“In Metaverse Cryptocurrencies We (Dis)Trust?”: Mediators and Moderators of Blockchain-Enabled Non-Fungible Token (NFT) Adoption in AI-Powered Metaverses

Abstract

Metaverses have been hailed as the next arena for a wide spectrum of technovation and business opportunities. This research (∑ N = 714) focuses on the three underexplored areas of virtual commerce in AI-enabled metaverses: blockchain-powered cryptocurrencies, non-fungible tokens (NFTs), and AI-powered virtual influencers. Study 1 reports the mediating effects of (dis)trust in AI-enabled blockchain technologies and the moderating effects of consumers’ technopian perspectives in explaining the relationship between blockchain transparency perception and intention to use cryptocurrencies in AI-powered metaverses. Study 1 also reports the mediating effects of Neo-Luddism perspectives regarding metaverses and the moderating effects of consumers’ social phobia in explaining the relationship between AI-algorithm awareness and behavioral intention to engage with AI-powered virtual influencers in metaverses. Study 2 reports the serial mediating effects of general perception of NFT ownership and psychological ownership of NFTs as well as the moderating effects of the investment value of NFTs in explaining the relationship between acknowledgment of the nature of NFTs and intention to use NFTs in AI-enabled metaverses. Theoretical contributions to the literature on digital materiality and psychological ownership of blockchain/cryptocurrency-powered NFTs as emerging forms of digital consumption objects are discussed. Practical implications for NFT-based branding/entrepreneurship and creative industries in blockchain-enabled metaverses are provided.

1. Introduction

The term metaverse was first coined by Stephenson in his novel Snow Crash [1]. The metaverse was initially conceptualized as a VR-based successor to the Internet, where humans-as-avatars interact with each other in an immersive world [2,3]. In the Metaverse Roadmap Project, Smart et al. [4] identified “virtual worlds”, “mirror worlds”, “augmented reality”, and “lifelogging” as the four key components of the 3D digital future of metaverses. Metaverses can be defined as “an immersive and shared virtual world in which different activities are allowed for its users, which are represented by avatars” [5].

Multiple key technologies that are powering metaverses include networks, computing, 3D modeling, Internet of Things (IoT), artificial intelligence (AI) techniques like machine learning and deep learning, blockchain, cryptocurrency, non-fungible tokens (NFTs), augmented reality (AR), virtual reality (VR), extended reality (XR), and interface devices [6,7,8]. Machine learning-based predictive modeling and simulation modeling algorithms, along with 3D virtual geospatial mapping tools, can enable immersive virtual experiences in metaverses [9]. The AI-enabled emerging technologies that empower metaverses are dramatically transforming the customer experience in service industries and service marketing [10,11,12]. Metaverses have been hailed as the next arena for a wide spectrum of business opportunities and technovation [13]. For example, the “Nike–Roblox” case study shows that metaverses will be a new future marketing platform for showcasing a variety of brands in the 3D interactive digital space [14] and for promoting the consumption and trading of virtual possessions [8] in various service industry sectors.

The business press and burgeoning body of market research predict that metaverses will form the backbone of Web 3.0 [15]. Despite the hype around metaverses, there is a dearth of scholarly research on consumer engagement with the key technological components of metaverses in the field of technovation, AI-enabled interactive service marketing, and service industries. The present research attempts to address this gap. AI and 5G connectivity, through emerging technologies like blockchain and IoT, have been identified as the drivers of the Fourth Industrial Revolution and have blurred boundaries between the physical and digital spheres [16]. The veiled potential of metaverses, as a hyper-connected phygital (physical + digital) world, may surface hopes and fears about the “AI-VR-Convergence”, referring to “the synergetic merging of AI technologies and VR technologies into a unified metaverse interface” [17] (p. 4), facilitate discourses about success and failure factors, and stimulate research on the promises and perils of business practices and technovation in metaverses.

The current research particularly focuses on the three underexplored areas of technovation, virtual commerce, and interactive service marketing in metaverses: (1) blockchain-powered cryptocurrencies; (2) non-fungible tokens (NFTs); and (3) virtual influencers in AI-powered metaverses. Beyond speculation and hype, research needs to inform and support the ongoing maturation of blockchain technology from a socio-technical perspective [18] and AI-enabled virtual influencers from a social-psychological perspective [19]. This research aims to examine the underlying psychological mechanisms and boundary conditions relevant to people’s adoption of cryptocurrencies, blockchain-powered NFTs, and AI-based virtual influencers in metaverse-powered technovation and service industries. Thus, the unique contributions of this research are to address the underexplored terrains of AI and blockchain applications in metaverses and to advance theoretical understanding of the social-psychological factors that affect consumers’ adoption of AI-powered blockchain systems, cryptocurrencies/NFTs, and virtual influencers in metaverses. Ultimately, this study may provide practical and managerial implications for developing business strategies that enhance consumer engagement and drive the growth of blockchain technologies and AI-powered virtual influencers in the evolving metaverse landscape.

The present research departs from the conventional Technology Acceptance Model (TAM) [20], which has several limitations, such as the focus on the implementation stage within organizations [21], the assumption of users as passive absorbers of technology, and the techno-centric nature of the approach, which overlooks people’s creative uses of new technologies [22]. To examine adoption of blockchain technologies, NFTs, and virtual influencers in metaverses, the current research draws from (1) the consumer psychology literature on trust [23,24]; (2) the literature on digital materiality [25], which is relevant to psychological ownership of blockchain/cryptocurrency-powered NFTs as emerging forms of digital consumption objects [15]; and (3) the emerging literature on NFTs used by AI-powered virtual influencers [26,27]. Building upon the literature review, theory-driven hypotheses are proposed in Section 2, research methods are explained in Section 3, the results of quantitative statistical analyses are presented in Section 4, and theoretical and practical implications are discussed in Section 5.

2. Conceptual Foundations, Theoretical Underpinning, and Hypothesis Development

2.1. Blockchain Technologies and Cryptocurrencies in Metaverses

Blockchain refers to a “shared, distributed transaction ledger that records all transactions” [28] (p. 78). Blockchains provide opportunities for decentralized, peer-to-peer transactions, thus reducing the intermediary role of central platforms [29]. The elimination of intermediaries from peer-to-peer transactions [30] makes the transactions quicker, more efficient, and more cost-effective [31]. Cryptographic technologies like blockchain are deployed to validate business transactions, while the transacting entities act as the nodes [32,33]. A blockchain can be considered as a “distributed database organized as a list or ordered blocks, where the committed blocks are immutable” [34] (p. 55), thus facilitating transparency, auditability, and security [35]. Blockchain technologies are proposed as one of the gamechangers for a wide variety of business applications and transactions, thus bearing enormous implications for e-commerce, fintech service industries, and technovation [36]. The blockchain technology, originally designed for cryptocurrencies, has been recently expanded to the e-commerce sector [37]. Due to their “conveyance, security, trust, and ability to make transactions without the aid of formal institutions and governing bodies” [38] (p. 1), the business of blockchain and cryptocurrency continues to evolve and pave the way for the transformation of the fintech industry and e-commerce markets, despite unpredictable and turbulent market conditions. Amazon’s test of digital currency suggests that cryptocurrencies could play a role in the future of e-commerce [39].

The key advantages of blockchain technologies include “cost optimization, effective tracking and traceability, verifiable record-keeping, transparency, and ease of collaboration for firms” [37] (p. 90). However, there are also issues, challenges, and limitations of blockchain technology, such as skepticism and concerns about transactional data privacy and information confidentiality [34,40], which may have a negative influence on consumers’ perception of blockchain transparency and consumers’ trust in blockchain technologies and banking services. Marketing researchers and social/economic scientists need to further examine the application of blockchain technologies and their impact on consumer trust [41].

Trust is defined as “a psychological state comprising the intention to accept vulnerability based upon positive expectations of the intentions or behavior of another” [24] (p. 395). On the other hand, transparency is a concept of clear understanding of transactions involving cryptocurrency exchanges and a critical element influencing cryptocurrency adoption [38,42]. Blockchain transparency, one of the major benefits of blockchain technologies, refers to the maintenance of a common database that permits the establishment of the “chronological order of cryptographically time-stamped entries” [43] (p. 3). Thus, the blockchain network can offer transparency for an auditable ledger of transactions since no entity can manipulate, amend, or remove any of the stored data validated by the decentralized network [44]. Transparency is also related to trust-building [45]. A recent study provides empirical evidence that blockchain transparency is positively related to trust in cryptocurrency and trust in cryptocurrency mediates the relationship between blockchain transparency and consumer behavior [43]. Furthermore, cryptocurrency transaction transparency is positively associated with consumers’ greater willingness to engage in additional transactions [46].

Metaverses can be decentralized, with a virtual economy utilizing emerging digital forms of payment, including blockchain-based cryptocurrencies and cryptographic assets like non-fungible tokens (NFTs) [47]. Blockchain technology can provide a trust mechanism for exchange parties in the blockchain ecosystem due to its decentralized networks [48,49]. Blockchain technology may enable the building of trust and traceability from a real business use case [50]. For example, since blockchain, as a distributed ledger, assigns unique digital identifiers to products, thus making products easily traceable throughout the supply chain, the food industry has considered the application of blockchain in increasing consumer trust [51]. Furthermore, blockchain-based apps could enable brands to minimize concerns about the authenticity of their intended purchase [52,53], as well as to track the entire lifecycle of each product [31]. It is essential to understand the factors and drivers that facilitate consumers’ trust toward crypto-tokens and their consequent adoption [54]. A study indicates that social influence, transparency, traceability, attitude, and customer satisfaction are significant antecedents of cryptocurrency adoption [42]. However, no prior research to date has empirically examined the relationships among consumers’ blockchain transparency perception, trust in the blockchain technologies, and behavioral intention to use cryptocurrencies for virtual commerce in the novel context of metaverses. Study 1 attempts to address this gap in the literature (H1, H2, and H3).

Prior research shows that consumers’ technopian view on AI-powered chatbots moderates the relationship between different types of chatbots (friend chatbot versus assistant chatbot) and consumer behavior [55]. Technopian advocates like Mark Zuckerberg predict that metaverses will be an avatar-based virtual space with ubiquitous connectivity in which customers’ avatars can browse products, shop, and consume entertainment as companies open virtual stores for business [15]. Metaverses may offer consumers experiences around play, work, connection, and consumption [56]. Technopian consumers tend to focus on the positive aspects of emerging technologies and predict that people can benefit from technological innovations [57]. It can be hypothesized that consumers with a high level of technopian perspective on metaverses and high blockchain transparency perception show the highest level of cryptocurrency use intention, whereas those with a low level of technopian perspective on metaverses and low blockchain transparency show the lowest level of cryptocurrency use intention in metaverses. Therefore, there will be two-way interaction effects of consumers’ technopian perspectives regarding metaverses and blockchain transparency perception on cryptocurrency use intention as the outcome variable, such that the effect of blockchain transparency perception on cryptocurrency use intention is stronger for technopian consumers (H4). Based on the so-far discussed theoretical reasoning, the following hypotheses are proposed.

H1: 

Blockchain transparency perception is a positive predictor of trust in the blockchain technologies.

H2: 

Trust in the blockchain technologies is a positive predictor of behavioral intention to use cryptocurrencies in metaverses.

H3: 

Trust in the blockchain technologies mediates the relationship between blockchain transparency perception and behavioral intention to use cryptocurrencies for virtual commerce in metaverses.

H4: 

A technopian perspective regarding metaverses moderates the relationship between blockchain transparency perception and behavioral intention to use cryptocurrencies for virtual commerce in metaverses.

2.2. AI-Powered Virtual Influencers in Metaverses

A virtual influencer refers to the computer-generated imagery (CGI) of a virtual persona, virtual model, virtual avatar, or fictional character [58,59]. Virtual influencers are “virtual robots that can emulate human appearance and behavior” and have become a trend in marketing [60] (p. 1). These CGI characters and virtual humanoid robots have been promoting prominent global brands like KFC (Kentucky Fried Daddy Colonel Sanders and his computer-generated girlfriend Dagny), IKEA (Imma), Balmain (the world’s first digital supermodel Shudu), Christian Louboutin (Shudu), Samsung (Sam), and Givenchy (Lil Miquela). Also, luxury brands are increasingly exploring metaverses by creating and engaging AI-powered virtual influencers such as Lil Miquela, Rozy, and Imma in virtual marketplaces. [61]. From a business perspective, the key benefits of employing AI-powered virtual influencers include lower production costs, lower labor costs, higher control over messaging, and ultimately the ability to create brand ambassadors that perfectly align with their brand image [58,62]. Marketing companies create and own virtual influencers who are “digitally flawless, scandal-free, and never aging” [63]. AI-generated virtual influencers that mimic humans are specifically created to attract social media followers and boost consumer engagement [64]. A report by social media analytics company HypeAuditor reveals that virtual influencers have an engagement rate that is three times higher than human influencers [65]. Study 1 also examines predictors of engagement with virtual influencers in the metaverses from a consumer perspective, drawing from the literature on the ontological issues of AI-algorithm awareness, Neo-Luddism, and social phobia, as elaborated below.

STARA (Smart Technology, Artificial Intelligence, Robotics, and Algorithms) awareness captures the degree to which “an employee views the likelihood of Smart Technology, Artificial Intelligence, Robotics, and Algorithms impacting on their future career prospects” [66] (p. 241). Study 1 tests the role of AI-algorithm awareness in impacting consumers’ engagement with AI-powered virtual influencers in metaverses. AI-algorithm awareness refers to “employees’ awareness that AI machines such as robots and algorithms may replace their current work in the future, which leads to employees’ perception of uncertainty of the workplace in the digital era” [67] (p. 719), [68] (p. 3). Relatedly, AI-algorithm awareness may be associated with consumers’ resistance to the metaverse technologies and AI-powered virtual influencers. Neo-Luddism is characterized by the promotion of a substantial rejection of modern technology [69]. Neo-Luddites question the embrace of technology and stay mindful of and vigilant toward adopting emerging technologies that may have long-term effects on humanity and society [70]. Consumers with Neo-Luddism perspectives on metaverses may claim that metaverses are a threat to natural and authentic ways of living human lives. A study empirically demonstrates the significant role of Neo-Luddism in consumers’ engagement with AI-powered anthropomorphic chatbots [55]. The proliferation of the trend of anthropomorphic virtual influencer marketing makes people wonder if virtual influencers will replace real human influencers in the near future [63] and be concerned about the ethical issues of AI-powered emerging technologies like virtual influencers [62], which rationalizes the examination of the role of AI-algorithm awareness and Neo-Luddism in virtual influencer engagement in metaverses (H5, H6, and H7).

Previous studies on a variety of emerging technologies indicate the role of consumers’ social phobia in their engagement with AI-based human-like chatbots [71], empathetic chatbots [72], technology-based self-service [73], quick response (QR) code promotion in e-commerce [74], etc. Study 1 proposes that consumers’ social phobia as a boundary condition that moderates the relationship between AI-algorithm awareness and behavioral intention to engage with virtual influencers in metaverses. For example, the effect of AI awareness on behavioral intention to engage with virtual influencers will be stronger for those consumers with high social phobia, whereas there is no significant effect of AI awareness on behavioral intention to engage with virtual influencers for those consumers with low social phobia. Therefore, there will be two-way interaction effects of consumers’ social phobia and AI awareness on behavioral intention to engage with virtual influencers as the outcome variable, such that the effect of AI awareness on engagement with virtual influencers is stronger for highly social-phobic consumers (H8). Based on the so-far discussed theoretical reasoning, the following hypotheses are proposed.

H5: 

AI-algorithm awareness is a positive predictor of a Neo-Luddism perspective on metaverses.

H6: 

A Neo-Luddism perspective on metaverses is a negative predictor of behavioral intention to engage with AI-powered virtual influencers in metaverses.

H7: 

A Neo-Luddism perspective on metaverses mediates the relationship between AI-awareness and behavioral intention to engage with AI-powered virtual influencers in metaverses.

H8: 

Social phobia moderates the relationship between AI-algorithm awareness and behavioral intention to engage with virtual influencers in the metaverse.

2.3. Cryptocurrency-Based Non-Fungible Tokens (NFTs) in Metaverses

Non-Fungible Tokens (NFTs) are defined as “pure digital assets that cannot be exchanged like-for-like” [5] (p.1) and “cryptographic assets on a blockchain with unique identification codes and metadata that distinguish them from each other” [75] (p. 3). Thus, NFTs are a type of blockchain-based asset and cryptocurrency that can represent ownership of digital or physical assets [76]. NFTs are a record of ownership of primarily digital media and NFT transactions are recorded on blockchains [77]. NFTs have received increasing attention from various industry sectors and scientific communities in the cryptocurrency market [5]. First proposed in 2017 and implemented on the Ethereum blockchain, NFTs are immutable blockchain-based tokens that are characterized by uniqueness, immutability, non-interchangeability, authenticity, and scarcity [77,78,79]. As one of the state-of-the-art use cases of blockchain technologies, NFTs have been realized by Ethereum Virtual Machine (EVM)-based blockchains such as Ethereum [80]. Studies have highlighted the significance of uniqueness and ownership that NFTs provide [81]. Study 2 addresses key factors that influence consumers’ behavioral intentions to use NFTs in metaverses.

Entrepreneurial digital artists and creative directors can monetize their work through metaverses in the NFT market. Virtual influencers also engage with fans by conveying virtual narratives and expressing their unique personalities in creative ways via NFTs. For example, Brud, the creator of the first virtual influencer Lil Miquela, with 2.4 million Instagram followers, launched the virtual influencer’s first NFTs “Rebirth of Venus”, which was sold for 159.5 ETH (Ethereum currency equivalent to USD 82,361 at the time of transaction in November 2020) on SuperRare [82]. Enterprises across industries, from Coca Cola to high-end luxury companies like Gucci, have created NFTs such that Coca Cola offered first-ever NFT collectibles in the International Friendship Day Charity Auction [83], while Gucci became the first luxury brand to launch an NFT [84]. Louis Vuitton, one of the favorite brands for fashionistas, even launched Louis: The Game, which rewards consumers with the chance to win exclusive postcards of the brand in the form of NFTs [85]. Due to the uncertainty and seemingly distant benefits, the market conditions often fluctuate and the demand for NFTs is volatile [86]. Despite the skepticism about NFTs and the 2022 crypto fallout, global brands still continue to seek strategic ways to not only utilize metaverses as an alternative marketing channel but also embrace and leverage NFTs for virtual commerce and virtual user experience (UX) services [87]. Therefore, it is imperative to examine consumers’ perception of NFTs as a new financial asset in light of the expanding investment inflows into the NFT market.

It is probable that NFTs will play an integral role in metaverses by attracting a variety of stakeholders to the virtual world [15,78,88]. Acknowledgment of the scarcity, exclusivity, uniqueness, and authenticity of objects are key drivers of consumers’ purchasing behaviors and desire for ownership. Psychological ownership refers to “a state in which individuals feel as though the target of ownership (or a piece of that target) is theirs” [89] (p. 86). The potential of monetizing the digital contents of various assets and introducing scarcity to the emerging fintech service market constitute the major impetus for the growing popularity and optimism about NFTs [76,86]. Unlike fungible and interchangeable cryptocurrencies like Bitcoin, NFTs are unique and non-fungible and, therefore, cannot be exchanged like-for-like [90,91]. NFTs, which contain built-in authentication serving as proof of ownership, allow buyers to own the original digital item [92]. Consumers who understand and know how cryptocurrencies work are more likely to trust and invest in the currency [93]. It can be hypothesized that consumers’ acknowledgement of the nature of NFTs (scarcity, uniqueness, non-fungibility, etc.) can be positively associated with consumers’ (a) general ownership perception of NFTs (i.e., “NFTs can serve as a proof of ownership, thus allowing NFT buyers to claim the ownership”) and (b) perceived psychological ownership of NFTs (i.e., “NFTs can be mine”), which in turn positively influence consumers’ intention to use NFTs in metaverses (H9, H10, H11, and H12).

The key underlying factors in NFTs’ success include their potential for investment and consumers’ willingness to buy, sell, and trade digital assets using cryptocurrencies [94]. The value for cryptocurrencies and NFTs depends on “the collective belief in the marketplace in its long-term survival as a store of value and a unit of exchange” [95] (p. 22). Study 2 proposes that the perceived investment value of NFTs among consumers, as a boundary condition, moderates the relationship between acknowledgement of the nature of NFTs and behavioral intention to use NFTs in AI blockchain-enabled metaverses. For example, the effect of acknowledgment of the nature of NFTs on behavioral intention to use NFTs in metaverses will be stronger for those consumers who perceive NFTs as having a high investment value, whereas there is no significant effect of acknowledgment of the nature of NFTs on behavioral intention to use NFTs for those consumers with low perceived investment value of NFTs. Therefore, there will be two-way interaction effects of consumers’ perceived investment value of NFTs and acknowledgement of the nature of NFTs on behavioral intention to use NFTs in metaverses as the outcome variable, such that the effect of acknowledging the nature of NFTs (e.g., unique, scarce, authentic, and non-fungible) on NFT usage intention is stronger for those with higher perceived investment value of NFTs (H13). Based on the theoretical reasoning discussed so far, the following hypotheses are proposed.

H9: 

Acknowledgement of the nature of non-fungible tokens (NFTs) is a positive predictor of the (a) general perception of NFT ownership and (b) psychological ownership of NFTs.

H10: 

(a) General perception of NFT ownership and (b) psychological ownership of NFTs are positive predictors of behavioral intention to use NFTs in metaverses.

H11: 

General perception of NFT ownership is a positive predictor of psychological ownership of NFTs.

H12: 

(a) General perception of NFT ownership and (b) psychological ownership of NFTs serially mediate the relationship between acknowledgment of the nature of NFTs and behavioral intention to use NFTs in metaverses.

H13: 

The investment value of NFTs moderates the relationship between acknowledgment of the nature of NFTs and behavioral intention to use NFTs in metaverses.

3. Research Models and Methodology

To empirically test the proposed hypotheses, two studies were conducted using survey methodology. Study 1 focuses on the (1) relationships among consumers’ trust, perception of blockchain technologies, technopian perspectives on metaverses, and behavioral intention to use blockchain-powered cryptocurrencies in metaverses; and (2) relationships among AI algorithm awareness, Neo-Luddism, social phobia, and behavioral intention to engage with AI-powered virtual influencers in metaverses. Building upon the findings from Study 1 regarding blockchain technologies and cryptocurrencies, Study 2 further examines consumers’ perception of the nature of NFTs and behavioral intention to use cryptocurrency-based NFTs in metaverses.

3.1. Study 1 Theoretical Models and Methodology

The conceptual models for the proposed mediation effects of trust in blockchain technologies (H1, H2, and H3) and moderation effects of technopian perspectives regarding metaverses (H4) are presented in Figure 1 and Figure 2, respectively.

The conceptual models for the proposed mediation effects of Neo-Luddism regarding metaverses (H5, H6, and H7) and moderation effects of social phobia in determining the relationship between AI-algorithm awareness and behavioral intention to engage with AI-powered virtual influencers in metaverses (H8) are presented in Figure 3 and Figure 4, respectively.

3.1.1. Study 1 Respondents and Data Collection

Participants (N = 386; 253 females, 132 males, 1 participant preferred not to answer; 75.4% White/Caucasian, 13.7% Black/African American, 4.1% Hispanic/Latin American, 5.2% Asian/Asian Indian, 0.3% American Indian/Alaska Native, 0.3% Hawaiian/Pacific Islander, 0.5% Mixed Race, 0.3% Other, 0.3% preferred not to answer) were recruited from the CloudResearch Prime Panels who reside in the USA. Empirical research shows Prime Panels participants, compared to MTurk workers, are more diverse in age, family composition, religiosity, education, and political attitudes, thus improving representativeness and data quality [96]. Qualtrics was utilized as the platform to host the survey questionnaire, and the URL was embedded in the CloudResearch platform. The principal investigator received ethical approval from the university’s institutional review board (IRB) before data collection. Participants electronically signed the approved informed consent form before proceeding to fill out the survey questionnaire.

3.1.2. Study 1 Measures

All items were measured with 7-point Likert scales ranging from 1 (strongly disagree) to 7 (strongly agree). Blockchain transparency perception (independent variable) was measured with 7 items [43]. Trust in blockchain technologies (mediator) was measured with the 4 items from consumer trust scales [97]. Technopian perspectives on metaverses (moderator) were measured with 5 items [55,57]. Behavioral intention to use cryptocurrencies in metaverses (dependent variable) was measured with 5 items modified for the use of cryptocurrencies [98]. AI-algorithm awareness (independent variable) was measured with 4 items [66,67,68]. Neo-Luddism perspectives on metaverses (mediator) were measured with 5 items [55,57]. Social phobia (moderator) was measured with 5 items [71,99]. Behavioral intention to engage with virtual influencers in metaverses (dependent variable) was measured with 5 items modified for the use of virtual influencers [98].

The list of variables with the number of items, the results of reliability testing (Cronbach’s Alpha), and sample items for Study 1 are presented in

Table 1. List of variables with results of reliability testing (Cronbach’s Alpha), and sample items for Study 1.

Variable	Number of Items	Cronbach’s Alpha	Sample Items
BTP: Blockchain Transparency Perception (IV)	7	0.915	“Blockchain promotes transparency”, “Blockchain achieves decentralized security”, “Blockchain prevents financial fraud”
BTR: Blockchain Trust (Mediator)	4	0.959	“Blockchain is a trustworthy technology”, “The blockchain technology can be relied on to keep its promises”, “I can count on the blockchain technology to protect customers’ personal information from unauthorized use”
TPM: Technopian Perspective on Metaverses (Moderator)	5	0.942	“With metaverses, anything is possible”, “The metaverse technology is a driver of social progress”, “Metaverses bring many benefits to people”
CUM: Cryptocurrency Adoption Intention in Metaverses (DV)	5	0.978	“I will use cryptocurrency for virtual commerce in metaverses in the future”, “I will use cryptocurrency for business purposes in metaverses”, “I will use cryptocurrency when I need swift virtual commerce transactions in metaverses”
AIA: AI-Algorithm Awareness (IV)	4	0.910	“I think AI might replace our jobs”, “Given that AI is being widely used in the workplace, I’m concerned about my future in various industry sectors”, “I think there is a possibility that my current job will be replaced by AI”
NLM: Neo-Luddism Perspective on the Metaverse (Mediator)	5	0.925	“The Metaverse is a threat to natural and authentic ways of our lives,” “The Metaverse makes people waste too much time”, “The Metaverse makes people more isolated”
SOP: Social Phobia (Moderator)	5	0.905	“Talking to strangers scares me”, “I avoid talking to people I do not know”, “I avoid speaking to people for fear of embarrassment”
VIE: Virtual Influencer Engagement Intention in Metaverses (DV)	5	0.970	“I intend to engage with virtual influencers in the Metaverse in the near future”, “I predict I would interact with virtual influencers in the Metaverse in the near future,” “I plan to engage with virtual influencers in the Metaverse for virtual commerce in the near future”

.

3.2. Study 2 Theoretical Model and Methodology

The conceptual models for the proposed serial mediation effects of the general ownership perception of NFTs and perceived psychological ownership of NFTs (H9, H10, H11, and H12), as well as the moderation effect of perceived investment value of NFTs, (H13) are presented in Figure 5 and Figure 6, respectively.

3.2.1. Study 2 Respondents and Data Collection

Participants (N = 328; 195 females, 130 males, 2 other, 1 participant preferred not to answer; 66.9% White/Caucasian, 16.9% Black/African American, 6.9% Hispanic/Latin American, 5.1% Asian/Asian Indian, 0.9% American Indian/Alaska Native, 0.6% Hawaiian/Pacific Islander, 2.1% Mixed Race, 0.6% preferred not to answer) were recruited from the CloudResearch Prime Panels who reside in the USA. Qualtrics was utilized as the platform to host the survey questionnaire, and the URL was embedded in the CloudResearch platform. The participants were redirected to the CloudResearch Platform for data collection among the Prime Panels. The principal investigator received ethical approval from the university’s institutional review board (IRB) before data collection. Participants electronically signed the approved informed consent form before proceeding to fill out the survey questionnaire. Using the CloudResearch Prime Panel’s filtering function, those who participated in Study 1 were excluded from the recruitment.

3.2.2. Study 2 Measures

All items were measured with 7-point Likert scales ranging from 1 (strongly disagree) to 7 (strongly agree). Acknowledgement of the nature of NFTs (independent variable) was measured with 5 items. General perception of NFT ownership (mediator) was measured with 3 items. Perceived psychological ownership of NFTs (mediator) was measured with 5 items. Perceived investment value of NFTs (moderator) was measured with 3 items. Behavioral intention to use NFTs in metaverses (dependent variable) was measured with 7 items. The list of variables with the number of items, the results of reliability testing (Cronbach’s Alpha), and sample items for Study 2 are presented in

Table 2. List of variables with results of reliability testing (Cronbach’s Alpha), and sample items for Study 2.

Variable	Number of Items	Cronbach’s Alpha	Sample Items
NFT: Acknowledgment of the Nature of NFTs (IV)	5	0.905	“NFTs are unique”, “NFT cannot be copied, substituted, or subdivided”, “NFTs are non-fungible”
GPO: General Perception of NFT Ownership (Mediator)	3	0.903	“NFTs allow the buyer to own the original item”, “NFTs can serve as a proof of ownership”, “NFTs can be used to represent ownership of unique items”
PPO: Perceived Psychological Ownership of NFTs (Mediator)	5	0.954	“I sense that NFTs could be mine”, “I feel some degree of personal ownership for NFTs”, “I think I can own NFTs”
PIV: Perceived Investment Value of NFTs (Moderator)	3	0.959	“NFTs are valuable”, “NFTs are assets”, “NFTs are worth investing in”
NFM: Behavioral Intention to use NFTs in Metaverses (DV)	7	0.980	“I predict I would use NFTs (non-fungible tokens) in metaverses in the near future”, “I intend to purchase NFTs (non-fungible tokens) using cryptocurrency in metaverses in the near future”, “I intend to sell NFTs (non-fungible tokens) using cryptocurrency in metaverses in the near future”

.

4. Results

4.1. Study 1 Results

4.1.1. Study 1 Descriptive Statistics

Descriptive statistics and a correlation matrix of Study 1 are presented in

Table 3. Descriptive statistics and correlation matrix for Study 1 (N = 386).

Variable	M	SD	1. BTP	2. BTR	3. TPM	4. CUM	5. AIA	6. NLM	7. SOP	8. VIE
1. BTP: Blockchain Transparency (IV)	4.3203	1.30025	1
2. BTR: Blockchain Trust (Mediator)	3.9017	1.57771	0.789 **	1
3. TPM: Technopian Perspective on the Metaverse (Moderator)	4.3710	1.62717	0.586 **	0.577 **	1
4. CUM: Cryptocurrency Usage Intention in the Metaverse (DV)	3.1000	2.01285	0.570 **	0.627 **	0.511 **	1
5. AIA: AI-Algorithm Awareness (IV)	3.5162	1.68026	0.116 *	0.114 *	0.121 *	0.221 **	1
6. NLM: Neo-Luddism Perspective on Metaverses (Mediator)	3.8420	1.61615	−0.009	−0.049	−0.181 *	−0.032	0.446 **	1
7. SOP: Social Phobia (Moderator)	3.5000	1.64711	0.041	0.034	0.035	0.028	0.290 **	0.243 **	1
8. VIE: Virtual Influencer Engagement Intention in the Metaverse (DV)	3.1922	1.85299	0.493 **	0.569 **	0.616 **	0.690 **	0.221 **	−0.162 **	0.028	1

* p < 0.05 (Pearson’s correlation is significant at the 0.05 level, 2-tailed). ** p < 0.01 (Pearson’s correlation is significant at the 0.01 level, 2-tailed).

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4.1.2. Mediation Effect of Trust in Blockchain Technologies

Data were analyzed using PROCESS version 4.2 Macro with 5000 bootstrap samples [100]. PROCESS is a widely used regression-based path analysis modeling tool to estimate direct and indirect effects in single and multiple mediator models, two-way interactions in moderation models, and more [100]. PROCESS Model 4 was used to test the mediating effect of trust in blockchain technologies. Blockchain transparency perception was a positive predictor of trust in blockchain technologies (b = 0.9571, t = 25.0842, p = 0.000), thus supporting H1. Trust in the blockchain technologies was a positive predictor of behavioral intention to use cryptocurrency in metaverses (b = 0.5958, t = 7.3357, p = 0.000), thus supporting H2. The results revealed a significant indirect effect of trust in blockchain technologies on behavioral intention to use cryptocurrencies in metaverses (b = 0.5702, Lower CI = 0.3935, Upper CI = 0.7394), as shown in Figure 7, thus supporting H3. Furthermore, the direct effect of blockchain transparency perception on behavioral intention in presence of the mediator (trust in the blockchain technologies) was also found significant. Hence, trust in blockchain technologies partially mediated the relationship between blockchain transparency perception and behavioral intention to use cryptocurrencies in metaverses. A mediation analysis summary for cryptocurrencies is presented in

Table 4. The mediation effect of trust in blockchain technologies (Study 1: H3).

Relationship	Total Effect	Direct Effect	Indirect Effect	Confidence Interval		Conclusion
				Lower Bound	Upper Bound
Blockchain Transparency Perception → Trust in Blockchain Technologies → Intention to Adopt Cryptocurrency in Metaverses	0.8756 (p = 0.0000)	0.3053 (p = 0.0021)	0.5702	0.3935	0.7394	Partial Mediation

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4.1.3. Moderation Effect of Technopian Perspectives Regarding Metaverses

PROCESS Model 1 was used to test the moderating effect of technopian perspectives regarding metaverses, as a continuous variable, on the relationship between blockchain transparency perception and behavioral intention to use cryptocurrencies in metaverses. The results revealed a significant moderating effect of technopian perspective (b = 0.1373, t = 4.7257, p = 0.0000), supporting H4. The results of using slope analysis to further understand the nature of the moderating effects are graphically presented in Figure 8. As shown in Figure 8, the line is steeper for high technopians, which shows the impact of blockchain transparency perception is stronger with a high level of technopian perspective. Furthermore, as the level of blockchain transparency perception increased, the strength of the relationship between technopian perspectives and behavioral intention to use cryptocurrencies in metaverses increased.

4.1.4. Mediation Effect of Neo-Luddism Regarding Metaverses

PROCESS Model 4 was used to test the mediating effect of Neo-Luddism. AI-algorithm awareness was a positive predictor of Neo-Luddism perspective on the Metaverse (b = 0.4245, t = 9.6373, p = 0.000), thus supporting H5. A Neo-Luddism perspective on metaverses was a negative predictor of behavioral intention to engage with virtual influencers in the metaverse (b = −0.3711, t = −6.0767, p = 0.000), thus supporting H6. The results revealed a significant indirect effect of Neo-Luddism perspective regarding metaverses on behavioral intention to engage with virtual influencers in metaverses (b = −0.1575, Lower CI = −0.2435, Upper CI = −0.0859), thus supporting H7. Furthermore, the direct effect of AI-algorithm awareness on behavioral intention to engage with virtual influencers in presence of the mediator (Neo-Luddism) was also found to be significant. Hence, Neo-Luddism partially mediated the relationship between AI-algorithm awareness and behavioral intention to engage with virtual influencers in metaverses, as shown in Figure 9. A mediation analysis summary for virtual influencers is presented in

Table 5. The mediation effect of Neo-Luddism (Study 1: H7).

Relationship	Total E.	Direct Effect	Indirect Effect	Confidence Interval		Conclusion
				Lower Bound	Upper Bound
AI-Algorithm Awareness → Neo-Luddism Perspective on the Metaverse → Intention to Engage with Virtual Influencers in Metaverses	0.2443 (p = 0.0000)	0.4018 (p = 0.0000)	−0.1575	−0.2435	−0.0859	Partial Mediation

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4.1.5. Moderation Effect of Social Phobia

PROCESS Model 1 was used to test the moderating effect of social phobia, as a continuous variable, on the relationship between AI-algorithm awareness and behavioral intention to engage with virtual influencers in metaverses. The results revealed a significant moderating effect of social phobia (b = 0.1613, t = 5.9375, p = 0.0000), supporting H8. The results of using slope analysis to further understand the nature of the moderating effects are graphically presented in Figure 10. As shown in Figure 10, the line is steeper for high social phobia, which shows that at high levels of social phobia, the impact of AI-algorithm awareness is stronger. Furthermore, as the level of AI awareness increased, the strength of the relationship between social phobia and behavioral intention to engage with virtual influencers in metaverses decreased.

4.2. Study 2 Results

4.2.1. Study 2 Descriptive Statistics

The descriptive statistics and correlation matrix of Study 2 are presented in

Table 6. Descriptive statistics and correlation matrix for Study 2 (N = 328).

Variable	M	SD	1. NFT	2. GPO	3. PPO	4. PIV	5. NFM
1. NFT: Acknowledgment of the Nature of NFTs (IV)	4.8163	1.54688	1
2. GPO: General Perception of NFT Ownership	4.8697	1.71161	0.733 **	1
3. PPO: Perceived Psychological Ownership of NFTs (Mediator)	3.9927	1.93388	0.585 **	0.516 **	1
4. PIV: Perceived Investment Value of NFTs (Moderator)	4.5110	1.87192	0.672 **	0.720 **	0.725 **	1
5. NFM: Behavioral Intention to use NFTs in Metaverses (DV)	3.5558	2.02372	0.461 **	0.396 **	0.755 **	0.624 **	1

** p < 0.01 (Pearson’s correlation is significant at the 0.01 level, 2-tailed).

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4.2.2. Serial Mediation Effects of the General Perception of NFT Ownership and Psychological Ownership of NFTs

Data were analyzed using PROCESS version 4.2 Macro with 5000 bootstrap samples [100]. PROCESS Model 6 was used to test the serial mediating effects of the general perception of NFT ownership and psychological ownership of NFTs. Acknowledgment of the nature of NFTs was a positive predictor of the general perception of NFT ownership (b = 0.8110, t = 19.2849, p = 0.000) and perceived psychological ownership of NFTs (b = 0.5590, t = 6.8426, p = 0.0034), thus supporting H9a and H9b. The general perception of NFT ownership was not a significant predictor of behavioral intention to use NFTs in metaverses (b= −0.0217, t = −0.3405, p = 0.7337), thus not supporting H10a. However, psychological ownership of NFTs was a positive predictor of behavioral intention to use NFTs in metaverses (b = 0.7753, t = 16.3309, p = 0.000), thus supporting H10b. The results revealed a significant indirect effect of psychological ownership on behavioral intention to use NFTs in metaverses (b = 0.5680, Lower CI = 0.4469, Upper CI = 0.6911), as well as a significant indirect effect of serial mediators (general perception of NFT ownership and psychological ownership of NFTs) (b = 0.1041, Lower CI = 0.0279, Upper CI = 0.1941), as presented in Figure 11, thus supporting H11 and H12. However, the direct effect of acknowledgement of the nature of NFTs on behavioral intention to use NFTs in metaverses in presence of the mediators (general perception of NFT ownership and psychological ownership) was found to be non-significant. Hence, the general perception of NFT ownership and psychological ownership of NFTs totally and serially mediated the relationship between acknowledgement of the nature of NFTs and behavioral intention to use NFTs in metaverses. A serial mediation analysis summary for Study 2 is presented in

Table 7. The serial mediation effects of psychological ownership of NFTs (Study 2: H11, H12).

Relationship	Total Effect	Direct Effect	Indirect Effect	Confidence Interval		Conclusion
				Lower Bound	Upper Bound
NFT Nature Acknowledgment → Psychological Ownership of NFTs → Intention to Use NFTs in Metaverses	0.5999 (p = 0.0000)	0.0318 (p = 0.5883)	0.5680	0.4469	0.6911	Total Mediation
NFT Nature Acknowledgement → General Ownership Perception of NFTs → Psychological Ownership of NFTs → Intention to Use NFTs in Metaverses	0.5999 (p = 0.0000)	0.0475 (p = 0.5257)	0.1041	0.0279	0.1941	Total Serial Mediation

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4.2.3. Moderation Effect of Investment Value of NFTs

PROCESS Model 1 was used to test the moderating effect of the investment value of NFTs, as a continuous variable, on the relationship between NFT nature acknowledgement and behavioral intention to use NFTs in metaverses. The results revealed a significant moderating effect of the perceived investment value of NFTs (b = 0.1026, t = 3.9890, p = 0.0001), supporting H13. The results of using slope analysis to further understand the nature of the moderating effects are graphically presented in Figure 12. As shown in Figure 12, the line is steeper for participants with high perceived investment value of NFTs, which shows that for high levels of perceived NFT investment value, the impact of acknowledgement of the nature of NFTs is stronger. Furthermore, as the level of acknowledgement of the nature of NFTs increased, the strength of the relationship between the investment value of NFTs and behavioral intention to use NFTs in metaverses increased.

5. Discussion

5.1. Summary of Key Findings and Theoretical Implications

The current research adds conceptual foundations and theoretical discussions about mediators and moderators relevant to cryptocurrencies, NFTs, and AI-powered virtual influencers in metaverse-based virtual commerce to the technovation and AI-enabled interactive service marketing literature. Study 1 reports mediating effects of trust in blockchain technologies and two-way interaction effects of consumers’ technopian perspective regarding metaverses (moderator) and blockchain transparency perception on behavioral intention to use cryptocurrencies in AI blockchain-enabled metaverses. Study 1 also reports the mediating effects of Neo-Luddism perspectives regarding metaverses and the two-way interaction effects of consumers’ social phobia (moderator) and AI-algorithm awareness on behavioral intention to engage with AI-powered virtual influencers in metaverses. Study 2 reports the serial mediating effects of the general perception of NFT ownership and psychological ownership of NFTs, as well as the two-way interaction effects of consumers’ perceived investment value of NFTs and acknowledgment of the nature of NFTs on behavioral intention to use NFTs in AI-enabled metaverses.

The theoretical contributions of Study 1 regarding virtual currencies in AI-powered metaverses include (1) adding conceptual foundations for, theoretical discussions about, and empirical support of the important roles played by consumers’ blockchain transparency perception and trust in blockchain technologies in increasing their willingness to use cryptocurrencies for virtual commerce in AI-powered metaverses to the extant literature on blockchain-enabled technovation [35] and cryptocurrency adoption [22,37,43,54,101]; and (2) adding philosophical discussion about consumers’ ideological perspectives (technopians and Neo-Luddites) on the emerging virtual world of AI-powered metaverses.

Building upon the empirical support for the foundational propositions about blockchain technologies and cryptocurrencies, Study 2 further contributes to the literature on “digital materiality” [25] and “algorithmic collectibles” [15] by evaluating the roles of psychological ownership of emerging forms of digital consumption objects. Study 2 also contributes to the emerging literature on the new types of ownership in AI-enabled metaverses [15]. More specifically, Study 2 provides the first empirical evidence about the important roles played by not only fundamental understanding of and general perception of NFT ownership (i.e., “In general, NFTs can certify ownership of original digital consumption objects”) but also psychological ownership and “strong feelings of ownership toward digital possessions and some possibilities for collecting them” [15] (p. 198) (i.e., “I can also own NFTs and NFTs can be mine”) in inducing consumers’ willingness to use NFTs in metaverse-based virtual commerce and creative service industries. Furthermore, the original empirical findings about the two-way interaction effects between consumers’ acknowledgment of the very nature of NFTs (unique, authentic, scarce, collectible, and non-fungible) and their perception of the investment value of NFTs from the consumer behavior perspective contribute to the fintech service sector and the finance/banking service literature, mostly examined from the macroeconomic perspective, on cryptocurrencies and NFTs [90,91].

5.2. Practical and Managerial Implications

Marketing managers and branding advisors can persuade consumers to purchase NFTs owing to their unique characteristics, including “scarcity, non-fungibility, proven authenticity, proof of ownership, royalties, and direct distribution infrastructure” [77]. Empirical findings from Study 1 may provide managerial implications regarding how to increase consumers’ behavioral intention to trade cryptocurrencies in AI-powered metaverses: campaigns designed to increase consumers’ awareness of the nature of blockchain technologies (i.e., blockchain transparency) and marketing efforts to build consumers’ trust in blockchain technologies may be effective strategies to induce consumers’ cryptocurrency use intentions, as empirically shown in the mediation analysis (Figure 7 and Table 4).

Furthermore, it may be helpful to acknowledge different market segments depending on consumers’ optimistic views on metaverses and virtual commerce, as well as understand the interaction between consumers’ blockchain transparency perception and their technopian views regarding metaverses in technovation and the service industries (Figure 2 and Figure 8). More specifically, those consumers who are optimistic about metaverses and whose perception of blockchain transparency is high are the most promising segment in the cryptocurrency-based virtual commerce market and AI-enabled virtual service industries. In contrast, consumers who are pessimistic and skeptical about metaverses and whose perception of blockchain transparency is low are the most difficult market segment to persuade.

Regarding consumers’ intention to trade NFTs in metaverses, Study 2 provides empirical data that indicate that those consumers who acknowledge the non-fungible nature of NFTs and perceive the investment value of NFTs to be high will certainly be early and enthusiastic adopters of NFTs (Figure 11). This finding has important managerial implications, especially for luxury brands since consumers’ desire for exclusivity, uniqueness, authenticity, and scarcity is the major impetus for luxury brand product consumption (i.e., material consumption) and possession, as well as for a luxury experience (i.e., experiential consumption such as travel, hospitality, entertainment, etc.) in technovation and various service sectors. NFTs, as an emerging form of “materializing digital collecting” [25], could be leveraged as an alternative platform for consumers to expand conspicuous consumption and to showcase digital possessions [102], as well as an innovative channel for brands to strategically “manufacture scarcity in the digital economy” [103]. Brands, especially luxury brands, can turn their physical products into NFTs to increase brand awareness, create cross-selling opportunities, boost perceived ownership of specific components (e.g., products, logos, images) of their brands, and even blend digital and physical product ownership [104,105,106].

The current study can also provide practical implications for the AI-empowered, metaverse-based gaming industry [107] and creative industry entrepreneurs [108,109]. The amalgamation of blockchain technologies and the gaming industry brought about the play-to-earn tokens in metaverses [5]. Market reports show that, since July 2020, the most exchanged NFTs belong to the gaming industry [110]. Many digital game-based virtual worlds already support NFT purchases for a variety of in-game items [106]. The findings from Study 2 suggest that game designers, NFT-enabled entrepreneurs, and creative directors need to highlight the key characteristics of NFTs (uniqueness, non-interchangeability, authenticity, scarcity, and collectability), ownership rights (Figure 11 and Table 7), and the long-term investment value of NFTs (Figure 12) in order to foster consumers’ intention to trade NFTs and crypto-assets in AI-powered metaverses and other creative service industries. Furthermore, since ownership is the primary impetus that enables the extraction of economic benefits and drives entrepreneurial pursuits [111], the current findings about the significant role of psychological ownership may serve as a steppingstone toward the examination of actual ownership in metaverse-based technovation and blockchain-enabled entrepreneurship.

5.3. Limitations and Suggestions for Future Research

Several limitations of the current research can be discussed to provide constructive suggestions for future research on cryptocurrencies and NFT-powered technovation in blockchain-enabled metaverses. First, this study measured only behavioral intentions to use cryptocurrencies and to trade NFTs in metaverses. Relatedly, all measures were based on self-reported Likert items using a single survey questionnaire, which may inflate associations due to shared method variance, thus raising methodological concerns about multicollinearity. The cross-sectional survey design fails to capture the market dynamics, since attitudes toward NFTs and crypto-assets fluctuate dramatically with the market conditions. Longitudinal surveys may address this shortcoming, and experimental designs will even strengthen the causal inferences. For example, future research can provide participants with hypothetical scenarios or experimental settings that prompt and measure consumers’ actual cryptocurrency/NFT purchase behavior (e.g., retail, gaming, and entertainment industry) and investment behavior (e.g., fintech and banking industries). Follow-up studies, using the mock-cryptocurrencies provided by the researcher, can also prompt participants to purchase NFTs recommended by AI-powered virtual influencers in an experimental setting.

Second, this study only considered consumers’ technopian perspective on metaverses as the individual difference factor that plays a moderating role in explaining the relationship between blockchain transparency perception and behavioral intention to use cryptocurrencies in blockchain-enabled metaverses. Follow-up studies on cryptocurrencies and NFTs need to test the moderating effects of consumers’ other individual difference factors relevant to ownership and possession. Such variables include materialism (versus immaterialism), materialistic envy, social comparison, need for uniqueness, and need for status.

Third, since the prices of NFTs and collectibles vary across different categories such as arts, music, sports, fashion, luxury goods, in-game items, entertainment tickets, club memberships, etc. [15,95,112], future research can employ more sophisticated experimental designs to test the effects of different digital product/service categories and various types of NFTs on consumers’ acknowledgement of the nature of NFTs, perceived investment value of NFTs, and willingness to spend cryptocurrencies to trade NFTs in the technovation marketplace. Furthermore, there exist different categories of virtual influencers and their associated NFTs, such as beauty/fashion/health, sports/entertainment, food/travel/lifestyle, money/business/financial investment, etc. Future research needs to address the effects of industry sectors/product categories and NFTs that different types of virtual influencers may promote, depending on the market segment. For example, virtual influencers in the fashion industry may need to express different personalities and possess different attributes than those influencers in the fintech industry in promoting specific NFTs. Additionally, news about crypto fluctuation (hypes versus fallout) might have induced the current participants’ optimism versus skepticism about cryptocurrencies and NFTs.

Fourth, NFT “ownership” is operationalized narrowly in the current study, with the focus only on consumers’ psychological ownership, thus overlooking legal, regulatory, and technical ownership complexities. Relatedly, several relevant cross-disciplinary studies and discussions are missing, such as the evolution of optimization strategies of a PBFT (Practical Byzantine Fault Tolerance) consensus algorithm for consortium blockchains [113] and AI-driven optimization of blockchain scalability, security, and privacy protection [114]. For example, the practicality of the recommendations from this study, such as encouraging firms to rely on NFT scarcity and blockchain transparency, may be limited, since this study does not address regulatory uncertainty, the environmental sustainability concerns of blockchain, consumer privacy concerns, and so forth. Follow-up studies need to address these legal, regulatory, and privacy issues.

Lastly, the participants were limited to panels recruited from the USA using the CloudResearch panels. The USA-centric participants restrict the generalizability of the sample, especially given the global and culturally diverse nature of AI and metaverse adoption. Follow-up research among diverse populations around the globe and comparative studies will provide deeper insights on the similarities and differences among diverse populations with different languages, cultural backgrounds, economic systems, and value systems.

6. Conclusions

Despite several limitations, this research addresses underexplored topics in AI-powered technovation: blockchain-powered cryptocurrencies, NFTs, and AI-enabled virtual influencers in metaverses. By addressing the overarching theme of the Special Issue (“When Trust Meets Intelligence: The Intersection Between Blockchain and Artificial Intelligence”) and specifically examining the sub-topic of “AI and blockchain applications in metaverses,” this research may contribute to the theoretical understanding of socio-psychological factors affecting consumers’ adoption of AI-enabled blockchain systems. The current study can provide conceptual frameworks and theoretical foundations for future scholarly research on consumers’ adoption of cryptocurrencies and investment in NFTs in metaverse-based technovation and blockchain-enabled interactive marketing. By exploring these dynamics, researchers and industry experts can better understand how trust and perceived intelligence shape consumer behavior in digital spaces. This knowledge will be essential for developing strategies that enhance user engagement and drive the growth of blockchain technologies in the evolving metaverse landscape.