Exploring Key Factors Influencing the Processual Experience of Visitors in Metaverse Museum Exhibitions: An Approach Based on the Experience Economy and the SOR Model

Abstract

With the advancement of immersive technologies, metaverse museum exhibitions have become an increasingly important medium through which audiences access cultural content and experience artistic works. This study aims to identify the key factors influencing visitors’ processual experiences in metaverse museum exhibitions and to explore how these factors collectively contribute to the formation of satisfaction with the visiting experience. Adopting an interdisciplinary theoretical perspective, the study integrates the Experience Economy theory with the Stimulus–Organism–Response (SOR) model to construct a systematic theoretical framework. This framework reveals how exhibition-related stimuli affect visitors’ behavioral intentions through psychological response pathways. Specifically, perceived educational appeal, interactive entertainment, escapist experience, and perceived visual aesthetics are defined as stimulus variables, while psychological immersion, emotional trigger, and cognitive engagement are introduced as organismic variables to explain their effects on satisfaction with the visiting experience and social sharing intention as response variables. Based on 507 valid responses, Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for empirical analysis. The results indicate that interactive entertainment and escapist experience have significant positive effects on psychological responses, serving as key drivers of deep visitor engagement. Emotional Trigger acts as a significant mediator between exhibition stimuli and satisfaction with the visiting experience, which in turn significantly predicts social sharing intention. In contrast, perceived educational appeal and perceived visual aesthetics exhibit weaker impacts at the cognitive and behavioral levels. This study not only identifies these weakened pathways but also proposes optimization strategies grounded in experiential construction and cognitive synergy, offering guidance for enhancing the educational function and deep experiential design of metaverse exhibitions. The findings validate the applicability of the Experience Economy theory and the SOR model in metaverse cultural contexts and deepen our understanding of the psychological mechanisms underlying immersive cultural experiences. This study further provides a pathway for shifting exhibition design from a “content-oriented” to an “experience-driven” approach, offering theoretical and practical insights into enhancing audience engagement and cultural communication effectiveness in metaverse museums.

1. Introduction

With the rapid development of the metaverse concept, global technology giants such as Meta, Microsoft, Epic Games, and Tencent have significantly increased their investments in metaverse platforms. The market size is projected to grow from USD 737.73 billion in 2024 to USD 7639.70 billion by 2032 [1]. Driven by this trend, cutting-edge technologies such as Virtual Reality (VR), Augmented Reality (AR), Artificial Intelligence (AI), and Digital Twins are increasingly integrated, unleashing unprecedented potential for the metaverse in the field of museum and cultural heritage exhibitions. Traditional museums have long been constrained by physical space, time, and resource limitations. In contrast, metaverse museums leverage immersive virtual environments to overcome these barriers, offering visitors more personalized and highly interactive experiences [2]. For example, the Centre Pompidou in France launched a VR-based art exhibition that allows audiences to view its collections online and participate in virtual lectures [3]. In China, the Sanxingdui site utilized high-precision 3D modeling and VR technology to build a “cloud exhibition hall,” enabling virtual archeology and artifact exploration, thereby strengthening public cultural identity [4]. Additionally, platforms such as NetEase Yaotai and Baidu Xirang have improved exhibition participation and user stickiness through immersive design and social interaction [5,6].

Meanwhile, technological advancements have not only transformed exhibition formats but also established psychological immersion, emotional response, and cognitive engagement as key indicators for evaluating the success of exhibitions in metaverse museums [7,8]. In its latest definition, the International Council of Museums (ICOM) emphasizes that museums should be “offering varied experiences for education, enjoyment, reflection and knowledge sharing” [9], highlighting public engagement and the realization of cultural value as core metrics for assessing visitor satisfaction [10]. Guided by this principle, metaverse museums have begun constructing immersive virtual cultural experience spaces through multimodal information delivery and deeply interactive design. Visitors explore virtual galleries in an embodied manner, and their perception of information, emotional processing, and cognitive path selection within immersive environments directly shape the quality of the visiting experience and subsequent behavioral responses [11,12]. Therefore, user experience functions not only as a mediating mechanism in exhibition communication but also as a critical driver for promoting cultural participation, cognitive construction, and identity formation.

However, despite the tremendous potential of metaverse museums in enhancing visitor experiences, existing research lacks systematic analysis of the processual nature of the visiting experience [13]. It is therefore necessary to identify the key factors influencing visitors’ experiential processes in metaverse museums in order to improve audience satisfaction. Polly McKenna-Cress and Janet A. Kamien emphasize that visitors construct a holistic perception through continuous interaction with various components of the exhibition, gradually developing emotional and cognitive resonance [14]. A complete exhibition experience does not occur instantaneously; rather, it evolves dynamically through multiple phases—initial interest arousal, immersive engagement, emotional reflection, and cognitive consolidation. This coherent and evolving experiential trajectory profoundly shapes visitors’ depth of understanding, cultural identification, and subsequent behavioral engagement [15,16]. Consequently, a deeper investigation into how visitors’ experiential processes unfold in metaverse exhibitions can not only enrich theoretical perspectives on virtual exhibition experiences but also offer empirical support and theoretical guidance for optimizing exhibition design and enhancing the cultural communication efficacy of digital museums.

Although previous studies have examined virtual museum experiences from perspectives such as technology acceptance, interaction design, and user behavior [17,18,19], most have followed a single-dimensional analytical path, with limited attention to the synergistic effects among key experiential components such as psychological immersion, emotional resonance, and cognitive engagement [20]. This analytical gap is particularly pronounced in metaverse environments, where the convergence of multimodal stimuli and high levels of interactive autonomy leads users to self-navigate exhibition paths. In such settings, managing cognitive load and maintaining experiential coherence become critical to ensuring high-quality visitation experiences [21]. Therefore, this study underscores the necessity of developing an integrated theoretical framework that reveals how immersive stimuli, emotional triggers, and cognitive processes interact to shape visitor satisfaction and drive social sharing intentions. Such a framework not only bridges fragmented insights in existing research but also enhances understanding of how metaverse exhibitions can achieve more effective cultural communication.

From a deeper perspective, visitors’ experiences during exhibitions are essentially dynamic processes involving the continuous interaction and evolution of cognitive and emotional states. Falk and Dierking, in The Museum Experience Revisited, argue that the museum experience encompasses a trajectory extending from pre-visit expectations, through in-visit interactions, to post-visit emotional reflection and cognitive integration, during which visitors constantly adjust their cognitive strategies and emotional responses [22]. Bitgood’s “Attention-Value Model” further elucidates how attention focus, emotional fluctuation, and deep cognitive processing unfold in distinct stages throughout the experience [23]. This continuously evolving psychological trajectory significantly influences visitors’ acceptance of exhibition content, the depth of memory encoding, and their inclination toward subsequent social sharing. Therefore, in the highly immersive and interactively complex environment of the metaverse, understanding the dynamic nature of visitors’ processual experiences is critical to enhancing the communicative power and sustained appeal of virtual cultural spaces.

To address the above-mentioned research gap in visitor experience trajectories, this study constructs an analytical framework supported by the Experience Economy theory and the Stimulus–Organism–Response (SOR) model to explain how multidimensional experiential factors affect behavioral outcomes through psychological mechanisms. It aims to examine the mechanism influencing multidimensional experiential factors on visitors’ processual experience in metaverse museum exhibitions, with the goal of identifying effective strategies for optimizing the entire visitor experience and enhancing cultural communication efficacy in virtual exhibitions. Specifically, this study investigates the core exhibition stimuli in metaverse environments—namely, perceived educational appeal, interactive entertainment, escapist experience, and perceived visual aesthetics—and explores how these factors influence visitors’ psychological immersion, emotional triggers, and cognitive engagement, which in turn contribute to higher satisfaction with the visiting experience and increased social sharing intention.

Experience Economy theory provides a logical foundation for constructing the processual experience of museum visits. It identifies four core experiential dimensions—education, entertainment, aesthetics, and escapism—which offer a theoretical basis for analyzing how different layers of experience influence visitors’ psychological and behavioral responses in metaverse museum contexts. Within these immersive environments, visitors’ engagement extends beyond knowledge acquisition to encompass emotional resonance and aesthetic appreciation. Therefore, this study adopts the Experience Economy theory as a key theoretical pillar for understanding the dynamic nature of the visitor experience process.

Meanwhile, the Stimulus–Organism–Response (SOR) model, through its three-layer structure of “stimulus–psychological response–behavioral response,” systematically reveals how environmental stimuli influence individual decision-making via cognitive and emotional mediators. It thus provides a structured theoretical foundation for exploring the underlying psychological mechanisms behind visitor behavioral responses in metaverse museums, while offering practical guidance for optimizing user experience and designing cultural communication strategies in digital exhibitions. In this study, digital exhibition content and interactive design are conceptualized as stimuli; organismic responses encompass visitors’ psychological immersion, emotional triggers, and cognitive engagement; and behavioral responses are reflected in satisfaction with the visiting experience and social sharing intention. Integrating the Experience Economy theory with the SOR model enables a deeper understanding of the evolving multi-level psychological mechanisms shaping visitor experiences in metaverse exhibitions.

In summary, this study integrates Experience Economy theory and the Stimulus–Organism–Response (SOR) model to construct a theoretical framework tailored to the analysis of exhibition experiences in metaverse museums. By adopting a dual perspective—immersive user experience and visitor behavioral path modeling—the research investigates the causal mechanisms among situational exhibition stimuli, visitors’ psychological responses, and behavioral intentions. Compared to traditional museology and exhibition design theories that primarily focus on spatial layout and communication flow, the integration of the Experience Economy and SOR models offers a more systematic approach to revealing the dynamic evolution of immersion, emotion, and cognition within virtual exhibitions. This interdisciplinary approach not only addresses the limitations of conventional museum research in adapting to virtual contexts, but also provides novel theoretical support for optimizing visitor experiences and realizing cultural value in digital cultural spaces.

Accordingly, the core objective of this study is to identify the key factors influencing the processual experience of visitors in metaverse museums and to examine how these factors collectively contribute to the formation of satisfaction with the visiting experience. Based on this research framework, the study proposes the following three specific research questions: (1) What are the key factors that influence visitors’ processual experiences during metaverse museum exhibitions? (2) How do these factors affect visitors’ behavioral intentions through underlying psychological mechanisms? (3) Do these factors, by influencing satisfaction with the visiting experience and social sharing intention, further promote sustained engagement and cultural communication within metaverse museum exhibitions? Addressing these questions will provide both theoretical insights and practical guidance for optimizing metaverse museum exhibitions.

To enhance the clarity of theoretical focus and structural coherence, this study employs the Experience Economy theory to define the types of exhibition stimuli and the SOR model to trace the psychological pathways and behavioral consequences, thereby constructing a comprehensive perspective for explaining metaverse museum experience mechanisms.

The structure of this study is as follows: Section 2 presents the theoretical background and literature review, focusing on the application of Experience Economy theory and the Stimulus–Organism–Response (SOR) model in metaverse museum exhibitions. Section 3 proposes the research model and hypotheses, constructing an analytical framework based on the Experience Economy theory and the SOR model. Section 4 outlines the research methodology, including questionnaire design, data collection, and measurement approaches. Section 5 presents the research findings, encompassing data analysis, reliability and validity assessments, and hypothesis testing. Section 6 discusses the study’s results and analyzes their theoretical and practical implications. Section 7 highlights the limitations of this research and suggests directions for future studies. Section 8 concludes the study. The entire research process strictly adheres to academic standards to ensure methodological soundness, analytical reliability, and the replicability of findings.

2. Theoretical Background and Literature Review

Against the backdrop of the metaverse accelerating the transformation of museum exhibitions, traditional disciplines such as museology, exhibition design, and audience studies, despite their substantial contributions, still fall short in addressing visitor behavior within virtual reality environments. Metaverse museums, characterized by immersion, multimodality, and high interactivity, have reshaped visitors’ navigation paths and experiential mechanisms, giving rise to embodied, contextualized, and real-time responsive forms of cultural participation [24]. This transformation has positioned user experience theory as a vital interdisciplinary bridge between technology and the humanities, offering significant value in understanding audience response mechanisms within virtual cultural settings.

Existing research has primarily focused on optimizing spatial layouts in traditional exhibition settings and analyzing audience satisfaction. However, in the context of the metaverse, where visitor experience paths are inherently dynamic and nonlinear, there remains a lack of systematic integration and in-depth analysis of the entire experiential process [25,26]. In particular, under the interactive influence of psychological variables such as immersion, emotional triggers, and cognitive engagement, how to transition from one-way information presentation to an experiential chain of “stimulating participation—guiding cognition—facilitating dissemination” has emerged as a critical challenge in both theoretical research and curatorial practice.

Based on this, the present chapter focuses on metaverse museums as the research subject, systematically reviewing the core characteristics of their digital exhibitions, the key dimensions of audience visiting experience, and the adaptability and limitations of existing theoretical models. Special attention is given to assessing the applicability of the Experience Economy Theory and the Stimulus–Organism–Response (SOR) model in analyzing the processual experience of metaverse exhibition visits. Through this theoretical integration and critical review, the chapter aims to establish a solid literature and conceptual foundation for constructing a research framework to explore the key factors influencing visitors’ experiences in metaverse museum exhibitions.

2.1. Digital Exhibitions and User Experience in Metaverse Museums

With the deepening integration of metaverse technologies into the cultural sector, museum digitalization is shifting from traditional webpage-based displays to immersive, interactive, and intelligent three-dimensional virtual environments. Supported by technologies such as Virtual Reality (VR), Augmented Reality (AR), Artificial Intelligence (AI), and blockchain, metaverse museums are constructing digital cultural spaces that transcend spatial and temporal limitations. Their core objective is to enhance visitors’ cultural understanding, willingness to participate, and interactive experiences [27]. Museums in various countries and regions—such as the Palace Museum in Beijing, the Louvre Museum, and the British Museum—have begun deploying virtual exhibition platforms. These platforms leverage high-precision modeling, immersive storytelling, motion capture, and virtual guided tours to enable remote cultural dissemination [28,29,30]. These practices indicate that the metaverse not only serves as a new medium for cultural preservation and communication but is also gradually evolving into a crucial vehicle for reshaping user experiences.

Compared to traditional digital exhibition platforms, metaverse museums offer not only functional advantages such as 3D visualization and remote accessibility but also activate distinct psychological mechanisms at the experiential level. Features such as sense of co-presence, avatar embodiment, and multisensory immersion enable users to experience heightened levels of presence and agency in virtual environments, fostering an embodied sense of “being there” that transcends the interactional boundaries of conventional digital media [31]. Existing research suggests that such environments facilitate psychological transfer and extension across identity, affect, and cognition, thereby encouraging active meaning-making behaviors that are inherently immersive in nature [32]. Therefore, although this study adopts the Experience Economy Theory and the Stimulus–Organism–Response (SOR) framework as its theoretical foundation, our model leverages the unique psychological characteristics of the metaverse to achieve contextual embedding and pathway reconstruction. This approach enhances the explanatory capacity and contextual adaptability of the integrated framework within immersive cultural environments.

Existing studies indicate that the value of digital exhibition technologies is no longer confined to visualizing information but lies in their capacity to stimulate users’ cognitive processing, emotional resonance, and behavioral engagement [33,34]. In immersive virtual environments in particular, psychological immersion, emotional triggers, and cognitive engagement have emerged as key dimensions influencing user experience. For example, enhanced interactivity—such as motion sensing, virtual character guidance, and real-time collaboration—has been shown to significantly boost users’ active exploration and sense of participation, thereby increasing exhibition stickiness and educational effectiveness [35]. Compared to traditional exhibition models that rely primarily on textual explanations, metaverse museums emphasize real-time interaction between visitors and exhibits, allowing users to freely navigate the space, manipulate virtual objects, and engage in social interaction [36].

First, psychological immersion is regarded as a core experiential variable in metaverse-based exhibitions, referring to the sense of presence and concentration that users attain in a virtual environment. High-fidelity visual rendering, spatial audio effects, and contextual storytelling jointly contribute to an immersive state in which users experience a sense of “escaping reality,” thereby significantly enhancing learning motivation and knowledge retention [37,38]. However, some studies have pointed out that excessive information density and sensory stimulation may lead to cognitive overload, thereby undermining the effectiveness of the exhibition experience [39]. Therefore, the design of immersive experiences must strike a balance between the depth of immersion and the manageability of information processing.

Second, emotional triggering serves as a vital mechanism in metaverse-based cultural experiences, enabling visitors to generate emotional responses and foster cultural resonance. Studies have shown that through virtual character narratives, historical scenario simulations, or interactive storytelling, visitors are more likely to establish emotional connections with the exhibition content, thereby enhancing cultural identity and their willingness to share such experiences [40]. Furthermore, collective interactions have also been shown to intensify emotional resonance—particularly during collaborative virtual visits and online discussions, where users tend to exhibit more positive emotional feedback [41].

Third, cognitive engagement reflects visitors’ active thinking and deep processing tendencies during the exhibition experience. The immersive environment of the metaverse stimulates users’ exploratory motivation, prompting them to actively retrieve exhibit information, raise questions, and construct knowledge [19]. For instance, virtual experiments, 3D decomposition of artifacts, and in-depth explanatory modules have been shown to significantly enhance users’ understanding of exhibition content [18]. However, empirical research remains limited regarding how to design appropriate cognitive pathways and optimize information load management for different user groups.

Overall, these key psychological variables provide an essential theoretical foundation for understanding visitors’ experiential processes in metaverse museums. However, current studies tend to focus on isolated experiential variables—such as enhancing immersion or eliciting emotional responses—within specific interaction segments, lacking a systematic model and empirical analysis of how multiple experiential factors (immersion, emotion, and cognition) dynamically evolve and interact throughout the entire visiting process [42,43]. In essence, the exhibition experience is a continuous process of perception, participation, and meaning making, characterized by temporal progression and cognitive staging. Relying solely on fragmented experiential indicators to evaluate exhibition outcomes fails to capture the overall logic of user experience in the metaverse. This research gap provides a clear entry point for the present study—namely, to explore how multiple experiential factors jointly influence visitors’ behavioral responses within a “full-process experience” framework.

It is particularly worth noting that current research on user experience in metaverse museums still suffers from three major limitations. First, many studies are predominantly driven by a technological perspective, focusing on platform functionality and interface interaction evaluation, while lacking psychological mechanism models centered on users’ subjective experiences [44,45]. Second, most existing research emphasizes immediate feedback or single-instance behavioral responses, yet fails to clarify the mechanisms through which exhibitions shape cultural identity at the cognitive level, stimulate social sharing intentions at the emotional level, and promote continued participation at the behavioral level [46]. Third, there is still a lack of systematic modeling and dynamic analysis regarding the interactions among multidimensional experiential factors—such as immersion, emotional resonance, and cognitive engagement—during the visiting process. In particular, how these experiential factors jointly influence visitor satisfaction and social dissemination intentions in immersive virtual environments remains underexplored [47].

In summary, although traditional theories such as museology, exhibition design, and audience research have provided valuable insights into visitor behavior, they primarily focus on physical space layout, exhibition structure, and media dissemination. These approaches lack theoretical adaptability to the immersive, interactive, and virtual nature of metaverse environments, particularly in capturing the full process of the visiting experience. Therefore, to deeply understand the dynamic formation mechanism of visitor experience in metaverse exhibitions, it is essential to introduce a theoretical framework that integrates the relationships among stimuli, psychological responses, and behavioral outcomes. Based on this need, the present study adopts the Experience Economy Theory and the Stimulus–Organism–Response (SOR) model to systematically analyze the key factors influencing the full-process user experience in metaverse museums from multidimensional, multi-stage, and multi-path perspectives, thereby laying a solid foundation for the development of the subsequent theoretical model.

2.2. Experience Economy Theory and Its Application in Metaverse Museum Exhibitions

To construct an analytical framework for understanding the visitor experience process in metaverse museum exhibitions, this study introduces the Experience Economy Theory. This theory identifies four core dimensions—education, escapism, aesthetics, and entertainment—to explain users’ psychological responses in immersive experiences, providing systematic support for understanding emotional resonance and behavioral reactions in virtual cultural spaces. Compared with traditional museology and exhibition design theories, which emphasize physical spatial layout and information dissemination, the Experience Economy Theory focuses more on the perceived value and emotional connection of the experience itself. This theoretical perspective aligns closely with the characteristics of metaverse exhibitions, which are defined by high levels of immersion, interactivity, and context-driven engagement.

This study adopts the Experience Economy Theory as an analytical framework to understand and enhance the quality and depth of visitor experiences, thereby better achieving the cultural and educational objectives of museums. First, visitors invest time and cognitive effort with the expectation of gaining experiential value from exhibitions—such as knowledge acquisition, emotional engagement, and aesthetic appreciation. The Experience Economy Theory offers a “value exchange” framework that enables museums to understand how experiential value is perceived and created and thus optimize exhibition design to meet audience expectations. Second, the theory emphasizes four core dimensions of experience. In the museum context, education represents the foundational function, aesthetics serves as a critical channel for cultural value transmission, entertainment increases attractiveness and memorability, while escapism allows visitors to become deeply immersed in the atmosphere and narrative of the exhibition. Moreover, compared with traditional museology and exhibition design theories—which tend to focus on physical space arrangement and information delivery—the Experience Economy Theory places greater emphasis on the perceptual value and emotional connection of the experience itself. This theoretical orientation aligns with the metaverse exhibition’s immersive, interactive, and context-driven nature. Therefore, this study employs the Experience Economy Theory as an analytical tool to better understand visitors’ psychological experiences and behavioral patterns within metaverse exhibitions.

The Experience Economy Theory, proposed by Pine and Gilmore (1998), argues that in the modern economic environment, competitive advantage has shifted from goods and services to the provision of immersive experiences, aiming to enhance consumers’ perceived value and loyalty [48]. The theory suggests that consumers’ core demands have evolved beyond material satisfaction, emphasizing instead the pursuit of personalized, highly interactive, and emotionally resonant experiences throughout the consumption process. To systematize the analysis of such experiences, Pine and Gilmore further identified four core dimensions of perceived experience—education, escapism, aesthetics, and entertainment—and developed a classical typology model of experiential perception. Notably, in the field of museum communication, Nechita and Rezeanu (2019) integrated the Experience Economy framework with the S-O-R model, proposing that enhancing educational and interactive elements is essential for attracting younger audiences. Their findings highlighted the pivotal role of emotional and immersive experiences in stimulating users’ intention to share, thereby offering a valuable theoretical supplement to the exhibition experience mechanisms explored in the present study [49].

This four-dimensional model has been widely applied in fields such as tourism, cultural consumption, and digital interaction. For instance, Lai et al. investigated the impact of dining experiences on tourists’ electronic word-of-mouth (e-WOM) generation, revealing that contextualized culinary experiences can significantly enhance social sharing and brand loyalty [50]. Song et al. explored temple stay experiences and confirmed that emotional value plays a critical role in improving visitor satisfaction [51]. Furthermore, Oh et al. developed a measurement scale for the experience economy and validated its effectiveness in immersive tourism and homestay consumption contexts [52].

From the fundamental perspective of the experience economy, Andersson et al. argue that experience serves as the key linkage between production and consumption, with its value varying according to individual characteristics and environmental changes, and dynamically evolving over time [53]. Genuine consumption, they assert, lies not in the ownership of goods, but in the psychological satisfaction and emotional responses gained during the process [53,54,55]. This perspective further confirms the applicability of experience economy theory in metaverse exhibition environments, especially given its emphasis on experiential fluidity and emotional arousal mechanisms, which closely align with the psychological journeys of users in immersive virtual settings.

Although direct research on the application of the experience economy in metaverse museums remains limited, existing empirical studies offer valuable references for this study. For example, Radder et al. examined three heritage museums in South Africa and explored the relationships among visitor experience, satisfaction, and behavioral intention based on the experience economy theory. Their findings indicated that “edutainment,” escapism, and aesthetic value were the key factors influencing the quality of museum experiences [56]. This study provides important insights for constructing the stimulus dimensions and developing measurement scales in the present research.

In the field of cultural metaverse applications, Yang et al. integrated experience economy theory with immersive user experience theory and conducted an experimental study at the Shanghai Museum of Glass. They developed an innovative AR-based narrative application and empirically demonstrated that immersive storytelling significantly enhances users’ sense of immersion and cultural engagement [57]. This finding further validates the explanatory power of the dimensions of the experience economy in virtual exhibition contexts and provides empirical support for the present study in modeling the mechanisms of immersion and emotional triggers.

In summary, the experience economy theory not only provides key variables for understanding the visiting experience in metaverse museums but also establishes a logical framework for modeling the entire experiential process through its focus on educational value, aesthetic triggers, escapist immersion, and entertainment participation. However, existing studies have largely focused on isolated experience measurements, lacking a systematic exploration of how these experiential dimensions interact to influence psychological responses and behavioral intentions. Therefore, this study builds upon the experience economy theory and further introduces the Stimulus–Organism–Response (SOR) model, aiming to uncover the procedural and structural mechanisms of exhibition experience in the metaverse by examining the full pathway from stimulus input and psychological processing to behavioral feedback.

2.3. Application of the Stimulus–Organism–Response (SOR) Model in Analyzing Audience Experience

To systematically examine how metaverse museum exhibitions shape audience experiences, this study employs the Stimulus–Organism–Response (SOR) model, a framework rooted in cognitive psychology and environmental behavior research. The SOR model posits that external stimuli (S) evoke internal organismic responses (O), which in turn lead to behavioral outcomes (R) [58,59]. Widely validated in domains such as consumer behavior, e-commerce, and immersive tourism, the model demonstrates strong explanatory power, particularly in interaction-intensive environments.

In this study, Stimuli (S) refers to four core experiential dimensions: Perceived Educational Appeal, Interactive Entertainment, Escapist Experience, and Perceived Visual Aesthetics. These stimuli elicit internal organismic responses—Cognitive Engagement, Emotional Trigger, and Psychological Immersion—which subsequently drive Response (R) outcomes: Satisfaction with Visiting Experience and Social Sharing Intention.

Recent empirical research demonstrates the adaptability of the SOR model to cultural and virtual contexts. For instance, Chin et al. applied the model to explore how media richness and presence shape hedonic and utilitarian values, driving behavioral and revisit intentions in VR tourism [60]. Jiang et al. combined the Experience Economy Theory with SOR to assess how aesthetics, education, and cultural connection influence perceived value and sustained engagement in virtual heritage tourism [61]. Other studies, such as that by Chen et al. also validate emotional and cognitive pathways in shaping visitor behavior in traditional festive landscapes [62]. Extensions by Jacoby et al. and Kim et al. further refine the organismic dimension into cognitive, affective, and physiological responses, and confirm SOR’s predictive power in e-commerce and online exhibitions [63,64].

In metaverse museum contexts, visitors are not passive recipients of information but active constructors of meaning, interacting through spatial co-presence, avatar embodiment, and multi-sensory immersion. While the Experience Economy Theory clarifies how audiences interact with dimensions such as education, aesthetics, escapism, and entertainment, it lacks a dynamic psychological mechanism to explain how those experiences translate into concrete behavioral outcomes. The SOR model complements this gap by modeling the process through which external stimuli trigger internal psychological changes that lead to observable actions.

To clarify the distinct contribution of this study,

Table 1. Comparison of Theoretical Models.

Study	Theoretical	Stimuli (S)	Organism (O)	Response (R)	Application Domain
Chin et al. [60]	SOR	Media Richness, Presence	Utilitarian Value, Hedonic Value	Behavioral Intention to Use VR in Tourism, Visit Intention	VR tourism sites
Jiang et al. [61]	Experience Economy + SOR	Aesthetics, Entertainment, Escapism, Education, Connection	Perceived Value, Satisfaction, Cultural Identity	Continuous Behavioral Intention	Cultural Heritage Virtual Tourism
Chen et al. [62]	SOR	Festivalscape	Spontaneous, Participation	Cognitive, Affective, Attitude and Behavior	Traditional Local Event
This Study	Integrated SOR + Experience Economy	Perceived Educational Appeal, Interactive Entertainment, Escapist Experience, Perceived Visual Aesthetics	Psychological Immersion, Emotional Trigger, Cognitive Engagement	Satisfaction with Visiting Experience, Social Sharing Intention	Metaverse Museum Exhibitions

presents a comparative synthesis of prior empirical applications of the SOR model in immersive cultural and digital exhibition environments. These studies illustrate the model’s versatility across domains such as digital commerce, immersive tourism, and cultural heritage exhibitions. However, most previous research has focused on single-dimensional stimuli or isolated psychological mechanisms, seldom integrating a comprehensive experiential framework into the SOR structure.

In contrast, the present study proposes a comprehensive analytical structure that embeds the four dimensions of the Experience Economy—Perceived Educational Appeal, Interactive Entertainment, Escapist Experience, and Perceived Visual Aesthetics—into the SOR framework. It introduces a tripartite organismic layer comprising Cognitive Engagement, Emotional Trigger, and Psychological Immersion, and includes dual response outcomes: Satisfaction with Visiting Experience and Social Sharing Intention. This integration enhances both the explanatory depth and the predictive validity of the model, while reinforcing its theoretical coherence in metaverse museum settings.

Instead of treating visitors as passive recipients, this study regards them as active constructors of meaning within multisensory, co-embodied, and avatar-mediated exhibition scenarios. Building upon the preceding comparative analysis, we argue that the core value of metaverse museum exhibitions lies in their ability to shape transformative visitor experiences through spatial co-presence, cognitive-emotional engagement, and immersive design strategies.

These experiences allow visitors to cognitively and emotionally engage with exhibition content in meaningful ways. Therefore, understanding how exhibitions in the metaverse influence the formation of visitor experience is essential for unlocking their communicative and cultural impact.

Building upon this premise, this study adopts the Stimulus–Organism–Response (SOR) framework and integrates the four experiential dimensions of the Experience Economy Theory—education, escapism, aesthetics, and entertainment—as the primary stimulus factors in analyzing how metaverse exhibitions influence visitor experiences. It further investigates the psychological responses and behavioral outcomes of visitors as “organisms,” thereby constructing a comprehensive analytical framework for the full-process experience in metaverse museum exhibitions. Based on a mechanism-oriented integration strategy, this study embeds the four experiential dimensions from the experience economy theory within the core mechanism of the SOR (Stimulus–Organism–Response) framework. Specifically, each experiential stimulus is conceptually and empirically aligned with distinct psychological responses: Perceived Educational Appeal is associated with heightened cognitive engagement; Escapist Experience evokes deep psychological immersion by simulating an alternative reality; Perceived Visual Aesthetics stimulates emotional arousal; Interactive Entertainment fosters participatory motivation. These structured mappings form a coherent stimulus–organism–response chain that extends from immersive stimuli to internal psychological states and ultimately to observable behavioral outcomes such as satisfaction and social sharing intention. Rather than serving merely as a descriptive backdrop, the experience economy theory is functionally embedded within the SOR structure as a driving mechanism. This enhances the model’s explanatory depth and internal coherence. This interdisciplinary theoretical integration not only expands the conceptual boundaries of virtual cultural experiences in the metaverse but also provides practical insights for optimizing digital exhibition design and enhancing the effectiveness of cultural communication.

3. Hypothesis Development

3.1. The Impact of Exhibition Experience Stimuli on Visitors’ Psychological Responses

According to the Stimulus–Organism–Response (SOR) model, external stimuli serve as the initiating mechanism that triggers internal psychological changes (Organism), which in turn influence subsequent behavioral responses (Response) [65]. Drawing on the Theory of Experience Economy, this study identifies four key stimulus dimensions in the context of metaverse museum exhibitions: Perceived Educational Appeal (PEA), Interactive Entertainment (IE), Escapist Experience (EE), and Perceived Visual Aesthetics (PVA). These dimensions correspond to knowledge transmission, interactive engagement, immersive escapism, and aesthetic appreciation, respectively. They are expected to activate visitors’ Psychological Immersion (PI), Emotional Trigger (ETE), and Cognitive Engagement (CE), thereby forming a comprehensive psychological response mechanism. Establishing the impact pathway from stimuli to psychological responses thus represents a critical starting point for understanding the experience mechanism of metaverse-based exhibitions.

Perceived Educational Appeal (PEA) in this study refers to the extent to which exhibition content facilitates knowledge acquisition, stimulates learning interest, and enhances visitors’ motivation to explore. As a critical stimulus, PEA reflects the audience’s subjective perception of the exhibition’s educational value and serves as a foundational element for achieving the cognitive construction and cultural dissemination goals of metaverse museums. As one of the core functions of museum exhibitions, a high level of educational appeal can significantly enhance visitors’ depth of cognitive processing and willingness to engage actively [66,67]. Through well-designed thematic narratives, immersive storytelling, and multimedia displays, visitors are able to acquire new knowledge, gain cross-cultural understanding, and further stimulate their curiosity through interactive elements such as quiz systems or virtual guides [68,69]. For instance, in history-themed exhibitions, the integration of artifacts, visual materials, and contextual storytelling can help visitors actively construct historical understanding within virtual environments, thereby fostering greater Cognitive Engagement (CE) and Emotional Trigger (ETE) [66]. Thus, PEA is regarded as a key stimulus that promotes Psychological Immersion (PI), emotional arousal, and cognitive involvement.

Interactive Entertainment (IE) refers to the exhibition’s capacity to enhance visitor engagement, strengthen immersive experience, and elevate the overall level of enjoyment through the design of interactive mechanisms. As a critical stimulus factor, IE aims to activate users’ initiative and participation motivation, serving as a key trigger that transforms “passive viewing” into “active exploration” in virtual exhibitions. Highly interactive exhibitions can stimulate visitors’ sensory perceptions and exploratory behavior, thereby deepening their involvement and understanding of exhibition content [70]. For instance, the integration of virtual reality (VR) experience zones, augmented reality (AR) interactive displays, or motion-capture-based interactions with virtual characters enables audiences to engage with exhibition themes in immersive and participatory ways [71,72]. Rhee et al. (2016), in their study on VR-based art experiences, emphasized that entertainment value plays a central role in enhancing immersion and user satisfaction [73]. Therefore, well-designed interactive entertainment mechanisms not only elevate the immediate enjoyment of the visiting experience, but also effectively contribute to the formation of Psychological Immersion (PI), Emotional Trigger (ETE), and Cognitive Engagement (CE) [74].

Escapist Experience (EE) refers to the state in which visitors, during the exhibition process, become immersed in virtual exhibition scenarios and temporarily detach from the real world, entering a highly immersive and surreal experience environment [75]. This critical stimulus factor is intended to construct an immersive participatory context that stimulates the audience’s imagination and emotional resonance beyond the boundaries of reality, thereby facilitating deeper psychological and cognitive processing. Metaverse-based exhibitions achieve this by creating virtual spaces and narrative environments that allow visitors to inhabit diverse historical, cultural, or fictional worlds, thus experiencing a strong sense of situational escapism [76]. Such escapism not only helps alleviate real-life stress but also enhances psychological immersion and emotional engagement. For example, immersive historical reconstructions, fantasy scenario simulations, and virtual world explorations can all trigger intense immersive experiences and emotional resonance. Existing studies have demonstrated that escapist experiences play a vital role in promoting emotional arousal, cognitive immersion, and positive behavioral responses [76,77]. Therefore, EE is expected to exert a significant positive influence on Psychological Immersion (PI), Emotional Trigger (ETE), and Cognitive Engagement (CE) as a key experiential stimulus.

Perceived Visual Aesthetics (PVA) refers to visitors’ subjective evaluations of the visual design of an exhibition, including color harmony, spatial composition, and artistic expression. This key stimulus factor serves to generate immediate sensory impressions, evoke aesthetic resonance, and activate emotional states that lay the perceptual foundation for subsequent immersion and cognitive engagement. In metaverse-based museums, visual design not only fulfills the function of information delivery but also enhances emotional guidance and cognitive processing through sensory aesthetics, making it a critical perceptual entry point for deep experiential engagement [78]. Research has shown that color schemes (e.g., brightness and contrast), spatial layering in composition, and the artistic quality of presentation significantly influence visitors’ aesthetic pleasure and sustained attention [79]. For instance, warm color tones tend to create a welcoming atmosphere, whereas cooler tones facilitate rational contemplation; artistic presentation methods can enhance the perceived symbolic value and cultural meaning of exhibits [70].

In immersive virtual environments, the enhancement of perceived visual aesthetics (PVA) can promote a higher degree of focused immersion, emotional resonance, and aesthetic contemplation among visitors, thereby improving the overall quality of their subjective experience and the level of psychological engagement. Prior studies have demonstrated that visual aesthetics play a positive role in increasing users’ cognitive pleasure and motivation for active exploration, and can significantly influence satisfaction with digital cultural experiences and subsequent behavioral responses [80]. Therefore, this study incorporates PVA as one of the key exhibition stimuli and hypothesizes that it exerts a significant positive effect on psychological immersion, emotional triggers, and cognitive engagement.

3.2. The Influence of Psychological Response Variables on Visiting Satisfaction

Within the Stimulus–Organism–Response (SOR) model, the Organism component functions as a mediating mechanism that bridges external stimuli and behavioral responses, reflecting individuals’ cognitive processing and emotional reactions during the experiential process [65,81]. This study focuses on three core psychological response variables: Psychological Immersion (PI), Emotional Trigger (ETE), and Cognitive Engagement (CE). These variables not only characterize the depth of users’ subjective experiences during the exhibition but also serve as critical psychological pathways influencing their Satisfaction with the Visiting Experience (SVE). A systematic analysis of these mechanisms helps to reveal how multidimensional experiential stimuli are internally transformed into positive evaluations and behavioral motivations.

Psychological Immersion (PI) refers to the subjective mental state in which visitors become fully absorbed in the exhibition experience, disregarding external distractions and deeply engaging with the exhibited content. This variable captures the extent to which users enter a flow experience, characterized by both cognitive and emotional absorption [74]. Studies have shown that a heightened sense of immersion extends users’ attention span, enhances cognitive processing efficiency, and increases situational involvement [82]. In immersive exhibitions, rich visual elements, narrative cues, and interactive mechanisms collectively create a sensory-enveloping environment that facilitates temporal distortion and focused cognitive engagement, thereby deepening visitors’ understanding of the exhibition themes [83]. For instance, empirical research on digital art exhibitions has revealed that environments integrating dynamic lighting, interactive projections, and sound design significantly enhance audience comprehension of artistic themes and emotional resonance. Moreover, immersion is often regarded as a psychological mediating mechanism that fosters cultural identification and knowledge retention. Accordingly, this study proposes the following hypotheses:

H1. 

PEA has a significant positive effect on PI.

H2. 

IE has a significant positive effect on PI.

H3. 

EE has a significant positive effect on PI.

H4. 

PVA has a significant positive effect on PI.

Emotional Trigger (ETE) refers to the subjective psychological response in which visitors experience emotional resonance, affective engagement, and situational connection during the exhibition. It serves as a key mediating mechanism in the formation of exhibition-related memory and evaluative attitudes [84]. This variable captures how emotional cues embedded in the exhibition activate internal affective responses and, through emotional arousal mechanisms, influence visitors’ satisfaction and behavioral intentions. In metaverse-based exhibitions, emotional triggers are often induced through visual stimuli, narrative construction, or interactions with virtual characters. These elements can evoke empathy, reverence, awe, or compassion in response to specific events or scenarios, thereby deepening users’ engagement and memorability of the exhibition content [85]. Prior research indicates that emotional resonance not only strengthens cultural identity but also enhances emotional activation and visitors’ willingness to share their experiences [86]. For instance, in virtual war memorial exhibitions, reconstructed historical scenes and immersive storytelling may elicit profound emotional responses to suffering and heroism, fostering identification and reflective thinking on the exhibition’s themes [87]. Furthermore, collective viewing and social interactions have also been shown to amplify emotional contagion and expressive willingness among participants. Based on this understanding, the study proposes the following hypotheses:

H5. 

PEA has a significant positive effect on ETE.

H6. 

IE has a significant positive effect on ETE.

H7. 

EE has a significant positive effect on ETE.

H8. 

PVA has a significant positive effect on ETE.

Cognitive Engagement (CE) reflects the extent to which visitors demonstrate active thinking, meaning-making, and deep information processing during the exhibition. It serves as a key path variable linking information acquisition to cognitive transformation [8,88]. This variable is used to examine whether, following exposure to exhibition stimuli, visitors are able to initiate deeper levels of cognitive processing and knowledge integration, thereby constructing more enduring and personally meaningful visiting experiences. In the context of metaverse exhibitions, immersive content presentation and highly controllable interactive mechanisms provide audiences with opportunities for autonomous exploration and problem discovery. These features stimulate intrinsic motivation for learning and encourage deeper cognitive engagement.

Research has shown that museums and other informal learning environments often encourage visitors to ask questions such as “what,” “why,” and “how,” thereby fostering the development of causal logic and historical context in their cognitive processing [89]. B Bartsch et al. pointed out that challenging gamified tasks and informational cues can enhance visitors’ ability to process complex information [90]. Meanwhile, the sense of presence in virtual scenarios can also promote knowledge internalization through immersive experiences [91]. Based on this, the following hypotheses are proposed:

H9. 

PEA has a significant positive effect on visitors’ CE.

H10. 

IE has a significant positive effect on visitors’ CE.

H11. 

EE has a significant positive effect on visitors’ CE.

H12. 

PVA has a significant positive effect on visitors’ CE.

3.3. The Path Mechanism Between Psychological Responses and Behavioral Outcomes

In the Stimulus–Organism–Response (SOR) model, Response refers to the final behavioral orientation exhibited by individuals after receiving external stimuli and undergoing internal psychological reactions. This study focuses on two key behavioral outcome variables: Satisfaction with the Visiting Experience (SVE) and Social Sharing Intention (SSI). The former measures visitors’ overall perception and emotional evaluation of the entire exhibition experience, while the latter reflects their willingness and inclination to share the experience through social channels.

Satisfaction with the Visiting Experience (SVE) is regarded as the direct outcome of psychological responses. This variable assesses visitors’ overall evaluation of multiple experiential dimensions—such as immersion, emotional engagement, and knowledge acquisition—encountered during the exhibition. It serves as a key mediating variable linking psychological reactions to subsequent behavioral intentions. Existing studies suggest that psychological immersion enhances users’ focus and emotional involvement within the exhibition space, thereby improving their overall satisfaction [82,92]. Emotional triggers strengthen the emotional connection between visitors and the exhibition content, leading to deeper emotional evaluations [93]. Cognitive engagement, in turn, promotes active information processing and meaning construction, increasing users’ recognition of the exhibition’s educational value and depth [94]. These findings indicate that the three psychological response variables play significant roles in shaping visitors’ satisfaction.

In addition, satisfaction is not only a critical indicator of users’ internal evaluations but also a key antecedent in predicting behavioral responses. Visitors with higher satisfaction levels are more likely to express opinions, recommend exhibitions, or share their visiting experiences through social media platforms, thereby extending the exhibition’s influence across broader communicative spaces [95]. Based on the above theoretical and empirical foundations, this study proposes the following hypotheses:

H13. 

PI has a significant positive effect on visitors’ SVE.

H14. 

ETE has a significant positive effect on visitors’ SVE.

H15. 

CE has a significant positive effect on visitors’ SVE.

H16. 

SVE has a significant positive effect on visitors’ SSI.

3.4. The Proposed Research Model

Based on Experience Economy Theory and the Stimulus–Organism–Response (SOR) model, this study constructs a theoretical framework to analyze the full-process experience of visitors in metaverse museum exhibitions (Figure 1). The model includes four categories of exhibition stimuli—Perceived Educational Appeal (PEA), Interactive Entertainment (IE), Escapist Experience (EE), and Perceived Visual Aesthetics (PVA)—as well as three types of psychological responses—Psychological Immersion (PI), Emotional Trigger (ETE), and Cognitive Engagement (CE)—and two behavioral outcome variables—Satisfaction with the Visiting Experience (SVE) and Social Sharing Intention (SSI). These variables form a causal path structure of “stimuli–psychological response–behavioral outcome.”

This study aims to apply the proposed model to empirically test how the four types of exhibition stimuli influence visitors’ satisfaction and sharing intentions through the mediating effects of psychological responses. Data will be collected through questionnaires and analyzed using structural equation modeling (SEM) to verify the hypothesized relationships.

By emphasizing the transformation mechanism from perceptual experience to behavioral intention in digital cultural contexts, this model fills the gap in traditional museum studies regarding immersive psychological mechanisms. The integration of multidimensional experiential stimuli and psychological processing paths provides a comprehensive theoretical basis for understanding visitor behavior in the metaverse exhibition context and lays the groundwork for subsequent empirical validation.

4. Research Methods

This study employs a structural equation modeling (SEM) approach, grounded in the Experience Economy Theory and the Stimulus-Organism-Response (SOR) model, to quantitatively examine how multidimensional experiential factors in metaverse museum exhibitions influence behavioral responses through psychological mechanisms.

4.1. Questionnaire Design and Measurement Variables

The proposed research model comprises nine key variables: Perceived Educational Appeal (PEA), Interactive Entertainment (IE), Escapist Experience (EE), Perceived Visual Aesthetics (PVA), Psychological Immersion (PI), Emotional Trigger (ETE), Cognitive Engagement (CE), Satisfaction with Visiting Experience (SVE), and Social Sharing Intention (SSI). Each variable was operationalized using validated items adapted from prior literature to ensure contextual relevance in the metaverse museum setting. Specifically, items measuring PEA were adapted from the work of Lee et al. [96,97]. IE items were revised based on Oh et al. [52,98]. EE items were derived from Radder et al. [52,56,99]. And PVA items were adjusted from Chen et al. [52,100,101]. PI was measured using modified scales from Tcha-Tokey et al. [102,103]. ETE items were adapted from Lee et al. [98]. And CE items were based on Hohyosol et al. [104]. Measurement of SVE followed scales validated by Jiang et al. [51,61,105]. While SSI was assessed using adapted items from Jo et al. [104,106,107].

All items were measured using a five-point Likert scale, ranging from 1 = “strongly disagree” to 5 = “strongly agree.” During the questionnaire development process, bilingual translation and semantic validation were conducted by three language experts. Subsequently, two museum studies scholars and three human–computer interaction experts evaluated the content validity and contextual appropriateness of each item. This process ensured the linguistic accuracy and theoretical robustness of the instrument.

The selection of the four experiential dimensions as stimulus variables—Perceived Educational Appeal, Interactive Entertainment, Escapist Experience, and Perceived Visual Aesthetics—is grounded in Pine and Gilmore’s Experience Economy framework, which identifies educational, entertainment, escapist, and aesthetic experiences as the foundational components of immersive user engagement. In parallel, the three organism variables—psychological immersion, emotional trigger, and cognitive engagement—are conceptualized to mirror the inner psychological mechanisms elicited by each experience type. This theoretical alignment ensures that the integration of the two models is both conceptually robust and empirically operationalizable. Such a design enables the SOR model to structurally capture the multi-layered nature of immersive stimuli and transform them into measurable cognitive–affective responses, thereby enhancing its explanatory power in the context of metaverse exhibitions.

4.2. Experimental Platform and Sample Recruitment

To ensure that the testing environment aligns with the context of metaverse exhibitions, this study selected the “One Woman’s Metaverse Art Gallery” on the Spatial.io platform as the experimental environment (Figure 2). Spatial.io offers a high level of immersive presentation, real-time voice and motion-based interaction mechanisms, and supports cross-platform access via WebXR technology, enabling users to seamlessly enter the same exhibition space through VR headsets, PCs, or mobile devices. Its architecture—characterized by “immersive virtual environments + synchronous multi-user interaction”—fully satisfies the technical requirements of this study, including embodied exhibition behavior, real-time experiential feedback, and measurement of Social Sharing Intention (SSI). Moreover, Spatial.io has been widely adopted in recent years across education, cultural exhibitions, and corporate collaboration scenarios, demonstrating strong technical maturity and platform stability [108].

In addition, metaverse platforms are widely recognized to require three essential characteristics—immersion, interactivity, and co-creativity—to effectively support users’ psychological pathways and behavioral mechanisms within virtual environments. These foundational dimensions are regarded as core pillars in shaping shared, persistent, and embodied digital spaces, as emphasized by Lee et al. and Li et al. [109,110]. Furthermore, recent research highlights that educational metaverse environments should integrate user interaction, platform implementation, and content application to enrich experiential learning [111]. Specifically, the Spatial.io platform has been empirically demonstrated to significantly enhance learners’ engagement, conceptual understanding, and digital literacy in educational and cultural scenarios, reinforcing both interactive and immersive learning experiences [112]. Therefore, the platform employed in this study not only fulfills the technical requirements but also exhibits high representativeness and contextual relevance, making it well-suited to support empirical investigations into cognitive–affective–social pathways within metaverse-based museum exhibitions.

Participants entered the virtual exhibition hall through their avatars and engaged in exhibit exploration, interactive manipulation, and virtual socialization. To ensure consistency in user experience, all participants were required to complete a structured visiting task lasting no less than 15 min. This task included viewing exhibits, interacting with virtual objects, and participating in virtual discussion sessions, thereby ensuring an authentic experience of the exhibition process.

A snowball sampling method was employed to recruit participants. Initial seed participants were undergraduate and graduate students majoring in museum studies, exhibition design, digital media, and interaction design from three universities. These students then invited additional participants with relevant academic backgrounds or experience via social networks. A total of 522 questionnaires were distributed. After removing responses that were incomplete or exhibited logical inconsistencies, 507 valid samples were retained for analysis.

In terms of demographic characteristics, among the valid sample (

Table 2. Demographics of participants (N = 507).

Measure	Items	Frequency	Percentage
Gender	Male	257	50.69%
	Female	250	49.31%
Age	18~24	144	28.4%
	25~34	125	24.65%
	35~44	100	19.72%
	45~60	76	14.99%
	60 and above	62	12.23%
Education	University degree or below (graduated or studying)	196	38.66%
	Bachelor’s degree (graduated or studying)	245	48.32%
	Master’s degree (graduated or studying)	52	10.26%
	PhD candidate (graduated or studying)	14	2.76%
Academic Background	Museum Studies/Cultural Heritage	194	38.26%
	Art and Design	143	28.21%
	History/Archeology	93	18.34%
	Computer Science/Digital Technology	328	64.69%
	Media/Communication	167	32.94%
	Education/Instructional Design	209	41.22%
	Business/Management	214	42.21%
	Natural Sciences/Engineering	191	37.67%
	Others	20	3.94%
Frequency of Metaverse Use	Never	36	7.1%
	Occasionally (less than once per month)	74	14.6%
	Moderate use (1–3 times per month)	283	55.82%
	Frequent use (weekly)	85	16.77%
	Highly proficient (daily)	29	5.72%
Traditional Museum Visit Frequency	Never	23	4.54%
	Rarely (once a year or less)	71	14%
	Occasionally (2–5 times per year)	236	46.55%
	Frequently (once per quarter or more)	117	23.08%
	Very frequently (monthly or multiple times per month)	60	11.83%

Variables such as “Academic Background” and “Frequency of Metaverse Use” allow multiple selections; thus, percentages are based on total option counts and may exceed the total number of participants.

), 257 participants were male (50.69%) and 250 were female (49.31%). The majority of respondents were aged between 18 and 34, accounting for 53.05%. The sample was highly educated, with 86.98% holding a bachelor’s degree or above. Participants were allowed to select multiple majors, and the primary academic backgrounds included computer science and digital technologies (64.69%), educational design (41.22%), and museum and cultural heritage studies (38.26%), indicating strong digital literacy and cultural engagement capabilities.

Regarding technological experience, 55.82% of the participants reported using metaverse platforms 1–3 times per month, and 16.77% used them weekly, reflecting a relatively high level of operational proficiency; only 7.1% indicated that they had never used such platforms. In terms of cultural participation, 46.55% of respondents reported visiting traditional museums 2–5 times per year, and another 23.08% visited at least once per quarter, demonstrating a stable foundation of cultural engagement and representativeness for analyzing responses to immersive exhibitions.

4.3. Data Analysis Methods

Data analysis was conducted using SmartPLS 4.0 and SPSS 27.0. The Partial Least Squares Structural Equation Modeling (PLS-SEM) approach was employed to evaluate both the measurement and structural models. The PLS method is particularly suitable for theory-driven exploratory research, especially under conditions involving relatively small sample sizes and complex model structures, demonstrating strong robustness and predictive capability [113,114].

The analytical procedure first assessed the reliability and validity of the measurement model, including factor loadings, composite reliability (CR), and average variance extracted (AVE). Subsequently, the structural model was evaluated by analyzing the significance of path coefficients, mediation effects, and model fit indices.

By employing a rigorous model construction and empirical testing strategy, this study reveals the underlying mechanism of the “stimulus–organism–response” process within the context of metaverse exhibitions. The findings provide a quantitative foundation for future research on optimizing museum exhibition experiences and understanding user behavior mechanisms in immersive cultural environments.

5. Results

5.1. Model Fit Evaluation

Before analyzing the structural model, it is essential to evaluate the overall model fit to ensure that the empirical data adequately matches the theoretical framework. In this study, two commonly used fit indices were employed: the Standardized Root Mean Square Residual (SRMR) and the Normed Fit Index (NFI) (

Table 3. Model fit.

Fit Index	Computed Values	Threshold Ref.
SRMR	0.047	[115]
NFI	0.783	[116]

).

The results show that the SRMR value was 0.047, well below the commonly accepted threshold of 0.08, indicating a low level of residuals and a good model fit [115]. Additionally, the NFI value was 0.783. Although traditional SEM guidelines recommend an NFI ≥ 0.90 for model adequacy, prior research has suggested that in PLS-SEM contexts—especially those involving small sample sizes or complex path structures—an NFI ≥ 0.60 can be considered acceptable [116]. In this context, the obtained NFI of 0.783 serves as valid evidence of an adequate model fit for the structural model.

In summary, the overall fit indices indicate that the model is well-calibrated and provides a solid foundation for subsequent measurement and structural model analysis.

5.2. Measurement Model Assessment

5.2.1. Indicator Reliability

Before evaluating the structural model, the reliability and validity of the measurement model must be assessed to ensure that all latent constructs are measured with sufficient quality. First, regarding factor loadings, all standardized loadings ranged from 0.819 to 0.882, well above the recommended minimum threshold of 0.70 [117], indicating that each item significantly explains its corresponding construct and possesses strong indicator reliability (

Table 4. Research constructs and factor loading.

Variables	Items	Factor Loads	Ref.
Perceived Educational Appeal (PEA)	1. This exhibition helped me acquire a great deal of knowledge and sparked my interest in the theme, motivating me to explore further. 2. I believe the exhibition provided rich and valuable educational content. 3. The exhibition presented knowledge in an engaging way, making it easier for me to understand and stimulating my motivation to learn.	0.838 0.855 0.833	[96,97]
Interactive Entertainment (IE)	1. The interactive design of the exhibition was enjoyable and fun, enhancing my visiting experience. 2. The interactive elements made me more engaged with the content and increased my sense of participation. 3. The exhibition’s interactivity enhanced my sense of immersion and encouraged me to explore and interact further.	0.819 0.829 0.855	[52,98]
Escapist Experience (EE)	1. During the exhibition, I was able to freely explore different areas and determine my own experiential path. 2. This exhibition gave me a feeling of entering another world, as if escaping from reality. 3. I could interact with the virtual environment and influence the exhibition content, making my experience more unique and personalized.	0.848 0.861 0.859	[52,56,99]
Perceived Visual Aesthetics (PVA)	1. The overall visual design of the exhibition was aesthetically pleasing and enhanced my visiting experience. 2. The color scheme, composition, and visual presentation were well-coordinated and left a strong impression. 3. The visual aesthetics and artistic expression enhanced my immersion and made me more willing to appreciate the exhibition content.	0.860 0.857 0.828	[52,100,101]
Psychological Immersion (PI)	1. While visiting the exhibition, my attention was fully focused on the content without being distracted. 2. I lost track of time during the exhibition and was completely immersed in it. 3. I experienced a strong sense of presence, as if the exhibition content were real.	0.831 0.844 0.882	[102,103]
Emotional Trigger (ETE)	1. The content of the exhibition triggered strong emotional responses in me. 2. I resonated with the exhibition theme and developed an emotional connection to it. 3. The emotional experience of this exhibition left a deep impression and prompted me to reflect on related topics.	0.848 0.825 0.853	[98]
Cognitive Engagement (CE)	1. I actively reflected on the meaning of the exhibits during the visit rather than merely viewing them. 2. The exhibition deepened my understanding of the topic and enriched my knowledge. 3. I asked many questions during the visit and tried to find the answers.	0.825 0.854 0.873	[104]
Satisfaction with Visiting Experience (SVE)	1. I was satisfied with the immersive, interactive, and educational aspects of the exhibition. 2. The overall experience met or exceeded my expectations and was highly rewarding. 3. The visit was enjoyable, and I would be willing to participate in similar exhibitions again.	0.822 0.846 0.844	[51,61,105]
Social Sharing Intention (SSI)	1. I would recommend this exhibition to friends or family so they can experience it too. 2. I am willing to share my experience on social media to let more people know about the exhibition. 3. I would like to disseminate the exhibition content through social networks and discuss it with others.	0.857 0.850 0.873	[104,106,107]

), and the finalized questionnaire structure is also presented in Table 4.

Specifically, the four stimulus dimensions—Perceived Educational Appeal (PEA), Interactive Entertainment (IE), Escapist Experience (EE), and Perceived Visual Aesthetics (PVA)—exhibited high internal consistency, with all factor loadings exceeding 0.82. This confirms the applicability of the four core dimensions of the Experience Economy theory in the context of metaverse exhibitions. The three organism-level variables—Psychological Immersion (PI), Emotional Trigger (ETE), and Cognitive Engagement (CE)—also demonstrated strong measurement validity, with all item loadings above 0.82, indicating their robustness in capturing users’ subjective experiences. Similarly, the response-level variables, namely Satisfaction with Visiting Experience (SVE) and Social Sharing Intention (SSI), showed loadings above 0.82, validating their appropriateness as behavioral outcome measures.

Overall, the distribution of factor loadings indicates that the measurement model meets the established standards of structural equation modeling. These results provide a strong foundation for subsequent assessments of convergent validity (AVE), composite reliability (CR), and discriminant validity.

To further assess the discriminant validity among the latent constructs, this study conducted a cross-loading analysis at the item level. According to the criterion proposed by Fornell and Larcker, discriminant validity is established when each measurement item’s factor loading on its corresponding construct is significantly higher than its loadings on other constructs [118].

The results showed that all measurement items had loadings above 0.80 on their respective constructs and were clearly higher than their loadings on non-corresponding constructs (

Table 5. Factor loads and cross-loads.

	CE	EE	ETE	IE	PEA	PI	PVA	SSI	SVE
CE1	0.825	0.220	0.180	0.291	0.208	0.197	0.175	0.286	0.208
CE2	0.854	0.232	0.237	0.313	0.197	0.156	0.169	0.201	0.207
CE3	0.873	0.252	0.204	0.308	0.276	0.258	0.231	0.320	0.240
EE1	0.222	0.848	0.249	0.302	0.266	0.270	0.334	0.288	0.253
EE2	0.250	0.861	0.254	0.246	0.299	0.287	0.306	0.308	0.256
EE3	0.237	0.859	0.233	0.259	0.235	0.239	0.289	0.321	0.311
ETE1	0.213	0.267	0.848	0.402	0.320	0.232	0.347	0.345	0.276
ETE2	0.183	0.247	0.825	0.351	0.284	0.217	0.332	0.327	0.245
ETE3	0.218	0.209	0.853	0.381	0.280	0.187	0.321	0.302	0.278
IE1	0.286	0.248	0.352	0.819	0.314	0.234	0.355	0.309	0.307
IE2	0.290	0.266	0.365	0.829	0.361	0.256	0.360	0.379	0.278
IE3	0.317	0.270	0.406	0.855	0.416	0.298	0.383	0.383	0.342
PEA1	0.193	0.277	0.323	0.377	0.838	0.306	0.440	0.345	0.362
PEA2	0.273	0.253	0.298	0.386	0.855	0.318	0.412	0.377	0.355
PEA3	0.208	0.261	0.261	0.343	0.833	0.271	0.412	0.375	0.282
PI1	0.233	0.251	0.197	0.253	0.284	0.831	0.246	0.250	0.205
PI2	0.191	0.279	0.162	0.245	0.304	0.844	0.229	0.204	0.193
PI3	0.194	0.266	0.280	0.308	0.321	0.882	0.277	0.220	0.215
PVA1	0.210	0.308	0.342	0.335	0.392	0.235	0.860	0.391	0.314
PVA2	0.205	0.296	0.357	0.411	0.464	0.264	0.857	0.402	0.346
PVA3	0.160	0.319	0.308	0.371	0.415	0.251	0.828	0.372	0.346
SSI1	0.267	0.350	0.343	0.364	0.405	0.245	0.426	0.857	0.361
SSI2	0.257	0.278	0.308	0.395	0.352	0.247	0.381	0.850	0.373
SSI3	0.294	0.294	0.344	0.349	0.364	0.189	0.378	0.873	0.403
SVE1	0.186	0.254	0.243	0.334	0.367	0.186	0.330	0.368	0.822
SVE2	0.214	0.269	0.253	0.319	0.293	0.226	0.333	0.390	0.846
SVE3	0.245	0.277	0.299	0.282	0.344	0.189	0.329	0.350	0.844

). For example, the loadings of items CE1 to CE3 under Cognitive Engagement (CE) were 0.825, 0.854, and 0.873, respectively, while their loadings on other constructs such as Interactive Entertainment (IE), Emotional Trigger (ETE), or Perceived Visual Aesthetics (PVA) were all below 0.32. Similarly, all three items under Emotional Trigger (ETE) had loadings above 0.82 on their designated construct, with substantially lower loadings on other constructs, further confirming the distinctiveness of the constructs.

Although some cross-loadings were observed between Social Sharing Intention (SSI) and Perceived Visual Aesthetics (PVA)—for instance, the loading of SSI1 on PVA was 0.426—SSI1 still exhibited a much higher loading on its primary construct SSI (0.857), thereby satisfying the criterion for discriminant validity.

In conclusion, all constructs demonstrated good discriminant validity without any evidence of cross-construct measurement confusion. This indicates that the latent variables are conceptually and operationally distinct, and the measurement model possesses a robust construct structure.

5.2.2. Internal Consistency Reliability and Convergent Validity

To further verify the convergent validity of the measurement model, this study calculated the Cronbach’s α, Composite Reliability (CR), and Average Variance Extracted (AVE) for each latent construct to assess their internal consistency and degree of convergent measurement. According to the criteria proposed by Fornell and Larcker (1981), a construct is considered to have adequate convergent validity when Cronbach’s α > 0.70, CR > 0.70, and AVE > 0.50 [118].

As shown in

Table 6. Indicators of the reliability and validity of the concept.

	CA	CR (rho_a)	CR (rho_c)	AVE
CE	0.809	0.813	0.887	0.724
EE	0.818	0.820	0.892	0.733
ETE	0.795	0.797	0.880	0.709
IE	0.782	0.787	0.873	0.696
PEA	0.795	0.800	0.879	0.709
PI	0.812	0.816	0.889	0.727
PVA	0.806	0.809	0.885	0.720
SSI	0.824	0.827	0.895	0.740
SVE	0.787	0.788	0.876	0.701

, all constructs reported Cronbach’s α values ranging from 0.782 to 0.824, significantly exceeding the recommended threshold of 0.70, indicating good internal consistency. In terms of Composite Reliability (CR), all constructs achieved CR (rho_c) values between 0.873 and 0.895, demonstrating strong reliability and convergent capacity among the indicators. Regarding Average Variance Extracted (AVE), all constructs had AVE values above 0.69. Specifically, Social Sharing Intention (SSI) reached an AVE of 0.740, while Perceived Educational Appeal (PEA) and Emotional Trigger (ETE) yielded AVE values of 0.709, reflecting a high level of variance explained by the respective items.

In summary, all latent variables met the statistical criteria for internal consistency, measurement reliability, and convergent validity, confirming that the measurement model is robust and providing a solid foundation for subsequent path analysis and structural model evaluation.

5.2.3. Discriminant Validity

This study adopted the Fornell–Larcker criterion to assess the discriminant validity among the latent variables. According to this method, the square root of the Average Variance Extracted (AVE) for each latent construct should be greater than its correlations with any other construct.

As shown in

Table 7. Distinguishing validity analyses.

Construct	CE	EE	ETE	IE	PEA	PI	PVA	SSI	SVE
CE	0.851
EE	0.276	0.856
ETE	0.244	0.287	0.842
IE	0.358	0.314	0.450	0.834
PEA	0.269	0.313	0.351	0.439	0.842
PI	0.241	0.311	0.252	0.316	0.356	0.853
PVA	0.227	0.362	0.396	0.439	0.500	0.295	0.849
SSI	0.317	0.357	0.386	0.429	0.434	0.263	0.458	0.860
SVE	0.257	0.318	0.317	0.372	0.398	0.239	0.395	0.441	0.837

, the diagonal elements of the correlation matrix—representing the square roots of AVE for each construct—are all substantially higher than the corresponding inter-construct correlation coefficients. For instance, the square root of AVE for Perceived Educational Appeal (PEA) is 0.842, which exceeds its correlations with Interactive Entertainment (IE) (0.439) and Perceived Visual Aesthetics (PVA) (0.500). Similarly, the square root of AVE for Cognitive Engagement (CE) is 0.851, greater than its correlations with Escapist Experience (EE) (0.276) and Social Sharing Intention (SSI) (0.317).

These results indicate that all latent constructs exhibit satisfactory discriminant validity, confirming that each construct is conceptually distinct from the others. In summary, the measurement model in this study demonstrates both strong convergent validity and adequate discriminant validity, thereby providing a solid foundation for subsequent structural path analysis.

In addition, all HTMT values between constructs, as presented in

Table 8. Distinguishing validity (HTMT values).

	CE	EE	ETE	IE	PEA	PI	PVA	SSI	SVE
CE
EE	0.339
ETE	0.303	0.354
IE	0.448	0.392	0.567
PEA	0.330	0.386	0.438	0.551
PI	0.296	0.380	0.311	0.393	0.440
PVA	0.278	0.446	0.493	0.552	0.624	0.363
SSI	0.386	0.436	0.476	0.533	0.537	0.324	0.563
SVE	0.321	0.398	0.400	0.473	0.502	0.299	0.496	0.547

, are below the recommended threshold of 0.85, further confirming that the latent variables demonstrate adequate discriminant validity.

To evaluate the model’s explanatory power for endogenous variables, the coefficient of determination (R²) was examined. As shown in

Table 9. Values of R2 and Q2.

	R2	R2 Adjusted	Q2
CE	0.166	0.159	0.116
ETE	0.268	0.262	0.184
PI	0.193	0.186	0.134
SSI	0.195	0.193	0.142
SVE	0.152	0.147	0.102

, the model accounts for 26.8% of the variance in Emotional Trigger (ETE), 19.3% in Psychological Immersion (PI), 16.6% in Cognitive Engagement (CE), 15.2% in Satisfaction with the Visiting Experience (SVE), and 19.5% in Social Sharing Intention (SSI), indicating a moderate level of explanatory power for key psychological and behavioral constructs.

Additionally, to assess the model’s predictive relevance, the Stone–Geisser Q² statistic was used through cross-validated redundancy analysis. The results show that all Q² values are greater than zero (ranging from 0.102 to 0.184), indicating that the model exhibits good predictive relevance for all endogenous variables [119].

5.3. Structural Model Assessment

To examine potential multicollinearity among the structural path variables, this study conducted a Variance Inflation Factor (VIF) analysis. As shown in

Table 10. Covariance diagnostics.

Paths	VIF
CE → SVE	1.103
EE → CE	1.208
EE → ETE	1.208
EE → PI	1.208
ETE → SVE	1.110
IE → CE	1.376
IE → ETE	1.376
IE → PI	1.376
PEA → CE	1.469
PEA → ETE	1.469
PEA → PI	1.469
PI → SVE	1.108
PVA → CE	1.512
PVA → ETE	1.512
PVA → PI	1.512
SVE → SSI	1.000

, all VIF values are well below the commonly accepted threshold of 5.0, with the highest value being 1.512. These results indicate that there is no significant multicollinearity issue in the model, and the estimated path coefficients are statistically robust and reliable in terms of interpretation [120].

5.3.1. Path Coefficient Analysis

As shown in

Table 11. Structural Model Path Coefficients.

Paths	β	SD	t-Value	p-Value	Results
N = 507
CE → SVE	0.165	0.045	3.644	0.000	Supported
EE → CE	0.162	0.046	3.482	0.001	Supported
EE → ETE	0.097	0.048	2.031	0.042	Supported
EE → PI	0.179	0.050	3.561	0.000	Supported
ETE → SVE	0.242	0.041	5.913	0.000	Supported
IE → CE	0.261	0.054	4.859	0.000	Supported
IE → ETE	0.296	0.057	5.183	0.000	Supported
IE → PI	0.142	0.052	2.742	0.006	Supported
PEA → CE	0.102	0.056	1.830	0.067	Unsupported
PEA → ETE	0.100	0.055	1.815	0.070	Unsupported
PEA → PI	0.205	0.057	3.626	0.000	Supported
PI → SVE	0.139	0.043	3.249	0.001	Supported
PVA → CE	0.003	0.054	0.052	0.959	Unsupported
PVA → ETE	0.182	0.058	3.156	0.002	Supported
PVA → PI	0.065	0.052	1.254	0.210	Unsupported
SVE → SSI	0.441	0.038	11.525	0.000	Supported

and Figure 3, among the 16 structural paths tested, 12paths demonstrated statistical significance at p < 0.05.

Specifically, Escapist Experience (EE) significantly and positively influenced Cognitive Engagement (β = 0.162, p = 0.001), Emotional Trigger (β = 0.097, p = 0.042), and Psychological Immersion (β = 0.179, p = 0.000), indicating its strong role as a core stimulus in immersive exhibition contexts. Interactive Enjoyment (IE) exhibited significant positive effects on all three psychological responses, with the strongest influence on Emotional Trigger (β = 0.296, p = 0.000). Perceived Visual Aesthetics (PVA) only significantly affected Emotional Trigger (β = 0.182, p = 0.002), with non-significant effects on the other organism variables. Perceived Educational Appeal (PEA) had a significant impact only on Psychological Immersion (β = 0.205, p = 0.000), and no significant effect on Emotional Trigger or Cognitive Engagement (p > 0.05).

Regarding the organism-to-response paths, Cognitive Engagement, Emotional Trigger, and Psychological Immersion all significantly predicted Satisfaction with the Visiting Experience (SVE), with Emotional Trigger being the strongest predictor (β = 0.242, p = 0.000). Finally, SVE had a strong predictive effect on Social Sharing Intention (SSI) (β = 0.441, p = 0.000), validating the behavior mechanism of “satisfaction-driven sharing”.

5.3.2. Mediation Analysis

To further uncover the psychological mechanisms underlying audience behavioral responses in the metaverse museum, a mediation path analysis was conducted, focusing on the indirect effects of key stimulus variables on behavioral intention through psychological response variables. As shown in

Table 12. Mediation Analysis Results.

Relationship	β	T-Value	p-Value	2.50%	97.5%	Results	VAF
EE -> PI -> SVE	0.025	2.386	0.017	0.009	0.050	Significant Mediation	25.00%
IE -> PI -> SVE	0.020	2.106	0.035	0.006	0.044	Significant Mediation	12.99%
PEA -> PI -> SVE	0.028	2.195	0.028	0.009	0.061	Significant Mediation	28.87%
PVA -> PI -> SVE	0.009	1.066	0.286	−0.003	0.031	Non-Significant Mediation	14.52%
PEA -> PI -> SVE -> SSI	0.013	2.090	0.037	0.004	0.028	Significant Mediation	29.55%
IE -> ETE -> SVE -> SSI	0.032	3.327	0.001	0.017	0.053	Significant Mediation	35.16%
EE -> CE -> SVE -> SSI	0.012	2.346	0.019	0.004	0.025	Significant Mediation	26.67%
IE -> CE -> SVE -> SSI	0.019	2.689	0.007	0.008	0.036	Significant Mediation	24.36%
CE -> SVE -> SSI	0.073	3.347	0.001	0.033	0.119	Significant Mediation	50.00%
ETE -> SVE -> SSI	0.107	4.919	0.000	0.067	0.152	Significant Mediation	50.00%
PI -> SVE -> SSI	0.061	3.004	0.003	0.025	0.106	Significant Mediation	50.00%
EE -> ETE -> SVE	0.023	1.925	0.054	0.003	0.051	Marginally Significant Mediation	23.47%
EE -> CE -> SVE	0.027	2.490	0.013	0.010	0.053	Significant Mediation	26.47%
IE -> ETE -> SVE	0.072	3.623	0.000	0.039	0.117	Significant Mediation	34.95%
PEA -> ETE -> SVE	0.024	1.762	0.078	−0.001	0.055	Marginally Significant Mediation	25.81%
EE -> PI -> SVE -> SSI	0.011	2.226	0.026	0.004	0.024	Significant Mediation	25.00%
IE -> CE -> SVE	0.043	2.858	0.004	0.019	0.078	Significant Mediation	24.29%
PVA -> CE -> SVE -> SSI	0.000	0.049	0.961	−0.008	0.009	Non-Significant Mediation	0.00%
PEA -> CE -> SVE	0.017	1.486	0.137	0.000	0.046	Non-Significant Mediation	19.77%
PVA -> ETE -> SVE	0.044	2.556	0.011	0.015	0.083	Significant Mediation	45.36%
PVA -> ETE -> SVE -> SSI	0.019	2.410	0.016	0.007	0.038	Significant Mediation	44.19%
IE -> PI -> SVE -> SSI	0.009	2.000	0.046	0.003	0.020	Significant Mediation	13.24%
PVA -> CE -> SVE	0.000	0.050	0.960	−0.018	0.020	Non-Significant Mediation	0.00%
EE -> ETE -> SVE -> SSI	0.010	1.847	0.065	0.001	0.023	Marginally Significant Mediation	23.26%
PVA -> PI -> SVE -> SSI	0.004	1.046	0.295	−0.001	0.014	Non-Significant Mediation	14.29%
PEA -> ETE -> SVE -> SSI	0.011	1.677	0.094	0.000	0.026	Marginally Significant Mediation	26.19%
PEA -> CE -> SVE -> SSI	0.007	1.440	0.150	0.000	0.021	Non-Significant Mediation	18.42%

, several mediation paths were found to be statistically significant.

Specifically, Perceived Educational Appeal (PEA) exerted a significant indirect effect on Satisfaction with the Visiting Experience (SVE) through Psychological Immersion (PI) (β = 0.028, T = 2.195, p = 0.028), accounting for 38.21% of the total effect, indicating a partial mediation. Similarly, Interactive Entertainment (IE) also had a significant indirect effect on SVE through PI (β = 0.020, T = 2.106, p = 0.035), with a VAF (Variance Accounted For) of 13.00%, suggesting a weak but statistically significant mediation, supporting the bridging role of PI between stimulus and satisfaction.

Several significant serial mediation paths leading to Social Sharing Intention (SSI) were also identified. For example, the paths IE → CE → SVE → SSI (β = 0.019, T = 2.689, p = 0.007) and EE → CE → SVE → SSI (β = 0.012, T = 2.346, p = 0.019) were both significant, with VAF values of 13.19% and 8.57%, respectively. These results indicate that interactive and escapist experiences can exert significant, albeit limited, indirect effects on behavioral intention via Cognitive Engagement (CE) and satisfaction.

Among all indirect effects, Emotional Trigger (ETE) demonstrated the strongest mediation effect on SSI via SVE (β = 0.107, T = 4.919, p < 0.001), with a VAF of 50.00%, confirming the central role of emotional response in driving behavioral intention.

In contrast, some mediation paths were not statistically significant. For instance, the indirect effects of Perceived Visual Aesthetics (PVA) on SVE via PI (p = 0.286) or CE (p = 0.960) were not significant, suggesting that aesthetic perception alone, without interactive support, may not be sufficient to trigger deeper processing or behavioral transformation. Similarly, the path PEA → CE → SVE → SSI was also non-significant (p = 0.150), indicating that the effective delivery of educational content still requires enhanced situational construction and experiential design.

Overall, the findings support a partial mediation model in which Psychological Immersion (PI), Cognitive Engagement (CE), and Emotional Trigger (ETE) function as key mediators linking perceived stimuli to behavioral responses. The VAF results further reveal that different types of psychological responses play distinct roles in the stimulus–behavior chain, with emotional and immersive mediators emerging as particularly influential mechanisms for driving user engagement and social sharing.

6. Discussion

Grounded in the theory of experience economy and the Stimulus–Organism–Response (SOR) model, this study systematically examined how four types of exhibition stimuli in metaverse museums—Perceived Educational Appeal, Interactive Entertainment, Escapist Experience, and Perceived Visual Aesthetics—influence visitors’ Satisfaction with the Visiting Experience and Social Sharing Intention through psychological mechanisms such as Psychological Immersion, Emotional Trigger, and Cognitive Engagement. The empirical results clearly demonstrate that Interactive Entertainment, Escapist Experience, and Emotional Trigger emerge as the key factors in shaping metaverse exhibition experiences, showing strong and significant path effects. These elements form the core mechanism driving deep user engagement and positive evaluations. In contrast, the effects of Perceived Educational Appeal and Perceived Visual Aesthetics were relatively weaker, suggesting that traditional knowledge-centered design may need to be re-evaluated in virtual environments.

Furthermore, in terms of theoretical contribution, this study does not merely juxtapose the Experience Economy Theory with the SOR model; Rather, it achieves a structured integration by aligning the four experiential dimensions—education, entertainment, escapism, and aesthetics—with the stimulus component of the SOR framework. These dimensions are conceptually and empirically mapped to corresponding organism variables—psychological immersion, emotional trigger, and cognitive engagement—thereby constructing a coherent “experience type–psychological mechanism–behavioral response” pathway. This structured alignment enhances both the explanatory depth and internal coherence of the SOR model in metaverse contexts. Notably, by embedding the Experience Economy typology into the core mechanism of the SOR framework, this study represents one of the first attempts to develop an integrated psychological-behavioral pathway in immersive digital museums. It expands the theoretical applicability of the SOR model while offering new insights into how sensory, emotional, and cognitive responses dynamically shape virtual exhibition experiences.

6.1. Key Drivers of Processual Experience

First, Interactive Entertainment was identified as the most significant factor influencing visitors’ psychological responses, exerting strong and positive effects on Emotional Trigger, Cognitive Engagement, and Psychological Immersion. This finding not only reinforces the foundational role of “entertainment experience” in the experience economy theory but also highlights that interactivity in metaverse cultural contexts is no longer a supplementary feature for enhancing amusement—it has become a critical catalyst that drives audience participation, facilitates comprehension of exhibition content, and stimulates deep reflection. Compared to the passive, reception-based experiences typical of traditional museums, metaverse exhibitions offer a more engaging and exploratory pathway, enabling visitors to achieve “learning through fun” and “knowledge through play.” This underscores a fundamental distinction between metaverse museums and conventional museum exhibitions. Consistent with the findings of Choi et al. on “enhancing cultural understanding through virtual reality narratives” [121], the present study suggests that future exhibition design should integrate interactive mechanisms into the core cognitive framework in a systematic manner.

Second, Escapist Experience also demonstrated positive effects across emotional, immersive, and cognitive dimensions. Contrary to traditional perspectives that treated escapist experience as mere transient emotional diversion or low-involvement entertainment, the present findings reveal that escapist experience in virtual exhibitions operates through a dual mechanism of emotional buffering and cognitive activation. Immersed in the virtual environment, visitors are able to temporarily detach from real-world distractions and enter a state of focused mental engagement, which facilitates deeper understanding of exhibition content. This mechanism aligns with the propositions of Trope and Liberman in their review of Construal Level Theory (CLT), which suggests that variations in psychological distance can influence individuals’ information processing strategies and thereby shape their learning styles and decision-making processes [122]. These findings imply that future exhibition design should consider developing a “layered immersion” structure—leveraging narrative guidance, spatial design, and role-based participation to create cultural environments that are both psychologically safe and cognitively stimulating.

Third, compared with other stimuli, the effect of Perceived Educational Appeal appears to be weakened in virtual environments. The findings indicate that it significantly influences only Psychological Immersion, but not Emotional Trigger or Cognitive Engagement, suggesting a potential dilution of the museum’s traditional educational function in immersive settings. This challenges the long-standing assumption that “authority of knowledge equals value” and reflects a shift in user attention—from “what is learned” to “how it is learned.” In highly immersive virtual spaces, the absence of contextualization and interactivity may hinder deep visitor engagement with educational content. This observation is consistent with the findings of Anderson and Rainie [123], who, based on expert interviews, argued that digital natives tend to prioritize immediacy and contextual relevance of experience over the precision of knowledge. To enhance the cognitive and behavioral impact of educational appeal in metaverse museums, educational strategies should transition from “content delivery” to “experience construction. “Based on this insight, the present study proposes three practical strategies. First, strengthen immersive narrative structures by embedding educational content within storylines, thereby internalizing learning tasks through contextual cues. Second, implement gamified learning incentives—such as task unlocking, knowledge challenges, and achievement badges—to increase the interactive value and motivational appeal of educational material. Third, create manipulable knowledge objects and collaborative exploration environments, such as task-based teamwork or VR-supported co-learning spaces, to encourage active processing and in-depth dialog around educational content. Fourth, integrate hybrid experience mechanisms that link virtual and physical exhibition narratives—for instance, providing digital previews of on-site exhibits, AR-guided physical visits, or virtual achievement redemption during in-person visits—to foster a continuum of engagement and enhance visitors’ intention to participate in offline museum activities. These approaches may help reconstruct the psychological activation pathways of educational appeal in virtual settings and restore its core function in shaping user experience and behavioral intention.

In addition, although Perceived Visual Aesthetics (PVA) was found to significantly promote Emotional Trigger, it did not exhibit direct effects on Psychological Immersion or Cognitive Engagement. This finding suggests that in metaverse environments, visual elements function more as emotional initiators rather than primary drivers of deep experiential engagement. While aesthetic design can indeed attract attention and evoke aesthetic resonance, its impact may remain superficial if not integrated with narrative logic and interactive mechanisms. This aligns with the argument by Elliott et al. [124], who emphasize that visual design should support users’ cognitive processing rather than rely solely on visual appeal. To enhance the impact of PVA on immersive and learning outcomes, a shift from emotional stimulation to cognitive coordination is essential. This study proposes that visual design should be reconceptualized to: (1) guide cognitive processing and organize information through graphical logic, hierarchical layers, and visual anchors; (2) enhance visual–interactive coupling by embedding visuals within navigational, triggering, and feedback mechanisms; and (3) align visual style with exhibition narratives and users’ psychological characteristics to foster cognitive coherence and emotional resonance. Through these strategies, visual aesthetics can move beyond surface-level appeal and become a critical experiential resource that supports immersion, cognitive engagement, and ultimately, deeper cultural understanding and behavioral intention. These findings collectively highlight the importance of integrating entertainment, immersion, and design logic as synergistic drivers of meaningful visitor experiences in metaverse museum environments.

6.2. Design Implications for Virtual Museums

Building on the effects of stimuli on organism variables, this study further confirmed the mechanisms influencing Psychological Immersion, Emotional Trigger, and Cognitive Engagement on Satisfaction with the Visiting Experience. Among them, Emotional Trigger exhibited the strongest effect, highlighting that establishing emotional connections between users and metaverse exhibitions is a critical pathway to enhancing experiential quality. This finding reinforces the theoretical stance of “emotion first,” and supports the contextual learning model proposed by Falk and Dierking, which emphasizes the essential role of emotional involvement in museum learning and memory formation [22]. It also suggests that metaverse exhibition design should place greater emphasis on narrative appeal, emotional expression, and mechanisms for identity resonance.

Meanwhile, both Psychological Immersion and Cognitive Engagement exerted significant effects on visitor satisfaction, indicating that users’ focused attention and depth of cognitive processing are fundamental to shaping overall experiential perceptions. In the highly open and flexible cultural space of the metaverse, immersion is not merely a product of sensory presentation, but a psychological state co-constructed through emotional involvement and cognitive guidance. This suggests that an effective exhibition experience should not aim solely for “immersion” in isolation but rather strive to establish a sequential experience pathway of “immersion → understanding → identification.”

It is worth emphasizing that this study found Psychological Immersion, Emotional Trigger, and Cognitive Engagement to be not only key direct predictors of user satisfaction, but also significant mediators linking external stimuli to behavioral responses through multiple indirect pathways in digital exhibitions within the metaverse museum context. Among these, Emotional Trigger emerged as the most prominent mediator, underscoring the central role of emotional experience in activating visitors’ intention to engage in social sharing. In contrast, Perceived Educational Appeal and Perceived Visual Aesthetics showed relatively weaker or non-significant effects, which invites critical reflection.

One plausible explanation is that the educational content in many metaverse exhibitions may be overly implicit or presented in ways that lack interactivity and contextual clarity, thereby weakening users’ perceived educational value and cognitive engagement. Additionally, the entertainment-centric orientation of virtual exhibitions may unintentionally overshadow the learning components, especially when visual spectacle dominates narrative substance. Similarly, although aesthetic elements can enhance visual appeal, they may fail to evoke meaningful emotional or cognitive responses unless tightly integrated with thematic relevance and interpretive cues. These findings suggest that effective immersive educational design should go beyond surface-level visual beauty and incorporate structured scaffolding, emotional anchoring, and participatory learning mechanisms to more effectively stimulate user satisfaction and behavioral intentions.

This finding highlights a paradigm shift from content-driven to psychologically driven experience mechanisms, offering both theoretical grounding and practical insights for pathway-oriented optimization in the design of metaverse-based cultural exhibitions.

6.3. Theoretical Advancement: Toward a Processual Experience Model

Finally, Satisfaction with the Visiting Experience was found to significantly influence Social Sharing Intention, indicating that a high-quality digital exhibition experience not only enhances user retention and revisit intention, but also stimulates users’ desire for expression and engagement in social dissemination. In the current cultural landscape characterized by active social media participation, experiential quality serves as a direct trigger for public expression and cultural influence. This finding reveals the transmission pathway through which digital cultural products evolve from individual immersion to collective diffusion, providing empirical support and strategic guidance for cultural communication design.

In summary, this study empirically constructs and validates a process experience mechanism in metaverse exhibitions characterized by interaction-led, emotion-driven, and cognition-regulated dynamics, extending beyond the traditional paradigm of “knowledge as value.” The findings suggest that immersive experience arises not only from visual stimulation, but more importantly from the co-activation of cognitive pathways and emotional engagement; emotional triggers serve as key mediators driving satisfaction and sharing behavior; and cognitive engagement determines whether an exhibition yields lasting educational impact. These insights provide a theoretical foundation for modeling cultural experiences in the metaverse, as well as practical strategies for optimizing content planning, interaction design, and dissemination mechanisms in virtual exhibitions.

Future research may further explore the moderating effects of individual user characteristics—such as cultural background, digital literacy, and aesthetic preferences—on the experiential pathway. Longitudinal studies are also encouraged to examine how immersive experiences influence knowledge construction, cultural identity formation, and cross-platform dissemination over time.

It is also worth noting that although this study is grounded in the Experience Economy Theory and the SOR framework, our empirical results suggest that certain psychological mechanisms may be amplified in the metaverse environment. For instance, the strong predictive power of psychological immersion and emotional trigger may stem from unique features of the metaverse, such as spatial co-presence, embodied navigation, and real-time social cues—experiential dimensions largely absent in traditional digital exhibitions. These findings imply that the metaverse may activate a distinct pathway of embodied cognition and immersive response, which merits further theoretical refinement and empirical validation. Building on this, future research may extend current models by incorporating constructs such as virtual self-expansion, identity-play, and presence-based agency, contributing toward a more robust theoretical framework for understanding cultural experiences in immersive virtual environments. These findings not only validate the psychological mechanisms predicted by the SOR model but also extend the application of Experience Economy theory from physical exhibitions to digital immersive spaces, thus providing a process-oriented lens for future metaverse-based cultural communication research.

7. Implications and Limitations

7.1. Theoretical Implications

This study constructs and empirically validates a theoretical framework grounded in the Stimulus–Organism–Response (SOR) model, aiming to uncover the underlying psychological mechanisms shaping visitors’ processual experiences in metaverse museum exhibitions. By integrating the theory of experience economy into the SOR framework, the study moves beyond traditional museum research that primarily centers on post-visit evaluations and cognitive learning outcomes, and instead adopts a more dynamic, interaction-driven, and process-oriented analytical perspective.

The empirical findings reveal that Interactive Entertainment and Escapist Experience are the most influential experiential stimuli in activating psychological responses, thereby challenging the long-established dominance of Perceived Educational Appeal in cultural exhibition settings. This indicates that in immersive and exploratory metaverse environments, visitors prioritize the mode of engagement over the volume of information delivered. Such a shift underscores a transformation in the epistemological foundation of cultural exhibitions—from knowledge transmission to experience construction—where cognitive agency is activated not through didactic instruction but through interactive, affective, and contextualized experiences.

Furthermore, this study confirms the mediating role of Emotional Trigger as a core mechanism in the experiential pathway, reinforcing the significance of emotional engagement in shaping meaning-making processes in digital culture. The validated effects of Psychological Immersion and Cognitive Engagement also extend existing theoretical understandings of deep user experience. Collectively, these insights contribute to the development of a more comprehensive explanatory model for immersive cultural experiences in the metaverse, enriching the application of SOR theory and advancing the theoretical discourse on digital exhibition design.

7.2. Practical Contributions

This study offers several practical contributions for the design, management, and dissemination of metaverse museum exhibitions.

First, interactive design should be embedded at the core of exhibition planning rather than treated as an auxiliary entertainment layer. Interactivity must be leveraged as a primary mechanism to stimulate visitors’ cognitive engagement and contextual immersion. Practically, this can be implemented through narrative-driven interaction, responsive feedback systems, and collaborative exploration modules that deepen users’ sense of participation and meaning-making.

Second, emotional engagement strategies should be recognized as essential pathways for constructing memorable and impactful exhibition experiences. By embedding character-driven narratives, culturally resonant themes, and historically grounded emotional contexts, designers can evoke users’ empathy, thereby enhancing both satisfaction and the willingness to share their experiences with others.

Third, the findings suggest that conventional museum education models may have limited direct impact on visitors’ cognitive and emotional responses in virtual immersive contexts. Consequently, metaverse museums need to reimagine the delivery of educational content. Strategies such as gamification, nonlinear storytelling, and exploratory learning environments can stimulate intrinsic motivation and facilitate the integration of situated learning with participatory cognition, thereby enhancing the perceived educational value of digital exhibitions.

Finally, this study reveals that satisfaction with the visiting experience significantly enhances social sharing intention, indicating that high-quality immersive experiences do not merely promote user retention but also activate an “experience–expression–dissemination” mechanism. This finding provides new strategic directions for expanding the cultural influence and communicative reach of metaverse-based exhibitions through visitor-driven diffusion.

7.3. Research Limitations and Future Directions

Despite the theoretical contributions and empirical findings of this study, several limitations should be acknowledged, which also indicate directions for future research.

First, the experimental platform—Spatial.io—provided a representative and immersive virtual exhibition environment, yet its thematic content and spatial configurations were relatively limited. Although the platform enabled high levels of interactivity, the singular exhibition scenario may constrain the generalizability of stimulus effects across more diverse exhibition formats. Future studies should incorporate a broader array of metaverse exhibition types to improve the external validity of the model.

Second, the sample predominantly comprised digitally literate young adults with higher education backgrounds. Although snowball sampling reached participants from varied academic disciplines, the demographic coverage excluded critical groups such as older adults, adolescents, and underrepresented cultural communities. This limits the representativeness of the findings. Future research should include more demographically and technologically diverse user groups to explore potential differences in experiential pathways across segments.

Third, the cross-sectional survey design used in this study only captures a single-time-point snapshot of user experience and thus limits insight into behavioral dynamics over time. Although significant associations among variables were identified, longitudinal trends and learning processes remain unexplored. Future research is encouraged to adopt longitudinal or behavioral tracking methods to investigate how immersive cultural experiences evolve and contribute to sustained knowledge construction and identity formation.

Moreover, while a digitally savvy sample enables the study of early adopters’ behaviors, it simultaneously restricts generalizability. Users with lower technological fluency may demonstrate distinct patterns of engagement, suggesting the need to investigate how digital literacy shapes user immersion and emotional involvement within virtual cultural spaces.

In light of these limitations, future research may be expanded along three key directions: (1) Implement longitudinal or experimental methods (e.g., eye-tracking, A/B testing) to examine the evolution of psychological and behavioral patterns across repeated exhibition experiences; (2) Investigate moderating effects of individual characteristics—such as digital literacy, aesthetic sensitivity, and cultural background—on the experiential mechanism; (3) Examine the long-term educational, communicative, and identity-related impacts of metaverse exhibitions in multi-platform and cross-cultural contexts.

In addition, although Spatial.io provided essential technical affordances—such as spatial co-presence, real-time interaction, and cross-device access—it lacks the narrative depth, curatorial logic, and cultural specificity of purpose-built metaverse museums. Future studies should explore more culturally immersive, thematically rich platforms to test and expand the current model in domain-specific exhibition contexts.

Finally, this study relied solely on self-reported Likert-scale measures. While statistically robust, such instruments may not fully capture the immediacy and variability of users’ psychological and emotional responses in immersive settings. Future research is encouraged to integrate biometric (e.g., EEG, eye-tracking) and behavioral (e.g., navigation patterns, dwell time, interaction frequency) data to triangulate and enrich the analysis of user engagement. The incorporation of physiological and behavioral metrics will enhance ecological validity and provide a more holistic understanding of affective and cognitive processes in metaverse cultural experiences.

8. Conclusions

This study constructed and empirically validated a theoretical model of stimulus–psychological response–behavioral outcome, grounded in the theory of experience economy and the Stimulus–Organism–Response (SOR) framework, to explore the experiential mechanisms of visitors in metaverse museum environments. Drawing on structural equation modeling based on 507 valid responses, the study systematically revealed how four types of exhibition stimuli—Perceived Educational Appeal, Interactive Entertainment, Escapist Experience, and Perceived Visual Aesthetics—influence Satisfaction with the Visiting Experience through Psychological Immersion, Emotional Trigger, and Cognitive Engagement, ultimately promoting Social Sharing Intention.

First, the results identified Interactive Entertainment and Escapist Experience as primary drivers of psychological responses. Interactivity fosters engagement and facilitates meaning-making, while escapist elements generate emotional resonance and cognitive involvement through immersive environments. In contrast, Perceived Educational Appeal was found to significantly impact only immersion, indicating that in metaverse settings, learning motivation is more effectively triggered by processual and experiential design than by the authority or volume of content. Visual Aesthetics, while effective in eliciting emotional responses, had limited direct influence on cognitive engagement. These findings emphasize that immersive, interactive, and emotionally rich stimuli are central to forming the core experience pathway leading to visitor satisfaction and sharing behavior.

Second, the relatively limited impact of educational stimuli suggests the need for a paradigm shift in digital cultural education. To enhance educational appeal in virtual exhibitions, abstract content must be translated into perceivable, actionable, and participatory experiences. This can be achieved through narrative-based exploratory tasks, gamified learning modules with real-time feedback, and collaborative learning spaces that promote meaningful interaction. The pedagogical focus should shift from passive information transmission to active sense-making, realizing a transformation from “knowledge output” to “experience construction.”

Third, although Visual Aesthetics positively influenced emotional response, its weak impact on cognitive engagement and immersion may reflect a lack of deeper narrative and interactive integration. For visual design to enhance cognitive and immersive outcomes, it should evolve from a purely decorative role to one that supports storytelling, guides cognition, and aligns with user interaction patterns. Aesthetic elements should be meaningfully tailored to the exhibition’s thematic narrative and target audience’s psychological profiles to optimize both affective and cognitive resonance.

Fourth, among the psychological response variables, Emotional Trigger exerted the strongest effect on satisfaction, underscoring the central role of emotional engagement in shaping digital cultural experiences. Psychological Immersion and Cognitive Engagement also demonstrated significant effects, supporting a chained experiential pathway of “immersion → understanding → identification.” In turn, satisfaction strongly predicted Social Sharing Intention, indicating that high-quality immersive experiences can extend individual engagement into secondary dissemination, thereby amplifying cultural influence and communication sustainability.

Fifth, the study successfully addressed its three core research questions: (1) Identifying the key experiential stimuli influencing the metaverse museum visiting experience; (2) Uncovering how these stimuli affect behavioral intention through psychological mechanisms; (3) Demonstrating how satisfaction mediates the pathway between psychological response and sharing intention, thereby promoting sustained engagement and cultural communication.

Sixth and most critically, this study introduced an interdisciplinary theoretical synthesis by integrating experience economy theory and the SOR model into the context of metaverse cultural experiences. Originally grounded in marketing and consumer psychology, these frameworks proved to be highly explanatory for digital museum settings. The four dimensions of experience economy—education, entertainment, escapism, and aesthetics—aligned coherently with the SOR structure of stimulus, organism, and response. This integration offers a novel analytical lens for virtual exhibition research and audience experience design, providing both theoretical innovation and empirical evidence for optimizing the design and dissemination strategies of digital cultural products.

In summary, this study identifies Interactive Entertainment and Escapist Experience as dominant experiential drivers, confirms Emotional Trigger as the core mediating mechanism, and verifies Satisfaction as a key predictor of Social Sharing Intention. The proposed stimulus–organism–response pathway systematically explains how digital visitors experience and disseminate metaverse exhibitions. These findings offer a structured model for understanding audience behavior in immersive cultural environments and contribute to the advancement of user-centered design for virtual exhibitions. Nevertheless, to generalize these findings more broadly, future research must address current methodological limitations—such as sample representativeness, platform specificity, and reliance on self-report data—by adopting more diverse samples, multi-platform validations, and multi-modal measurement techniques to improve ecological validity and theoretical robustness.