experience and optimising human–machine interactions.
Authors
- Chunjia Han (ORCID: https://orcid.org/0000-0002-8210-385X)
- Joseph Amankwah‐Amoah (ORCID: https://orcid.org/0000-0003-0383-5831)
- Brij B. Gupta (ORCID: https://orcid.org/0000-0003-4929-4698)
- Mu Yang (ORCID: https://orcid.org/0000-0001-9442-9243)
Institutions
- Asia University (TW)
- China Medical University (TW)
- Durham University (GB)
- Korea University (KR)
- Symbiosis International University (IN)
- Kyung Hee University (KR)
- China Medical University Hospital (TW)
- Birkbeck, University of London (GB)
Publication Details
- Journal
- Transportation Research Part E Logistics and Transportation Review
- Published
- 2025-09-27
- DOI
- https://doi.org/10.1016/j.tre.2025.104423
- Citations
- 1
- Primary Topic
- Digital Marketing and Social Media
- Type
- article
- Field-Weighted Citation Impact
- 4.20