Enhancing Health Tourism Through Gamified Experiences: A Structural Equation Model of Flow, Value, and Behavioral Intentions

Abstract

As health and well-being become central concerns in the post-pandemic tourism landscape, health tourism is evolving to prioritize not only physical recovery but also psychological engagement and emotional value. This study explores how gamified design can enhance tourist participation and experience quality within health-related tourism contexts. By integrating theories from tourism psychology and game-based experience design, a structural equation model is proposed to examine the relationships among memorable tourism experiences, tourist motivation, game design elements, flow experience, and perceived value, and their joint influence on behavioral intention. Data collected from tourists who engaged in gamified experiences were analyzed using structural equation modeling (SEM) techniques. The results identify a dynamic “participation–immersion–value” mechanism, in which gameful design fosters flow and perceived value, thereby mediating gamification’s impact on behavioral intention. These findings offer valuable insights for health tourism developers and experience designers seeking to create emotionally engaging, motivating, and sustainable visitor experiences in the context of health and well-being.

1. Introduction

The COVID-19 pandemic severely disrupted the global economy, with tourism among the most affected sectors. In 2020, international tourist arrivals dropped by 74%, leading to the loss of up to USD 1.3 trillion in export revenue and endangering over 100 million jobs (UNWTO, 2021). Leisure complexes and tourist attractions suffered in particular, due to their dependence on physical interaction and spatial immersion (Hu et al., 2024). Although the outbreak of COVID-19 and the ensuing pandemic in 2020 brought the tourism sector to a near standstill, recovery is now well under way. The year 2024 represents a turning point, marking the consolidation of international tourism’s recovery from its most severe crisis in history, four years after the onset of the COVID-19 pandemic (UNWTO, 2024). As recovery unfolds, tourism is gradually rebounding. However, tourists’ motivations and behaviors have shifted—traditional sightseeing is giving way to immersive, interactive, and personalized experiences (Beck et al., 2019). In the post-pandemic era, the increased demand for digital and interactive experiences has made gamification a key strategy in tourism. Studies have shown that digital interactive applications have significantly increased tourist engagement and destination attachment, positioning them as vital tools for tourism recovery and innovation (Akhtar et al., 2021; Calza et al., 2022). Against this backdrop, the integration of culture and tourism is widely recognized as a pathway to sustainable development.

Digital games, known for their interactivity, narrative depth, and immersive potential, have emerged as effective tools for innovating cultural tourism experiences. Through systematic literature reviews, Pradhan et al. (2025), Pasca et al. (2021), and Xu et al. (2014) have mapped the current state and developmental trajectory of gamification in tourism and hospitality, identifying major research clusters and proposing future directions. Existing research in this field can be grouped into three interrelated thematic areas. The first concerns the underlying motivational mechanisms that drive tourist engagement with gamified experiences. Studies have shown that participation is influenced by a combination of intrinsic motivations, such as enjoyment and challenge, and extrinsic motivations, including rewards and social interaction (Xu et al., 2017, 2021). A second area of research investigates how specific game design elements—such as interactivity, feedback systems, and narrative structures—contribute to enhancing tourists’ flow experience and perceived value, fostering both emotional immersion and cognitive appraisal (Swacha, 2019; Deterding et al., 2011). Building upon these psychological foundations, a growing body of literature further explores the behavioral outcomes of gamified tourism. These studies suggest that, by enriching memorable tourism experiences and promoting sustainable engagement, gamification can positively influence key behavioral intentions, including revisit intention, word-of-mouth recommendation, and willingness to pay a premium (Negruşa et al., 2015; Souza & Marques, 2022; Skinner et al., 2018).

Despite the growing scholarly interest in tourism gamification, significant research gaps remain. Prior studies tend to rely heavily on qualitative approaches and often lack empirical validation with large-scale data, resulting in an incomplete understanding of the psychological mechanisms at play—particularly the mediating roles of flow experience and perceived value. Furthermore, the existing literature presents fragmented insights into the pathways connecting game design elements, tourist motivation, and memorable tourism experiences (MTEs) to behavioral intentions, with few studies offering a comprehensive theoretical framework. Flow experience refers to a mental state in which an individual becomes deeply immersed in an activity, experiencing a sense of focus and enjoyment while losing awareness of time and surroundings (Csikszentmihalyi, 2000). Perceived value, on the other hand, represents the tourist’s overall evaluation of the experiential benefits received relative to the costs involved (Zeithaml, 1988). A more integrated understanding of these constructs is crucial for advancing gamification-based tourism research.

Addressing these gaps, this study proposes and empirically tests a structural equation model that centers on the multi-path mechanism of “game design elements—flow experience and perceived value—behavioral intentions.” By integrating core constructs such as motivation and MTEs, the study systematically reveals the psychological and behavioral mechanisms through which gamification shapes tourist behavior. Methodologically, it adopts an interdisciplinary perspective that bridges game design and tourism psychology, and innovatively employs structural equation modeling (SEM) to analyze the dynamics of gamified tourism. This approach deepens the explanatory power of the “participation–immersion–value” pathway, providing a robust theoretical foundation for tourism experience design in the context of the experience economy. The findings not only advance theoretical understanding of gamified tourism experiences but also offer practical implications for enhancing visitor engagement, fostering cultural interaction, and supporting the sustainable transformation of the tourism industry in the post-pandemic era.

2. Literature Review and Hypotheses Development

2.1. Literature Review

2.1.1. Gamification in Tourism

In recent years, with the deep integration of the gaming and tourism industries, gamified tourism has emerged as a vital strategy for enhancing destination attractiveness, user engagement, and brand equity (Hamari, 2017). Fundamentally, gamification is an interdisciplinary approach that incorporates game design elements—such as points, tasks, feedback, levels, and challenges—into non-game contexts to stimulate user motivation, behavior, and emotional involvement (Deterding et al., 2011; Chan et al., 2020). Within the tourism sector, gamification facilitates a shift from passive consumption to immersive and participatory experiences, while also promoting value co-creation between service providers and tourists (Huotari & Hamari, 2012; Majuri et al., 2018).

The application of gamification in tourism can be categorized into five major forms. First, technology-driven applications, such as virtual reality (VR) tours and augmented reality (AR) quests, enhance immersion and improve information delivery efficiency (Beck et al., 2019). Second, behavioral incentive mechanisms—including point systems, badges, and check-in challenges—are commonly embedded in tourism apps to increase user participation and social interaction. Third, narrative-driven designs, such as immersive storytelling or cultural treasure hunts, guide tourists in exploring destinations and understanding local culture (Swacha, 2019). Fourth, sustainability-oriented gamification integrates environmental awareness into tasks, such as waste-sorting challenges or low-carbon travel missions, encouraging pro-environmental behavior (Andersson et al., 2018). Finally, lifecycle-based engagement mechanisms span the entire tourist journey—from virtual planning before departure, to interactive missions during travel, and post-trip content sharing or reward redemption—creating a continuous and memorable experience (Corrêa & Kitano, 2015; Xu & Fox, 2014).

Collectively, these gamified practices reflect a broader shift in tourism from a service-oriented paradigm to one grounded in the experience economy and participatory engagement, thereby enhancing tourist immersion and memory while amplifying destination visibility and branding (Godovykh et al., 2022).

2.1.2. Flow Theory

Flow is a psychological state of deep engagement, commonly experienced in activities such as sports, gaming, and shopping (Moneta & Csikszentmihalyi, 1996). Flow theory integrates motivation, personality, and subjective experience, emphasizing that a balance between skill and challenge can trigger flow experiences (Csikszentmihalyi, 2000). Its nine key characteristics include a challenge–skill balance, a sense of control, immediate feedback, clear goals, concentration, a merging of action and awareness, a loss of self-consciousness, a distorted sense of time, and intrinsic enjoyment (Nakamura & Csikszentmihalyi, 2014). Flow can be categorized into three levels: engagement, deep concentration, and complete immersion (Brown & Cairns, 2004). The flow framework has been proposed as a tool to improve tourist experiences, highlighting the importance of studying flow specifically within tourism contexts (da Silva deMatos et al., 2021). Previous studies have widely applied flow theory in areas such as online shopping and human–computer interaction. Aguiar-Castillo et al. (2020) examined the use of gamified applications in education, while Y. N. Kim et al. (2021) found that reward mechanisms in maze parks enhanced tourist flow experiences. In addition, gamified tourism provides tourists with flow experiences by offering enjoyment, game design elements, and immersion (Xu et al., 2017).

2.1.3. Perceived Value

Perceived value is a well-established concept in marketing, frequently used to examine variables influencing future service use, purchasing decisions, and customer loyalty (Jamal & Sharifuddin, 2015). In tourism, it serves as a reliable predictor of tourist behavior and satisfaction, significantly impacting intentions such as revisit or loyalty (Eid & El-Gohary, 2015). Initially studied in the context of hotel services, the application of perceived value has since extended to vacation, nature-based, and cultural tourism (M. Kim & Thapa, 2018). Zeithaml (1988) defined perceived value as a consumer’s overall assessment of utility based on what is received versus what is given. Factors such as tourist experience, emotional response, price, and reputation have been shown to influence perceived value, with motivation and involvement also playing significant roles (Prebensen et al., 2013). As a mediating variable in models of tourist experience, perceived value has been proven effective (Cronin et al., 2000).

Recent studies highlight the growing influence of gamification in tourism, enhancing immersion, interactivity, and emotional resonance, all of which elevate perceived value (Corrêa & Kitano, 2015).

2.1.4. Behavioral Intention

Behavioral intention is crucial for customer retention and the sustainable development of tourism (Yun & Liu, 2023). Behavioral intention is a significant predictor of actual behavior, reflecting tourists’ future motivations and destination choices, such as revisit, recommendation, and willingness to pay a premium (Afshardoost & Eshaghi, 2020; Zhang et al., 2018). Revisit intention denotes the likelihood of returning, recommendation intention reflects the likelihood of recommending the destination, and willingness to pay a premium indicates readiness to spend more on tourism products and services (Pandža Bajs, 2015).

This study focuses on the integration of game design elements in tourism, exploring how immersive and interactive experiences enhance tourists’ behavioral intentions. Flow experience and perceived value are proposed as the core psychological dimensions that influence these intentions—flow representing emotional immersion and perceived value as a cognitive evaluation of the experience. As the “tourism + gaming” model expands, it increasingly serves as a tool for stimulating tourist interest, enhancing destination appeal, and strengthening cultural expression.

2.2. Development of Research Hypotheses

In marketing, the concept of tourist experience has evolved from a focus on satisfaction and service quality to an emphasis on extraordinary and memorable tourism experiences (Han & Lee, 2022). J. H. Kim (2018) identified key components of tourism experiences—such as involvement, hedonism, excitement, social interaction, and novelty—emphasizing that selectively recalled experiences, or memorable tourism experiences, influence future decisions. Positive memories enhance travel desire, while negative ones reduce behavioral intent by associating unfavorable emotions with the destination. Thus, MTEs are those that evoke strong, positive recollections and stand out among trip activities (Coelho & Gosling, 2018). Existing studies emphasize that MTEs positively contribute to the development of flow experiences by deepening emotional engagement. Cho et al. (2019) have demonstrated that nostalgic feelings promote immersive participation and lay the foundation for flow, while Wei et al. (2019) have highlighted that novelty, involvement, and social interaction enhance MTEs, which in turn foster the emotional immersion that is conducive to flow.

Recent studies suggest that MTEs play a key role in enhancing perceived value. Antón et al. (2019) showed that authenticity and cultural contrast significantly shape memorable gastronomy experiences, which serve as important precursors to value recognition. Zhang et al. (2018) and Y. F. Huang et al. (2019) found that memorable tourism experiences (MTEs) play a mediating role in the relationship between destination image and revisit intention, and significantly influence tourists’ perceived value, thereby reinforcing behavioral intentions in various tourism contexts. These findings provide empirical support for the positive influence of MTEs on flow experiences and perceived value. Taken together, these studies provide empirical evidence for the positive influence of MTEs on flow experience and perceived value. Therefore, we propose the following hypotheses:

H1. 

Memorable tourism experiences have a positive effect on flow experience.

H2. 

Memorable tourism experiences have a positive effect on perceived value.

Tourist motivation strongly affects travel behavior. It includes both intrinsic and extrinsic drivers, as well as push and pull factors (Crompton, 1979). Push factors are internal needs or desires. Pull factors relate to the appeal of external destinations. In leisure and entertainment settings, tourists are often drawn by a place’s attractiveness and functional value. Havitz and Dimanche (1999) have described involvement as a psychological state shaped by motivation, arousal, or interest. This state depends on both personal traits and situational factors. In the context of cultural tourism games, this relationship becomes more complex.

Tourist motivation plays a key role in shaping engagement and experience in cultural tourism (Goossens, 2000; Devesa et al., 2010). Flow experiences—marked by deep focus and enjoyment—are more likely when personal interests align with the activity’s challenge. Mannell and Iso-Ahola (1987) have argued that such psychological benefits stem from internal motivation. Boniface (2000) further found that the motivation of thrill-seeking tourists to pursue adventure and challenge significantly facilitates their experience of flow during these activities. These immersive states enhance satisfaction and emotional resonance, supporting the role of motivation in facilitating flow.

Motivation also influences perceived value. When tourists feel their motives are fulfilled, they tend to rate experiences more positively. S. Huang et al. (2015) found that motivation directly affects perceived value, which then drives word-of-mouth. Similarly, Prebensen et al. (2013) has shown that, in creative tourism, both motivation and perceived value impact decisions. These findings highlight motivation as a key factor in both flow and value creation. Based on this theoretical foundation, the following hypotheses are proposed:

H3. 

Tourist motivation has a positive effect on flow experience.

H4. 

Tourist motivation has a positive effect on perceived value.

Gamification, defined as the application of game design elements in non-game contexts, has emerged as a powerful tool for enhancing user engagement, emotional involvement, and behavioral outcomes (Xu et al., 2017). In service and experiential marketing, gamification is increasingly recognized for its persuasive potential and capacity to convert routine interactions into meaningful experiences (Zichermann & Linder, 2010). In cultural tourism, the integration of game elements—such as interactive NPCs, recreated game scenes, or site-specific levels—transforms traditional sightseeing into immersive, participatory experiences. These transformations are driven by motivational mechanisms like achievement, immersion, and creativity, which foster emotional resonance, active participation, and satisfaction (Eppmann et al., 2018). Similarly, in cultural tourism, the destination becomes part of a co-created service system where tourists engage with resources such as NPCs, prior experiences, and cultural narratives.

Through these dynamic interactions, tourists form unique emotional experiences, leading to the emergence of flow (Mullins & Sabherwal, 2020). Gamification also aids memory formation by engaging emotional and cognitive pathways, improving both working and episodic memory (Berger et al., 2018). By combining interactivity and challenging tasks, gamification strengthens tourists’ emotional connection with destinations, increasing brand affinity and perceived value. Similarly, Hsu and Chen (2018) have demonstrated that gamified elements enhance both hedonic and utilitarian value, leading to satisfaction and loyalty. Frijda (1993) and Gutierrez (2021) have confirmed the positive impact of gamification on flow, with the latter highlighting the perceived role of gamification in sustaining engagement in games. These findings emphasize the impact of gamification on psychological engagement and value perception. Accordingly, the following hypotheses are proposed:

H5. 

Game design elements have a positive effect on flow experience.

H6. 

Game design elements have a positive effect on perceived value.

In cultural tourism, flow experiences significantly enhance tourists’ satisfaction and enjoyment, often stimulating future behavioral intentions. Bai et al. (2024) have found that both flow and memorable tourism experiences positively influence behavioral intentions in the context of ancient town tourism. Similarly, M. J. Kim and Hall (2019) have demonstrated that flow experiences contribute to greater subjective well-being and impact behavioral intentions within travel and tourism marketing. Ghaderi et al. (2024) have also found that flow experience enhances tourists’ psychological satisfaction and experience quality. These studies highlight the importance of flow in shaping tourists’ future engagement with destinations.

Perceived value also plays a crucial role in driving revisit intentions in cultural tourism (Peng et al., 2023). Pandža Bajs (2015), using Dubrovnik as a case study, confirmed that perceived value positively affects both tourist satisfaction and future behavioral intentions, including revisits and word-of-mouth recommendations. In line with this, Marques et al. (2021) have shown that destination image components—especially affective and unique images—significantly influence satisfaction and post-visit behavioral intentions. Moreover, Cronin et al. (2000) have demonstrated that perceived value impacts behavioral intentions directly or indirectly through satisfaction.

Thus, the following hypotheses are proposed:

H7. 

Flow experience positively affects behavioral intention.

H8. 

Perceived value positively affects behavioral intention.

Thus, the conceptual model and proposed hypotheses are shown in Figure 1.

3. Research Method

3.1. Sampling Design and Data Collection

This study targeted individuals aged 18 and above who had recently participated in multiple cultural tourism experiences involving game-based elements. To identify and recruit participants with relevant gamification experience, we utilized online tourism forums, social media groups dedicated to cultural travel, and collaborated with travel agencies offering gamified cultural tours. Invitations containing a brief study introduction and questionnaire link were distributed through these channels, ensuring that respondents had direct experience with gamified tourism products.

Participants were instructed to complete the questionnaire based on their most recent interactions with cultural tourism games. The data collection period spanned from 30 July 2024, to 1 February 2025. To enhance the accuracy and reliability of responses, detailed explanations of each questionnaire item were provided prior to administration. Throughout the distribution process, efforts were made to achieve a demographically balanced sample in terms of age and educational background. A total of 420 questionnaires were disseminated, and, after excluding responses that were either incomplete or demonstrated patterns of non-differentiated answers, 399 valid responses were retained for analysis. Participants represented diverse nationalities, predominantly from China and South Korea, enhancing the generalizability of the findings. Regarding their gamified experiences, respondents reported interacting with various game-based elements embedded in cultural tourism, including mobile applications (65%), augmented reality (AR) features (25%), and location-based gamification tools (10%). This diversity in gamification types allowed for a comprehensive analysis of their effects on tourist behavior.

The demographic characteristics of the respondents are presented in

Table 1. Demographic profile (N = 399).

Demographic	Frequency	Percentage
Gender
Male	215	53.9
Female	184	46.1
Age (years)
21–30	142	35.6
31–40	154	38.6
>40	63	15.8
Education
High school or below	29	7.3
Bachelor’s degree	256	64.2
Master’s degree or above	114	28.5
Frequency of visiting scenic areas that include game design elements
1–2 times per year	73	18.3
3 or more times per year	326	81.7

. The gender composition was relatively balanced, with 53.9% male and 46.1% female participants. Most respondents fell within the 21–40 age bracket, with 35.6% aged 21–30 and 38.6% aged 31–40, indicating a predominance of young and middle-aged adults. Additionally, 10.0% were aged 16–20, and 15.8% were above 40. Regarding educational attainment, a substantial majority held at least a bachelor’s degree: 64.2% had a bachelor’s degree, 28.5% held a master’s degree or above, and only 7.3% had a high school diploma or less.

In terms of experience with gamified tourism attractions, 81.7% of respondents reported frequent engagement, while 18.3% visited such sites occasionally. This suggests a high level of interest in gamified tourism experiences, especially among the younger and more educated demographic. Overall, the respondent pool is well-aligned with the target market for cultural tourism with game design elements in China, supporting the validity of the subsequent analysis.

3.2. Measurement Development

To ensure alignment with the research objectives, this study refined and adopted measurement items from well-established literature. Given that the original scales were in English, a bilingual translation process was applied: the items were first translated into Chinese by a certified translator, and then a second translator conducted a back-translation to verify conceptual consistency. A pilot test was then conducted among 40 individuals with prior experience in cultural tourism games, both domestic and international. Feedback from this pre-survey was used to make appropriate adjustments to item wording and structure. Ultimately, 18 items across six key constructs were finalized, grounded in theoretical frameworks and adapted for the context of gamified tourism experiences.

In this study, the measurement scale for memorable tourism experience was adapted from J. H. Kim (2018), Cho et al. (2019), and related literature. Travel motivation was measured using items derived from M. Kim and Thapa (2018) and S. Huang et al. (2015), as well as other empirically validated studies. Game design elements were assessed based on the frameworks proposed by Frijda (1993), Gutierrez (2021), Chan et al. (2020), and Eppmann et al. (2018). Flow experience was measured using scales adapted from Bai et al. (2024), M. J. Kim and Hall (2019), and Kanagasapapathy (2017). Perceived value was evaluated using measurement items developed by Cronin et al. (2000) and Pandža Bajs (2015), and supported by subsequent empirical work. Behavioral intention was measured using scales from J. H. Kim (2018) and Marques et al. (2021), along with insights from additional relevant scholarship.

3.3. Data Analysis

This study employed structural equation modeling (SEM) as the primary analytical method, as it allows for the simultaneous evaluation of both the measurement model’s validity and the hypothesized structural relationships. All model estimations were conducted using AMOS 24.0. This study implemented a two-phase approach. In the first phase, latent construct assessment was conducted to verify indicator reliability and the distinctiveness of each dimension. Upon confirming acceptable measurement properties, the second phase involved analyzing the theoretical linkages among variables and evaluating the overall structural coherence of the model (McDonald & Ho, 2002). This approach is also supported by Jöreskog and Sörbom (1993), who emphasized that structural path analysis should only proceed after ensuring sufficient model fit in the measurement stage.

4. Analysis Results

4.1. Measurement Model

4.1.1. Reliability Analysis

Before testing the study’s hypotheses, a reliability analysis was conducted to assess the appropriateness of the measurement instrument and the consistency of the data. Cronbach’s alpha coefficients were calculated to evaluate the internal consistency of each latent construct.

According to Nunnally (1978), a Cronbach’s α exceeding 0.9 suggests excellent reliability, while values ranging from 0.7 to 0.9 are considered acceptable. In this study, Cronbach’s α values for all constructs were found to be between 0.788 and 0.908, indicating that the measurement scales demonstrate satisfactory internal consistency. Detailed results are presented in

Table 2. Scale items and reliability analysis.

Construct	Item	Cronbach’s α	Reference
Memorable tourism experience	MTE1: I really enjoyed this travel experience.	0.908	J. H. Kim (2018). Cho et al. (2019). Wei et al. (2019). Antón et al. (2019). Zhang et al. (2018)
	MTE2: I learned more about myself through this travel experience.
	MTE3: I experienced new things during this travel experience.
Motivation	MOT1: My main purpose for traveling is to experience different cultures, places, and atmospheres, learn new things, and meet people who are different from me.	0.788	M. Kim and Thapa (2018). Kanagasapapathy (2017). S. Huang et al. (2015).
	MOT2: My purpose for traveling is to temporarily forget about work and responsibilities, relax, and relieve stress.
	MOT3: My main purpose for traveling is to improve relationships with others, spend time with family and friends, and meet like-minded people
Game design elements	GDE1: The reason I chose to experience this tourist attraction is because it showcases unique creativity through gamification elements (such as NPC interaction, game levels, and scene recreation), allowing me to experience a unique travel story in the real world.	0.804	Frijda (1993). Gutierrez (2021). Chan et al. (2020). Eppmann et al. (2018)
	GDE2: I am confident that I can successfully complete the gamified tasks at this tourist attraction, such as interacting with NPCs, completing game levels, or exploring virtual scenes, and enjoy the fun of it.
	GDE3: When I engage in gamified experiences at this tourist attraction, I feel like I have entered a world that feels more real than reality, almost as if I am in a virtual scene from an online game.
Flow experience	FLE1: Have you experienced flow during your travel?	0.904	Bai et al. (2024) M. J. Kim and Hall (2019) Marques et al. (2021) M. Kim and Thapa (2018). Kanagasapapathy (2017).
	FLE2: Most of the time, do you feel like you are experiencing flow?
	FLE3: I was completely immersed in this trip.
Perceiving value	PEV1: Gamified tourism makes me feel pleasant, relaxed, and I really enjoy the experience.	0.866	Peng et al. (2023) Pandža Bajs (2015) Cronin et al. (2000) M. Kim and Thapa (2018). J. H. Kim (2018).
	PEV2: Gamified tourism not only improves my perception of travel, but also leaves a lasting impression on others, enhancing my social identity with them.
	PEV3: Gamified tourism is consistently high quality in every aspect, especially in NPC interactions, game levels, and the recreation of virtual scenes.
Behavioral intention	BEI1: I will give a positive verbal evaluation of this travel experience. BEI2: I will recommend this destination to others. BEI3: I will revisit this place in the future.	0.895	J. H. Kim (2018). M. Kim and Thapa (2018). Marques et al. (2021). Cronin et al. (2000).

.

4.1.2. Convergent Validity

To assess the validity of the measurement model, confirmatory factor analysis (CFA) was conducted to evaluate both the convergent and discriminant validity of the constructs. The model fit indices indicated a good overall fit, with values meeting the commonly recommended thresholds in the literature, thus supporting the statistical adequacy and explanatory strength of the measurement model. The fit statistics were as follows: χ² = 171.9 (df = 124), χ²/df = 1.386, GFI = 0.955, AGFI = 0.937, NFI = 0.961, IFI = 0.989, TLI = 0.986, CFI = 0.989, and RMSEA = 0.031.

To evaluate convergent validity, this study followed the criteria suggested by Fornell and Larcker (1981), focusing on factor loadings, composite reliability (CR), and average variance extracted (AVE). As shown in

Table 3. Results of confirmatory factor analysis.

Construct	Item	Factor Loading	Construct Reliability	Convergent Validity
			CR	AVE
Memorable tourism experience	MTE1	0.938	0.920	0.793
	MTE2	0.866
	MTE3	0.865
Motivation	MOT1	0.798	0.810	0.588
	MOT2	0.685
	MOT3	0.812
Game design elements	GDE1	0.830	0.808	0.585
	GDE2	0.725
	GDE3	0.735
Flow experience	FLE1	0.928	0.911	0.774
	FLE2	0.854
	FLE3	0.855
Perceiving value	PEV1	0.944	0.874	0.700
	PEV2	0.756
	PEV3	0.799
Behavioral intention	BEI1	0.945	0.902	0.756
	BEI2	0.818
	BEI3	0.840

, all standardized factor loadings were between 0.685 and 0.945, exceeding the recommended threshold of 0.6. The CR values for all constructs ranged from 0.808 to 0.920, well above the commonly accepted benchmark of 0.70 (Raykov & Marcoulides, 2011). Additionally, all AVE values fell within the range of 0.585 to 0.793, surpassing the 0.50 criterion, indicating that each construct exhibited adequate convergent validity.

4.1.3. Discriminant Validity

To evaluate the distinctiveness of each latent variable, the method proposed by Fornell and Larcker (1981) was employed. This approach involves verifying whether the square root of the average variance extracted (AVE) for each dimension surpasses its shared variance with other dimensions. If this condition is met, it suggests that a given variable is more strongly associated with its own observed indicators than with those of other variables (X. Chen et al., 2020). In

Table 4. Discriminant validity results.

	MTE	MOT	GDE	FLE	PEV	BEI
MTE	0.891
MOT	0.153	0.767
GDE	0.181	0.310	0.765
FLE	0.429	0.258	0.243	0.880
PEV	0.327	0.210	0.375	0.205	0.837
BEI	0.204	0.125	0.150	0.377	0.248	0.869

, the diagonal values—indicating the square roots of AVE—are consistently higher than the respective inter-construct correlations found off-diagonal. This outcome supports the notion of sound discriminant validity, confirming that the measured dimensions maintain conceptual independence.

4.2. Structural Model Analysis

Maximum likelihood estimation was used to test the structural model, and the model fit indices indicated a good overall fit (χ² = 171.9, df = 124, χ²/df = 1.386, GFI = 0.955, AGFI = 0.937, NFI = 0.961, IFI = 0.989, TLI = 0.986, CFI = 0.989, RMSEA = 0.031). The SEM analysis results are shown in Figure 2 and

Table 5. Hypothesis testing.

Path	Path Coefficient	p Value	Supported?
H1: Memorable tourism experience has a positive effect on flow experience.	0.557	*** 1	Yes
H2: Memorable tourism experience has a positive effect on perceived value.	0.215	*** 1	Yes
H3: Motivation has a positive effect on flow experience.	0.341	0.004	Yes
H4: Motivation has a positive effect on perceived value.	0.091	0.178	NO
H5: Game design elements have a positive effect on flow experience.	0.278	0.027	Yes
H6: Game design elements have a positive effect on perceived value.	0.386	*** 1	Yes
H7: Flow experience has a positive effect on behavioral intention.	0.334	*** 1	Yes
H8: Perceived value has a positive effect on behavioral intention.	0.307	*** 1	Yes

¹ *** p < 0.001.

.

The path from memorable tourism experience (MTE) to flow experience (H1) was significant (coefficient = 0.557, p < 0.001), supporting H1. MTEs also significantly affected perceived value (H2) (coefficient = 0.215, p < 0.001), confirming H2. Motivation positively influenced flow experience (H3) (coefficient = 0.341, p = 0.004), but had no significant effect on perceived value (H4) (coefficient = 0.091, p = 0.178).

Game design elements significantly influenced both flow experience (H5) (coefficient = 0.278, p = 0.027) and perceived value (H6) (coefficient = 0.386, p < 0.001), supporting H5 and H6. Finally, flow experience (H7) (coefficient = 0.334, p < 0.001) and perceived value (H8) (coefficient = 0.307, p < 0.001) both significantly influenced behavioral intention, supporting H7 and H8. These findings show that both emotional (flow experience) and cognitive (perceived value) factors play critical roles in shaping behavioral intentions.

4.3. The SEM Effects of the Model

To test the mediating effects among variables, this study employed bootstrapping to examine model path significance. Results show that both memorable tourism experiences (MTEs) and tourist motivation exert significant direct and indirect effects on behavioral intention. In contrast, game design elements influence behavioral intention only indirectly through flow experience and perceived value.

Specifically, MTEs significantly affected behavioral intention through flow experience (total effect = 0.668, indirect = 0.141, p < 0.001) and perceived value (total = 0.670, indirect = 0.072, p = 0.003), confirming partial mediation. Motivation also showed significant indirect effects via flow experience (indirect = 0.181, p < 0.001) and perceived value (indirect = 0.105, p = 0.002), indicating both as partial mediators.

However, the direct effects of game design elements on behavioral intention were not significant (p > 0.7), while the indirect effects via flow (0.196, p < 0.001) and perceived value (0.235, p < 0.001) were significant, indicating full mediation.

These results highlight that, while MTEs and motivation affect behavioral intention both directly and indirectly, the impact of gamification relies entirely on enhancing flow experience and perceived value. Among the two, flow experience plays a more prominent mediating role, underscoring its importance in the design of gamified tourism experiences. Specific data can be found in

Table 6. The SEM mediating effects of the model.

Path	Effect	Estimate	95% Confidence Interval		p
			Bootstrapped Lower Limit	Bootstrapped Upper Limit
Memorable tourism experience—flow experience—behavioral intention	Total effect	0.668	0.538	0.814	0.000
	Direct effect	0.527	0.386	0.680	0.000
	Indirect effect	0.141	0.074	0.213	0.000
Memorable tourism experience—perceived value—behavioral intention	Total effect	0.670	0.539	0.816	0.000
	Direct effect	0.072	0.026	0.136	0.000
	Indirect effect	0.072	0.026	0.136	0.003
Motivation—flow experience—behavioral intention	Total effect	0.480	0.268	0.742	0.000
	Direct effect	0.299	0.092	0.539	0.002
	Indirect effect	0.181	0.100	0.296	0.000
Motivation—perceived value—behavioral intention	Total effect	0.487	0.274	0.754	0.000
	Direct effect	0.382	0.168	0.638	0.001
	Indirect effect	0.105	0.034	0.225	0.002
Gamification design elements—flow experience—behavioral intention	Total effect	0.228	−0.008	0.482	0.061
	Direct effect	0.032	−0.196	0.276	0.775
	Indirect effect	0.196	0.096	0.345	0.000
Gamification design elements—perceived value—Behavioral intention	Total effect	0.229	−0.008	0.481	0.063
	Direct effect	−0.005	−0.249	0.266	0.972
	Indirect effect	0.235	0.134	0.371	0.000

.

5. Discussion

This study constructs a theoretical framework integrating game design elements, tourist motivation, and memorable tourism experiences (MTEs), and empirically tests their relationships using structural equation modeling (SEM). The analysis confirms that gamified cultural tourism influences tourist experiences through two core mediators—flow experience and perceived value. This finding aligns with previous studies that highlight flow as a key factor in enhancing engagement in tourism contexts (M. Kim & Thapa, 2018) and supports the conceptualization by Zeithaml (1988) that perceived value is a critical driver of behavioral intention. By focusing on psychological mechanisms rather than surface-level enjoyment, this study reveals how gamified tasks and narratives foster immersion and subjective value, shifting tourists from passive observers to active participants. Rather than viewing tourism behavior as a response to static attractions, the study emphasizes a dynamic “participation–immersion–value” chain, offering a richer understanding of how interactive, gamified contexts shape tourism experiences. The results support the applicability of this multi-path mechanism for analyzing behavioral tendencies and lay a foundation for further theory-driven development in tourism experience design.

5.1. Theoretical Implications

This study introduces a novel and comprehensive theoretical framework, employing structural equation modeling to investigate the multi-path mechanisms linking MTEs, motivation, game design elements, flow experience, perceived value, and behavioral intentions. In contrast to previous studies that primarily connect gamification with tourist satisfaction or enjoyment (Hsu & Chen, 2018), this research extends theoretical boundaries by uncovering the deeper psychological impacts of gamification—its role as a situational activation and psychological transformation mechanism. The findings confirm that gamified tourism significantly enhances both flow experience and perceived value, which in turn drive behavioral intentions, aligning with prior studies (J. H. Kim, 2018).

A key contribution of this study lies in redefining the role of MTEs: rather than being seen as a static post-travel memory, MTEs are conceptualized as dynamic psychological drivers that operate through the “participation–immersion–value perception” pathway. By actively engaging in gamified tasks, tourists experience emotional immersion, which fosters positive value judgments and ultimately shapes their behavior. This extends the traditional MTE framework (Zhang et al., 2018), which often considers an MTE as a post-travel evaluative outcome, by conceptualizing it as an active psychological driver within the gamified experience. This re-conceptualization extends MTE theory into gamified and interactive tourism contexts, contributing to a more nuanced understanding of how experience-driven behaviors form.

Corroborating prior evidence from Ding and Hung (2021) and Xu et al. (2014), the findings confirm that gamified tourism significantly enhances both flow experience and perceived value, which in turn drive behavioral intentions. In particular, this study deepens the understanding of how psychological responses translate into behavioral transformation in gamified tourism. From the cognitive preparation stage, gamification—with its clear goals, structured rules, and instant feedback—enhances the predictability and perceived control of tourism activities. This reduces uncertainty in decision-making and facilitates the transition from intention to action. From an emotional engagement perspective, flow experience—marked by immersion and enjoyment—can serve as an affective trigger that strengthens behavior persistence and encourages social behaviors such as content sharing or recommending the destination. Furthermore, perceived value, encompassing functional, emotional, and social aspects, emerges as a decisive determinant of behavioral intention. While motivation initiates interest, it is the gamified design that transforms this interest into value recognition, ultimately driving behavioral outcomes.

These insights highlight a dual-pathway mechanism: flow experience represents affective immersion, while perceived value reflects cognitive evaluation. Together, they jointly influence behavior, consistent with the broader framework of the experience economy (C. F. Chen & Chen, 2010). Game design elements, although not directly impacting behavioral intentions, act as indirect enablers by enhancing these mediating experiences. This supports the view that gamification functions not merely as a content or engagement strategy, but as a contextual mediator—facilitating meaningful, co-created experiences between tourists and tourism providers (Huotari & Hamari, 2012). In the long term, such immersive and value-rich experiences can shape tourists’ behavioral tendencies, fostering habitual engagement, brand attachment, and sustained loyalty to gamified tourism destinations.

Finally, by bridging gamification theory with tourism behavior models, this study lays a conceptual foundation for exploring more complex forms of tourist behavior—such as cultural participation, place identity construction, and post-visit advocacy—shaped by gamified and interactive tourism environments. It encourages a shift from viewing tourism behavior as reactive, to seeing it as actively constructed through emotional immersion, meaning-making, and contextual value creation.

5.2. Practical Significance

This study offers practical insights into the sustainable application of gamification in tourism experience design, highlighting its role in adapting to shifting consumer trends and advancing cultural sustainability. With the growing emphasis on emotional engagement, participation, and digital innovation in tourism, gamification has gained attention as a strategic approach. By incorporating entertainment, educational content, and interactive elements, it contributes to destination attractiveness, visitor retention, and the advancement of sustainable tourism.

To achieve sustainable optimization of the tourist experience chain, this research emphasizes the importance of constructing a seamless flow throughout the pre-visit, on-site, and post-visit stages. Tourism operators should systematically embed gamification across the entire travel experience—from initial engagement to immersive participation and memory formation. In the field of health tourism, gamification can also motivate visitors to engage in health management and wellness activities, promoting physical and mental well-being through interactive challenges and personalized feedback. Integrating health elements into game design not only enriches the visitor experience but also fosters the adoption of healthy lifestyles and sustainable development. By integrating local culture, ritualized touchpoints, and immersive settings, such strategies can transform passive consumption into meaningful emotional and cultural connections.

From the perspective of cultural communication and cognitive construction, gamification functions not merely as an entertainment enhancer but as a powerful medium for conveying local culture and constructing place-based identity. By embedding culturally meaningful tasks and interactive scenarios within tourism experiences, visitors can simultaneously enjoy entertainment while deepening their understanding of and resonance with local values. This approach not only enhances the visitor experience but also contributes to cultural preservation and revitalization, offering innovative avenues for the sustainable transmission of intangible cultural heritage through digital and interactive means.

Overall, gamification—as a mechanism of “co-creation of experiences” and “contextual engagement”—is evolving beyond mere tourism optimization to serve as a critical driver of integrated cultural tourism development, modernized cultural communication, and sustainable local cultural revitalization. The synergy of gamification and digital innovation enables the tourism sector to meet contemporary travelers’ expectations while safeguarding, transmitting, and revitalizing indigenous cultural heritage, thereby contributing to broader social, cultural, and economic sustainability goals.

It is important to recognize that the strength and manifestation of the “participation–immersion–value” pathway may vary across different types of destinations. For instance, cultural destinations—where gamification can be effectively combined with storytelling, historical narratives, and rich contextual backgrounds—may foster deeper immersion and stronger value perceptions compared with natural or urban tourism sites. In cultural settings, gamified experiences can enhance visitors’ emotional engagement and cultural identity construction by embedding meaningful tasks and narrative-driven interactions. Conversely, natural or urban destinations might benefit more from gamification elements that emphasize exploration, discovery, or social interaction, thus adapting the pathway to suit their unique experiential characteristics. Future practical applications should tailor gamification designs to the destination type to maximize the psychological and behavioral impacts, thereby enhancing sustainable tourism development in diverse contexts.

5.3. Limitations and Future Research

While this study introduces an innovative framework, several limitations suggest directions for future research. First, it primarily focuses on psychological mechanisms, giving limited attention to multisensory and social dimensions. Future studies could examine how visual, auditory, and tactile stimuli, along with social presence, affect immersion and engagement, especially in sustainable tourism contexts. Additionally, exploring gamification’s application in health tourism could provide valuable insights into promoting wellness and preventive health behaviors through engaging digital experiences. Second, the sample was mainly drawn from Chinese participants, which may limit cultural generalizability. Future research could further explore how cultural backgrounds influence tourists’ responses to gamified experiences, providing insights for culturally adaptive design. Third, the study does not differentiate between types of gamified formats. Comparative studies assessing the effectiveness of various gamification tools—such as augmented reality (AR), virtual reality (VR), and mobile applications—would deepen understanding of their unique impacts on tourist motivation and experience. Fourth, potential limitations of gamification—such as excessive entertainment or novelty fatigue—should be explored, particularly regarding their effects on cultural understanding. Finally, future research should also address potential value conflicts and acceptance issues in diverse cultural settings, using frameworks of cross-cultural communication and adaptability.