1 Introduction

The advent of technologies such as Artificial Intelligence (AI), big data, cloud computing, and wireless connection has contributed to creating a ubiquitous society. Against this backdrop, the internet-based virtual environment has become a vital part of human life (Guitton 2019). New technologies that are intended to merge the real and virtual worlds (Kang 2016) are emerging, with ubiquitous portable devices, such as virtual equipment, having altered human life and been widely adopted (Agarwal and Lucas 2005).

The metaverse industry has a huge potential for growth. According to Emergen Research (2022), the total revenue of the metaverse market would reach USD 1,607.12 billion in 2030, with a revenue compound annual growth rate of 43.3%. Numerous organizations consider the metaverse as the next generation of digital transformation (Gökhan, 2021). Besides, the metaverse has been defined as a 3D virtual world that could break physical boundaries; it allows users to communicate and interact with each other in the form of virtual characters (Davis et al. 2009; Siyaev and Jo 2021). Furthermore, the metaverse is an upgraded version of the Massively Multiplayer Online Role-Playing Game (MMORPG).

The metaverse harnesses plenty of technologies and it has received attention since 2021. However, there has been limited academic literature on the metaverse. To address this literature gap, the present study applied the self-efficacy theory and Theory of Reasoned Action (TRA) to investigate metaverse users’ attitudes toward participating in this virtual world. Based on the results of a literature review, this study identified several basic concepts of the metaverse: Avatars, Immersive Experience, and Decentralized Value Exchange. Moreover, through a review of factors affecting the users’ willingness to use VR and MMORPG, the users’ attitudes toward metaverse participation were classified into Presence in Second-Life, 3D Interactivity, and Play-to-Earn.

Although the metaverse is a futuristic technology, it is not entirely ubiquitous or well-known yet. This study performed purposive and snowball sampling on the Internet to collect a small number of questionnaire responses and investigate users’ attitudes toward participating in the metaverse. The findings may inform the understanding of what may affect users’ willingness to participate in the metaverse, fill the literature gap, and facilitate the access of businesses to the metaverse market.

2 Background

The concept of the metaverse has been extensively discussed in the literature. Lee et al. (2011) proposed that the term “metaverse,” which consists of “meta” and “universe, represents a three-dimensional (3D) virtual world within real space. Nonetheless, it was not until the advent and gradual maturation of blockchain technology that many companies began to establish 3D virtual worlds, offering unique user experiences. For instance, Disney has created virtual spaces where users can engage in role interaction through Virtual Reality (VR), Augmented Reality (AR), and digital avatars (Chmielewski 2021). Social media giant Facebook has recently rebranded itself as “Meta Platforms, Inc.” Nvidia, a leader in visual computing technology, has launched the Omniverse, a platform for building and operating metaverse apps. Nevertheless, the metaverse remains under-explored in the academic literature, and it is still an unprecedented and remarkable concept (Park & Kim 2022a).

One concept of the metaverse—the immersive experience —has been applied in various domains, including avatars (Davis et al. 2009), VR (Yang and Han 2020), AR (Gómez-García et al. 2018), cryptocurrency (Pernice and Scott 2021), the MMORPG, blockchain, and Non-Fungible Token (NFT) decentralized value exchange. Previously, user data was managed separately across different platforms, with platform owners exercising control over their share of the data. However, in the metaverse, users can create, maintain, and manage their own virtual identities. They can seamlessly transition between the real and virtual worlds, engage with others, and construct alternative lives through virtual avatars. Moreover, within the virtual economic environment, transactions are facilitated through cryptocurrencies to exchange assets among users—a departure from conventional modes of value exchange (Newbery 2021).

Much of the previous research has discussed the acceptance of different technologies (Allcoat et al. 2021; Fussell and Truong 2021; Han et al. 2020; Jung et al. 2014; Lau and Lee 2018). The Technology Acceptance Model (TAM) has been extensively employed to examine users’ acceptance of novel technologies. Technologies such as VR and the MMORPG have found growing use in domains including education, medicine, and entertainment (Ng et al. 2021; Yang and Han 2020). Moreover, enjoyment (Han et al. 2020; Syed-Abdul et al. 2019), presence (Jang and Park 2019; Huang et al. 2021), and interactivity (Huang et al. 2021; Kim et al. 2021) are recognized as crucial factors affecting the acceptance of emerging technologies.

Through participation in the online world, people can shift from reality to virtuality, and their sensory experience becomes immersive. This immersive experience is a state of complete involvement in a virtual world that parallels and partially emerges with the real world. In the metaverse, users can use digital characters called “Avatars” to interact with each other and the virtual world. They can also create content and construct virtual lands and streets. Virtual assets in the metaverse, such as land, artworks, and images, can be registered and traded using NFTs. Decentralized virtual currencies can be exchanged without having to deal with the limitations of a physical bank. Therefore, for the metaverse to achieve its objectives, it may require an integration of hardware, software, and design.

3 Literature review

3.1 Metaverse

The concept of the metaverse has been discussed in recent years. The metaverse provides a sensory experience represented by users’ immersive participation through their virtual characters. Users can participate in a variety of metaverse activities and exchange their assets by immersing in virtual reality uninterruptedly. The words “Metaverse” and “Avatars” first appeared in the science fiction novel “Snow Crash,” written by Neal Stephenson in 1992; the work describes how humans can interact and communicate with each other in a 3D environment (Duan et al. 2021). The metaverse has undergone developments in many aspects over the past 30 years, and with the growing maturity of AR, VR, and Mixed Reality (MR) technologies, digital virtual worlds have seen growing demand.

However, the concept, definition, and classification of the metaverse are under-explored in the literature. Smart et al. (2007) first proposed a definition of the metaverse. They suggested four standards for metaverse classification that are organized into a two-dimensional coordinate plane: AR, life logging, mirror world, and virtual world (Park & Kim 2022b; Smart et al. 2007). Dionisio et al. (2013) indicated that the transfer of a virtual world to a 3D virtual world depends on immersive realism, the ubiquity of access and identity, interoperability, and scalability. The concepts above have become the dominant feature of the metaverse. Some studies have discussed the practical application of the metaverse. For example, Siyaev and Jo (2021) demonstrated MR-based education in aircraft maintenance to provide a near-real maintenance experience. Choi and Kim (2017) presented a content service for museum exhibitions that was enabled by a Head-Mounted Display (HMD), enhanced with a storytelling feature, and made through a combination of AR and a virtual world.

The metaverse is enormous in that it uses various technologies to obtain content that is hard to access. Moreover, the metaverse has many uses, which include gaming, online shopping, content creation, social media, conferencing, and virtual performance (Emergen Research 2022). For instance, Ariana Grande, a famous American female singer, held a virtual concert on a virtual game platform that attracted 78 million participants (EPIC Games 2021). Roblox is an online game platform dedicated to building a virtual world comparable to the real world. Roblox is also known as “a first stock of the metaverse” (Schwab 2021). The entertainment empire Disney has announced the establishment of a powerful 3D virtual space where users can access different story scenes through VR, AR, and digital twins, thereby interacting with story characters (Chmielewski 2021). Nvidia, a leader in visual computing, has introduced the Omniverse platform, which integrates several innovative technologies. During the Computer Graphics Conference SIGGRAPH 2021, Nvidia’s CEO Jensen Huang utilized software rendering to create highly realistic virtual environments (Marko 2021).

Based on what was described above, this study defined the metaverse as a combination of various MR technologies that immerse users in a virtual world and enable value exchange through avatars. Within the 3D virtual realm of the metaverse, users can manifest their desired lifestyles by self-representing themselves through digital avatars, thus facilitating their exploration of an alternative existence in a parallel space-time. Users’ activities and personal information are continuously logged and stored within the metaverse. This affords users exclusive control over their digital avatars, giving them unrestricted access to the immersive metaverse while simultaneously taking advantage of the decentralized value exchange (which is intended for digital asset transactions). Furthermore, considering the aforementioned uses and definitions regarding the metaverse, this study categorized the basic concepts of the metaverse into three main aspects: Avatars, Decentralized Value Exchange, and Immersive Experience. The study aimed to examine the role of these concepts in individuals’ willingness to participate in the metaverse.

3.2 Theories of technology adoption

The theories of technology adoption encompass a range of frameworks and models that aim to elucidate the process through which individuals, organizations, or societies embrace and incorporate new technologies (Salahshour Rad et al. 2017). These theories offer a systematic understanding of the factors that shape technology adoption behaviors and shed light on the subsequent effects of technology adoption. Prominent theories in this field include the Diffusion of Innovation (DOI), Technology Acceptance Model (TAM), Theory of Reasoned Action (TRA), Task-Technology Fit (TTF) model, and Unified Theory of Acceptance and Use of Technology (UTAUT), and others (Xu and Lu 2022). These theories provide valuable insights into the motivations, attitudes, and contextual factors that drive the acceptance and utilization of technology in various settings.

The DOI theory describes the process by which new technologies spread and are adopted within a social system (Xu and Lu 2022). It emphasizes different adopter categories, as well as their varying rates and styles of technology acceptance. Another widely used theory in the field is the TAM (Al-Adwan et al. 2023), which focuses on individual users’ acceptance of new technology. It identifies the perceived usefulness and perceived ease of use as key factors influencing technology adoption (Davis 1989). The TRA provides a framework for explaining human behavior, positing that attitudes and subjective norms influence behavioral intentions, which in turn predict behavior (Taherdoost 2022). The TTF model emphasizes the alignment between task requirements and technological characteristics as a determinant of technology adoption. This model presumes that when there is a high degree of fit between task demands and technological features, individuals are more likely to accept and use the technology (Xu and Lu 2022). The Technology–Organization–Environment (TOE) framework, proposed by Tornatzky et al. (1990), is used to explain the background factors and implementation process that influence the decision-making on technology innovation adoption within organizations, and this decision-making process encompasses three characteristics: environment, organization, and technology (Salahshour Rad et al. 2017; Tornatzky et al. 1990). When there is a strong alignment and fit among these characteristics, new technologies are more likely to be adopted and implemented (Xu and Lu 2022). The UTAUT is an integrative model that combines perspectives from multiple technology adoption theories and explores the factors underlying individuals’ acceptance of new technologies (Ustun et al. 2022).

Technology adoption theories and the Expectation-Confirmation Model (ECM) have been widely utilized to investigate and elucidate users’ acceptance of and usage behaviors toward technology. In particular, the ECM is used to acquire in-depth insights into users’ levels of acceptance of and satisfaction with technology, serving as a prominent theoretical framework for elucidating technology acceptance (Brown et al. 2014). This model explicates the impact of users’ pre-usage expectations and post-usage confirmation on their satisfaction with the technology they use and their intention to maintain usage (Bhattacherjee 2001). In the context of technology adoption, numerous studies have harnessed the ECM and the self-efficacy theory to elucidate and explore salient factors that influence users’ intention to sustain technology usage (Ifinedo 2018; Li 2021; Malik and Rao 2019). The self-efficacy theory examines the impact of individuals’ confidence and competence in successfully utilizing a new technology on their adoption behavior, underscoring the significance of the users’ self-evaluation and levels of confidence throughout their adoption of the technology (Bandura 1977).

In brief, while technology adoption theories focus on users’ adoption behavior towards new technology, self-efficacy can influence their expectations and subsequently affect their satisfaction with the technology and willingness to continue using the technology (Li 2021; Macakova and Wood 2020). Based on this rationale, the present study utilized the TRA and self-efficacy theory to investigate users’ willingness to engage with the metaverse, which incorporates a variety of technologies.

3.3 Self-efficacy theory

The self-efficacy theory, which consists of the Social Cognitive Theory (SCT) and Social Network Theory (SNT), is regarded as an essential theory that influences users’ acceptance of new technology (Lu and Lien 2019). It states that human behavior is influenced by the interaction between internal motivation and external environment, and the self-efficacy of personal cognition can significantly affect this process (Bandura 1977). Bandura (1977) describes self-efficacy as when an individual confronts a situation, they would act based on the outcome of the situation, determine whether they can cope with the situation, exhibit appropriate behavior, and decide whether their action will achieve a good result. This theory is a cognitive mechanism that controls an individual’s intrinsic motivation, thinking patterns, and behavior (Bandura 1994). Therefore, self-efficacy is generated through the interaction between an individual and the environment, and the individual acts according to the outcome. Self-efficacy can be improved effectively through encouragement, positive responses, positive emotions, and the successful experiences of others. Furthermore, people with high self-efficacy are generally more capable of evaluating their conditions and persistent in what they decide to do, and vice versa. This study argued that, as technology continues to advance, self-efficacy can be effectively improved through participation in the virtual environment (Song et al. 2021).

In previous research, many scholars have used the self-efficacy theory to examine the impact of users’ confidence and competence in adopting complex new technologies on their willingness to use them in diverse domains, including education and healthcare. Furthermore, the use of VR training systems has significantly increased in education and healthcare in recent years. Several studies have contended that self-efficacy and interactivity play crucial roles as predictors of learning outcomes in virtual learning environments. For instance, Mondellini et al. (2021) examined the impact of anxiety levels and self-efficacy when patients watch educational VR videos before chemotherapy. The authors reported a significant improvement in the patient’s self-efficacy after exposure to these videos. Song et al. (2021) employed HMDs with VR to enhance the learning abilities and self-efficacy of technical high school students. Xie et al. (2022) reported a strong correlation between computer self-efficacy, perceived immersion, and the intention to use VR training systems. All these studies highlight the importance of self-efficacy and interactivity in the context of VR training systems and their impact on users’ attitudes and behaviors.

Despite its extensive presence in the literature, the self-efficacy theory necessitates more research to be validated in different fields. It is still uncertain whether self-efficacy can influence the willingness to participate in the metaverse. Therefore, this study focused on the ability of users to utilize the basic concepts of the metaverse and examined their self-efficacy about metaverse-related technologies to establish correlations between this self-efficacy and the users’ preference for the metaverse. Self-efficacy about the metaverse was described in this study along three dimensions—Avatars, Decentralized Value Exchange, and Immersive Experience—to investigate users’ willingness to participate in the metaverse.

3.4 Virtual reality in the metaverse

As technology continues to evolve, VR has altered user experience and become a revolutionary technology (Yang and Han 2020). VR can be defined as a computer-generated simulation of a 3D environment that can be interacted with in a seemingly physical way through special electronic equipment (Han et al. 2020; Zhang et al. 2018). VR has been employed in different domains, such as games, medicine, retailing, social media, and tourism (Yang and Han 2020). Nevertheless, the low affordability of VR equipment limits their accessibility (Han et al. 2020; Zhang et al. 2018).

Since VR can provide users with diverse experiences and increase the willingness of users to participate in the metaverse, many market leaders have used VR devices and technology to attract customers, increase customer engagement, and create customer value. Han et al. (2020) stated that Alibaba, the largest online retailer in China, had planned to establish a department store by utilizing VR and providing consumers with the same experience at home as in the physical shopping center to improve customer engagement. Lee et al. (2020) noted that numerous large-scale museums (e.g., the British Museum and Vatican Museum) have adopted VR equipment to provide visitors with a spectacular and immersive experience to enhance their pleasure. In the field of education, Allcoat et al. (2021) observed that compared with traditional learning, students are more willing to engage in VR and MR experiences. Fussell and Truong (2021) also argued that if VR is easy to use, students are more likely to use it, and it will become suitable for education. VR is also increasingly utilized in medicine. Using VR to simulate surgical training can effectively increase surgical residents’ learning accomplishment and reduce the time spent on surgeries (Lohre et al. 2020). Long et al. (2020) reported that VR training can effectively increase stroke patients’ self-efficacy and improve their daily living.

In conclusion, VR technology is indispensable in the metaverse. It increases users’ virtual presence and provides a 3D stereoscopic environment for immersive interaction. The metaverse, a space established by VR and AR that utilizes 3D virtual experience to interact with others, has received growing attention (Siyaev and Jo 2021). The metaverse, which is combined with several new technologies, such as immersive experience, MMORPG, and cryptocurrency, provides users with various near-real experiences.

3.5 Massively multiplayer online role-playing game (MMORPG) in the metaverse

An MMORPG is a two-dimensional (2D) or 3D graphical game. Many users have created virtual game characters in an MMORPG, and such a game is considered the most attractive online game to date (Chen et al. 2020). In addition, the MMORPG lays down rules and provides feedback for users. It also allows users to interact with each other in the virtual environment and create an emotional social network through this interaction (Sourmelis et al. 2017). Most MMORPGs are characteristically online communities and game platforms, and they provide users with social circles (Chen et al. 2020).

More and more people play MMORPGs in their leisure time. Jung et al. (2014) proposed that there are several factors that influence consumers’ intention to use MMORPGs and their attitudes toward the games; these include product functions, technique functions, and user-oriented design. Wang and Wang (2008) used the self-efficacy theory to investigate the male and female users’ acceptance of MMORPGs and their intention to play the games. The authors concluded that self-efficacy plays a more significant role in men’s intention to play MMORPGs, whereas women show weaker intention to play the games because of their preconception about the complexity of the games. MMORPGs also have use in the education domain. It helps language learners to acquire vocabulary as well because the game storylines deepen immersion in the games, afford the freedom to learn without being subject to the rules imposed on the physical classroom, and enable social interaction and collaboration to enrich the learning experience (Ng et al. 2021).

Considered an upgraded version of the MMOPRG, the metaverse can provide entertainment and enable social interaction. Thus, the features of the metaverse (Play-to-earn, VR, and MMORPG) were analyzed to integrate the three dimensions of the metaverse (Presence in Second-Life, 3D Interactivity, and Play-to-earn) and thus determine the factors affecting users’ willingness to participate in the metaverse.

4 Research model and hypotheses

Numerous organizations have established virtual metaverse platforms (such as Roblox, Decentraland, and Opensea), which break physical boundaries and allow users to utilize their virtual characters to communicate with each other (Siyaev and Jo 2021). Users can project their ideal life into the metaverse using digital avatars and leading their second life in parallel space. The users can manipulate their digital characters; their activities and information are recorded continually. They can navigate freely with an immersive experience and exchange digital assets in a decentralized way.

Taking into account the actual application of the metaverse, this study described the basic concepts of the metaverse along three dimensions: Avatars, Immersive Experience, and Decentralized Value Exchange. Figure 1 depicts the research model of this study. The research model was built around the self-efficacy theory and the metaverse’s basic concepts to examine self-efficacy about the metaverse. Moreover, a review of the literature on VR and MMORPGs suggested that presence, enjoyment, and interactivity are vital factors affecting users’ willingness to use innovative technology. Hence, this study examined the effects of the three basic concepts of the metaverse—Avatars, Immersive Experience, and Decentralized Value Exchange—on metaverse users’ Presence in Second-Life, 3D Interactivity, and Play-to-Earn.

Fig. 1
figure 1

Illustration of the research model

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4.1 Self-efficacy in the metaverse

Bandura (1977) defined self-efficacy as the user’s ability to make decisions and act based on their self-assessment outcomes. Song et al. (2021) argued that the user’s self-ability in learning can improve in the virtual learning environment. The present study defined self-efficacy about the metaverse as the degree to which users perceive themselves as being capable of using the basic concepts of the metaverse—namely, Avatars, Immersive Experience, and Decentralized Value Exchange.

4.1.1 Avatars in the metaverse

Through the remarkable improvement of computing speed, the advent of the fifth-generation network, and the growing popularity of big data, the metaverse platforms have been developed in ways that allow users to create and manage their own digital twins without having to undergo third-party certification (Ofelia et al., 2017). Users can build a world of digital twins with virtual characters. For instance, Nvidia has utilized Omniverse to build a 3D model and rapidly code a scripting language. The real estate industry provides 3D and VR models for customers to preview houses; video game developers can build 3D simulation video games expeditiously that take into account real-world physics, such as the centrifugal force of a racing car. This study defined Avatars as users’ virtual characters in the metaverse. Meanwhile, self-efficacy about Avatars in the metaverse was defined as the degree to which users believe that they can use virtual characters to navigate the activities of metaverse platforms.

Presence in Second-Life is the subjective awareness that users have when they feel connected to the external world (Fussell and Truong 2021). It can be seen as a space where users obtain new information and activities by creating a virtual world (Smart et al. 2007). It has been widely used to describe users’ perceptual experience that utilizes a specific technique and services when the users switch from a physical environment to a virtual one (Huang et al. 2021; Jang and Park 2019). This study argued that users could repeatedly access a parallel space through their digital virtualized images and experience a wonderful second life in the metaverse. Hence, this study defined Presence in Second-Life as the user’s immersive engagement in reciprocal interactions with other users, devices, and objects within the metaverse using their avatars, which leads to the acquisition of a sense of identity and an enhanced sense of belonging. Thus, the following hypothesis was proposed:

H1a:

The user’s self-efficacy about Avatars in the metaverse positively affects their preference for Presence in Second-Life.

In the metaverse, users can navigate the environment by using their virtual characters. Users can enhance interaction in a virtual learning environment using the characters (Gámez Díaz et al. 2020). This study defined 3D interactivity as an opportunity for metaverse users to use avatars to engage in reciprocal interactions with each other, devices, and objects facilitated by immersive experiences and value exchange. Therefore, this study argued that the user’s ability to use digital virtual characters can influence their preference for communicating with others in the 3D environment, which is created by using VR and MR-related technologies in the metaverse. Therefore, the following hypothesis was proposed:

H1b:

The user’s self-efficacy about Avatars in the metaverse positively affects their preference for 3D Interactivity.

This study defines “Play-to-Earn” as a form of enjoyment experienced by users in the metaverse virtual world while actively participating in immersive experiences through their digital avatars and earning digital assets. Scholes et al. (2021) stated that students can enhance their enjoyment by utilizing digital virtual characters in games and increasing their willingness to learn independently. The present study argued that users navigating the metaverse using their virtual characters could both enhance their willingness to have entertainment and obtain digital assets. Hence, the following hypothesis was proposed:

H1c:

The user’s self-efficacy about Avatars in the metaverse positively affects their preference for Play-to-Earn.

4.1.2 Decentralized value exchange in the metaverse

Karim et al. (2021) noted that digital assets are inseparable from the metaverse, and decentralized digital assets, such as cryptocurrency and NFT, have become a basic metaverse concept. Therefore, the present study defined the Decentralized Value Exchange as when users utilize decentralized means to acquire new assets and exchange NFTs or digital values with others in the metaverse. In addition, the self-efficacy about the Decentralized Value Exchange in the metaverse was defined as the degree to which users believe they can utilize a decentralized method to exchange NFTs or digital values with each other in the metaverse. Jin et al. (2017) observed that users’ willingness to purchase virtual products is influenced by their perceived presence in virtual games. The present study argued that when users become more capable of exchanging products in a decentralized way, their preference in the virtual life in the metaverse will improve. Thus, the following hypothesis was proposed:

H2a:

The user’s self-efficacy about the Decentralized Value Exchange in the metaverse positively affects their preference for Presence in Second-Life.

The metaverse virtual world incorporates various technologies, allowing users to trade digital assets in a decentralized way without going through a specific platform. This study indicated that the user’s ability to make a deal in a decentralized way in the metaverse can effectively enhance their preference for communicating and interacting with others in the 3D environment. Thus, the following hypothesis was proposed:

H2b:

The user’s self-efficacy about the Decentralized Value Exchange in the metaverse positively affects their preference for 3D Interactivity.

Moreover, the metaverse offers users different transaction methods from the real world. It allows users to trade digital assets in a decentralized way. This study proposed that when users believe they can trade NTFs decentralized, their preference for obtaining entertainment and assets in the metaverse virtual world will improve. Hence, the following hypothesis was proposed:

H2c:

The user’s self-efficacy about the Decentralized Value Exchange in the metaverse positively affects their preference for Play-to-Earn.

4.1.3 Immersive experience in the metaverse

With the rapid development of science and technology, humans continue to pursue immersive online experiences. Oriti et al. (2021) referred to immersive experience as utilizing equipment and technologies (such as VR helmets, smart glasses, and gloves with sensors) to perceive and experience reality in the virtual world (Hashemian et al. 2022; Verhulst et al. 2021). The present study defined immersive experience as an act of immersing oneself in the metaverse virtual world by utilizing various multi-technique equipment, such as VR, AR, and MR. Moreover, self-efficacy about immersive experience in the metaverse was defined as the extent to which users believe they can access the metaverse virtual world and actively engage in the immersive environment. This study argued that the interaction is vital in the metaverse. Lee and Kim (2021) defined interactivity in the virtual world as a form of two-way communication in real time between users and machines. Users who employ VR and AR equipment may become immersed in the metaverse and obtain greater enjoyment of a different wonderful life from the real world. Therefore, the following hypothesis was proposed:

H3a:

The user’s self-efficacy about Immersive Experience in the metaverse positively affects their preference for Presence in Second-Life.

Kim and Ha (2021) noted that user experience can be enhanced through increased interaction with other users in an immersive environment. In the metaverse, users may employ different devices and equipment to establish a 3D environment and communicate with each other to become more immersed in the virtual world. This study argued that when users employed such equipment to access and navigate the metaverse, their preference for social interaction in a 3D environment will improve. Thus, the following hypothesis was proposed:

H3b:

The user’s self-efficacy about Immersive Experience in the metaverse positively affects their preference for 3D Interactivity.

There are various technologies used to access the metaverse and obtain entertainment there. The metaverse provides users with enjoyment and a platform for making transactions. Users play the games and receive digital assets in the virtual world. This study argued that when users employ certain devices to immerse in the metaverse, their preference for the features of the metaverse—which are the opportunities to obtain entertainment and digital assets—will improve. Hence, the following hypothesis was proposed:

H3c:

The user’s self-efficacy about Immersive Experience in the metaverse positively affects their preference for Play-to-Earn.

4.2 Preference

The degree of preference plays a role in decision-making. Preference is the actual feeling in people’s minds and can affect the vital attitude of decision-making (Lopez et al. 2021; Wiggers et al. 2005). Kim et al. (2021) and Singh et al. (2017) suggested that user preference is strongly related to self-efficacy. Therefore, the present study defined preference as the degree of the user’s attitude toward enjoying Presence in Second-Life, 3D Interactivity, and Play-to-Earn in the metaverse. In addition, the willingness to participate in the metaverse was defined as the degree of willingness to adopt metaverse applications and engage in metaverse activities.

4.2.1 Presence in Second-Life

People can use VR and AR devices to access the metaverse and achieve virtual presence. Yeh et al. (2019) defined the willingness to participate as when users consistently demonstrate certain behaviors. Li and Wang (2021) indicated that the use of VR can effectively enhance the willingness to participate in the metaverse. Diemer et al. (2015) believed that presence could enhance participation and the willingness to immerse in a virtual experience. The present study argued that users can lead a second life in the metaverse virtual world and utilize related technologies to establish a sense of presence. In addition, by leading a different life in the metaverse, users may increase their willingness to access this virtual environment. Thus, the following hypothesis was proposed:

H6:

The preference for Presence in Second-Life positively affects the willingness to participate in the metaverse.

4.2.2 3D interactivity

Users may become immersed in a virtual space by utilizing different equipment to establish a 3D environment. This study defined 3D Interactivity as the degree to which users communicate with each other in the 3D virtual environment of the metaverse. Kim and Jo (2022) maintained that the user’s presence in a virtual space may be increased when they participate in an immersive 3D environment. Thus, the following hypothesis was proposed:

H4:

3D Interactivity positively affects the preference for Presence in Second-Life.

One feature of the metaverse is that it is accessible through different devices and allows users to communicate with each other in a 3D virtual environment, exchange digital assets, and obtain entertainment. Mikalef et al. (2012) suggested that higher interactivity means more benefits. Therefore, the present study argued that when users utilize technologies to access a 3D virtual environment and obtain higher interactivity with others, they will become more interested in obtaining entertainment and acquiring digital assets. Therefore, the following hypothesis was proposed:

H5:

3D Interactivity positively affects the preference for Play-to-Earn.

In addition, Lee and Kim (2021) pointed out that users’ perceived interactivity may affect their willingness to use technology. Jang and Park (2019) stated that when users perceive pleasure, interaction, and enjoyment, they may become more willing to use a technology in the virtual world. Therefore, the present study argued that it would effectively increase the user’s willingness to participate in the metaverse when users enjoy interacting with others in the 3D environment. Hence, the research assumes:

H7:

The preference for 3D Interactivity will positively affects the willingness to participate in the metaverse.

4.2.3 Play-to-earn

This study defined Play-to-Earn in the metaverse as follows: the user can obtain both entertainment and digital assets. This entertainment is derived from playing online games and interacting with others in the metaverse virtual world. The assets are obtained when users engage in decentralized asset exchange (for instance, exchanging NFTs)—a feature available in numerous metaverse virtual worlds. Enjoyment occurs when the user feels pleased utilizing a particular system or engaging in a particular activity (Venkatesh 2000). Moreover, users who operate information systems and obtain Immersive Experiences may exhibit greater happiness about their virtual presence and a stronger willingness to participate in the virtual world (Jang and Park 2019; Kim and Ha 2021). Thus, the following hypothesis was proposed:

H8:

The preference for Play-to-Earn positively affects the willingness to participate in the metaverse.

5 Research methods

5.1 Sampling and data collection

Taiwan has the world’s highest volume of mobile data transmission (Chen et al. 2018). This makes it easy for new technologies to be adopted in Taiwan; the present study was therefore conducted in the country to explore local users’ willingness to participate in the metaverse.

An online questionnaire with an explicit disclosure that the responses were collected anonymously and solely intended for research purposes. Moreover, since the metaverse is a forward-looking but lesser-known concept than in other fields, this study performed purposive and snowball sampling to obtain a small sample of responses (Etikan et al., 2016).

Firstly, we asked top-level managers from the information technology industry to recommend ten professionals in the field. Participants were then selected through snowball sampling from among the professionals. Snowball sampling involves one subject referring the name of another subject to the researcher, and this process keeps identifying subsequent participants (Baltar and Brunet 2012). Besides, at the beginning of the questionnaire, a comprehensive definition of the metaverse is provided to preclude any variability in participants’ perceptions of the term. Furthermore, the questionnaire confirms whether the participants have a clear understanding of the metaverse as it is defined in the first question. Should respondents elect either a lack of awareness or an absence of understanding regarding the metaverse, the survey protocol is designed to terminate the session forthwith, thereby precluding any subsequent involvement.

The questionnaire results revealed that all the participants had utilized metaverse-related technologies for more than one year. The majority of responses were obtained from the Digital Nation Working Group of Taiwan’s Board of Science and Technology (24%), ICT technology researchers of Taiwan’s Ministry of Economic Affairs (22%), experts in Decentralized Value Exchange from Taiwan’s Institute of Market Intelligence & Consulting Institute (15.3%), Blockchain research advisors (14%), and NFT developers (8.6%). The questionnaire was administered from April 4 to April 17, 2022, during which a total of 151 responses were collected, with 150 of them deemed valid. Of the151 participants, 86 were males (57.3%) and 64 were females (42.7%). Most participants were aged 21–30 years (43.3%) and held either an undergraduate (48%) or graduate (51.3%) degree. Table 1 summarizes the demographics of the participants.

Table 1 Participant demographics
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5.2 Variable measurement

The design of the questionnaire was mostly based on previous studies, and its questions were measured on a five-point Likert-type scale from 1 (“Strongly disagree”) to 5 (“Strongly agree”). Table 2 summarizes all survey items of the research.

Table 2 Measures
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5.3 Results of the measurement model

Smart PLS3.0 was used to perform a confirmatory factor analysis (CFA) to test the measurement model. Table 3 describes the convergent discriminant validity of the model. The Cronbach’s alpha value of all constructs ranged from 0.834 to 0.961, higher than the recommended value of 0.7 (Hair et al. 2014). The CR score exceeded 0.9 across all constructs, which was higher than the score of 0.7 scores recommended by Fornell and Larcker (1981). Moreover, the factor loading of all the items and the average variance extracted (AVE) were, respectively, 0.817–0.977 and 0.9–0.975—higher than the 0.5 recommended by Fornell and Larcker (1981) and Hair et al. (2014).

Table 3 Statistics of construct items
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In terms of discriminant validity, the square root of the AVE for each construct was more significant than the correlation coefficients (Fornell andLarcker 1981; Hair et al. 2014), as shown in Table 4. Given all the results above, the measurement model demonstrated satisfactory reliability, convergent validity, and discriminant validity. Table 4 illustrates that the diagonal elements, which are the square roots of the Average Variance Extracted (AVE), surpass the magnitudes of the inter-correlational coefficients denoted by the off-diagonal entities within the corresponding rows and columns.

Table 4 Discriminant validity
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5.4 Results of the structural model

The structural model was tested through SEM using SmartPLS 3.0, with the results summarized in Fig. 2. The SmartPLS 3.0 algorithm yielded the following R-squared values: 45.2% of the variance in Willingness of Participation, 56.9% in Presence in Second-Life, 22.8% in 3D Interactivity, and 46.5% o in Paly-to-Earn.

Fig. 2
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Smart PLS 3.0 results for the structural model. ***P < 0.001

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Figure 2 illustrates the final model paths of hypothesis testing. Avatars (β = 0.255, p < 0.01) and 3D Interactivity (β = 0.563, p < 0.001) positively affected Presence in Second-Life, validating H1a and H4. However, the hypotheses that Decentralized Value Exchange (H2a) and Immersive Experience (H3a) influence the Presence in Second-Life were rejected. Avatars (β = 0.222, p < 0.05) and Immersive Experience (β = 0.213, p < 0.05) had significant effects on 3D Interactivity, validating H1b and H3b. Nonetheless, since Decentralized Value Exchange did not influence 3D Interactivity, H2b was rejected. Furthermore, Decentralized Value Exchange (β = 0.206, p < 0.05), Immersive Experience (β = 0.22, p < 0.05), and 3D Interactivity (β = 0.458, p < 0.001) were positively related to Play-to-Earn; however, Avatars had negative effects on 3D Interactivity. Thus, H2c, H3c, and H5 were validated, whereas H1c was rejected. Finally, Presence in Second-Life (β = 0.261, p < 0.05) and Play-to-Earn (β = 0.461, p < 0.001) had significant effects on Willingness of Participation, validating H6 and H8. However, the hypothesized path for 3D Interactivity had no direct effects on Willingness of Participation, thus rejecting H7.

6 Conclusions and discussion

This study investigated the factors affecting the willingness to participate in the metaverse. It was found that users’ willingness to participate in the metaverse was significantly affected by Presence in Second-Life and Play-to-Earn, with Play-to-Earn exerting stronger effects than Presence in Second-Life on this willingness.

Second, while previous studies have shown that interaction and enjoyment have significant effects on the adoption of AR, VR, MR, and MMORPGs (Chen et al. 2018; Morschheuser et al. 2017; Ortiz de Gortari 2018; Rauschnabel et al. 2017), the path analysis conducted in this study suggested no significant relationship between 3D Interactivity and willingness to participate in the metaverse. However, the bivariate correlation between 3D Interactivity and willingness to participate was as high as 0.507, with p < 0.01 (see Table 4). This was mainly due to the fact that 3D Interactivity was indirectly affected—via Presence in Second-Life (β = 0.563, p < 0.001) and Play-to-Earn (β = 0.458, p < 0.001)—the willingness to participate in the metaverse (Fig. 2).

Finally, Avatars, a basic concept of the metaverse, can affect a user’s preference for Presence in Second-Life and 3D Interactivity. This preference may take place because of Avatars and Immersive Experience, indicating that avatars and immersion experience significantly affect 3D Interactivity. Furthermore, a preference for Play-to-Earn may happen because of Decentralized Value Exchange and Immersive Experience. The findings suggested that avatars significantly affect users’ preference for Presence in Second-Life and 3D Interactivity but have no correlation with Play-to-Earn; Decentralized Value Exchange is significantly related only to Play-to-Earn; and Immersive Experiences are significantly related to 3D Interactivity and Play-to-Earn.

6.1 Theoretical contribution

The research addresses gaps in the existing literature by providing a structured framework for studying the metaverse and its user engagement factors. By focusing on the interplay between attitudes, preferences, and willingness to participate, the study lays the groundwork for future research endeavors in this evolving field. Besides, this research contributes by providing a theoretical framework, identifying crucial factors, and offering practical insights that contribute to the ongoing discourse on virtual reality and user engagement, specifically within the context of the metaverse. It builds upon and extends existing literature by addressing the unique challenges and opportunities presented by this emerging technological landscape.

First, the metaverse industry is still in nascency, and there is no universally accepted definition of the metaverse. Therefore, we developed a research model based on the self-efficacy theory and TRA. This study argued that the metaverse has three features (Avatars, Decentralized Value Exchange, and Immersive Experience), generates three user attitudes (Presence in Second-Life, 3D Interactivity, and Play-to-Earn), and triggers the willingness to participate in this virtual world. Thus, the basic concepts of the metaverse were summarized in terms of Avatars, Decentralized Value Exchange, and Immersive Experience. Based on these concepts, we observed that users may develop attitudes toward Presence in Second-Life, 3D Interactivity, and Play-to-Earn, which then affect their willingness to participate in the metaverse.

Second, since the metaverse incorporates various technologies and symbolizes technological advancements with respect to its creation, this study successfully used the TRA and self-efficacy theory to investigate the factors affecting users’ willingness to participate in the metaverse. Moreover, this study contributes to the understanding of the three dimensions of the metaverse: Avatars, Decentralized Value Exchange, and Immersive Experiences, as well as three preferences: Presence in Second-Life, 3D Interactivity, and Play-to-Earn. The research methodology may provide fresh insight into integrating these two theoretical frameworks into metaverse-related research and pave the way for further research.

Third, this study identified the crucial factors in the willingness to participate in the metaverse. The most significant factor is Play-to-Earn, followed by Presence in Second-Life. 3D Interactivity has no direct effect on the willingness to participate in the metaverse, but preference for 3D Interactivity plays a vital role in this willingness. It affects users’ preference for Presence in Second-Life and Play-to-Earn and, ultimately, the willingness to participate in the metaverse. Hence, one should not only focus on the role of 3D interactivity in this willingness but also take into account 3D interactivity to enhance users’ preference for presence in second life and play-to-earn.

Finally, this study showed that 3D Interactivity indirectly affects participation willingness. When 3D Interactivity does not encourage preference for Presence in Second-Life or Play-to-Earn, then it may not affect the users’ willingness to participate in the metaverse. As such, even a well-designed VR headset may have no significant effect on this willingness if it does not trigger preference for Presence in Second-Life or Play-to-Earn.

6.2 Managerial implications

The findings of this study may contribute to the understanding of the metaverse’s basic concepts and the factors affecting participation in the metaverse. First of all, the metaverse can be divided into two categories. The first category is Meta-based, under which an immersive experience of presence in second life is created by utilizing VR, AR, and related technologies. The second category is based on the NFT transaction of the blockchain, which emphasizes play-to-earn features (such as Roblox and Sandbox).

This study found that Avatars have strong effects on the first category of the metaverse but no remarkable effect on the second category (users can trade NFTs without having to use avatars). Moreover, Decentralized Value Exchange has no direct relationship with the first category of the metaverse, yet Decentralized Value Exchange and Immersive Experience were positively related to the second category, and Immersive Experience was indirectly related to the first category. In addition, 3D Interactivity has considerable effects on both the metaverse’s first (Meta) and second (Blockchain) categories. The findings also suggested that Play-to-Earn has more significant effects than Presence in Second-Life on the willingness to participate in the metaverse. This explains why blockchain games (such as Roblox and Decentraland) are more famous than Meta’s metaverse.

Hence, the findings of this study may influence practical applications in metaverse development and user experience design. First, the study underscores the significant impact of avatars in the context of Meta-based metaverse experiences. Developers are encouraged to focus on elevating the quality and personalization of avatars that involve advanced customization options and increased interactivity to enhance users’ sense of presence in the second life. Second, the influence of 3D interactivity across both metaverse categories necessitates a concentrated effort in metaverse design to prioritize the development of highly interactive elements. This entails incorporating sophisticated environmental interactions, object manipulation, and real-time interactions with other users to amplify user immersion. Third, the study highlights the pronounced impact of play-to-earn features on user engagement within the metaverse. Organizations could optimize these features by designing more enticing reward systems and introducing compelling tasks and challenges. Fourth, while decentralized value exchange exhibited no direct correlation with the first metaverse category, its positive association with the second category suggests the importance of incorporating decentralized mechanisms. Integrating features such as NFT transactions and ownership transfers of digital assets can enhance user interaction and participation within blockchain-based metaverse platforms. Furthermore, the indirect relationship between immersive experiences and the first metaverse category, strategic investments in immersive technologies such as AR, VR, and MR become crucial for Meta-based metaverse platforms. Providing more realistic and captivating experiences can significantly augment user preferences for the second life.

These findings provide actionable insights for developing more captivating and engaging metaverse experiences. By understanding user preferences for avatars, 3D interactivity, play-to-earn features, and immersive technologies, developers can effectively shape and promote metaverse applications, thereby increasing user engagement and satisfaction.

6.3 Limitations and future research directions

Although this study provides valuable and interesting findings, it is not without limitations.

First, the metaverse has limited popularity, even though related technologies have been around for many years. It also lacks integrity technology-wise and has high entry barriers. Considering the limitations of the metaverse, the participants in this study might have been conversant only in their own areas of specialization, which might have contributed to biased results. Therefore, only metaverse specialists were enrolled in this study. A larger-scale study that recruits general users should be conducted if the metaverse becomes more popular in the future.

Second, this study only used quantitative methods to explore factors affecting the willingness to participate in the metaverse and distribute an online questionnaire. The responses could not be completely screened, and they might have contained repeat answers or unanswered questions. Moreover, responses obtained through online questionnaires may have a self-selection bias (Chen et al. 2018); hence, future studies should conduct interviews in addition to administering questionnaires.

Finally, this study was conducted only in Taiwan, and it examined a convenience sample of Taiwanese participants. However, the findings may be extrapolated to other Asian countries with have equally high population density and rapid technological development. The findings may also inform similar studies undertaken in other Asian countries.