“In the Metaverse We (Mis)trust?” Third-Level Digital (In)equality, Social Phobia, Neo-Luddism, and Blockchain/Cryptocurrency Transparency in the Artificial Intelligence-Powered Metaverse

Abstract

The Metaverse, powered by a variety of key innovative technologies including 3D virtual reality (VR)/augmented reality (AR), artificial intelligence (AI), blockchain/cryptocurrency-based non-fungible tokens (NFTs), and the Internet of Things, has been proposed as the future of a virtual universe for education, work, business, and commerce. This research (∑ N = 954) presents the results of three cross-sectional surveys that examine the influence of third-level digital (in)equality and consumer (mis)trust on Metaverse adoption intention. Study 1, focusing on the Metaverse for hybrid education, reports the mediating effect of (mis)trust in the Metaverse on the relationship between the educational dimension of third-level digital (in)equality and behavioral intention to adopt the Metaverse for virtual learning as well as the moderating effect of social phobia. Study 2, focusing on the Metaverse for remote working, reports the mediating effect of (mis)trust in the Metaverse on the relationship between the economic labor dimension of third-level digital (in)equality and Metaverse adoption for virtual working as well as the moderating effect of neo-Luddism. Study 3, focusing on the Metaverse for business, reports the mediating effect of (mis)trust in the Metaverse on the relationship between the economic commerce dimension of third-level digital (in)equality and Metaverse adoption for virtual commerce as well as the moderating effect of blockchain/cryptocurrency transparency perception. This research can provide theoretical frameworks to examine people's hopes and fears about the Metaverse and consequential adoption versus non-adoption of the Metaverse for hybrid education, hybrid remote working, and omni-channel virtual commerce. Practical, managerial, and policy implications for the Metaverse and the NFT market are also discussed.

Introduction

The Metaverse, coined by cyberpunk author Neal Stephenson, was initially conceptualized as a virtual reality (VR)-based interface, where humans, in the form of virtual avatars, interact with one another in immersive virtual environments.¹ “Virtual worlds,” “mirror worlds,” “augmented reality,” and “lifelogging” have been proposed as the four key components of the digital future of the Metaverse.²

In light of the evolving nature of the Metaverse in the emerging Web 3.0 environment, the Metaverse can be contemporarily defined as “a network of 3-D virtual worlds where people can interact, do business, and forge social connections through their virtual avatars.”³

More specifically, the Metaverse can be described as “an augmented digital world that is blending physical and virtual spaces through the use of extended reality (XR) and artificial intelligence-based systems for uses to interact, and/or trade virtual goods or services through cryptocurrencies (e.g., NFTs).”^4(p18) The Metaverse has been proposed as the next big thing for social connection.^5,6

In the Metaverse, people can engage in a variety of activities, including avatar-based real-time collaboration, multi-user game play, remote working, omni-channel marketing, virtual social gathering, hybrid learning, telemedicine, and so forth.^7–10 Despite the great potential and many promises of the Metaverse, the interconnected nature of the Metaverse may raise users' concerns about personal privacy, information security, and (dis)trust in multi-user virtual environments (MUVE).¹¹

The Metaverse environments integrating immersive VR and emerging technologies, including artificial intelligence (AI) and Web 3.0, may introduce new paradigms for how we learn (shared, persistent, decentralized, and hybrid learning),^5,12 how we work (e.g., hybrid, virtual, and remote work environments),^5,13 and how we do business (e.g., virtual commerce via blockchain/cryptocurrency and virtual non-fungible tokens [NFTs]).^13,14

The adoption and use of the Metaverse for hybrid education, remote work, and omni-channel business entail both promises and challenges. With regard to the potential of the Metaverse for hybrid education, the Metaverse can provide both instructors and students with alternative ways of teaching and learning such as engaging instructional strategy for inverted class/flipped classroom, collaborative learning via virtual avatars, diversification/scalability of the spectrum of teaching/learning curriculum according to instructors/students' research and academic needs, creation of virtual spaces for extracurricular activities, and so forth.¹²

Regarding the potential of the Metaverse for virtual working, the Metaverse can be proposed a virtual workplace solution that provides platforms for virtual offices, meeting rooms in real-time, efficient employee skill development/training, immersive teamwork/collaboration, and more.³

Metaverse may also offer exciting opportunities for virtual commerce such that there is an emerging business model of providing new products to consumers' avatars, which is called Direct-to-Avatar (D2A) model.¹⁵ The Metaverse also aligns with an emerging consumer marketing trend of “experiential luxury,” which indulges consumers' senses on multiple levels, transporting consumers to an immersive environment.¹⁶

In light of the potential ethical issues in the Metaverse, the current study proposes theoretical models and presents empirical data on the predictors of users' (dis)trust and behavioral intention (not) to adopt the Metaverse in (a) interactive learning environments for virtual learning, (b) hybrid work environments for virtual working, and (c) integrated marketing environments for virtual commerce.

The conceptual and theoretical models propose relevant variables as predictors of (non)adoption of the Metaverse, including (a) third-level digital inequality¹⁷ (i.e., gaps in users' capacity to translate their digital access and use into offline outcomes and resources); (b) concerns about privacy and data security¹¹ in the Metaverse; and (c) feelings of (dis)trust in the Metaverse. The models propose positive correlations among “equality, trust, and adoption” as well as positive correlations among “inequality, mistrust, and non-adoption.”

This study also aims at examining the moderating effects of users' (a) social phobia (defined as “anxiety or apprehension experienced in social or performance situations”),^18(p94),19 (b) neo-Luddism (referring to “critical evaluation of our relationship with technology” and “the task of putting new technology to examination”)^{20(pp263,266),21} perspective, and (c) blockchain/cryptocurrency transparency (blockchain referring to “a distributed database that stores transactions in cryptographically linked blocks, which creates an immutable ledger”^13(p605) and blockchain/cryptocurrency transparency defined as “establishment and maintenance of the decentralized database network which is stored in the chronological order of cryptographically time-stamped entries which cannot be manipulated, amended, or removed”)^22(p3) on intention to use the Metaverse for (a) virtual education; (b) virtual working; and (c) virtual commerce, respectively.

Literature Review and Hypotheses

One of the important principles for designing a humane Metaverse is to embrace inclusion and equity.²³ The first-level digital inequality refers to unequal access to the Internet,²⁴ whereas the second-level digital inequality refers to inequalities in Internet skills and uses.²⁵ The third-level digital divides refer to differences in the gains from Internet use.²⁶

“Third-level divides, therefore, relate to gaps in individuals' capacity to translate their Internet access and use into favorable offline outcomes.”^{17 (p30)} It can be predicted that people with higher (vs. lower) educational/economic/commercial digital access and usage show higher (vs. lower) trust in the Metaverse (H1/H5/H9) since they tend to believe that they can further (vs. cannot) benefit from access to and usage of emerging technologies.

Their trust (vs. mistrust) in the Metaverse, in turn, will be a positive antecedent of intention to adopt (vs. not to adopt) the Metaverse for virtual learning/virtual working/virtual commerce (H2/H6/H10). Trust is an important mediator in consumers' adoption of a variety of emerging technologies (H3/H7/H11).^22,27,28

The potential of VR as an educational and diagnostic tool for people with social anxiety has been reported.^29–31 Prior research has explicated the theoretical relevance of social phobia to VR-based education.^29–31 People with different levels of social phobia may indicate differential levels of Metaverse adoption intention, depending on their capacity to translate their digital access into educational outcomes in the real world.

It can be hypothesized that there will be a two-way interaction effect of the educational dimension of the third-level digital (in)equality and social phobia such that highly social phobic consumers with lower digital resources (higher digital inequality) may adopt the Metaverse as an educational solution to mitigate their social anxiety, whereas consumers with higher digital resources (lower digital inequality) are willing to adopt the Metaverse for virtual learning regardless of their social phobia level (H4).

The emergence of AI that may surpass human intelligence is perceived as a threat to human existence.³² Neo-Luddism serves as relief from the fear of the eerie and the unknown.^33,34 Neo-Luddism is historically rooted in “Luddites” and the concept of “Luddism” (human resistance to and protesting against the introduction of machinery perceived as a threat to human labor in working environments).³⁴

Thus, neo-Luddism is theoretically relevant to the “labor” dimension of digital (in)equality in the contemporary context of the digital transformation of employment.³⁵ AI-driven digital transformation of the economy and consequent ramifications for labor markets³⁵ makes it imperative to examine the role of neo-Luddism in relation to the emerging concept of the Metaverse-based working environment.

Therefore, it can be hypothesized that there will be a two-way interaction effect of the economic labor dimension of the third-level digital (in)equality and neo-Luddism such that people with high neo-Luddism with lower digital resources (higher digital inequality) are least likely to adopt the Metaverse for virtual working whereas those with higher digital resources (lower digital inequality) and lower neo-Luddism are most likely to adopt the Metaverse for virtual working (H8).

Blockchain technologies, which fuel and drive innovation and increase efficiencies in a variety of new domains including creative digital arts rights management, supply chain management, entrepreneurship, health care, etc., form the bedrock for cryptocurrencies and play a vital role in virtual commerce.³⁶ Transparency refers to “the extent to which information is easily accessible to both counterparts in exchange and external observers.”^37(p4) Blockchain transparency is an important factor to consider in Metaverse-based virtual commerce since “a platform that allows the maintenance of a common database for consumers devoid of a trusted central controller”^22(p3) may impact consumers' adoption of the emerging platform for virtual commerce.

Transparency, therefore, is a fundamental parameter of blockchain technology³⁷ in the novel context of virtual commerce in the Metaverse. It can be hypothesized that there will be a two-way interaction effect of the economic commerce dimension of the third-level digital (in)equality and blockchain/cryptocurrency transparency perception such that people with higher blockchain transparency perception with higher digital resources (lower digital inequality) are most likely to adopt the Metaverse for virtual commerce whereas those with lower digital resources (higher digital inequality) and lower blockchain transparency perception are least likely to adopt the Metaverse for virtual commerce (H12).

Based on these theoretical rationales and preliminary empirical findings, the following hypotheses are proposed for Study 1 (H1, H2, H3, and H4), Study 2 (H5, H6, H7, and H8), and Study 3 (H9, H10, H11, and H12) and the conceptual models are presented in Figures 1–3, respectively.

FIG. 1.

Study 1: mediation conceptual model (left) and moderation conceptual model (right).

FIG. 2.

Study 2: mediation conceptual model (left) and moderation conceptual model (right).

FIG. 3.

Study 3: mediation conceptual model (left) and moderation conceptual model (right).

H1: The third-level digital inequality (educational dimension) is a negative predictor of trust in the Metaverse (People's capacity to translate their digital access and use into offline educational outcomes and resources is a positive predictor of trust in the Metaverse).

H2: Trust in the Metaverse is a positive predictor of behavioral intention to adopt the Metaverse for virtual learning.

H3: Trust mediates the relationship between the third-level digital (in)equality (educational dimension) and behavioral intention to adopt the Metaverse for virtual learning.

H4: Social phobia moderates the relationship between the third-level digital (in)equality (educational dimension) and behavioral intention to adopt the Metaverse for virtual learning.

H5: The third-level digital inequality (economic labor dimension) is a negative predictor of trust in the Metaverse (People's capacity to translate their digital access and use into offline economic labor outcomes and resources is a positive predictor of trust in the Metaverse).

H6: Trust in the Metaverse is a positive predictor of behavioral intention to adopt the Metaverse for remote working.

H7: Trust mediates the relationship between the third-level digital (in)equality (economic labor dimension) and behavioral intention to adopt the Metaverse for virtual working.

H8: Neo-Luddism moderates the relationship between the third-level digital (in)equality (economic labor dimension) and behavioral intention to adopt the Metaverse for virtual working.

H9: The third-level digital inequality (economic commerce dimension) is a negative predictor of trust in the Metaverse (People's capacity to translate their digital access and use into e-commerce outcomes and resources is a positive predictor of trust in the Metaverse).

H10: Trust in the Metaverse is a positive predictor of behavioral intention to adopt the Metaverse for virtual commerce.

H11: Trust mediates the relationship between the third-level digital (in)equality (economic commerce dimension) and behavioral intention to adopt the Metaverse for virtual commerce.

H12: Blockchain/cryptocurrency transparency perception moderates the relationship between the third-level digital (in)equality (economic commerce dimension) and behavioral intention to adopt the Metaverse for virtual commerce.

Methods

Control variables (covariates) and outlier control

Participants' demographic variables (age, gender, education level, income level, and ethnicity)¹⁷ were measured as statically controlled variables and entered in the PROCESS models as covariates. Regarding outlier control and outlier elimination procedure, three Distance criteria (Mahalanobis, Cook's, and Leverage values) in the SPSS regression analysis were examined. Based on the results of the outlier elimination procedure, outliers were excluded from the final data analysis.

Respondents, procedure, and measures

Participants were recruited from the CloudResearch Prime Panels³⁸ in November 2022. Using the CloudResearch filtering criterion,³⁸ participants were allowed to participate in only one of the three surveys. The principal investigator received approval from the university's institutional review board (IRB) before data collection. A total of 954 U.S. residents (Study 1: N = 321 after outlier elimination; Study 2: N = 318 after outlier elimination; Study 3: N = 315 after outlier elimination) completed the survey. Socio-demographic profiles of the participants in each study are presented in Table 1.

Table 1.

Demographic Profiles of Participants in Study 1, Study 2, and Study 3

Demographic variables	Categories	Study 1 (N = 321), percent	Study 2 (N = 318), percent	Study 3 (N = 315), percent
Gender	Females	60.4	61	66.3
	Males	38.9	37.7	33.7
	Others	0.1	0.6
	Preferred not to answer	0.6	0.6
Age	≤45	49.2	52.8	44.6
	≤65	24.8	28	32.2
	66+	26	19.2	23.2
Education	High school	31.7	39.6	34
	College	54.2	50.4	55.2
	Masters, PhD, above	12.5	10	10.5
	Preferred not to answer	1.5		0.3
Income	≤$49,999	51.7	62.2	52.1
	≤$99,999	27	24.5	28.6
	≤$149,999	11	7.6	10.1
	$150,000+	6.9	3.8	6
	Preferred not to answer	3.4	1.9	3.2
Ethnicity	White/Caucasian	71.8	67.9	75.9
	Black/African American	16.9	19.2	15.2
	Hispanic/Latin American	5	3.5	3.8
	Asian/Asian Indian	3.1	4.4	4.1
	American Indian/Alaska Native	0.3	0.9
	Native Hawaiian/Pacific Islander		0.3	0.3
	Mixed race	0.9	2.8	0.3
	Other	0.3	0.3	0.3
	Preferred not to answer	1.6	0.6
Metaverse awareness	Yes vs. No	68.3 vs. 31.7	73.2 vs. 26.8	66.3 vs. 33.7
Metaverse experience	Yes vs. No	18.8 vs. 81.2	22.7 vs. 77.3	21 vs. 79
Metaverse dissemination	Yes vs. No	12.8 vs. 87.2	20.8 vs. 79.2	14.6 vs. 85.4

Participants' awareness of, experience with, and dissemination of the Metaverse were measured with three questions (“Have you ever heard of a new technology called the Metaverse?,” “Have you ever experienced the Metaverse?,” “Have you ever used social media to share your Metaverse experience?”) with dichotomous scales (Yes/No) (Table 1).

After measuring participants' awareness, experience, and dissemination, a brief description about the concept of the Metaverse was provided (“Metaverse is an AI-powered virtual world in which people can work, learn, shop, and interact with others. The Metaverse uses virtual reality (VR), augmented reality (AR), and artificial intelligence (AI) technologies to transport people to a virtual world.”).

Third-level digital inequality, as the independent variable, was measured with the third-level digital divide scales¹⁷ (e.g., “Through the Internet ….” “I followed a course that I would not have been able to follow offline” [educational dimension] for Study 1 [Cronbach's α = 0.821]; “I found a (better) job” [economic labor dimension] for Study 2 [Cronbach's α = 0.892]; “I bought a product more cheaply than I could in the local store” [economic commerce dimension] for Study 3 [Cronbach's α = 0.844]). Trust, as the mediator, was measured with the four items from consumer trust scale³⁹ (e.g., “The Metaverse can be relied on to keep its promises” [Study 1 Cronbach's α = 0.961; Study 2 Cronbach's α = 0.957; Study 3 Cronbach's α = 0.958]).

Behavioral intention to adopt the Metaverse, as the dependent variable, was measured with items from the system adoption intention scale⁴⁰ (e.g., “I intend to use Metaverse for virtual learning in the near future” Study 1 [Cronbach's α = 0.980]; “for virtual working” Study 2 [Cronbach's α = 0.980]; “for virtual commerce” for Study 3 [Cronbach's α = 0.976]).

Social phobia, as the moderator for Study 1, was measured with five items from the social phobia inventory (e.g., “Being embarrassed or looking stupid are among my worst fears” [Cronbach's α = 0.924]).^19,41 Neo-luddism, as the moderator for Study 2, was measured with five items²¹ (e.g., “The Metaverse makes people lose their jobs” [Cronbach's α = 0.904]). Blockchain transparency, as the moderator for Study 3, was measured with three items²² (e.g., “Blockchain is a transparent technology” [Cronbach's α = 0.822]). Descriptive statistics and correlation matrix are presented in Table 2.

Table 2.

Descriptive Statistics and Bivariate Correlation

Variables	M	SD	1-1.	1-2.	1-3.	1-4.	2-1.	2-2.	2-3.	2-4.	3-1.	3-2.	3-3.	3-4.
Study 1 (N = 321)
1-1. Digital equality (education)	4.1485	1.8363	1
1-2. Trust in the Metaverse	4.3411	1.7004	0.491**	1
1-3. Social phobia	3.4696	1.7164	0.214**	0.138**	1
1-4. Metaverse adoption for virtual learning	4.1246	1.9689	0.581**	0.791**	0.154**	1
Study 2 (N = 318)
2-1. Digital equality (labor)	4.5314	1.6541					1
2-2. Trust in the Metaverse	4.2366	1.7583					0.661**	1
2-3. Neo-Luddism	3.8698	1.6872					−0.167*	−0.258**	1
2-4. Metaverse adoption for virtual working	3.7742	2.0688					0.658**	0.750**	−0.152**	1
Study 3 (N = 315)
3-1. Digital equality (economic commerce)	4.7676	1.3911									1
3-2. Trust in the Metaverse	3.7968	1.6297									0.511**	1
3-3. Blockchain transparency	4.4360	1.3345									0.489**	0.524**	1
3-4. Metaverse adoption for virtual commerce	3.2032	1.8812									0.436**	0.763**	0.470**	1

^* p < 0.05; ^**p < 0.01.

M, mean; SD, standard deviation.

Results

Data were analyzed using PROCESS version 4.2 Macro with 5,000 bootstrap samples.⁴²

Study 1: digital (in)equality, social phobia, and trust in the Metaverse for virtual learning

The third-level digital inequality (educational dimension) was a negative predictor of trust in the Metaverse. People's capacity to translate their digital access and use into offline educational outcomes and resources (digital equality) was a positive predictor of trust in the Metaverse (b = 0.4659, t = 9.0280, p = 0.0000), supporting H1. Trust was a positive predictor of behavioral intention to adopt the Metaverse for virtual learning (b = 0.7619, t = 17.5988, p = 0.0000), supporting H2.

There was a significant indirect effect of the third-level digital (in)equality on behavioral intention to adopt the Metaverse for virtual learning and education (b = 0.3550, Lower confidence interval [CI] = 0.2677, Upper CI = 0.4539), supporting H3. The direct effect of third-level digital (in)equality on adoption intention in the presence of the mediator (trust) was also found to be significant.

Hence, trust partially mediated the relationship between the third-level digital (in)equality (educational dimension) and Metaverse adoption intention. Mediation analysis summary for Study 1 is presented in Table 3 (top).

Table 3.

Mediation Analysis Summary (Study 1: Metaverse for Virtual Learning [Top]; Study 2: Metaverse for Virtual Working [Middle]; Study 3: Metaverse for Virtual Commerce [Bottom])

Relationship	Total effect	Direct effect	Indirect effect	Confidence interval		Conclusion
				Lower bound (LLCI)	Upper bound (ULCI)
Study 1 Digital (In)equality [educational dimension] → trust → metaverse adoption for virtual learning	0.6434 (p = 0.0000)	0.2884 (p = 0.0000)	0.3550	0.2677	0.4539	Partial mediation
Study 2 Digital (In)equality [labor dimension] → trust → metaverse adoption for virtual working	0.7175 (p = 0.0000)	0.2828 (p = 0.0000)	0.4346	0.3446	0.5272	Partial mediation
Study 3 Digital (In)equality [economic commerce dimension] → trust → metaverse adoption for virtual commerce	0.5281 (p = 0.0000)	0.0829 (p = 0.1370)	0.4452	0.3370	0.5526	Total mediation

LLCI, lower level confidence interval; ULCI, upper level confidence interval.

Study 1 also tested the moderating role of social phobia on the relationship between digital (in)equality (educational dimension) and behavioral intention to adopt the Metaverse for virtual learning. The analysis revealed a significant moderating effect of social phobia (b = −0.0710, t = −2.5388, p = 0.0116), supporting H4. The results of moderation model testing are summarized in Table 4 (top).

Table 4.

Moderation Analysis Summary (Study 1: Metaverse for Virtual Learning; Study 2: Metaverse for Virtual Working; Study 3: Metaverse for Virtual Commerce)

Moderation models	Predictors	Coefficient	SE	t	p	LLCI	ULCI
Study 1 DV = metaverse adoption for virtual learning	Intercept	4.9912	0.5287	9.4406	0.0000	3.9510	6.0314
	IV: Digital (In)Equality	0.6109	0.0561	10.8966	0.0000	0.5006	0.7212
	MoV: Social phobia	0.1119	0.0583	1.9184	0.0560	−0.0029	0.2267
	Interaction Term: Digital (In)Equality × Social Phobia	−0.0710	0.0280	−2.5388	0.0116	−0.1260	−0.0160
	R2 = 0.3425
Study 2 DV = metaverse adoption for virtual working	Intercept	5.0566	0.4542	11.1335	0.0000	4.1630	5.9503
	IV: Digital (In)Equality	0.6830	0.0540	12.6586	0.0000	0.5768	0.7891
	MoV: Neo-Luddism	−0.1051	0.0521	−2.0161	0.0446	−0.2076	−0.0025
	Interaction Term: Digital (In)Equality × Neo-Luddism	0.0645	0.0259	2.4928	0.0132	0.0136	0.1155
	R2 = 0.4912
Study 3 DV = metaverse adoption for virtual commerce	Intercept	5.4380	0.4816	11.2904	0.0000	4.4901	6.3858
	IV: Digital (In)Equality	0.4120	0.0702	5.8676	0.0000	0.2738	0.5501
	MoV: Blockchain Transparency	0.4277	0.0722	5.9245	0.0000	0.2856	0.5697
	Interaction Term: Digital (In)Equality × Blockchain Transparency	0.1286	0.0343	3.7476	0.0002	0.0611	0.1961
	R2 = 0.4609

DV, dependent variable; IV, independent variable; MoV, moderating variable; SE, standard error.

The results of slope analysis to further understand the nature of the moderating effects are graphically presented in Figure 4. The line is steeper for low social phobia, which shows that at the low level of social phobia, the impact of digital (in)equality is stronger in comparison to that at the high level of social phobia. Further, as the level of digital equality (educational dimension) increased, the strength of the relationship between social phobia and adoption decreased.

FIG. 4.

Study 1: two-way interaction effect of third-level digital (in)equality and social phobia on Metaverse-based virtual learning.

Study 2: digital (in)equality, neo-Luddism, and trust in the Metaverse for virtual working

The third-level digital inequality (economic labor dimension) was a negative predictor of trust in the Metaverse. People's capacity to translate their digital access and use into offline economic labor outcomes and resources (digital equality) was a positive predictor of trust in the Metaverse (b = 0.6861, t = 14.4060, p = 0.0000), supporting H5. Trust was a positive predictor of behavioral intention to adopt the Metaverse for remote working (b = 0.6334, t = 12.2015, p = 0.0000), supporting H6.

There was a significant indirect effect of the third-level digital (in)equality (economic labor dimension) on behavioral intention to adopt the Metaverse for remote working (b = 0.4346, Lower CI = 0.3446, Upper CI = 0.5272), supporting H7. The direct effect of the third-level digital (in)equality on adoption intention in the presence of the mediator (trust) was also found to be significant. Hence, trust partially mediated the relationship between the third-level digital (in)equality (economic labor dimension) and Metaverse adoption intention (Table 3, middle).

Study 2 also tested the moderating role of neo-Luddism perspectives on the Metaverse in accounting for the relationship between digital (in)equality (economic labor dimension) and behavioral intention to adopt the Metaverse for remote working. The results revealed a significant moderating effect of neo-Luddism (b = 0.0645, t = 2.4928, p = 0.0132), supporting H8.

The results of moderation model testing are summarized in Table 4 (middle). The results of slope analysis to further understand the nature of the moderating effects are graphically presented in Figure 5. The line is steeper for high Luddites, which shows that at the high level of neo-Luddism, the impact of digital (in)equality is stronger in comparison to the low level of neo-Luddism. Further, as the level of digital equality increased, the strength of the relationship between neo-Luddism and adoption decreased.

FIG. 5.

Study 2: two-way interaction effect of third-level digital (in)equality and neo-Luddism on Metaverse-based virtual working.

Study 3: digital (in)equality, blockchain transparency, and trust in the Metaverse for virtual commerce

The third-level digital inequality (economic commerce dimension) was a negative predictor of trust in the Metaverse. People's capacity to translate their digital access and use into real-life e-commerce outcomes and resources (digital equality) was a positive predictor of trust in the Metaverse (b = 0.5775, t = 9.8605, p = 0.0000), supporting H9. Trust was a positive predictor of behavioral intention to adopt the Metaverse for virtual commerce (b = 0.7709, t = 16.3378, p = 0.0000), supporting H10.

The results revealed a significant indirect effect of third-level digital (in)equality (e-commerce dimension) on behavioral intention to adopt the Metaverse for virtual commerce (b = 0.4452, Lower CI = 0.3370, Upper CI = 0.5526), supporting H11.

The direct effect of third-level digital (in)equality on adoption intention in the presence of the mediator (trust) was not significant. Therefore, trust totally mediated the relationship between the third-level digital (in)equality (economic commerce dimension) and Metaverse adoption intention (Table 3, bottom).

Study 3 also tested the moderating role of blockchain/cryptocurrency transparency perception on the relationship between digital (in)equality (economic commerce dimension) and behavioral intention to adopt the Metaverse for virtual commerce. The results revealed a significant moderating effect of blockchain/cryptocurrency transparency perception (b = 0.1286, t = 3.7476, p = 0.0002), supporting H12.

The results of moderation model testing are summarized in Table 4 (bottom). The results of slope analysis to further understand the nature of the moderating effects are graphically shown in Figure 6. The line is steeper for high blockchain transparency, which shows that at the high level of blockchain transparency perception, the impact of digital (in)equality is stronger in comparison to the low level of blockchain transparency perception. Further, as the level of digital equality increased, the strength of the relationship between blockchain transparency perception and adoption increased.

FIG. 6.

Study 3: two-way interaction effect of third-level digital (in)equality and blockchain/cryptocurrency transparency on Metaverse-based virtual commerce.

Discussion

Key findings and theoretical contributions

Departing from the conventional Technology Acceptance Model,^40,43 this research attempts to approach the special and emerging issue of the Humane Metaverse from the perspectives of “digital (in)equality and trust.” Empirical findings from the three surveys support the proposed hypotheses about the mediating effects of trust and the moderating effects of social phobia in virtual learning, neo-Luddism in virtual working, and blockchain/cryptocurrency transparency in virtual commerce on the relationship between the third-level digital (in)equalities and Metaverse adoption intention.

For those people with high educational digital equality (low educational digital inequality), social phobia did not have a significant effect on Metaverse adoption intention. People with high educational digital resources are willing to adopt the Metaverse for virtual learning regardless of their social phobia level. In contrast, for those with low educational digital equality and resources (high educational digital inequality), high social phobia was associated with higher behavioral intention to adopt the Metaverse for virtual learning.

People with different levels of social phobia indicate differential levels of adoption intention depending on their capacity to translate their digital access into educational outcomes. The interaction effect between social phobia and digital (in)equality is an interesting finding since it suggests the potential of the Metaverse in inviting people with low educational digital resources and with high social phobia for hybrid learning in the virtual environments that may mitigate social phobia. This finding is relevant to the recent empirical data about highly social phobic consumers' preference for anthropomorphic AI-empowered chatbots.¹⁹

For those people with high economic labor-related digital equality (low economic labor digital inequality), neo-Luddism did not have a significant effect on Metaverse adoption intention. People with high economic digital resources are willing to adopt the Metaverse for virtual working regardless of their neo-Luddism level. In contrast, for those with low economic digital equality (high economic digital inequality), high neo-Luddism was associated with even lower behavioral intention to adopt the Metaverse for virtual working.

This study adds important data about the interaction effects of luddite views on the Metaverse and digital inequality to the literature on neo-Luddism. This finding is relevant to the recent empirical data about the moderating effect of technopian versus Luddite ideological views on consumer behavior.²¹

For those people with high economic commerce-related digital equality (low e-commerce digital inequality), blockchain/cryptocurrency transparency perception had stronger effects on Metaverse adoption intention. Most importantly, as the level of digital equality increased (the level of digital inequality decreased), the strength of the relationship between blockchain/cryptocurrency transparency perception and behavioral intention to adopt the Metaverse for virtual commerce increased, which implies the importance of blockchain/cryptocurrency transparency perception especially for those with high digital resources in adopting the Metaverse for virtual commerce.

When the blockchain technology is not perceived to be transparent (low blockchain transparency), even those with high economic commerce-related digital equality showed relatively low intention to adopt the Metaverse for virtual commerce.

Practical, managerial, and policy implications

Practical, managerial, and policy implications of the current findings include: (a) the importance of trust in tackling fears and doubts about the concept of the Metaverse and in increasing people's behavioral intention to adopt the Metaverse; (b) the significance of understanding consumers' personality and individual difference factors in segmenting the emerging market; and (c) policy implications regarding the role of digital inequality in emerging Web 3.0 environments.

Marketing communication and campaigns need to focus on designing messages that help build and increase people's trust in the emerging/evolving platform of the Metaverse. When crafting marketing messages and executing campaigns about the Metaverse, the empirical findings about the moderating effects of social phobia, neo-Luddism, and blockchain/cryptocurrency transparency perception may provide helpful insights for brand managers and social marketers in segmenting/customizing the consumer market based on the key characteristics of consumers relevant to the Metaverse interface for education, working, and commerce.

Increasing trust in the blockchain/cryptocurrency technologies and emphasizing blockchain/cryptocurrency transparency will be (a) the most effective campaign/marketing strategies to attract not only commercial brands⁴⁴ but also creative artists and digital content generators to enter the NFT market and (b) key to the success of the emerging, decentralized NFT market in the Metaverse.

Most importantly, the current research also highlights the importance of tackling “digital inequality” (“the rich get richer”) in a variety of areas for policy making (education, labor market, and commerce), which policy makers should factor into the AI-based Metaverse/NFT-related legislative process.

Limitations and avenues for future research

Several limitations of this research include: (a) one-time cross-sectional survey without experimental control, which limits the inference of cause-and-effect relationships among the proposed variables; (b) lack of qualitative comments collected from the participants regarding their sentiment about the Metaverse; and (c) data collection in the month of news about mega tech companies' layoffs (Google, Amazon, Meta, and Twitter),^45–48 which might have induced the public skepticism about the future of AI-empowered Metaverse and technological innovation.

Follow-up studies may address these limitations by conducting mixed-method research with high-control experiments,⁴⁹ qualitative ethnographic interviews,²³ machine learning/AI neural network/deep learning-based sentiment analysis (opinion mining),^50,51 and longitudinal surveys;⁵² and (d) no measurement of variables such as perceived system usefulness, ease of use, learner self-efficacy, and information quality, which may influence users' adoption of Metaverse for virtual learning.

These variables proposed from the Technology Acceptance Model^40,43 are important factors, especially in the context of hybrid educational platforms for virtual learning. Despite these caveats, this research can provide theoretical frameworks to examine people's hopes and fears about the Metaverse and consequential adoption versus non-adoption of the Metaverse for hybrid education, omni-channel virtual commerce, and hybrid remote working.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This work was partially supported by Northwestern University in Qatar (NU-Q) Professional Development Fund.