Search Results (220)

This study aims to systematically analyze scholarly research on virtual reality (VR), augmented reality (AR), and the metaverse in the tourism and hospitality sectors, offering insights into publication patterns, key contributors, thematic evolution, and potential research directions from 2016 to mid-2025. It maps how the literature evolved in response to technological maturation and changing tourism constraints. A systematic literature review and comprehensive bibliometric analysis were conducted using the Scopus database. The analysis encompassed bibliographic metrics, thematic clustering, and content analysis techniques to identify influential journals, authors, and evolving research themes. The results reveal a pronounced acceleration in research activity post-2020, reflecting heightened interest due to the COVID-19 pandemic’s push towards digital and immersive solutions. Core journals identified include Tourism Management, Current Issues in Tourism, and Journal of Travel Research. Influential contributors such as Timothy H. Jung, M. Claudia tom Dieck, and Dimitrios Buhalis significantly shaped the field. The thematic trajectory demonstrates a shift from initial exploration and application of VR and AR technologies toward comprehensive integration into metaverse ecosystems, with emerging themes such as digital twins, synthetic experiences, immersive storytelling, and growing emphasis on ethical and sustainability considerations. By synthesizing nearly a decade of research, this study provides valuable insights into immersive technologies’ evolution in tourism and hospitality, identifying critical areas for future investigation aligned with enterprise information management strategies. Full article

Industrial metaverse systems enable shared, immersive environments for coordinating complex, data-intensive industrial workflows; however, ensuring effective and usable interaction remains a key barrier to professional adoption. This study examines immersive point cloud- and CAD-based inspection tasks in an industrial metaverse context using a mixed-methods evaluation that combines perceived usability ratings, cognitive workload assessment (NASA-TLX), validated presence and flow instruments, qualitative interviews, and structured observation. The results indicate that users generally experienced smooth navigation, manageable cognitive workload, and a meaningful sense of spatial presence, supporting focused and task-oriented engagement. At the same time, execution-level challenges—particularly related to tool discoverability, annotation flexibility, system feedback clarity, and interaction ergonomics—introduced workflow friction for some users. By triangulating quantitative, qualitative, and observational evidence, the study derives actionable design recommendations, including adaptive onboarding, improved feedback mechanisms, and refinements to interaction design. Overall, the findings provide empirical insight into how usability, cognitive workload, presence, and flow jointly shape user experience in industrial metaverse inspection environments and inform the development of more robust, user-centered industrial systems. Full article

Deaf and Hard-of-Hearing (DHH) students face persistent barriers in geometry education due to instructional approaches that inadequately support visual communication and embodied learning. This study examined DHH students’ experiences with GeoMETriA, a metaverse-based geometry learning platform integrating sign language instruction, three-dimensional visualization, and avatar-mediated interaction. Guided by the Cognitive Affective Model of Immersive Learning (CAMIL), a multi-phase qualitative design was employed, including pre-workshop interviews with four special education teachers and post-workshop focus group discussions with seven DHH secondary students following a four-session learning workshop. The findings indicate that gamified activities and peer collaboration enhanced interest and sustained engagement, while avatar customization supported embodiment and a sense of presence. Students described progression from initial uncertainty to greater confidence through practice and scaffolded support. However, cognitive and usability challenges emerged, particularly concerning sign language video pacing, navigation complexity, and limited instructional scaffolding. The study contributes theoretically by extending CAMIL-informed interpretations to sign-supported metaverse learning, empirically by documenting how engagement, embodiment, and self-efficacy develop during immersive geometry learning, and practically by offering design implications including adjustable sign language delivery, structured scaffolding, and culturally responsive avatar options. These findings suggest that metaverse-based platforms hold promise for supporting DHH learners when accessibility and learner-centered principles are embedded as foundational design considerations. Full article

The Metaverse has become a central concept in the evolution of digital transformation, but its current development is marked by conceptual ambiguity, technological fragmentation and the limited presence of structured frameworks for the systematic assessment of its maturity. The Metaverse is currently approached from partial perspectives that often focus on virtual worlds rather than conceptualizing it as a multidimensional digital ecosystem. This study proposes a multidimensional model of Metaverse maturity divided into three stages (Emergent, Developed and Integrated) and five analytical dimensions (experience, interoperability, standardization, technology and resources). The model is based on a systematic literature review of the academic and non-academic sources. It aligns these dimensions systematically with the layered architecture of the Metaverse and formalizes their interdependence through a structured impact-mapping procedure. This maturity model offers an analytical tool for comparing contexts and sectors, identifying bottlenecks, and guiding strategic planning. It establishes a conceptual framework for future empirical validation and sector-specific applications. Full article

With the growing integration of AR/VR/Metaverse technologies across luxury brands, advertising has shifted to providing consumers with a personalised experience in which they can engage with brands via digital avatars. Given the considerable success of Metaverse advertising, it is apparent that organisations need to reinvent their advertising strategies to enhance consumer experience and brand engagement over digital platforms. However, this reinvention would require organisations to develop an advertising strategy that creates a coherent brand experience for consumers and provides them with an immersive brand experience on Metaverse platforms. As a result, this study undertakes a bibliometric approach to provide a comprehensive understanding of how integrating Metaverse platforms with advertising strategies can enhance brand engagement among consumers. More precisely, a keyword search strategy is formulated, and a multi-database search is performed across key databases, including Scopus, EBSCOhost, and ProQuest. In doing so, results from Scopus databases are visualised through network and overlay visualisation maps to understand how key themes/knowledge structures are associated with Metaverse advertising and brand engagement. Besides this, the study also showcases the key theoretical perspectives (i.e., psychological perspectives, value-based perspectives, technology/innovation perspectives, and social interaction perspectives) across these studies to understand how brands have well-infused Metaverse advertising to enhance brand engagement among consumers. Lastly, the study also provides a deeper understanding of the key challenges that are associated with the widespread implementation of Metaverse advertising. Full article

The ongoing digital revolution is reshaping human communication and collaboration. Immersive technologies and artificial intelligence are opening new avenues for interaction, raising the question of whether these innovations can support Deliberative Polling^®, a social science method of engaging the public, in virtual environments. This study aims to explore the feasibility of conducting Deliberative Polling^® in the Metaverse. Thirty individuals from 10 nationalities participated in three experiences conducted on two different platforms. The first experience, conducted on Meta Horizon Worlds, served as a preliminary test to evaluate the platform’s usability and interaction dynamics. The second and third experiences, following the Deliberative Polling methodology, were conducted on Meta Horizon Worlds and Spatial, respectively. Each experience lasted approximately two hours. Across sessions, opinion changes were observed, and participants displayed virtual social dynamics similar to those in face-to-face deliberation. The results suggest that Deliberative Polling^®-like deliberations appear feasible in social VR under these exploratory conditions, as reflected in balanced discussions and topic-focused engagement. However, current VR hardware and software still require improvements to enhance accessibility, usability, and inclusivity for broader adoption. Future research with larger and more diverse participant pools is needed to assess not only feasibility but also effectiveness relative to traditional approaches. Full article

This study examines customers’ continuance intention in metaverse services by integrating technological, content, and social-relational dimensions and assessing the role of immersiveness. Six focal antecedents are considered, namely, technological sophistication, security, content creativity, content richness, social interaction, and social presence. Survey data from 231 metaverse users in China show that technological sophistication, content creativity, social interaction, and social presence are positively associated with immersiveness, whereas security and content richness are not. In addition, continuance intention is positively associated with technological sophistication, security, content richness, social interaction, and immersiveness. Despite the absence of clear indirect effects via immersiveness, the results suggest that continuance intention reflects not only immersive experience but also post-adoption evaluations of assurance and usefulness. As metaverse services move toward broader adoption and commercialization, these findings distinguish experience-building drivers from retention-relevant factors and offer implications for service development, content strategy, and community experience design. Full article

Metaverse presents significant opportunities for educational advancement by facilitating immersive, personalized, and interactive learning experiences through technologies such as virtual reality (VR), augmented reality (AR), extended reality (XR), and artificial intelligence (AI). However, this potential is compromised if digital environments fail to uphold individuals’ privacy, autonomy, and equity. Despite their widespread adoption, the privacy implications of these environments remain inadequately understood, both in terms of technical vulnerabilities and legislative challenges, particularly regarding user consent management. Contemporary Metaverse systems collect highly sensitive information, including biometric signals, spatial behavior, motion patterns, and interaction data, often surpassing the granularity captured by traditional social networks. The lack of privacy-by-design solutions, coupled with the complexity of underlying technologies such as VR/AR infrastructures, 3D tracking systems, and AI-driven personalization engines, makes these platforms vulnerable to security breaches, data misuse, and opaque processing practices. This study presents a structured literature review and comparative analysis of privacy risks, consent mechanisms, and digital boundaries in metaverse platforms, with particular attention to educational contexts. We argue that privacy-aware design is essential not only for ethical compliance but also for supporting the long-term sustainability goals of digital education. Our findings aim to inform and support the development of secure, inclusive, and ethically grounded immersive learning environments by providing insights into systemic privacy and policy shortcomings. Full article

The Immersive Decentralized Digital space (IDDs), derived from blockchain technology and Massively Multiplayer Online Games (MMOGs), enables real-time multisensory interactions that support social connection under metaverse concepts. Although recognized as a technology with significant potential for educational innovation, IDDs remain underutilized in health professions education. Health profession students are often unaware of how IDDs’ features can be applied to their learning through in- or after-classroom activities. This study employs a quantitative research design to evaluate students’ perceptions of next-generation digital learning without any prior exposure to IDDs. An electronic survey was developed to examine four dimensions of learning facilitation: “Remote Learning” for capturing past experiences with digital competence during the COVID-19 era; “Digital Evolution,” reflecting preferences in utilizing digital spaces; “Interactive Communication” and “Knowledge Application” for applicability of IDDs in the health professions education. Statistical analyses revealed no significant differences in perceptions based on gender or major on all factors. Nevertheless, significant differences emerged based on nationality in “Digital Evolution”, “Interactive Communication”, and “Knowledge Application”, highlighting the influence of cultural and educational backgrounds on receptiveness to virtual learning environments. By recognizing the discrepancies and addressing barriers to digital inclusion, IDDs hold strong potential to enhance health professional learning experiences and educational outcomes. Full article

Although metaverse model houses have recently emerged as an interactive alternative to traditional housing marketing tools, empirical research addressing users’ experiences within these environments remains limited. This study aimed to examine how three dimensions of user experience (UX)—operational, sensory, and exploratory—affect user satisfaction and behavioral intentions in metaverse model houses. A total of 83 participants explored a metaverse model house using a tablet PC and completed a questionnaire. Multiple linear regression analysis revealed that exploratory experience significantly influenced user satisfaction, while sensory experience was positively associated with all behavioral intentions, including the intention to revisit, recommend, reside, and purchase. These findings advance our understanding of UX in virtual housing environments and highlight the importance of immersive and exploratory elements in designing effective metaverse model houses. The results offer practical implications for improving digital housing marketing strategies and guiding the future development of metaverse-based architectural platforms. Full article

In social virtual reality (VR) and metaverse platforms, users express their identity through both avatar appearance and on-avatar textual cues, such as speech balloons. However, little is known about how the harmony between these cues influences self-representation and social impressions. We propose that when avatar appearance and text design, including color, font, and tone, are consistent, users experience a stronger self-expression fit and elicit greater interpersonal affinity. A within-subject study ($N=21$) in VRChat manipulated the social context, color harmony between avatar hair and text, and style or content consistency between tone and font. Questionnaires provided composite indices for perceived congruence, self-expression fit, and affinity. Analyses included repeated-measures ANOVA, linear mixed-effects models, and mediation tests. Results showed that congruent pairings increased both self-expression fit and affinity compared to mismatches, with mediation analyses indicating that self-expression fit fully mediated the effect. These findings integrate theories of avatar influence and computer-mediated communication into a framework for metaverse design, highlighting the value of consistent avatar and text styling. Full article

This paper deals with unwanted spatial distortion in virtual environments and its impact on the construction of metaverse environments that require high precision, especially in fields with specific requirements, such as medicine. At the same time, it presents the main technical factors leading to this phenomenon. The paper also emphasizes that data reliability is the first factor that needs to be analyzed and evaluated. Through a comprehensive analysis of the limitations of traditional methods and the development trend of techniques based on Artificial Intelligence (AI), a data processing method based on the Gaussian process regression method is proposed. Through experiments and result analysis, this method significantly improves data reliability, thereby enhancing the accuracy of avatar motion simulation in the virtual environment of the metaverse. Future research trends include further improvement of processing accuracy and speed; deploying on real devices; expanding the research into other factors contributing to unintended spatial distortions; exploring and applying appropriate processing techniques and technologies to enhance simulation reliability in virtual metaverse environments. Full article

In the context of post-pandemic remote work normalization and the emergence of the metaverse, virtual workspaces have attracted significant attention as critical digital infrastructure with promising application prospects. While virtual workspaces enable efficient task performance, compared with traditional ones, the lack of emotional connection between humans and machines adversely affects participants’ mental health. The emergence of affective computing has made it possible to endow virtual workspaces with “affective intelligence”. Therefore, this study aims to clarify the relationship between color and participants’ emotions in virtual workspaces through an experiment involving 48 participants, and eight virtual workspaces were constructed, incorporating four color conditions (red, blue, yellow, and green) and two workspace types (shared and single). Data were synchronously collected using the Positive and Negative Affect Schedule (PANAS), a questionnaire item on arousal, electrodermal activity (EDA), and heart rate variability (HRV). The results successfully established specific associations between colors and emotions: red with “anxious”, yellow with “happy”, and blue with “calm”. Although no specific emotion word was identified for green, this study successfully achieved the emotion classification of virtual workspaces and constructed a corresponding dataset. These findings provide a theoretical foundation for the development of affective computing models. Full article

This article proposes a complex solution to improve sustainable intelligent building management based on the principles of Environmental, Social, and Governance (ESG) factors. The ESG KPI Framework–Metaverse-Enabled Operations incorporates the latest digital twin solutions, IoT sensor systems, and metaverse platforms to deliver real-time management and optimization of ESG factors. A hybrid solution strategy has been used in this framework, focusing on auto-acquisition of information and multiple validations at different levels through correlation analysis, Principal Component Analysis (PCA), Ordinary Least Squares (OLS) regression, and Machine Learning. The designed prototype links all the solutions together in a multi-level dashboard to represent key performance factors such as carbon footprint, energy consumption, renewable energy use, and occupant wellness. Experiments conducted validate the effectiveness of the proposed solution in improving prediction efficiency and user interaction experience during metaverse simulations. Full article

This article presents a part of the industrial metaverse for electric drive system diagnostics. The advantages of using a low-code/no-code platform for electric drive systems diagnostics are demonstrated. Five diagnostic scenarios were developed, programmed, and implemented. The article demonstrates the implementation and use of the platform’s main functional blocks: a visualization block (which displays the state of electric machines in any user-friendly form—graphs, Park’s vector diagrams, or diagnostic curves); a digital twin block (which simulates various engine states); a digital twin block with an engine defect (which simulates faulty engine states); and an artificial intelligence block (which trains classification model to predict various engine states). Experiments on training the artificial intelligence block using a misalignment defect dataset are presented. The dataset was divided into six classes: engine operation with/without a defect under no load, engine operation with/without a defect under a 50% load, and engine operation with/without a defect under a 100% load. The workflow for training and using the model, the basic training approaches, and the distinguishability of the presented classes are demonstrated. The model training results are shown. The article presents a methodology for extensive testing of program functionality. The obtained results demonstrate the feasibility of implementing a low-code/no-code platform and the feasibility of solving the assigned tasks with its help, as well as the simplification and reduction in engineering solution development time. Full article