How Does Digital Experience of Cultural Heritage Transform into Sustained Behavioral Intention? Assessing Perceived Value and Place Attachment Mechanisms Based on Value Adoption Model

Abstract

The rapid development and deep integration of digital technology into cultural heritage have created new experiential paradigms for tourists. However, to transform from technological application to behavioral retention, the internal mechanisms through which digital experiences are internalized into stable, sustained behavioral intentions must be elucidated. The influence of perceived value on tourists’ long-term behavioral intentions via place attachment remains largely unexplored. Using the value adoption model (VAM), this study constructs a sequential mediation model of “digital experience–perceived value–place attachment–sustained behavioral intentions” and employs structural equation modeling to examine cross-sectional survey responses from 618 tourists visiting Shandong Museum, China. Findings reveal that the functional dimensions of interactive experience and perceived ease of use significantly enhance perceived value, whereas the sensory dimensions of immersive and hedonic experiences have no significant impact on perceived value—possibly because tourists in cultural heritage contexts prioritize knowledge acquisition over sensory stimulation. Perceived value significantly and positively predicts place attachment and sustained behavioral intentions, and place attachment strongly predicts sustained behavioral intentions (including word-of-mouth recommendation, revisit intention, and sharing). This study extends the VAM to offline cultural heritage digital experience contexts, demonstrates that functional utility is more critical than sensory stimulation in driving value perception, and validates the value attachment–behavior transformation pathway, providing theoretical foundations and practical implications for cultural heritage digitalization management.

1. Introduction

Driven by the global wave of digitalization, cultural heritage tourism destinations are undergoing a profound transformation. They are implementing virtual reality (VR) and augmented reality (AR) solutions to forge immersive experiential contexts, alongside enhancing engagement and pleasure through interactive touchscreens, mobile applications, and gamification design [1]. Traditional sightseeing models have gradually failed to satisfy modern tourists’ needs for in-depth experiences, convenient personalized interactions, and sensory pleasure [2,3]. In 2025, the “Museums in the Metaverse” global survey led by the University of Glasgow showed that 79% of respondents expressed willingness to use VR/AR to access collections and artifacts that are difficult to publicly exhibit, reflecting the synchronous growth of supply and demand for digital technology experiences among visitors [4]. Digital technologies provide unprecedented possibilities for presenting and disseminating heritage content [5,6]. These technologies can transcend spatial and temporal limitations, allowing tourists to perceive history and culture in entirely new ways, such as through VR reconstruction of ancient architectural landscapes [7] or AR overlay of historical information onto real-world scenes [8]. More importantly, they significantly enhance the quality of tourist experiences [9]. Understanding how much they impact visitor experience quality is crucial in enhancing economic returns for cultural heritage sites.

Within the increasingly competitive tourism market, tourists’ post-visit behavioral tendencies—including intentions to revisit, recommend, and engage in word-of-mouth communication—are core indicators for measuring long-term viability and sustainable growth of tourism destinations [10]. Sustained customer sources are key for enterprises to maintain resilience and achieve sustainable development [11]. Therefore, providing high-quality services and experiences is pivotal for establishing and maintaining customer loyalty [12]. Thus, examining the relationship between heritage destinations’ digital experiential dimensions and visitor sustained behavioral intentions is particularly important. Unique immersive experiences, such as VR tourism participation, can significantly enhance tourists’ attachment to cultural heritage sites [13] because they provide them with high perceived value and satisfaction, making them more likely to revisit, recommend to others, or actively participate in heritage conservation [6,14].

Prior research on digital technology in heritage tourism has primarily addressed digitized preservation, exhibition, and visitor engagement through VR/AR platforms [6,15]. Most studies have adopted theoretical frameworks such as the Technology Acceptance Model (TAM), Stimulus–Organism–Response model (S-O-R), and Expectation–Confirmation Model (ECM) to examine how technological attributes influence user satisfaction and behavioral intentions [6,16,17,18,19,20], with emotional attachment recognized as a critical antecedent of sustained behavioral intentions [21,22]. However, three significant limitations persist in the existing literature. First, related studies have predominantly focused on online digital platforms and virtual display contexts, with insufficient attention to offline digital experience settings where visitors interact with digital technologies at physical heritage sites [3,6,23,24,25,26]. Second, a considerable portion of research focuses on single experiential cues, failing to systematically examine the synergistic effects of multiple experience dimensions—such as immersion, interactivity, ease of use, and hedonism—on perceived value and behavioral intentions [27,28,29,30]. Third, existing research emphasizes immediate visitor reactions rather than long-term behavioral changes, limiting our understanding of how digital technologies enable sustainable growth of cultural heritage [31,32].

Furthermore, although a few researchers have examined place attachment formation through virtual experiences [33,34] and others have investigated how digital experiences influence perceived value [14,35], most studies regard perceived value as a direct antecedent of behavioral intentions [36], neglecting the transmission mechanism through place attachment. This fragmentation has led to significant insufficiency in explaining tourists’ long-term behavioral intentions. In summary, three critical gaps remain in the existing literature: (1) a lack of integrated frameworks examining how multiple digital experience dimensions collectively influence perceived value; (2) insufficient understanding of the transmission mechanism from perceived value to place attachment in digital heritage contexts; and (3) limited empirical evidence on how place attachment mediates the relationship between value perception and sustained behavioral intentions in offline cultural heritage settings.

To address this, we employed the value adoption model (VAM) as the core theoretical framework for analysis. VAM theory emphasizes that users’ perceived value of products or services is a key driving factor for their adoption and sustained behavior [37,38]. This aligns with the logic of this study’s focus on how digital technology experiences influence tourists’ behavioral intentions through value perception. By introducing VAM, this study analyzes how offline cultural heritage digital technology experiences combine with tourists’ behavioral characteristics. Additionally, VAM provides a multidimensional perspective to address the limitations of single-dimensional analysis. Compared to TAM and ECM models, which solely emphasize “perceived usefulness” or “satisfaction,” the VAM model can simultaneously capture tourists’ rational and emotional evaluations [39], which helps explore long-term sustained intention issues in depth. Based on VAM, this study examines how digital technology experiences enable tourists to form long-term emotional connections and behavioral intentions toward cultural heritage sites by enhancing their perceived value and place attachment. The introduction of this long-term perspective affords us complete awareness of the potential of digital technology to promote sustained advancement across heritage contexts.

This study addresses these gaps and makes three distinct contributions to the literature. First, it extends the VAM to offline cultural heritage digital experience contexts by incorporating four experience dimensions—immersive, interactive, ease of use, and hedonic experiences—into a unified perceived value framework, thereby bridging the disconnect between technology acceptance research and tourists’ emotional–cognitive experiences. Second, it establishes and empirically validates the “perceived value–place attachment–sustained behavioral intentions” transmission mechanism, revealing how tourists’ value assessments are internalized into emotional identity connections with heritage sites and subsequently transformed into long-term supportive behaviors. This mechanism explains why tourists who perceive high value from digital experiences develop stronger place attachment and demonstrate greater intentions to revisit, recommend, and share their experiences. Third, it provides differentiated insights into the relative effectiveness of functional versus sensory experience dimensions in driving value perception, offering evidence-based guidance for heritage destination managers to optimize digital technology investments.

The subsequent sections unfold in the following manner. Section 2 establishes conceptual foundations alongside research hypotheses, systematically reviewing the relevant literature. Section 3 details methodological approaches and data acquisition procedures. Section 4 demonstrates empirical outcomes and validates hypothesized relationship paths among the variables. Section 5 examines the main findings. Finally, the concluding Section 6 and Section 7 draw research conclusions, summarizes the study’s contributions, proposes practical recommendations, and highlights the limitations of this study alongside prospective inquiry avenues.

2. Theoretical Background and Hypotheses

2.1. VAM

VAM was proposed by Kim et al. [40] to explain individuals’ adoption mechanisms when faced with innovative technologies or services. Its core construct is perceived value—the users’ subjective evaluation of the net utility obtained from using a particular technology or service. In related research over the past decade, perceived value has been consistently regarded as an overall assessment formed through “benefit–sacrifice” trade-offs and has been proven to be an important antecedent and mediating mechanism of attitudes and behavioral intentions [41]. Furthermore, the benefit side typically encompasses functional and hedonic values simultaneously; the former emphasizes utility, ease of use, and other instrumental attributes, while the latter emphasizes pleasure, emotional satisfaction, and other experiential attributes. The synergistic enhancement of both can significantly strengthen an individual’s overall value assessment and promote subsequent decision-making [39]. Compared to TAM, which primarily focuses on functional acceptance pathways, VAM explicitly incorporates hedonic and emotional dimensions into value assessment, thus possessing stronger explanatory power for the chain process of “value judgment–continuous use” in complex digital contexts [42]. Combined with the digital experience context of this study, cues such as immersion, interactivity, ease of use, and hedonic experiences jointly enter value trade-offs and converge into higher value perception, driving adoption and continuous participation. This has received empirical evidence support in mobile and immersive applications, like VR/AR sightseeing plus virtual participations [24,37].

As a powerful theoretical framework, VAM has been widely validated across multiple fields, with application research showing diverse trends. In the field of customized services and technology adoption, VAM has been used to reveal users’ value perceptions of personalized services, with research finding that perceived value plays a mediating role in adoption intention [43]. Additionally, regarding emerging technologies and continuous usage behavior, VAM can effectively explain users’ long-term adoption intentions for new technologies, such as wearable devices [44] and smart mobility services [45], highlighting the central position of value assessment in user acceptance of innovative services and the cultivation of technology stickiness. In cultural tourism research, the application of VAM and its core concept of perceived value has also been fully validated. Perceived value and satisfaction play mediating roles between experience quality and behavioral intentions, revealing how high-quality experiences are transformed into positive behaviors through value perception [36,46]. Perceived value enhances tourists’ revisit and recommendation intentions and emphasizes its role in constructing tourists’ place identity and emotional connections with destinations [47]. These applications collectively demonstrate that perceived value in VAM is not limited to traditional functional or emotional benefits but also includes deep value judgments consistent with tourists’ personal values. VAM can effectively explain the transformation process from multidimensional experience value to sustained behavioral intentions, particularly within cultural heritage settings.

Specifically, VAM can systematically reveal the psychological mechanism from tourists’ digital experiences to sustained behavior. Based on VAM theory, when tourists’ perceived benefits are significantly enhanced across multiple dimensions of digital experiences, this will ultimately lead to higher perceived-value evaluations [37,40]. Although VAM originally emphasizes ‘perceived benefits–perceived sacrifice’ net value assessment, this study adopts a benefit-focused conceptualization of perceived value, operationalizing only benefit-side experience cues into the model. This approach is justified on both theoretical and contextual grounds. First, this benefit-focused operationalization aligns with established practices in cultural heritage tourism research, where perceived value has been predominantly measured through experiential benefits including functional, emotional, and epistemic dimensions [36]. Second, in free-admission museum contexts such as Shandong Museum, the primary monetary costs associated with museum visits are substantially reduced. While some digital experience equipment (e.g., AR glasses) may involve optional fees, the overall cost threshold for engaging with digital heritage experiences remains relatively low, thereby diminishing the salience of sacrifice-related trade-offs for most visitors. Third, meta-analytic evidence indicates that in value perception, the effect sizes of perceived benefits are generally stronger than those of perceived sacrifices [41], suggesting that benefit-side variables offer greater explanatory power for understanding tourist value judgments. Therefore, in this study, perceived value refers specifically to tourists’ subjective assessment of the experiential benefits obtained from digital technology interactions at cultural heritage sites. The four experience dimensions of this study—immersion, interactivity, ease of use, and hedonic experiences—jointly enhance tourists’ intrinsic motivation and perceived extrinsic quality. When perceived value is significantly increased, tourists form positive attitudes and further develop cognitive and emotional attachment more easily, manifesting as a deep identification with cultural heritage values and a psychological sense of belonging [36,47]. Place attachment serves as a psychological bridge, transforming value perception into sustained behavior, including revisit intentions, positive word-of-mouth recommendations, and participation in sustained cultural behavioral intentions [47,48].

2.2. Tourism Digital Technology Experience

Tourism experience is academically defined as a comprehensive process of subjective feelings, emotions, cognitions, and behavioral responses that tourists generate after interacting with destinations, local residents, and tourism services during their tourism journey [49]. Researchers have generally emphasized the multidimensional attributes of experience as a core topic in tourism research. Otto and Ritchie [50] proposed that the tourism experience comprised six sub-dimensions: novelty, hedonism, interactivity, and comfort, highlighting the holistic and sensory characteristics of the experience. Subsequently, the tourism industry was defined as a typical service industry, and the tourist experience was regarded as a psychological evaluation process based on subjective feelings [51]. With increasing research, the connotations of experience have expanded continuously. Kim et al. [52] developed a specialized tourism experience scale that measured tourist experience from multiple dimensions, such as hedonism, local culture, meaning depth, knowledge acquisition, sense of participation, and novelty; scholars began placing greater emphasis upon cultural plus cognitive aspects of experience.

Entering the digital era, research has gradually shifted toward the deep integration of technology and experience. With the widespread application of digital mechanisms, notably VR and AR, tourism fields are actively exploring and innovating forms of experience. Studies show that digital technologies can reshape tourist experiences at multiple levels, including visual, auditory, interactive, and narrative, significantly enhancing tourists’ sense of immersion and presence [53]. Specifically, the core elements of VR experience include visual attractiveness, entertainment, pleasure, and immersive escapism; digital systems increasingly drive determining pleasure and presence illusion, emphasizing how essential interactivity coupled with technological intuitiveness remains for digitally enhanced tourism experiences [54,55,56].

When users visit cultural heritage destinations, they often immerse themselves in highly realistic digital environments, obtaining a “being there” feeling through high-quality visual presentation and multisensory stimulation. This deep immersive experience enhances tourists’ cognitive focus and helps improve cultural learning effectiveness [15,57]. Meanwhile, human–computer interaction and personalized exploration functions provided by digital museums significantly enhance users’ sense of participation and perceived control, effectively stimulating their learning motivation and continuous participation intention [58,59]. Additionally, systems’ ease of use and interface friendliness have been proven to be key factors in users’ perceived value and usage attitudes as they can effectively lower technology usage thresholds, reduce user frustration, and significantly increase usage intentions [60]. More importantly, the entertainment and emotional pleasure experiences brought by digital technologies in cultural heritage museums can significantly enhance tourist satisfaction and sustained behavioral intentions, such as revisit intention [61]. In summary, tourism experience in the digital era no longer focuses solely on traditional cognitive and emotional levels but increasingly emphasizes the sense of immersion, interactivity, convenience, and emotional value brought by technology.

2.3. Impact of Cultural Heritage Digital Technology Experience on Perceived Value

2.3.1. Immersive Experience

Immersive experience originates in flow theory, referring to an optimal experience state in which individuals become completely engaged, with time perception disappearing due to highly concentrated attention when interacting with the environment [62]. This psychological state is a core variable in digital tourism and experience economy research. Early researchers proposed that people often actively sought alternative contexts that could alleviate daily stress and negative emotions to obtain psychological comfort and emotional regulation [63]. Subsequent scholars further pointed out that tourists pursued knowledge acquisition and sightseeing activities during their tourism journey and opportunities to temporarily “escape reality,” satisfying their need for emotional release and self-realization through wholehearted immersion [64]. Therefore, immersive experience is regarded as a key dimension in tourism that allows tourists to detach from daily life and completely immerse themselves in unfamiliar and fresh environments, satisfying their multiple motivations for exploration and pleasure [65].

Perceived value is tourists’ subjective and holistic evaluations that form after weighing the benefits obtained from tourism experiences, such as experience quality, emotional satisfaction, and knowledge acquisition, against the costs paid [66]. In the context of cultural heritage tourism, perceived value emphasizes tourists’ assessment of cultural significance, historical authenticity, and knowledge acquisition [67]. When tourists obtain highly immersive experiences through digital technology, their attention becomes highly focused, perceived experience benefits are significantly amplified, and attention to costs is weakened [54,65]. This mechanism of benefit maximization and cost weakening makes immersive experience a key driving force in enhancing tourists’ perceived value of digital cultural heritage tourism [68]. A high sense of presence and flow experienced by tourists in immersive scenarios can significantly increase their perceived value of virtual tourism products [69]. In the field of heritage tourism, a high-quality experience has proven to be a significant antecedent of perceived value [67]. Furthermore, the degree of immersive experience demonstrates a strong positive association with perceived value, and high-immersion scenarios can significantly enhance tourists’ value perception and re-participation intention for the overall experience [70]. Accordingly, we hypothesize the following:

H1. 

Immersive experience significantly and positively impacts perceived value.

2.3.2. Interactive Experience

Interactivity is a key element in digital technology experience research and is widely recognized as an important mechanism that drives user engagement and perceived satisfaction. It is typically defined as a process by which users can actively influence environmental or system content and obtain real-time feedback during operations [71]. In VR and AR environments, systems can adjust the presented content in real time according to users’ movements, gestures, walking trajectories, and gaze directions, creating highly dynamic and personalized experience contexts [72]. In digital applications used in cultural heritage museums, interactivity is an important link between achieving immersive experiences and promoting knowledge absorption. Interactive functions in digital museum exhibitions can enhance visitors’ emotional connections with exhibits, transforming them from passive viewing to active exploration [14]. Virtual tours, AR overlay explanations, digital puzzles, and multi-user collaborative experiences enable audiences to learn historical and cultural backgrounds during operations, enhancing their sense of participation and interest and improving their perceived value of the overall visiting experience [15]. High levels of interactivity provide convenience in information acquisition and make visitors feel autonomous and engaged during exploration, enhancing their emotional satisfaction and cognitive gains [73]. High interactivity significantly enhances users’ information acquisition efficiency and interactive enjoyment, improving their perceived value and satisfaction [74]. Accordingly, we hypothesize the following:

H2. 

Interactive experience significantly and positively impacts perceived value.

2.3.3. Perceived Ease of Use (PEOU)

The ease-of-use experience in digital technology experience research is widely regarded as an extension and concretization of “PEOU” in TAM. Its core connotation is that users perceive that using a system requires minimal effort and that the operation process is simple and easy to learn, emphasizing the barrier-free nature of system use and low-effort perception [75]. In digital museums and immersive technology environments, ease of use is directly related to users’ operational efficiency, learning curve, and psychological load. When users perceive interfaces as simple and operational steps as intuitive, they become more prone to perceiving fluency and positive emotions, enhancing their technology acceptance intention [74]. Particularly in virtual tours or AR scenarios at cultural heritage museums, a good usability design can reduce users’ distraction during operations, allowing them to focus on exhibiting content and cultural narratives, enhancing immersion and overall satisfaction [76]. Additionally, ease-of-use experience helps tourists obtain more knowledge and emotional and entertainment returns with less effort, enhancing their evaluation of the functional, learning, and emotional value of the entire digital-museum experience [68]. Therefore, in digital tourism and online exhibition environments, ease of use significantly enhances users’ perceived value and satisfaction [77]. Accordingly, we hypothesize the following:

H3. 

PEOU significantly and positively impacts perceived value.

2.3.4. Hedonic Experience

Hedonic experience refers to users’ subjective psychological feelings driven by intrinsic pleasure, excitement, and happiness during the process of using technology or services; it is a process-centered experience that pursues emotional satisfaction [78]. In the digital presentation of cultural heritage museums, hedonic experience is regarded as an important component of visitor experience, with its core purpose being to stimulate positive emotions and participation intention through interest and immersion [14,15]. Perceived enjoyment is a core intrinsic motivation variable that describes information system adoption that is capable of promoting users’ positive attitudes and value assessments toward platforms and content [79]. In AR/VR contexts, immersion and interactivity can significantly enhance telepresence functions, making users feel as if they are in real scenarios, triggering flow states and enhancing pleasure [80]. This emotional state further improves users’ value perception of digital exhibitions, enabling them to understand cultural content more profoundly at the cognitive and emotional levels [68]. Perceived enjoyment is also an important antecedent that drives users’ perceived value, satisfaction, and continued usage intention toward technology or platforms [81]. Accordingly, we hypothesize the following:

H4. 

Tourists’ hedonic experience positively influences their perceived value.

2.4. Impact of Perceived Value on Place Attachment

Perceived value refers to tourists’ comprehensive subjective assessment during tourism experience processes, encompassing multidimensional values, including functional, emotional, cultural, and social aspects, and it dynamically adjusts according to tourists’ cultural backgrounds and time changes [82]. Place attachment is a multidimensional relational construct pertaining to destination relationships. According to relevant review studies, its connotation typically encompasses interrelated psychological components, including functional dependence on places, symbolic identification, and emotional bonding while exhibiting diverse structural configurations and measurement approaches across different contexts [83]. Halpenny [84] conceptualized place attachment as a composite construct comprising place dependence, place identity, and place affect and examined the explanatory and predictive power of this three-dimensional structure on pro-environmental behavior. Recent tourism research continues to operationalize place attachment through dimensions such as place dependence, place identity, place affect, and place social bonding, with its structural validity and behavioral explanatory power being consistently validated across various contexts [85]. Within the realm of cultural heritage visitation and museum experiences, visitors’ place attachment is more prominently manifested through cognitive internalization and identity confirmation of historical and cultural significance, as well as through positive emotions evoked by experiences, such as pleasure, pride, nostalgia, and belonging. Empirical support has been provided from perspectives including how museum experiences facilitate place identity and cultural identity, and how emotions reinforce place attachment [86,87,88].

Notably, the emergence of digital technologies, particularly VR and AR, has introduced distinctive pathways for place attachment formation in cultural heritage contexts. Unlike traditional place attachment that typically develops through repeated physical visits and prolonged direct exposure to a place [83] or destination image that primarily captures cognitive and affective evaluations of a location [33], digitally mediated place attachment can emerge through technologically enabled presence and virtual engagement within a single visit, representing a distinct formation pathway that transcends physical and temporal constraints. Research indicates that VR tourism involvement can significantly enhance tourists’ place attachment through the sense of presence—the psychological feeling of “being there”—even without physical co-presence [34]. This telepresence effect, generated by immersive technologies, enables visitors to experience spatial and temporal immersion in reconstructed historical environments, facilitating cognitive engagement with cultural narratives and emotional connections with heritage sites [56]. Furthermore, VR experiences have been found to positively influence destination image and place attachment formation, with the immersive and interactive nature of digital technologies enabling personalized exploration that strengthens identity-based attachment [33,34]. However, whether digitally mediated place attachment formed through on-site digital experiences at actual heritage sites follows similar mechanisms remains underexplored, highlighting the need for empirical investigation in offline digital experience contexts.

Therefore, this study adopts the core dimensions of “identity” and “affect” to more precisely capture the key psychological changes driven by heritage experiences [22,89]. Overall, place attachment serves as a critical psychological foundation for transforming experiences and value into long-term relationships. Existing studies have validated its role as either a key mediator or an important antecedent in destination models. The higher tourists’ perceived value of heritage sites, the greater the likelihood of forming emotional and identity-based connections with them, thereby significantly strengthening place attachment [90].

Therefore, from the VAM theoretical perspective, perceived value directly enhances tourists’ attitudes and satisfaction and strengthens their place attachment by promoting cognitive and emotional identification. Accordingly, we hypothesize the following:

H5. 

Perceived value significantly and positively impacts place attachment.

2.5. Impact of Perceived Value on Cultural Heritage Sustained Behavioral Intention

Sustained behavioral intentions represent a critical outcome variable in cultural heritage tourism research, reflecting tourists’ future behavioral orientations following their experiences. This construct emphasizes tourists’ tendencies toward relationship continuity with destinations and positive dissemination after completing their experiences, with its conceptual foundation traceable to the tradition of defining and measuring favorable behavioral intentions in service quality and customer relationship research [91]. Prior studies examining tourists’ subsequent behavioral intentions have explored multiple dimensions, including word-of-mouth evaluation, consumption, recommendation and revisit intentions, and loyalty, among which recommendation- and revisit-related intention indicators have been widely employed to capture post-experience sustained behavioral orientations [92]. In research related to digital cultural heritage experiences, two primary streams have emerged. One stream focuses on explaining continuance usage and continued participation intentions through technological attributes and acceptance mechanisms, establishing a theoretical tradition of continuance usage centered on expectation confirmation and subsequent satisfaction, which has been continuously validated and extended within cultural heritage technology contexts such as digital museums [68,93] while also integrating with value-oriented technology adoption perspectives that emphasize continuance usage and adoption mechanisms based on perceived value [94,95]. The other stream predominantly reveals the formation pathways of subsequent intentions from the perspectives of experiential mechanisms and psychological responses, emphasizing the driving effects of psychological variables such as emotional experiences, satisfaction, and place attachment on subsequent intentions including recommendation and revisit [96].

Consequently, the existing literature has established an operationalization tradition surrounding sustained behavioral intentions that centers on relationship maintenance and word-of-mouth diffusion while accommodating experience continuity in digital contexts [68,97]. Building upon the classical operationalization tradition of recommendation and revisit in prior research and incorporating how tourism experience sharing studies capture experience spillover and dissemination intentions, this study adopts three indicators—word-of-mouth recommendation, revisit intention, and sharing—to represent sustained behavioral intentions in the context of on-site visits to cultural heritage museums [92,98]. Research generally maintains that sustained behavioral intentions serve as a critical indicator in driving sustainable tourism destination advancement while measuring the experiential success of tourist experiences [99].

Perceived value is a key antecedent of tourists’ behavioral intentions. High levels of perceived value may trigger favorable affective reactions and attitudes, elevating the probability of future behaviors [100]. Zhou [101] found that in the context of cultural heritage digital museums, perceived value was validated as a key mediator connecting technology and continued participation intention. From the VAM perspective, perceived value influences tourists’ emotional attitudes and their behavioral intentions, driving their intention to continue participating in cultural heritage tourism activities in the future. Accordingly, we hypothesize the following:

H6. 

Perceived value significantly and positively impacts cultural heritage sustained behavioral intentions.

2.6. Impact of Place Attachment on Cultural Heritage Sustained Behavioral Intentions

In cultural heritage digital experience research, place attachment has been confirmed as an important antecedent of tourists’ sustained behavioral intentions. In VR and other digital contexts, tourists’ immersive participation can significantly enhance place attachment, whereas place attachment significantly and positively predicts tourists’ revisit and recommendation intentions [34]. A large body of empirical work has revealed that place attachment demonstrates marked positive influences on sustained behaviors associated with revisits alongside word-of-mouth [22,34,96]. Place attachment enhances tourists’ psychological belonging and responsibility identification, transforming the meaning identification and emotional investment formed during experiences into commitment behaviors, reducing alternative and transfer intentions, stabilizing loyalty tendencies, and ultimately driving revisits, active recommendations, and continued attention [34,102]. In digital experiences, technologies such as VR/AR, immersive projection, and interactive installations enhance tourists’ cognition of functional, emotional, and symbolic values, stimulating positive attitudes [14], subsequently enhancing place attachment and increasing sustained behavioral intentions such as revisit and recommendation [34]. Accordingly, we hypothesize the following:

H7. 

Place attachment significantly and positively impacts tourists’ cultural heritage sustained behavioral intentions.

2.7. Sequential Mediation Mechanism of Perceived Value and Place Attachment

While the preceding hypotheses establish individual relationships among digital experience dimensions, perceived value, place attachment, and sustained behavioral intentions, these relationships do not fully capture the process by which digital experiences are transformed into long-term behavioral orientations. Building upon this logic, we propose a sequential mediation mechanism wherein perceived value and place attachment function as distinct yet interdependent stages in the experience-to-behavior transformation process [96,103].

Specifically, perceived value represents the initial cognitive appraisal stage, reflecting tourists’ evaluations of the experiential benefits derived from digital interactions [66,104]. Subsequently, place attachment constitutes the affective identity stage, through which tourists internalize their evaluative judgments into identity-based recognition of cultural heritage significance and develop emotional bonds characterized by pride, belonging, and affective ties with heritage sites [105].

This staged mechanism is particularly salient in digitally mediated heritage contexts [31]. Digital technologies primarily function to enhance interpretive experiences; consequently, their influence on sustained behavioral intentions tends not to manifest immediately [106]. Rather, digital experiences first shape tourists’ value perceptions, which in turn cultivate identity-based emotional attachment, ultimately driving sustained behaviors such as revisit, recommendation, and experience sharing [107].

Accordingly, we conceptualize perceived value and place attachment as theoretically ordered sequential mediators rather than parallel mediators—together constituting a value attachment chain that links digital-experience dimensions to sustained behavioral intentions.

H8. 

Perceived value and place attachment sequentially mediate the relationship between digital experience dimensions and sustained behavioral intentions.

Based on these hypotheses, the following theoretical model was constructed (Figure 1):

3. Research Design

3.1. Case Site Selection

This study selected Shandong Province, which is the birthplace of Confucian culture, with its “ritual and music culture” and “benevolence and righteousness thought” profoundly shaping the spiritual foundation of traditional Chinese culture. Shandong Museum, as a centralized display platform for Qilu culture, is also an important symbol of Shandong culture, known as the “reception hall of Qilu culture” [108]. Shandong Museum has unique advantages in terms of cultural resources and thematic focus. The exhibition design of Shandong Museum emphasizes the in-depth presentation of Confucian thought, ritual and music systems, and local historical culture, forming a distinctive cultural recognition [109]. Therefore, the survey data can reflect tourists’ attitudes and cognitions of traditional Chinese culture.

The digital construction of Shandong Museum has always been at the forefront domestically, launching digital exhibition halls, immersive interactive exhibitions, and various online virtual exhibitions. It extensively introduces technologies including VR, AR, AI-powered storytelling, large-scale data representation and embodied immersion; it has promoted the upgrade from traditional static displays to multisensory, interactive, and immersive experiences and has provided tourists with mature immersive experience scenarios. Therefore, the site selection ensures that research results can authentically reflect tourists’ perceived experiences with digital technology.

Selecting Shandong Museum as the survey case site and tourists at Shandong Museum as survey subjects can comprehensively capture tourists’ cognitive, emotional, and behavioral responses in the context of digital dissemination of Confucian culture, providing solid empirical support for exploring how digital technology enhances tourist experiences and promotes cultural inheritance.

3.2. Questionnaire Design

An initial section within the survey introduced participants to digital experience technologies that are mainly used in most museums to facilitate their responses. The second survey component recorded detailed descriptive information on the respondents, including gender, education level, age, occupation, monthly income level, and daily Internet usage time. The third part contained 36 questions involving eight measurement dimensions: immersive experience, interactive experience, PEOU, hedonic experience, perceived value, place attachment, and sustained behavioral intentions. All questionnaire items were scored on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). The items in each dimension of this section were adapted from previous studies. Immersive experience and PEOU scales for this study were obtained from research by Cheng et al. [23] and were measured by four items each. The interactive experience scale was adopted from Deng et al. [110], Jin et al. [111], and Shipps and Phillips [112] and was measured using four items. The hedonic experience scale was based on Yersüren and Özel [113] and Kim and Hall [114] and adjusted to four measurement items for use in combination with the specific context of this study. The perceived value scale was adopted from Xie [115] and included 11 measurement items. The place attachment scale was based on research by Hoang et al. [116], Luo and Xia [117], and Yuksel et al. [118], adjusted to six measurement items for use in combination with the specific context of this study. The sustained behavioral intention scale was adopted from Fan et al. [119] and Lin and Kuo [120] using three items—word-of-mouth, revisit, and recommendation—for measurement in combination with the specific context of this study.

To validate survey rigor in addition to utility, multiple seasoned tourism industry specialists were invited to review and critique various survey aspects, including item wording and answer option settings, ensuring the questionnaire’s accuracy. As all the scales adopted in this study referenced mature foreign literature, two bilingual experts were specially hired to proofread to guarantee that the survey content precisely conveyed the original meanings and aligned with the Chinese cultural context.

A small-scale pilot survey was conducted in late July 2025 to test the usability of the questionnaire. Thirty surveys were disseminated, and respondents with museum visiting experience were invited to complete them. Drawing from initial feedback outcomes, the questionnaire underwent adjustments in three ways: first, simplifying some item expressions; second, correcting terms prone to ambiguity; and last, deleting some items with duplicate meanings.

3.3. Data Collection and Sample Characteristics

The survey was conducted in August 2025 at Shandong Museum. A convenience sampling method was employed, targeting visitors who had experienced digital technology installations during their visit. Trained research assistants distributed paper-based questionnaires to visitors at the museum exit area after confirming their digital technology experience through a screening question. A total of 644 questionnaires were collected. Questionnaires were deemed invalid and excluded based on the following criteria: (1) excessive missing data (more than 10% of items unanswered); and (2) patterned responding (e.g., selecting the same response option for all or nearly all items). After applying these exclusion criteria, 618 valid questionnaires were retained, yielding a valid response rate of 95.9%, meeting the sample collection standards recommended by Comrey and Lee [121].

3.4. Reliability and Validity

SPSS (version 29.0) was used to test the reliability and validity of the questionnaires. First, Cronbach’s alpha coefficient was used as a reliability test indicator. Second, the Kaiser–Meyer Olkin (KMO) sampling method and Bartlett’s test of sphericity were used to test the sample data and determine the applicability of the sample.

3.5. Data Analysis

This study adopted the two-step method proposed by Anderson and Gerbing [122] for data analysis: confirmatory factor analysis (CFA) and structural equation modeling (SEM).

3.5.1. CFA

The AMOS 27.0 software was used to test composite reliability and convergent validity. To test discriminant validity, Fornell and Larcker’s [123] criterion was adopted, comparing the square root of each latent variable’s average variance extracted (AVE) with its correlation coefficients with other latent variables. The AMOS software was also employed to test the model fit on the collected data using the maximum likelihood method.

3.5.2. SEM Analysis

This study used AMOS 27.0 to test the proposed SEM to analyze the causal relationships among the latent variables. Hypotheses were examined based on standardized path coefficients and their significance levels. In addition, to further test the mediation effects embedded in the model and enhance the robustness of inference, a bootstrap resampling procedure with 5000 iterations was performed, and 95% bias-corrected confidence intervals were reported to determine the significance of the mediation effects.

4. Results and Analysis

4.1. Descriptive Statistics

The sample comprised 311 men (49.7%) and 307 women, at 50.3%. Most participants (60.2%) were in the 18–30 year age range. In terms of education, the highest number of participants (34.8%) had bachelor’s degrees. In terms of occupation, 39% were students. Participants included museum tourists of different ages, educational backgrounds, and occupational groups, indicating a representative and diverse sample.

Table 1. Descriptive statistics.

Variable	Category	Number	Percentage
Gender	Female	307	49.7
	Male	311	50.3
Education Level	Junior high school and below	65	10.5
	High school (including technical secondary school)	80	12.9
	Junior college	161	26.1
	Bachelor’s degree	215	34.8
	Master’s degree and above	97	15.7
Age	Under 18 years old	1	0.2
	18–30 years old	372	60.2
	31–44 years old	192	31.1
	45–60 years old	37	6
	60 years old and above	16	2.6
Occupation	Government and public institution staff	94	15.2
	Enterprise staff	211	34.1
	Industrial and agricultural workers	37	6
	Self-employed	18	2.9
	Retirees	17	2.8
	Students	241	39
Monthly Income Level	Below 3000 yuan	41	6.6
	3000–5000 yuan	64	10.4
	5001–7000 yuan	317	51.3
	7001–10,000 yuan	113	18.3
	Above 10,000 yuan	83	13.4
Daily Internet Time	Less than 3 h	81	13.1
	3–5 h	256	41.4
	5–7 h	137	22.2
	7–9 h	38	6.1
	More than 9 h	106	17.2

presents detailed descriptive statistics of the sample.

4.2. Reliability and Validity Analysis

First, the α coefficients of the seven latent variables in the model were 0.831, 0.83, 0.845, 0.866, 0.976, 0.947, and 0.931, respectively, exceeding the 0.70 standard [124]. Thus, the scale’s measurement items scale were reliable.

Table 2. Questionnaire variable description and statistics.

Variable	Item	Item Description	Factor Loading
Immersive Experience (IE, α = 0.831)	IE1	I feel like I have entered a whole new world	0.816
	IE2	I feel as if I have traveled through time and space, living in another era or place	0.753
	IE3	I can immerse myself in the historical context and imagine myself becoming another person	0.773
	IE4	I temporarily escape from the real world	0.800
Interactive Experience (IX, α = 0.830)	IX1	I can freely choose the content I want to see	0.766
	IX2	Each of my operations receives a good response	0.765
	IX3	I can interact in real-time and get timely feedback	0.790
	IX4	I can feel a connection with people and do not feel lonely	0.791
Perceived Ease of Use (PEOU, α = 0.845)	PEOU1	Learning how to use these digital technologies is easy	0.811
	PEOU2	The operation instructions are clear and easy to understand	0.803
	PEOU3	I can quickly master the use of these digital technologies	0.811
	PEOU4	These digital technologies are easy to use	0.805
Hedonic Experience (HE, α = 0.866)	HE1	The digital technology experience is exciting	0.793
	HE2	The digital technology experience is pleasant	0.800
	HE3	The digital technology experience is full of fun	0.800
	HE4	The digital technology experience is satisfying	0.780
Perceived Value (PV, α = 0.976)	PV1	The visiting experience is vivid and interesting	0.876
	PV2	The visiting process is easy and convenient	0.882
	PV3	The museum deeply explores the value of collections in history, art, and technology	0.878
	PV4	Through digital technology, I can more easily acquire knowledge and broaden my horizons	0.870
	PV5	My mood is relaxed and pleasant during the visit	0.887
	PV6	This experience touched my inner emotions	0.891
	PV7	I can immerse myself in the atmosphere and resonate with the exhibition content	0.895
	PV8	I am willing to visit again	0.870
	PV9	I can’t wait to share this visiting experience with family and friends	0.891
	PV10	My cultural appreciation ability has been enhanced	0.865
	PV11	My influence on relatives and friends in terms of ideology and values has improved	0.884
Place Attachment (PA, α = 0.947)	PA1	This museum is a very special place to me	0.638
	PA2	This museum has great significance for me	0.619
	PA3	I fully recognize the cultural and historical value conveyed by this museum	0.696
	PA4	The heritage presented makes me feel proud	0.664
	PA5	I feel a strong emotional attachment to this museum	0.660
	PA6	I felt a strong sense of belonging to this museum	0.651
Sustained Behavioral Intentions (SBI, α = 0.931)	SBI1	I will recommend others to visit this museum	0.542
	SBI2	I will visit this museum again in the future	0.568
	SBI3	I will share my experience at this museum with others	0.555

Note: All items were measured on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). All items refer to digital technology experiences at cultural heritage museums. Scale sources: Immersive Experience and Perceived Ease of Use adapted from Cheng et al. [23]; Interactive Experience adapted from Deng et al. [110], Jin et al. [111], and Shipps and Phillips [112]; Hedonic Experience adapted from Yersüren and Özel [113] and Kim and Hall [114]; Perceived Value adapted from Xie [115]; Place Attachment adapted from Hoang et al. [116], Luo and Xia [117], and Yuksel et al. [118]; Sustained Behavioral Intentions adapted from Fan et al. [119] and Lin and Kuo [120].

presents the outcomes of the specific analyses. Second, the KMO value was 0.951, and Bartlett’s test of sphericity was significant at p < 0.001, indicating that Bartlett’s test of sphericity results were significant; therefore, further factor analysis could be conducted. Finally, principal component analysis was used to conduct exploratory factor analysis of the data. Following Hair et al.’s [125] recommendation, items with factor loading coefficients below 0.50 were examined for potential removal. All 36 items demonstrated factor loadings above the 0.50 threshold (ranging from 0.542 to 0.895), and therefore, seven factors were retained, cumulatively explaining 73.6% of the total variance. Detailed analytical results are presented in Table 2.

Multicollinearity and Common Method Bias Assessment

To address potential multicollinearity concerns, variance inflation factor (VIF) values were calculated. For the regression of digital experience dimensions on perceived value, the VIF values were 1.017 (IE), 1.021 (IX), 1.016 (PEOU), and 1.010 (HE), all substantially below the threshold of 5 recommended by Hair et al. [125]. Similarly, for the regression of perceived value and place attachment on sustained behavioral intentions, the VIF values were 1.185 for both predictors. These results indicate that multicollinearity does not pose a concern in the current study.

To examine common method bias, Harman’s single-factor test was conducted by loading all 36 measurement items into an exploratory factor analysis with the number of factors constrained to one. The results revealed that the single factor explained only 35.84% of the total variance, which is below the 50% threshold [126]. This suggests that common method bias is not a significant concern in this study.

4.3. CFA

4.3.1. Composite Reliability and Convergent Validity Analysis

The analysis results showed that the factor loading coefficients ranged from 0.705–0.917, all greater than 0.5, meeting the discrimination criteria recommended by Hair et al. [125] and satisfying the requirements for convergent validity. The AVE values of each latent variable ranged from 0.555 to 0.819, all greater than 0.5, meeting the discrimination criteria recommended by Fornell and Larcker [123]; the scale had good convergent validity. The composite reliability values ranged from 0.833 to 0.976, all greater than 0.7, meeting the discrimination criteria recommended by Fornell and Larcker [123]—the scale had good internal consistency. Therefore, the scale had good reliability and convergent validity for each dimension. The results of the specific analyses are presented in

Table 3. Composite reliability and convergent validity analysis.

Variable	Measurement Item	Factor Loading	Average Variance Extracted (AVE)	Composite Reliability
Immersive Experience (IE)	IE1	0.779	0.555	0.833
	IE2	0.705
	IE3	0.724
	IE4	0.768
Interactive Experience (IX)	IX1	0.715	0.551	0.831
	IX2	0.732
	IX3	0.758
	IX4	0.764
Perceived Ease of Use (PEOU)	PEOU1	0.726	0.582	0.847
	PEOU2	0.787
	PEOU3	0.754
	PEOU4	0.782
Hedonic Experience (HE)	HE1	0.783	0.619	0.867
	HE2	0.810
	HE3	0.793
	HE4	0.761
Perceived Value (PV)	PV1	0.893	0.788	0.976
	PV2	0.895
	PV3	0.885
	PV4	0.871
	PV5	0.891
	PV6	0.892
	PV7	0.897
	PV8	0.871
	PV9	0.898
	PV10	0.875
	PV11	0.894
Place Attachment (PA)	PA1	0.874	0.748	0.947
	PA2	0.874
	PA3	0.892
	PA4	0.847
	PA5	0.858
	PA6	0.843
Sustained Behavioral Intentions (SBI)	SBI1	0.907	0.819	0.931
	SBI2	0.890
	SBI3	0.917

.

4.3.2. Discriminant Validity Analysis

The results showed that each latent construct’s AVE square root value exceeded its corresponding inter-construct correlation estimates, as presented in

Table 4. Correlation analysis and AVE square root values.

	AVE	IE	IX	PEOU	HE	PV	PA	SBI
IE	0.555	0.745
IX	0.551	0.107	0.742
PEOU	0.582	0.101	0.118	0.763
HE	0.619	0.078	0.091	0.043	0.787
PV	0.788	0.133	0.327	0.334	0.101	0.888
PA	0.748	0.422	0.476	0.159	0.606	0.409	0.865
SBI	0.819	0.386	0.397	0.293	0.247	0.694	0.586	0.905

Note: Inter-construct correlation coefficients are presented diagonally. IE: immersive experience, IX: interactive experience, PEOU: perceived ease of use, HE: hedonic experience, PV: perceived value, PA: place attachment, SBI: sustained behavioral intention.

, meeting the discrimination criterion proposed by Fornell and Larcker [123] and indicating good discrimination among the latent variables and satisfactory discriminant validity.

4.3.3. Model Fit Analysis

The fit test results were as follows: χ²/df = 2.770, RMSEA = 0.054, CFI = 0.947, GFI = 0.841, TLI = 0.942, IFI = 0.947, NFI = 0.920. The indicators reached the judgment standards recommended by Hair et al. [125] and Kline [127], indicating that the model fit the sample data relatively well and that the overall explanatory power of the model was generally high.

4.4. SEM Testing and Analysis

4.4.1. SEM Fit Analysis

The SEM fit results were as follows: χ²/df = 3.5660, RMSEA = 0.054, CFI = 0.922, GFI = 0.822, TLI = 0.915, IFI = 0.922, and NFI = 0.895. These fit indicators met the judgment standards recommended by Hooper et al. [128] and Marsh and Hocevar [129].

4.4.2. Path Analysis

Path coefficients derived from SEM signify the interrelationships and influencing potency among constructs under investigation. Standardized coefficient estimates are documented in

Table 5. Path analysis.

Hypothesis	Path and Hypothesis	Standardized Path Coefficient	Standard Error	Composite Reliability	p
H1	IE ⟶ PV	0.077	0.052	1.862	0.063
H2	IX ⟶ PV	0.285	0.052	6.632	***
H3	PEOU ⟶ PV	0.292	0.050	6.894	***
H4	HE ⟶ PV	0.063	0.053	1.558	0.119
H5	PV ⟶ PA	0.414	0.037	10.351	***
H6	PV ⟶ SBI	0.547	0.034	15.779	***
H7	PA ⟶ SBI	0.362	0.035	10.821	***

Note: *** p < 0.001; IE = immersive experience; IX = interactive experience; PEOU = perceived ease of use; HE = hedonic experience; PV = perceived value; PA = place attachment; SBI = sustained behavioral intentions.

. H1 was not supported (β = 0.077, p > 0.05); the positive impact of immersive experience on perceived value was not significant. H2 (interactive experience significantly and positively influences perceived value) was supported (β = 0.285, p < 0.001). H3 (PEOU significantly and positively influences perceived value) was supported (β = 0.292, p < 0.001). H4 was not supported (β = 0.063, p > 0.05); the direct effect of hedonic experience on perceived value was not significant. H5 (perceived value significantly positively influences place attachment) was supported (β = 0.414, p < 0.001). H6 was supported (perceived value significantly positively influences sustained behavioral intentions) (β = 0.547, p < 0.001). H7 (place attachment significantly positively influences sustained behavioral intentions) was supported (β = 0.362, p < 0.001).

In summary, the results verified the explanatory power of the “experience–perceived value–place attachment–sustained behavioral intentions” action chain, with VAM as the core for users’ sustained behavioral intentions in digital museums, and they further indicated significant positive relationships between digital museum users’ sustained behavioral intentions and their perceived value and place attachment.

Notably, the nonsignificant direct effects of immersive experience (H1) and hedonic experience (H4) on perceived value suggest that in cultural heritage museum contexts, sensory-oriented experience dimensions may not directly translate into value perception. This pattern indicates that functional dimensions (interactivity and ease of use) play a more critical role than sensory dimensions in shaping tourists’ value assessments within this specific context.

4.5. Mediation Effects Testing (H8)

By default, we report a 95% bias-corrected and accelerated confidence interval. As shown in

Table 6. Results of mediation analyses with multiple independent variables.

Paths	β [95% CI]
Total effects (c)
IE ⟶ SBI	0.22 *** [0.12, 0.33]
IX ⟶ SBI	0.39 *** [0.27, 0.51]
HE ⟶ SBI	0.18 ** [0.18, 0.45]
PEOU ⟶ SBI	0.15 ** [0.15, 0.45]
Mediation effects
IE ⟶ PV ⟶ PA ⟶ SBI	0.16 *** [0.06, 0.64]
IX ⟶ PV ⟶ PA ⟶ SBI	0.12 * [0.01, 0.76]
HE ⟶ PV ⟶ PA ⟶ SBI	0.60 [−0.29, 0.80]
PEOU ⟶ PV ⟶ PA ⟶ SBI	0.10 [−0.06, 0.064]

Note: The fast-and-robust bootstrap (=5000); * < 0.05, ** < 0.01, *** < 0.001.

, the indirect effect of IE on the SBI relationship is significant (β = 0.16, p < 0.001; 95% CI [0.06, 0.64]). In addition, the indirect effect of IX on the SBI relationship is positive and significant (β = 0.12, p < 0.05; 95% CI [0.01, 0.76]). Overall, the hypotheses were partially supported. The significant serial mediation effects for immersive and interactive experience pathways indicate that these experience dimensions can influence sustained behavioral intentions through the perceived value–place attachment transmission mechanism. Conversely, the nonsignificant mediation effects for hedonic experience and PEOU pathways suggest that not all experience dimensions contribute equally to the value attachment–behavior chain, highlighting the differentiated roles of various experience dimensions in this model.

As shown in Table 6, H8 was partially supported. The sequential mediation effects through perceived value and place attachment were significant for immersive experience (β = 0.16, p < 0.001; 95% CI [0.06, 0.64]) and interactive experience (β = 0.12, p < 0.05; 95% CI [0.01, 0.76]) but not significant for hedonic experience (β = 0.06, 95% CI [−0.29, 0.80]) and PEOU (β = 0.10, 95% CI [−0.06, 0.64]). These results indicate that the sequential mediation mechanism operates selectively across different experience dimensions.

To provide a clearer summary of the mediation hypothesis verification,

Table 7. Summary of sequential mediation hypothesis (H8) verification results.

Mediation Path	β	95% CI	Result
IE ⟶ PV ⟶ PA ⟶ SBI	0.16 ***	[0.06, 0.64]	Supported
IX ⟶ PV ⟶ PA ⟶ SBI	0.12 *	[0.01, 0.76]	Supported
HE ⟶ PV ⟶ PA ⟶ SBI	0.60	[−0.29, 0.80]	Not supported
PEOU ⟶ PV ⟶ PA ⟶ SBI	0.10	[−0.06, 0.64]	Not supported

Note: Bootstrap samples = 5000; * p < 0.05, *** p < 0.001. H8 was partially supported: sequential mediation effects were significant for immersive and interactive experience pathways.

presents the results for each pathway. As shown in Table 7, the sequential mediation hypothesis (H8) was partially supported, with two of the four pathways demonstrating significant indirect effects.

5. Discussion

This study explored the influence mechanism of digital technology experience on tourists’ sustained behavioral intentions at cultural heritage tourism destinations. Through a questionnaire survey of tourists at Shandong Museum and SEM analysis, this study yields empirical substantiation regarding understanding mechanisms wherein digital experience technology at cultural heritage destinations affects tourists’ sustained behavioral intentions.

The results revealed a significant positive impact of interactive experience and PEOU on tourists’ perceived value (H2 and H3 received strong support), which is highly consistent with the viewpoints in the existing literature. By endowing tourists with the ability to actively explore, personalize customization, and receive real-time feedback, interactive experience enables them to participate more deeply in the narrative and interpretation of cultural heritage [14,77]. This high degree of participation and sense of control significantly enhances tourists’ value perceptions in terms of knowledge acquisition, cultural understanding, and entertainment. Similarly, the importance of the ease-of-use experience has been verified, which aligns with De Paolis et al.’s [76] and Cheng et al.’s [23] findings. These findings collectively emphasize that, in cultural heritage digital experience design, user-centered interactivity and ease of use are key to enhancing tourists’ perceived value. The primacy of interactive experience and PEOU as core drivers can be explained through complementary theoretical lenses. From cognitive load theory [130], ease of use reduces extraneous cognitive load, enabling visitors to focus on cultural content rather than technology operation. From self-determination theory [131], interactive experience satisfies visitors’ needs for autonomy and competence through content choice, exploration control, and responsive feedback. Furthermore, in cultural heritage contexts where knowledge acquisition is a primary motivation [132], functional dimensions directly support this epistemic goal, whereas sensory dimensions serve peripheral roles—explaining why interactivity and ease of use demonstrate stronger value-driving effects than immersion and hedonism.

However, this study found that the direct positive impact of immersive and hedonic experiences on perceived value did not reach statistical significance (H1 and H4 were not supported). This finding diverges from conclusions articulated by Ma et al. [133], who emphasized immersion, and Chen [134] regarding hedonism enhancing perceived value; however, it is consistent with the latest evidence from museum digital scenarios. First, Li and Lv [77] point out that immersive experience in online VR exhibitions does not necessarily translate into enhanced evaluative cognition of value. Second, museum AR research shows that value-related evaluations more often exert effects through indirect pathways from ease-of-use experience to attitudes, with the direct effect of hedonic experience being unstable [23]. This nonsignificance may stem from the complex interweaving of multiple factors. First, it is rooted in the fundamental attributes of cultural heritage museum experiences, in which tourists pay more attention to content depth, historical and cultural learning, and knowledge acquisition rather than to pure sensory stimulation or superficial entertainment [132]. If digital experiences fail to convey and transmit these deep values effectively, the direct contributions of immersive and hedonic experiences to perceived value may be diluted. Second, current technological limitations may hinder tourists from obtaining high-quality immersion; once experience continuity is compromised, it becomes difficult to effectively transform it into an overall value perception. Additionally, if immersive content only remains at the visual impact level and lacks engaging narratives and deep cultural interpretation, it is difficult to form significant perceived value. When immersive and hedonic experiences fail to organically integrate with educational and cultural aspects and remain superficial, their direct driving effect on perceived value is not obvious. This reminds us that in cultural heritage digital experience design, we must deeply integrate tourist experiences with educational and cultural aspects to achieve more effective value transformation. Several alternative mechanisms warrant consideration. First, immersion and hedonism may influence perceived value through indirect pathways—flow experience [62] may mediate the immersion–value relationship, requiring immersion to first trigger absorptive states before translating into value assessments. Second, moderating effects likely exist: digital literacy may strengthen or weaken how ease of use influences value perception, while prior museum experience may moderate how experience dimensions translate into value judgments. Third, nonlinear relationships deserve attention—immersion may exhibit threshold effects whereby only experiences exceeding certain intensity levels significantly impact value perception. Finally, these patterns may reflect distinctive characteristics of on-site digital experiences, where physical presence and authentic artifacts remain central, potentially diminishing the relative importance of digital sensory stimulation compared with that of purely virtual contexts.

The results strongly support the significant positive impact of perceived value on place attachment (H5) and sustained behavioral intentions (H6). The conclusion of H5 is consistent with Fu and Dong’s [90] finding that higher perceived value strengthens tourists’ emotional connections and identification with heritage sites, enhancing place attachment. Meanwhile, the conclusion of H6 aligns with Valverde-Roda et al.’s [67] finding that perceived value significantly and positively predicts tourists’ revisit and recommendation intentions and other behavioral intentions. In other words, when tourists obtain high degrees of knowledge and cultural and emotional satisfaction from digital experiences, this positive value assessment encourages them to establish deeper connections with cultural heritage sites, forming a place identity and a sense of belonging. Therefore, enhancing tourists’ perceived value is an effective way to cultivate place attachment. This demonstration emphasizes perceived value as an important antecedent of tourists’ behavioral intentions. The stronger the tourists’ value perception of experiences is, the stronger are their intentions to revisit, recommend, or continuously participate in cultural heritage activities. This further validates the effectiveness of VAM in explaining tourists’ sustained behavioral intentions, emphasizing the importance of driving tourists’ long-term participation and support by enhancing perceived value.

Moreover, the results indicate that place attachment significantly enhances tourists’ sustained behavioral intentions (H7 supported). This is consistent with Li et al.’s [87] and Zhou et al.’s [135] finding that place attachment is a key driving factor of sustained behavioral intentions. Tourists who form deep emotional connections and identify with cultural heritage sites are more inclined to take positive actions to maintain and support those sites, including the intention to revisit, recommend, and participate in conservation activities. This indicates that place attachment, as an important psychological mediating mechanism, effectively transforms tourists’ internal emotions into external behaviors, supporting the sustainable development of cultural heritage (Fu & Dong [90]; Zhou et al. [135]). Therefore, in cultural heritage site management and digital experience design, attention should be paid to cultivating tourists’ place attachment to promote the formation of long-term sustained behavioral intentions.

Regarding the sequential mediation effects (H8 partially supported), the results reveal differentiated patterns across experience dimensions. Notably, despite the nonsignificant direct effect of immersive experience on perceived value (H1), the indirect pathway IE⟶PV⟶PA⟶SBI was significant. This suggests that immersion may influence sustained behavioral intentions primarily through the value attachment chain rather than through direct value enhancement. Conversely, although PEOU demonstrated a significant direct effect on perceived value (H3), its sequential mediation pathway was not significant, indicating that ease of use primarily operates through direct value perception rather than through place attachment. These differentiated patterns suggest that different experience dimensions may operate through distinct psychological mechanisms in cultural heritage contexts. Regarding the effect sizes, it is noteworthy that while both indirect pathways were significant, the interactive experience pathway (β = 0.12, p < 0.05) demonstrated a smaller effect size and lower significance level compared with the immersive experience pathway (β = 0.16, p < 0.001). This difference may be attributed to the substantial direct effect of interactive experience on perceived value (β = 0.285, p < 0.001), suggesting that interactivity primarily influences behavioral intentions through direct value enhancement rather than the sequential mediation route.

In summary, the present work reveals a fundamental driving effect of interactivity plus ease of use upon perceived value of cultural heritage digital experiences, while it deeply analyses the underlying reasons for the nonsignificance of immersion and hedonic experiences. This inquiry further substantiates the promotive effect of perceived value with respect to place attachment and sustained behavioral intentions and emphasizes the core mediating role of place attachment in transforming tourists’ emotional connections into long-term supportive behaviors.

6. Conclusions and Contributions

6.1. Conclusions

This study was based on VAM as the theoretical hub, focusing on the “digital technology experience–perceived value–place attachment–sustained behavioral intentions” action chain, exploring how digital technology experiences at cultural heritage tourism destinations influence tourists’ sustained behavioral intentions through a series of psychological mediations. We constructed a chain mediation model containing four types of experience dimensions and conducted empirical testing based on tourist samples from Shandong Museum. In the context of the digital era, this study offers a new explanatory lens to comprehend interaction mechanisms linking tourists with cultural heritage while revealing the complex psychological path from technology experience to behavioral intention transformation of “value assessment–emotional belonging.”

This study draws the following conclusions. First, perceived value plays a crucial role in the influence mechanism constructed in this study. The study confirms that interactive and ease-of-use experiences are effective ways to enhance tourists’ perceived value, whereas perceived value can significantly promote the formation of place attachment and the generation of sustained behavioral intentions. This indicates that in the digital transformation of cultural heritage, technology applications should pursue sensory stimulation and pay attention to whether they can bring practical convenience and interaction to tourists, creating recognized value. Second, the findings that direct impacts of immersive and hedonic experiences on perceived value are not significant challenge the common perception that “the more dazzling the technology, the better the effect.” In heritage tourism, tourists may value knowledge acquisition and meaningful interaction more than pure sensory immersion or entertainment. Finally, this study successfully validates the transmission path of “perceived value–place attachment–sustained behavioral intentions,” emphasizing that cultivating tourists’ emotional connections with cultural heritage sites in digital experiences is key to driving their long-term supportive behaviors.

In summary, this study argues that development of digital technologies within heritage destinations should be a systematic project with value co-creation as the core and emotional connection as the orientation. Technology integration should not be the goal but rather a means to achieve deep integration of cultural inheritance and tourist participation (Mazzanti et al. [136]). Subsequent studies may further examine perceptual differences among different tourist groups in digital experiences or test the universality of this study’s model across broader cultural heritage types, deepening our understanding of the dynamic relationships among people, technology, and cultural heritage. The results from this study also offer guidance on how cultural heritage sites might balance technology and cultural authenticity, emphasizing that digital transformation should always be oriented toward the core values of cultural heritage, avoiding over-commercialization and entertainment. This viewpoint aligns with the latest research trends, namely that while utilizing digital technology to enhance tourist experiences, cultural heritage sites must avoid the erosion of cultural heritage authenticity that technology may cause (Jones et al. [137]) and actively explore innovative paths for protecting it.

6.2. Theoretical Contributions

This study advances current conceptual foundations through several contributions.

First, it overcomes the contextual limitations of existing research and deepens our understanding of digital interaction mechanisms in offline experiences. This study successfully extended VAM to the complex context of tourists’ digital interactive experiences in offline cultural heritage sites using multidimensional digital experiences as antecedent variables of VAM. This validates the effectiveness of VAM in explaining cultural heritage tourist behavioral intentions and contextualizes and enriches it. This study offers a new empirical framework for applying VAM in contextualization and humanistic depth embedding, effectively responding to academia’s call to explore the long-term mechanisms of offline digital experiences.

Second, this inquiry refines theoretical appreciation for compositional architecture underlying multiple experience dimensions, revealing their differentiated mechanisms of action on perceived value. By testing the differentiated effects of four experience dimensions (immersion, interaction, ease of use, and hedonism), the study reveals that not all experience dimensions could be directly transformed into perceived value. Specifically, functionally oriented interactive and ease-of-use experiences were core factors driving value perception, whereas the direct impacts of sensorially oriented immersive and hedonic experiences were not significant. This finding diverges markedly from previous research emphasizing the significant positive impact of hedonism and immersion on value creation, highlighting the importance of technological functional value in the cognitively oriented contexts of cultural heritage. This conclusion aligns with some of the latest research trends, namely that in specific consumption contexts, instrumental value has a more critical influence on consumer behavioral intentions than hedonic value (Maulina et al. [138]), deepening our understanding of the complexity of cultural heritage consumption behavior within contemporary digital environments.

Finally, regarding the contribution of place attachment, this study validates the complete chain-mediation effect of perceived value–place attachment–sustained behavioral intentions through empirical data. This confirms the direct driving influence from perceived value over behavioral intentions whilst revealing the key mechanism that destination bonding plays. The findings suggest that tourists’ value perceptions need to be internalized into emotional identification and cultural cognition of cultural heritage sites to be more effectively transformed into long-term and sustainable supportive behaviors. This finding provides a clear theoretical framework for understanding tourists’ complete psychological transformation process from value perception to cognitive and emotional connection and then to sustained behavioral intentions, effectively filling the gap in the scarce evidence regarding this sequential mechanism in the context of heritage tourism digital technology experiences and significantly enhancing our explanatory power for tourists’ long-term behavioral intentions.

6.3. Practical Contributions

This research offers several actionable recommendations to cultural heritage professionals and tourism industry stakeholders by explicitly linking management implications to empirical findings.

First, in digital project investment and design, priority should be given to enhancing tourist interactivity and PEOU, as these dimensions demonstrate the strongest and most direct effects on perceived value. The empirical evidence clearly substantiates that among all four experience dimensions examined, PEOU (β = 0.292, p < 0.001) and interactive experience (β = 0.285, p < 0.001) exert the most significant positive effects on perceived value. This indicates that optimizing system usability and interaction design yields higher value returns compared to other experience attributes. Therefore, when developing digital products such as AR/VR tour-guide apps, virtual exhibition halls, and interactive installations, cultural heritage institutions should prioritize investment in optimizing user interfaces, simplifying operational processes, and designing interactive features that allow tourists to actively participate, explore, and co-create content. This result-oriented investment strategy coincides with Campos et al.’s [139] viewpoint that tourism development increasingly emphasizes participatory experiences and value co-creation. By focusing on these high-impact dimensions, museums can both meet tourists’ needs for personalized engagement and strengthen the transmission of cultural heritage value.

Second, immersive and hedonic experiences should be strategically integrated rather than serve as primary investment drivers. Although immersive (β = 0.077, p > 0.05) and hedonic (β = 0.063, p > 0.05) experiences did not demonstrate statistically significant direct effects on perceived value, this does not render them irrelevant. Rather, the findings suggest that pure sensory stimulation or entertainment-oriented design is insufficient to generate value perceptions in on-site cultural heritage contexts. Therefore, managers should avoid excessive investment in immersive or entertainment technologies that are disconnected from interpretive clarity and functional utility. Instead, immersive and hedonic elements should be deliberately embedded within cultural narratives and educational objectives, ensuring that entertainment serves the purposes of heritage interpretation and learning [58]. This approach avoids fleeting novelty effects while enhancing the substantive meaning of digital experiences.

Third, given its critical role in translating value perceptions into sustained behavioral intentions, cultivating tourists’ place attachment should be regarded as a strategic long-term goal of digital heritage management. Our findings demonstrate that perceived value strongly predicts place attachment (β = 0.414, p < 0.001), which in turn significantly influences sustained behavioral intentions (β = 0.362, p < 0.001); this sequential pattern indicates that investments aimed at strengthening place attachment yield indirect but enduring behavioral effects. Place attachment in this study encompasses two interrelated dimensions: the cognitive dimension involving tourists’ understanding of and identification with the cultural heritage site’s historical and cultural symbolism, and the affective dimension involving emotional connections, feelings of belonging, and attachment. Accordingly, cultural heritage institutions should utilize digital technologies not only to deliver information but also to systematically cultivate identity recognition and emotional resonance. By integrating humanistic stories, local spirit, and cultural connotations into interactive and immersive digital content, museums can simultaneously enhance tourists’ cognitive understanding and emotional connections. This cognition–emotion-oriented attachment cultivation strategy can transform one-time visitors into long-term supporters with strong cultural identification, thereby promoting the sustainable development and social influence of cultural heritage destinations.

7. Limitations and Recommendations for Future Research

Although the current work possesses theoretical and practical significance, it has some limitations that also offer valuable avenues for subsequent investigation. First, the current investigation focused on tourists visiting Shandong Museum, potentially constraining the applicability of results across other cultural heritage sites. Different types of cultural heritage tourism destinations, such as natural heritage sites, historical districts, and intangible cultural heritage sites, have unique attributes, and tourists’ experience perceptions and sustained behavioral intentions may differ. Second, the sample characteristics may constrain the generalizability of the findings. The sample predominantly comprised young adults aged 18 years–30 years (60.2%) and students (39%). While this demographic distribution may partially reflect the actual visitor profile of museums engaging with digital technologies—as younger, digitally native visitors tend to be more inclined to interact with digital installations—it nonetheless limits the applicability of findings to older age groups and non-student populations. Younger visitors may possess greater digital literacy and different expectations regarding digital experiences compared to older visitors, potentially influencing their perceived value assessments and behavioral intentions differently. Future research should employ stratified sampling methods to ensure more balanced representation across age groups and occupational categories, enabling examination of potential moderating effects of demographic characteristics on the relationships identified in this study. Third, although this study explored functional elements (immersion, interaction, ease of use, and hedonism), the diversity of digital technology types and content was not fully explored. For example, different forms of content may have different impacts on tourist experiences and behaviors. Subsequent investigations could examine specific impacts from particular digital content types or themes on immersion, perceived value, and sustained behavioral intentions to obtain more refined management insights. Fourth, although discriminant validity was established statistically, some measurement items exhibited surface-level semantic similarities (e.g., sharing-related items across perceived value and behavioral intention constructs). Future research could further refine item wording to enhance conceptual distinctiveness while preserving theoretical coverage. Finally, although this work developed a conceptual framework regarding how functional elements within digital experiences influence perceived value, place attachment, and sustained behavioral intentions, the existing model may not fully capture the complex mechanisms in cultural heritage contexts. Subsequent scholarly work could contemplate introducing enriched mediating or buffering variables, exemplified through heritage responsibility, flow experience, and digital literacy, to understand tourists’ behavioral decision-making processes in cultural heritage digital experiences from a broader perspective. In summary, the factors in how digital technology experiences at cultural heritage destinations form tourists’ sustained behavioral intentions are a relatively new research topic that can be explored further using multidisciplinary and multi-perspective approaches.