The term ‘metaverse’ has gained significant attention in recent years. For instance, the governments of South Korea and Dubai have invested millions in developing metaverse ecosystems (Piscione & Drean, 2023). Scholars also predict that the metaverse trend will continue to grow (Sami et al., 2024). However, user adoption has not progressed as quickly as expected. Metaverse adoption in educational settings, for example, remains low (Talan & Kalinkara, 2022), largely due to challenges related to technology, usability, cost, and privacy concerns (Al-Kfairy et al., 2024; Iwanaga et al., 2023).

As a result, there has been a growing body of research focused on understanding the drivers of metaverse adoption. Drivers are factors that encourage, facilitate, or support individuals in their adoption of technologies (Makransky & Mayer, 2022). Examples include perceived enjoyment and satisfaction (Makransky & Mayer, 2022), as well as user expectations of performance (Lee, Trimi, & Kim, 2013). Such research is crucial because it offers strategies to enhance the adoption of potentially transformative technologies and provides valuable insights into ensuring their sustained usage.

There are three research gaps in extant work on the drivers of metaverse adoption. First, existing studies predominantly focused on general users or university students (Alawadhi et al, 2023; Almarzouqi et al, 2022) with limited exploration of younger age groups. To date, only a few empirical studies specifically addressed adolescents’ perceptions of the metaverse: two studies examined the effectiveness of metaverse applications in educational settings (Makransky & Mayer, 2022; George Reyes, 2020), one proposed a prototype for a metaverse-based physical fitness service for youth (Lee et al, 2023), another investigated why teenagers remained engaged in social virtual reality (Maloney et al, 2021), and the final one reviewed the benefits and potential concerns among adolescents (Kim & Kim, 2023).

Second, most empirical research has been conducted in Europe (Makransky & Mayer, 2022), North America (George Reyes, 2020; Maloney et al, 2021), and Gulf-region countries (Alawadhi et al., 2023; Almarzouqi et al, 2022), with minimal representation from the Asian region. Given that cultural differences influence technology adoption (Sewandono et al., 2023), studying metaverse adoption in Asia could significantly enrich the existing literature. Notably, only one study was Asian-focused, examining metaverse acceptance among Korean university students (Lee & Kim, 2022). Third, existing research on children’s and youths’ adoption of the metaverse has been largely confined to educational settings, with few studies investigating usage outside of this context.

To address these gaps, the present study addresses two research questions: (1) what activities do children and youths engage in the metaverse? (2) what factors drive their adoption? To answer these questions, we employ the unified theory of acceptance and use of technology 2 (UTAUT2) as our theoretical framework (Venkatesh, Thong, & Xu, 2012). The UTAUT2 extends the original UTAUT model by incorporating three new factors - hedonic motivation, price value, and habit - thus enhancing its applicability to both organizational and non-organizational settings (Venkatesh, Thong & Xu, 2012; Blok et al., 2020).

Qualitative interviews were conducted with 20 children between 13 and 17 years old (represented by ‘C’ and a unique number in subsequent sections), and 20 youths between 18 and 24 years old (represented by ‘Y’ and a unique number) to understand their metaverse usage habits and perceived drivers of metaverse adoption. The interview method was chosen because it allows for an in-depth examination of participants’ experiences, considerations, and interpretations, thereby enhancing our understanding of metaverse use and perceptions (Lee, Kang, & Kim, 2023). Participants were recruited from the Asia-Pacific region including Singapore, India, and China.

Participants consisted of 19 females and 21 males, with 38 still in school, ranging from secondary school to university levels, and two who had just entered the workforce. Parental consent was obtained for participants under 21 years old, while those 21 and above provided their own consent. Recruitment was carried out using snowball sampling, starting with the researchers’ network, and expanding through voluntary referrals from participants at the end of each interview.

All interviews were conducted online via Zoom, each lasting approximately 45 minutes. The audio recordings were initially transcribed using Zoom’s caption function and then manually corrected by a researcher. The transcripts were analyzed through an iterative process to ensure internal consistency. A researcher and a trained student assistant jointly coded four transcripts (10% of the total) based on themes related to UTUAT2. During this process, disagreements were highlighted, discussed, and resolved. Subsequently, the remainder of the transcripts were equally divided between the two coders for analysis. The intercoder reliability achieved a 93% agreement. This approach aligns with existing content analysis practices (Stemler, 2000).

This study investigated the types of activities children and youths performed on metaverse platforms and the factors driving their adoption. Our findings revealed that the most frequently cited activities were entertainment, followed by socialization, education, and exploration. Using the UTAUT2 framework, we identified three major drivers for metaverse adoption: performance expectancy, social relations and social influence, and facilitating conditions. Effort expectancy, perceived value, and habit were mentioned less frequently by participants.

Given the dominance of gaming in metaverse usage, it was unsurprising that hedonic goals, namely, entertainment, socializing, and exploration were frequently cited reasons for engagement. Closer examination of participants’ responses indicated that these motivations were often interconnected. For instance, in multi-user metaverse games, participants reported playing them for enjoyment and staying in touch with their friends, highlighting the appeal of such games in fulfilling multiple gratifications simultaneously (Yu, 2024).

Consistent with the UTATU2 literature (Abbad, 2021; Sewandono et al., 2023), performance expectancy emerged as the primary driver for metaverse adoption. This may be attributed to the metaverse’s role as a technological tool for enhancing well-being and providing a social space for meeting and making friends. Social influence was also found to be a significant driver of adoption (Okumus et al., 2018), potentially due to younger users being more sensitive to peer influence (Ciranka & Van den Bos, 2019) and experiencing a ‘fear of losing out’ when others used the metaverse (Lee, Nguyen, & Yang, 2023). Moreover, in Asian countries where collectivistic cultures are predominant, people tend to rely on other likeminded individuals who have already adopted the innovation for their own decision making (Lee et al, 2013). Next, facilitating conditions, such as personnel and educational resources, were found to support metaverse adoption, aligning with recent studies that emphasized the importance of perceived support and resource accessibility in technology acceptance (Abbad, 2021; Patil et al, 2020).

It was interesting that effort expectancy, perceived value, and habit were the least mentioned drivers among participants. This suggests a lower emphasis on these factors compared to prior research (Yang et al, 2022). One possible explanation is that younger individuals are generally more open to new technology and are technologically savvy (Szymkowiak et al, 2021). To them, their focus is more on using new technology than about usability or value. Additionally, since many participants were school going, they likely did not have sufficient time to form habitual metaverse usage (Bayram, 2022). As well, examining habitual use of the metaverse may be more appropriate and productive during its growth or maturity stage. This is because with more people adopting a mature technology, there will likely be more opportunities to study habit formation and prolonged use (Tamilmani et al, 2019).

This study makes both theoretical and practical contributions. Theoretically, it extends the applicability of the UTAUT2 model to the metaverse context by adapting its factors to suit metaverse-specific use cases. It also enriches the metaverse adoption literature by including perspectives from children and youths in the Asia-Pacific region. Practically, the study suggests that metaverse companies focus on performance expectancy when developing platform functionality. Additionally, it recommends providing increased support personnel and training resources during the initial deployment of metaverse applications. This could be achieved through partnerships and collaborations between metaverse companies and educational institutions, for example, building an education-oriented metaverse ecosystem where teaching and learning occur virtually with interactive and shared open resources (Zhai et al., 2023). However, this study has limitations. The sample size was small, and the results may not be generalizable. Future research could address this issue by recruiting larger samples of participants and conducting quantitative surveys to validate the findings. Furthermore, as the study was conducted at a single point in time, future longitudinal research is needed to examine how perception of drivers evolves as children and youths mature in both age and metaverse experience.