Posting the Urban Tourism Experience: Motivations Behind Multimodal UGC Sharing

Abstract

As a vital component of urban tourism, urban theme parks increasingly face experience homogenization and intensifying competition. Accordingly, the implementation of refined digital marketing and operational strategies based on visitor digital behavior has become increasingly essential. In this context, tourists’ social media sharing has become a crucial link between destination marketing and visitors’ experience construction. Within the SOBC (Stimulus–Organism–Behavior–Consequence) framework, this study examines how theme park servicescapes (S) shape sharing motivations (O), which, in turn, influence multimodal sharing intentions (B—text, image + text, video) and subsequently contribute to memorable theme park experience (C). A two-stage, mixed-method design was employed, and the study considered visitors to Beijing Universal Studios and Shanghai Disney Resort. Semi-structured interviews and grounded analysis identified five motivations: altruism, self-presentation, affective expression, hedonic motivation, and community identification. Testing was performed using a survey (N = 604), along with structural equation modeling. The findings indicate that the staff-related social environment exerts significant positive effects on all five motivations, whereas the effects of the physical environment are more selective. Motivations differentially predict modal intentions: text aligns with altruism and affective expression; image + text aligns with altruism, community identification, and self-presentation; and video aligns with self-presentation, hedonism, community identification, and affective expression. All three intentions positively affect memorable theme park experience. These results clarify how motivations map onto content forms and validate a support SOBC framework from servicescapes to memorable experience, offering actionable implications for experience design and digital marketing.

1. Introduction

As significant carriers of large-scale cultural and tourism projects in modern cities, urban theme parks leverage a high density of cultural and entertainment offerings, excellent transportation accessibility, and comprehensive accommodation and commercial facilities to attract large volumes of visitors in a short period. By extending the duration of stay and stimulating ancillary consumption, they generate spillover effects that contribute to the shaping of urban image, job creation, and the clustering of related industries, thereby becoming pivotal to the competitiveness of urban destinations and the aggregation of cultural tourism consumption [1,2]. In addition, theme parks serve as strategic sites for urban governance, enhancing spatial vitality through concentrated flows of people, content, and interactions, contributing to place branding via digital narratives shaped by visitor experiences [2].

In recent years, the theme park industry in China has experienced rapid growth. According to the China Theme Park Development Report 2025, 90 super-large and large theme parks included in the statistics attracted approximately 130 million visitors and generated revenue of CNY 29.252 billion in 2024 [3]. Meanwhile, factors such as intensified industry competition, homogenization of supply, and seasonal fluctuations in demand are reshaping the visitor flow structure of theme parks [4]. The 2025 China Theme Park Competitiveness Evaluation Report indicates that, compared to 2023, the number of visitors to theme parks in mainland China was projected to decline by 1.76%, and operating revenue was projected to decline by 3.74% in 2024, reflecting a slight overall negative growth [3]. In this context, relying solely on spontaneous word-of-mouth from existing visitors is no longer sufficient to sustain the ongoing development of urban theme parks. Operators must enhance reach efficiency and conversion quality through precise digital marketing strategies and adopt data-driven content strategies to stabilize visitor flow and consumption [5,6]. After experiencing intense on-site experiences, visitors often share user-generated content (UGC) on social media platforms such as Weibo, documenting emotions, disseminating experiences, and influencing the decisions of others [7,8]. Due to its authenticity and high interactivity, UGC has become an irreplaceable core source of information and communication resource in destination marketing [9,10].

Prior research shows that social media sharing intention and behavior are fundamentally driven by motivations, and different motivations can lead to distinct forms and paths of expression [11]. Motivations are, in turn, shaped by external stimulus. Evidence indicates that the servicescape can activate tourists’ sharing motivations [12,13]. However, most studies focus on hotels, homestays, or generic attractions. In the highly immersive, IP-driven, and participation-intensive context of theme parks, tourists’ sharing motivations have not been systematically identified, and the mechanism linking servicescapes to sharing motivations remains underexplored [14,15].

A second gap concerns modality. Much UGC research examines a single format, such as text, photo, or short-form video content [16,17]. However, modalities differ in information richness, production cost, interaction effects, and the consolidation of subsequent experience [18,19]. Few studies compare text, image + text, and video intentions within a single framework, and fewer have tested motivation–modality differences in theme parks.

Moreover, social media sharing is not only a marketing device but also part of how tourists construct the self and strengthen memorable tourism experiences. Sharing through narrative reconstruction, social feedback, and multisensory re-presentation can enhance vividness, retrievability, and emotional depth of memory [20,21,22]. Whether intentions across different modalities contribute differently to memorable theme park experience remains unclear.

To address these gaps, implementing a mixed-method design, we conducted a study on visitors to Beijing Universal Studios and Shanghai Disney Resort. Semi-structured interviews and grounded analysis first identified sharing motivations in the theme park context. Guided by the SOBC (stimulus–organism–behavior–consequence) framework, this study develops a theoretically structured model that links servicescapes (S) to sharing motivations (O), to modality-specific sharing intentions (B: text, image + text, video), and to memorable theme park experience (C). A survey and structural equation modeling tested path significance and compared the direction and strength of the three modality paths within a single model. The study addresses three research questions: RQ1 (what sharing motivations characterize theme park tourists on social media?); RQ2 (how do different motivations differentially drive sharing intentions across modalities?); and RQ3 (how do servicescapes, motivations, and modality-specific intentions jointly shape memorable theme park experience along the SOBC framework).

This study contributes to the literature in three ways. First, five core sharing motivations in the theme park context are identified and validated: altruism, self-presentation, affective expression, hedonism, and community identification. Second, differential links between motivations and intentions across text, image + text, and video content are revealed. Third, the SOBC framework, encompassing servicescapes to motivations, modality-specific intentions, and memorable experience, is established, offering theoretical grounding and practical guidance for experience management and digital marketing in theme parks.

2. Literature Review and Research Model

2.1. SOBC (Stimulus–Organism–Behavior–Consequence) Framework

The SOBC framework, grounded in social learning theory [23], extends the classic SOR model [24] by conceptually distinguishing behavioral responses (B) from their subsequent consequences (C), allowing for a more structured analysis of sequential psychological processes. This structure clarifies how external stimulus (S) shapes internal organismic states (O), which then drive behavior (B) and yield consequences (C). Unlike SOR, which emphasizes immediate affective reactions, SOBC highlights the dynamic linkage between behavior and its outcomes, making it suitable for analyzing complex behavioral sequences. In tourism and social media research, SOBC enables modeling the full progression from on-site experience to post-visit outcomes.

Recent applications in tourism contexts support its utility. For instance, Sreen et al. applied SOBC to pandemic-era travel decisions and showed that extraversion and neuroticism influence perceived travel safety through introjected motivation and amotivation, thereby affecting intention to travel and willingness to pay a safety premium [25]. Similarly, Yang et al. used SOBC in livestream marketing and found that social sharing value [26], via trust and satisfaction, enhances behavioral intention and subsequently strengthens word-of-mouth, forming a closed stimulus–organism–behavior–consequence loop.

In this study, as illustrated in Figure 1, SOBC provides a theoretical lens for understanding tourists’ social media UGC sharing in theme parks: the physical and social environments constitute stimulus (S); sharing motivations (O) translate these stimuli into modality-specific sharing intentions, related to (B) text, image + text, and video content, which ultimately shape memorable theme park experience (C).

2.2. Stimulus and Servicecapes

In this study, stimuli (S) are defined as two servicescape cues in theme parks that are perceptible to visitors and pertinent to sharing: the physical environment and the social environment. The servicescape concept refers to controllable environmental elements through which service organizations shape affective, cognitive, and behavioral responses via spatial and situational design [27]. Subsequent research shows that a physical–social bifurcation helps identify differentiated effects: the physical environment primarily influences pleasure and immersion through sensory and spatial attributes, whereas the social environment shapes evaluations and intentions through service interactions [28,29,30].

Within the theme park context, the physical environment denotes environmental conditions such as spatial facilities and layout, signage and wayfinding, cleanliness, and decor. The social environment refers to employee-related service cues, including courtesy and friendliness, professional demeanor and appearance, responsiveness, and communicative conduct [31]. Accordingly, the physical and social environments are modeled as the two dimensions of stimulus (S) to examine their effects on sharing motivations (O) and, in turn, on modality-specific sharing intentions (B).

2.3. Organism

In this study, the organism (O) is defined as tourists’ sharing motivations for social media. As the psychological mechanism linking external stimulus to concrete behavior, motivation is the core transforming element within the SOBC framework. Prior work has documented widely observed motives behind online sharing, including altruism [32,33], self-presentation [34,35], affective expression and hedonism [36,37], community relational motives [38,39], and information management [11,15].

Building on semi-structured interviews conducted for this research (see Section 3), five sharing motivations were specified for the theme park context: altruism, self-presentation, affective expression, hedonism, and community identification. Grounded in our textual analysis and the literature, these are defined as follows. Altruism refers to the desire to help others make better trip and in-park decisions by providing actionable tips and guidance. Self-presentation refers to the desire to construct and signal one’s image and esthetic taste, showcasing distinctive experiences and competencies to gain attention and recognition. Affective expression refers to the desire to externalize and communicate emotions, such as joy, excitement, awe, and disappointment, and to recreate scenes that prolong feelings and enable resonance with others. Hedonism refers to treating online sharing as an extension of on-site entertainment, seeking fun, relaxation, and novelty through content creation and interaction. Community identification refers to the desire to maintain and expand social connections, seek feedback and support, signal in-group preferences, and strengthen belonging and identity tied to specific communities.

These five sharing motivations constitute O in the model; they translate the theme park servicescapes (S) into modality-specific sharing intentions (B) for text, image + text, and video content.

2.4. Behavior

In this study, behavior (B) is operationalized as tourists’ sharing intentions on social media, distinguished by three modalities: text-only, image + text, and video content. Specifically, text-only content refers to posts that consist solely of written content without any accompanying images or videos; image + text content denotes posts that combine static images with descriptive or captioned text; and video content refers to posts containing short-form videos, regardless of whether they are accompanied by text. Behavioral intention is a reliable predictor of subsequent behavior and is widely used as a proxy for action [40,41]. Accordingly, the analysis focuses on sharing intentions.

Modal differentiation is essential, as formats vary in information richness, affective expressivity, and affordances [42]. Text-only sharing relies on narrative and abstract symbols, supporting complex exposition and deeper storytelling [43]. Image + text sharing combines the immediacy of visuals with the explicative power of language, enabling both informational elaboration and visual self-presentation [44,45]. Video sharing offers dynamic, immersive, multisensory experiences, with distinctive advantages for conveying emotion and presence [46,47,48,49]. As outlined in Section 2.3, modality choice is closely linked to sharing motivations (O).

Within the SOBC framework, modality-specific sharing intentions constitute behavior (B), translating motivational states (O) into concrete tendencies to share.

2.5. Consequence

The consequence (C) is defined as memorable theme park experience (MTTE). The broader construct of memorable tourism experience (MTE) refers to “a tourism experience positively remembered and recalled after the event has occurred” and is typically shaped by sensory stimulation, cognitive impact, and affective arousal [20,50,51]. MTTE extends this lens to the theme park context [52]. As highly contextualized entertainment settings, theme parks integrate multisensory cues, themed narratives, and real-time interaction, which intensify emotional and cognitive responses and thereby enhance memory persistence and recall value [53,54].

Accordingly, within the SOBC framework, MTTE is modeled as the consequence (C), shaped by upstream servicescapes (S), sharing motivations (O), and modality-specific sharing intentions (B).

Figure 1. Hypothesized SOBC framework.

Figure 1. Hypothesized SOBC framework.

2.6. Hypothesis Development

2.6.1. Stimulus–Organism

In theme parks, the servicescape functions as the focal external stimulus (S). Consistent with Section 2.2, it comprises two core dimensions: the physical environment and the social environment. We argue that both dimensions activate tourists’ sharing motivations (O) by meeting distinct psychological needs, thereby differentially energizing altruism, self-presentation, affective expression, hedonism, and community identification.

The tangible physical environment of theme parks—including ambient conditions, spatial layout, facilities, signage, and style—forms the visual and sensory core of the visitor experience and can shape affective and psychological responses [55]. Within the SOBC framework, tourists’ sharing motivations on social media are treated as psychological reactions during the visit that can be activated by the physical environment. Well-maintained and thoughtfully designed settings also convey care for visitors, which may evoke altruistic motives and prompt the sharing of practical information to help others obtain similarly high-quality experiences [56]. Carefully designed photo spots and themed atmospheres provide an ideal stage for self-presentation [57], motivating visitors to showcase taste and experiences through sharing. Moreover, powerful and novel sensory stimuli can trigger affective expression and foster the desire to extend on-site enjoyment through sharing [54,58].

The social environment in theme parks—understood as human cues or the communicative staging of the servicescape—typically shapes emotions and psychological reactions through service interactions [28,29,31]. Professional, friendly, and empathic employee behavior builds trust and goodwill [52], thereby stimulating altruistic motives and a willingness to share on social media to enhance the park’s word-of-mouth [59]. High-quality interpersonal encounters are pleasurable in themselves [60], directly reinforcing hedonic motives. Employee participation in role-play and celebratory activities helps create a strong collective atmosphere, strengthening visitors’ sense of belonging and community identification [52]. In addition, receiving special attention during interactions, such as in-character greetings, or timely assistance serves as a form of social capital, encouraging self-presentation and positive affective expression. Accordingly, the following hypotheses are proposed:

H1. 

The physical environment exerts positive effects on (a) altruism, (b) self-presentation, (c) affective expression, (d) hedonism, and (e) community identification.

H2. 

The social environment exerts positive effects on (a) altruism, (b) self-presentation, (c) affective expression, (d) hedonism, and (e) community identification.

2.6.2. Organism–Behavior

As a key internal state, sharing motivations decisively drive social media sharing behavior [61,62]. Prior research consistently shows that diverse motivations positively promote overall sharing intentions. Altruism encourages helping others by providing practical tips and itineraries [63,64]. Self-presentation fosters identity construction and the display of distinctive experiences [34,65]. Affective expression supports the release of immediate emotions such as joy, excitement, and being moved [50,66]. Hedonism encompasses sharing as an extension of on-site enjoyment [37,67]. Community identification strengthens group belonging and participation in shared narratives [13,39,68]. Accordingly, the following hypotheses are proposed:

H3. 

Altruism positively influences (a) text-only sharing intention, (b) image + text sharing intention, and (c) video sharing intention.

H4. 

Self-presentation positively influences (a) text-only sharing intention, (b) image + text sharing intention, and (c) video sharing intention.

H5. 

Affective expression positively influences (a) text-only sharing intention, (b) image + text sharing intention, and (c) video sharing intention.

H6. 

Hedonic motivation positively influences (a) text-only sharing intention, (b) image + text sharing intention, and (c) Video sharing intention.

H7. 

Community identification positively influences (a) text-only sharing intention, (b) image + text sharing intention, and (c) video sharing intention.

2.6.3. Behavior–Consequence

Sharing intentions entail more than the act of posting; through narrative reconstruction and affect amplification, they strengthen overall evaluations of the theme park visit and deepen long-term memory, that is, the formation of memorability [20,21]. Memorable experiences are understood to arise from intense affect, meaning-making, and repeated recall; the retelling, selection, and reorganization inherent in sharing promote deeper encoding and consolidation [69].

The three modalities operate through distinct memory pathways. Text-only sharing revolves around narrative reworking and elaborative processing—translating experience into language enhances semantic depth and organization, thereby facilitating durable memory [70]. Image + text sharing combines verbal statements with static visuals, yielding dual coding and richer retrieval cues. Visuals increase salience and recallability, while text supplies context and meaning frameworks; together, they reinforce memory [71,72]. Video sharing strengthens memory via multichannel cues and temporal re-enactment—synchronized audio-visual streams and situational continuity heighten presence and arousal, promoting consolidation and subsequent recall [73,74]. Given the inherently immersive, multisensory nature of theme parks, such modality-specific re-presentations are especially effective at converting on-site emotions and contextual cues into vivid, retrievable memories. Accordingly, the following hypotheses are proposed:

H8. 

Text-only sharing intention positively influences memorable theme park experience.

H9. 

Image + text sharing intention positively influences memorable theme park experience.

H10. 

Video sharing intention positively influences memorable theme park experience.

3. Materials and Methods

3.1. Research Design

A mixed-method research design was employed to address the research questions and test the proposed hypotheses. Beijing Universal Studios and Shanghai Disneyland, two leading urban theme parks in China featuring globally recognized intellectual properties, were selected as the study sites. The overall research design and analytical procedure are illustrated in Figure 2. As shown in Figure 2, the study was conducted in three sequential phases, encompassing qualitative exploration, pretest validation, and formal hypothesis testing.

3.2. Qualitative Research

3.2.1. Purpose and Samples

First, to identify the antecedents of multimodal UGC sharing intentions, we conducted semi-structured interviews from October 2024 to March 2025 following a unified interview protocol. Participants were recruited through a combination of on-site invitations at Beijing Universal Studios and Shanghai Disney Resort, as well as online recruitment via Weibo travel-related communities. Eligibility required participants to (i) have an authentic visit to Beijing Universal Studios or Shanghai Disney Resort within the previous six months and (ii) be active Weibo users over the past month who had shared, or intended to share, travel-related content. A total of 74 valid interviews were completed (female = 46; male = 28; Mean age = 29.22 ± 8.45), yielding approximately 500,000 characters of textual data.

3.2.2. Data Collection

The interviews (offline and online) systematically documented participants’ direct perceptions of the physical and social environment, the triggers of sharing, reasons for modality choice, and post-sharing subjective changes. All interviews were audio-recorded with informed consent and transcribed verbatim. Data collection proceeded iteratively. After approximately 60 interviews, no substantively new themes or motivation categories emerged, and subsequent interviews largely replicated existing patterns. The remaining interviews were conducted to confirm category stability, providing evidence of thematic saturation.

3.2.3. Data Analysis

Two researchers independently conducted open coding, extracting meaning units related to the “why visitors share their experiences on social media.” Through axial coding, these initial codes were grouped into higher-order subcategories and iteratively refined into five core motivational dimensions: altruism, self-presentation, affective expression, hedonism, and community identification. To enhance coding reliability, the two coders compared results after each coding stage. Discrepancies were discussed within the research team until consensus was reached, and category definitions were refined accordingly. The constant comparison method was applied across interviews to verify the stability of emerging categories and ensure internal consistency. Through selective coding, core propositions were integrated, resulting in a coherent motivational structure. After consolidation through merging overlapping expressions and removing redundancies, the interview phase yielded 45 distinct motivation statements directly related to social media sharing, which served as the empirical foundation for subsequent scale development. Each dimension was assigned 6–10 preliminary items, capturing different nuances of sharing motivations. Representative examples include the following: altruism—“I share to help others plan their trips more efficiently”; self-presentation—“I share to express my personal esthetics and identity”; and community identification—“Sharing helps me connect with like-minded people in this community.”

Building on the qualitative findings, we converted representative quotes into first-person statements, explicitly anchored in the Weibo context and rated on a seven-point Likert scale. To ensure content validity without introducing new constructs, we systematically compared and aligned wording with established motivation measures, refining synonymous or ambiguous expressions and supplementing coverage where needed [15,34,75,76]. Following revision and removal of redundancies, we finalized 25 items capturing the five sharing-motivation dimensions for subsequent quantitative testing.

3.3. Survey 1 (Pretest)

3.3.1. Purpose and Sample (Survey 1)

Based on the items generated from the qualitative phase, a first-round questionnaire survey (pretest) was conducted to purify the sharing motivation scale and to establish a reliable measurement instrument for subsequent analysis. The data from this survey were subjected to exploratory factor analysis (EFA) to identify the underlying factor structure of sharing motivations and to remove items that did not meet psychometric criteria.

Before completing the questionnaire, all respondents were provided with brief explanations of the key constructs and item meanings to ensure consistent understanding. Specifically, the online portion was distributed through Credamo, while the offline survey was conducted outside the park gates, targeting those who had already completed their visit. This ensured that responses regarding memorable theme park tourism experience (MTTE) were based on full and completed visits. Overall, 350 tourists from two major theme parks (Beijing Universal Studios and Shanghai Disneyland) were featured. Participants who had not used Weibo in the previous month were not included. A final sample of 298 respondents was selected for the data analysis, following the exclusion of 52 respondents who did not meet the requirements. The majority of respondents were female (57.4%, n = 171) and between the ages of 18 and 35 (66.1%, n = 197). Most respondents had a bachelor’s degree (51.7%, n = 154).

3.3.2. Measurement Instruments (Survey 1)

Twelve items for physical environment and nine items for social environment were borrowed from Dong and Siu [31]; text-only sharing intention, image + text sharing intention, and video sharing intention were modified from Ham et al. [39]; and memorable theme park tourism experience was borrowed from Zheng et al [52]. Each item was assessed on a seven-point Likert scale ranging from strongly disagree (1) to strongly agree (7). The English scales used in this study were translated into Chinese following a standard back-translation procedure. Furthermore, the design and wording of the questions were examined during a pretest to ensure the appropriateness of the survey. The use of these well-established scales helps ensure that the items are unambiguous. Furthermore, we assured all participants of the anonymity of the questionnaire and the confidentiality of the data. These procedural control measures all contribute to reducing the risk of common method bias.

3.3.3. Data Analysis Methods (Survey 1)

We conducted an EFA on the 25 motivational items. The EFA employed principal component analysis for factor extraction with varimax (orthogonal) rotation. Factor retention was determined by considering multiple criteria, including eigenvalues greater than 1, the inflection point on the scree plot, and theoretical interpretability. We removed items with factor loadings below 0.50 or those exhibiting significant cross-loadings (defined as a difference of less than 0.20 between their highest and next-highest loadings). Additionally, to preliminarily examine the structural validity of the measurement model encompassing all constructs, we performed a confirmatory factor analysis on all items to assess the initial model fit and provide a basis for potential adjustments.

3.4. Survey 2 (Formal Survey)

3.4.1. Purpose and Sample (Survey 2)

To examine the hypothesized SOBC framework, we conducted a second survey involving 700 tourists from two major theme parks in China—Beijing Universal Studios and Shanghai Disneyland—via both Credamo and offline data collection. After data cleaning, 604 valid responses were retained for analysis. Most respondents’ ages ranged from 18 to 35 (66.6%, n = 402). Overall, 51.8% (n = 313) were female. More than half of the participants (52.3%, n = 316) held a bachelor’s degree, and most reported a monthly income below CNY 15,000 (88.2%, n = 533). In terms of visit status, 74.3% (n = 449) had completed their visits, while 25.7% (n = 155) were still on-site during the survey.

3.4.2. Measurement Instruments (Survey 2)

The measurement items in this survey were derived from prior scales. Specifically, sharing motivations were measured using a 19-item scale that was identified and retained through the exploratory factor analysis conducted in Survey 1 (see Section 4.1.1 for details). The measurement items for the physical environment, social environment, text-only sharing intention, image + text sharing intention, and video sharing intention were adopted from the established scales used in Survey 1, ensuring consistency across the two survey stages.

3.4.3. Data Analysis Methods (Survey 2)

Mplus 8.3 software was used to conduct reliability and validity testing, common method bias testing, and hypothesis testing on the model containing all 11 latent variables. The CFA was performed using the maximum likelihood (ML) estimation method in Mplus software. Prior to the analysis, we examined the univariate normality of the item scores. To ensure our data met this assumption and to verify the suitability of the ML estimator, we checked the skewness and kurtosis of all items. These values fell within acceptable ranges (absolute skewness < 2, absolute kurtosis < 7), supporting the use of ML.

4. Results

4.1. Scale Development and Survey 1 Results

4.1.1. Exploratory Factor Analysis

To validate the assessed items (including physical environment, social environment, altruism motivation, self-presentation motivation, affective expression motivation, hedonic motivation, community identification motivation, text-only sharing intention, image + text sharing intention, image + text sharing intention, and memorable theme park experience), we ran a confirmatory factor analysis (CFA) using Mplus on the Survey 1 data. The initial model test fit findings were unacceptable: χ² (2166) = 33043.002, p < 0.001; χ²/df = 15.255, CFI = 0.227, TLI = 0.187, SRMR = 0.250, and RMSEA = 0.219.

To improve construct validity, we then performed an exploratory factor analysis (EFA), resulting in KMO = 0.936 (p < 0.001), confirming sampling adequacy. Based on the common criterion of factor loadings above 0.50, six items with loadings below this threshold were eliminated (altruism motivation: ALT2 “I share to express my personal value judgements about the trip.” ALT6 “I share to present a lifestyle image that fits who I am.”; community identification motivation: CI1 “As a community member, platform-level recognition matters to me.” CI3 “I feel a strong sense of belonging to this community.” CI6 “I share to express our community’s preferences or stance.” CI7 “Interacting around posts helps me maintain relationships with other community members.” (See

Table 1. EFA results (Survey 1).

Construct and Indicators	Standardized Factor Loading	p-Value
Physical environment (Cronbach’s α: 0.941)
PE1	0.828	0.000
PE2	0.782	0.000
PE3	0.733	0.000
PE4	0.724	0.000
PE5	0.772	0.000
PE6	0.729	0.000
PE7	0.781	0.000
PE8	0.696	0.000
PE9	0.707	0.000
PE10	0.778	0.000
PE11	0.722	0.000
PE12	0.800	0.000
Social environment (Cronbach’s α: 0.912)
SE1	0.741	0.000
SE2	0.728	0.000
SE3	0.731	0.000
SE4	0.723	0.000
SE5	0.732	0.000
SE6	0.746	0.000
SE7	0.720	0.000
SE8	0.717	0.000
SE9	0.783	0.000
Altruism motivation (Cronbach’s α: 0.841)
ALT1	0.761	0.000
ALT3	0.776	0.000
ALT4	0.771	0.000
ALT5	0.711	0.000
Self-presentation motivation (Cronbach’s α: 0.845)
SP1	0.792	0.000
SP3	0.749	0.000
SP4	0.734	0.000
SP5	0.769	0.000
Affective expression motivation (Cronbach’s α: 0.825)
AE1	0.757	0.000
AE2	0.718	0.000
AE3	0.760	0.000
AE4	0.708	0.000
Hedonic motivation (Cronbach’s α: 0.817)
HED1	0.797	0.000
HED2	0.705	0.000
HED3	0.681	0.000
HED4	0.730	0.000
Community identification motivation (Cronbach’s α: 0.814)
CI2	0.736	0.000
CI4	0.775	0.000
CI5	0.801	0.000
Text-only sharing intention (Cronbach’s α: 0.857)
SI_T1	0.770	0.000
SI_T2	0.894	0.000
SI_T3	0.829	0.000
Image + text sharing intention (Cronbach’s α: 0.782)
SI_I1	0.737	0.000
SI_I2	0.744	0.000
SI_I3	0.739	0.000
Video sharing intention (Cronbach’s α: 0.872)
SI_V1	0.856	0.000
SI_V2	0.837	0.000
SI_V3	0.809	0.000
Memorable theme park experience (Cronbach’s α: 0.824)
MTTE1	0.790	0.000
MTTE2	0.733	0.000
MTTE3	0.819	0.000

Note: PE = physical environment; SE = social environment; ALT = altruism motivation; SP = self-presentation motivation; AE = affective expression motivation; HED = hedonic motivation; CI = community identification motivation; SI_T = text-only sharing intention; SI_I = image + text sharing intention; SI_V = video sharing intention; MTTE = memorable theme park tourism experience.

for details).

The EFA produced five factors that accounted for 68.229% of the total variance after removing the six items (see Table 1): altruism (14.735% of variance; four items; α = 0.841), self-presentation (14.332% of variance; four items; α = 0.845), affective expression (14.190% of variance; four items; α = 0.825), and hedonism (13.851% of variance; four items; α = 0.817), and community identification (11.121% of variance; three items; α = 0.814). These five factors, comprising 19 motivational items, represent five basic social media sharing motivations.

4.1.2. CFA

We retested the measurement model’s model fit after the modification procedures. The results revealed that the model and the data fit well: χ² (1219) = 1622.559, p < 0.001; χ²/df = 1.331, CFI = 0.955, TLI = 0.951, RMSEA = 0.033, and SRMR = 0.036.

4.2. Measurement Results (Survey 2)

Moreover, convergent validity was examined. The results revealed that all AVE values were larger than 0.5 (e.g., affective expression motivation = 0.525) [77], and CR values were larger than 0.8 (e.g., text-only sharing intention = 0.806); thus, we confirmed the convergent validity of all seven constructs. Discriminant validity was also established because the square root of each construct’s AVE was greater than its correlations with other constructs.

Table 2. Convergent and discriminant validity test (Survey 2).

Construct	CR	AVE	PE	SE	ALT	SP	AE	HED	CI	SI_T	SI_I	SI_V	MTTE
PE	0.944	0.584	0.764
SE	0.917	0.551	0.251 ***	0.742
ALT	0.847	0.581	0.373 ***	0.371 ***	0.762
SP	0.831	0.552	0.357 ***	0.354 ***	0.267 ***	0.743
AE	0.816	0.525	0.281 ***	0.358 ***	0.239 ***	0.248 ***	0.725
HED	0.823	0.538	0.151 ***	0.399 ***	0.207 ***	0.204 ***	0.163 ***	0.733
CI	0.815	0.595	0.214 ***	0.418 ***	0.226 ***	0.245 ***	0.236 ***	0.186 ***	0.771
SI_T	0.865	0.682	0.302 ***	0.323 ***	0.457 ***	0.255 ***	0.435 ***	0.168 ***	0.228 ***	0.826
SI_I	0.806	0.581	0.299 ***	0.344 ***	0.407 ***	0.370 ***	0.206 ***	0.254 ***	0.366 ***	0.262 ***	0.762
SI_V	0.855	0.664	0.332 ***	0.338 ***	0.243 ***	0.482 ***	0.292 ***	0.324 ***	0.387 ***	0.274 ***	0.329 ***	0.815
MTTE	0.827	0.614	0.318 ***	0.346 ***	0.355 ***	0.348 ***	0.308 ***	0.276 ***	0.303 ***	0.483 ***	0.432 ***	0.491 ***	0.784

Note: *** p < 0.001. PE = physical environment; SE = social environment; ALT = altruism motivation; SP = self-presentation motivation; AE = affective expression motivation; HED = hedonic motivation; CI = community identification motivation; SI_T = text-only sharing intention; SI_I = image + text sharing intention; SI_V = video sharing intention; MTTE = memorable theme park tourism experience.

provides further details.

The structural model demonstrated a good fit with the data: χ² (1219) = 1986.301, p < 0.001; χ²/df = 1.629, CFI = 0.955, TLI = 0.951, SRMR = 0.029, and RMSEA = 0.032.

4.3. Common Method Bias (Survey 2)

Common method bias was examined using Harman’s one-factor test [78]. Overall, 26.303% (less than 50%) of the variation in the data was explained by a single unrotated factor, which means the data did not exhibit serious common technique bias [79]. In addition, we conducted a confirmatory factor analysis of the single-factor model for further examination. The results showed a severe degradation in model fit (χ² (1274) = 10775.867, p < 0.001; χ²/df = 8.458, CFI = 0.429, TLI = 0.406, SRMR = 0.115 and RMSEA = 0.111). This indicates that a model attributing all variance to a single common method factor fails to fit the data, thereby providing further evidence that the common method bias in this study’s data is within controllable limits and does not pose a substantial threat to the subsequent structural model analysis.

4.4. Structural Results and Hypotheses Tested

Data were analyzed using SEM via Mplus. Among the 28 hypotheses tested, 5 were not supported (H1d, H3c, H5b, H6a, and H7a), while the remaining 23 were statistically significant (see

Table 3. The results of hypothetical path analysis (Survey 2).

Hypothetical Path	Estimate	S.E.	Est./S.E.	p-Value
H1a PE → ALT	0.326	0.042	7.717	0.000
H1b PE → SP	0.327	0.039	8.480	0.000
H1c PE → AE	0.231	0.044	5.207	0.000
H1d PE → HED	0.058	0.045	1.298	0.194
H1e PE→CI	0.136	0.046	2.946	0.003
H2a SE → ALT	0.344	0.040	8.556	0.000
H2b SE → SP	0.317	0.043	7.403	0.000
H2c SE → AE	0.352	0.043	8.102	0.000
H2d SE → HED	0.442	0.042	10.533	0.000
H2e SE → CI	0.445	0.041	10.787	0.000
H3a ALT → SI_T	0.366	0.043	8.599	0.000
H3b ALT → SI_I	0.318	0.045	7.126	0.000
H3c ALT → SI_V	0.009	0.043	0.215	0.830
H4a SP → SI_T	0.076	0.045	1.665	0.096
H4b SP → SI_I	0.259	0.048	5.443	0.000
H4c SP → SI_V	0.422	0.043	9.891	0.000
H5a AE → SI_T	0.361	0.042	8.570	0.000
H5b AE → SI_I	−0.016	0.046	−0.353	0.724
H5c AE → SI_V	0.112	0.044	2.570	0.010
H6a HED → SI_T	0.005	0.044	0.122	0.903
H6b HED → SI_I	0.115	0.047	2.427	0.015
H6c HED → SI_V	0.198	0.041	4.784	0.000
H7a CI → SI_T	0.050	0.045	1.103	0.270
H7b CI → SI_I	0.268	0.048	5.625	0.000
H7c CI → SI_V	0.264	0.045	5.845	0.000
H8 SI_T → MTTE	0.358	0.039	9.143	0.000
H9 SI_I → MTTE	0.282	0.043	6.590	0.000
H10 SI_V → MTTE	0.358	0.044	8.218	0.000

Note: PE = physical environment; SE = social environment; ALT = altruism motivation; SP = self-presentation motivation; AE = affective expression motivation; HED = hedonic motivation; CI = community identification motivation; SI_T = text-only sharing intention; SI_I = image + text sharing intention; SI_V = video sharing intention; MTTE = memorable theme park tourism experience.

).

The analysis first examined the influence of stimulus servicescape on various sharing motivations. Physical environment was positively associated with altruism motivation (H1a: β = 0.326, p < 0.001), self-presentation motivation (H1b: β = 0.327, p < 0.001), affective expression motivation (H1c: β = 0.231, p < 0.001), and community identification motivation (H1e: β = 0.136, p < 0.01), but no significant association with hedonic motivation was found (H1d: β = 0.058, p > 0.05). Social environment was positively associated with altruism motivation (H2a: β = 0.344, p < 0.001), self-presentation motivation (H2b: β = 0.317, p < 0.001), affective expression motivation (H2c: β = 0.352, p < 0.001), hedonic motivation (H2d: β = 0.442, p < 0.001), and community identification motivation (H2e: β = 0.445, p < 0.001).

The subsequent analysis investigated the pathways through which social media sharing motivations influence the three content formats of sharing intention. Altruism motivation was positively associated with text-only sharing intention (H3a: β = 0.366, p < 0.001) and image + text sharing intention (H3b: β = 0.318, p < 0.001), but its effect on video sharing intention was not significant (H3c: β = 0.009, p > 0.05). Self-presentation motivation exhibited a particularly strong association with image + text sharing intention (H4b: β = 0.259, p < 0.001) and video sharing intention (H4c: β = 0.422, p < 0.001), but it did not exhibit a significant relationship with text-only sharing intention (H4a: β = 0.076, p > 0.05). Affective expression motivation showed a strong association with text-only sharing intention (H5a: β = 0.361, p < 0.001), a weakly significant association with video sharing intention (H5c: β = 0.112, p < 0.05), and no significant association with image + text sharing intention (H5b: β = −0.016, p > 0.05). Hedonic motivation positively demonstrated a weak association with image + text sharing intention (H6b: β = 0.115, p < 0.05) and a moderately strong association with video sharing intention (H6c: β = 0.198, p < 0.001), while showing no significant association with text-only sharing intention (H6a: β = 0.005, p > 0.05). Community identification motivation showed a moderately strong association with both image + text sharing intention (H7b: β = 0.268, p < 0.001) and video sharing intention (H7c: β = 0.264, p < 0.001), but it did not show a significant association with text-only sharing intention (H7a: β = 0.050, p > 0.05).

Finally, the contribution of different formats of sharing intention to the formation of a memorable theme park experience was tested. The results revealed that the text-only sharing intention (H8: β = 0.358, p < 0.001), image + text sharing intention (H9: β = 0.282, p < 0.001), and video sharing intention (H10: β = 0.358, p < 0.001) all had a positive association with memorable theme park experience.

4.5. Model Explanatory Power Assessment

To evaluate the explanatory power of the structural model, we found the coefficients of determination (R²) for all endogenous latent variables. As shown in

Table 4. Model explanatory power.

Variables	Estimate	S.E.	Est./S.E.	p-Value
ALT	0.291	0.037	7.893	0.000
SP	0.268	0.036	7.484	0.000
AE	0.229	0.035	6.482	0.000
HED	0.216	0.037	5.886	0.000
CI	0.250	0.037	6.676	0.000
SI_T	0.403	0.038	10.524	0.000
SI_I	0.416	0.040	10.502	0.000
SI_V	0.466	0.038	12.407	0.000
MTTE	0.555	0.036	15.281	0.000

Note: ALT = altruism motivation; SP = self-presentation motivation; AE = affective expression motivation; HED = hedonic motivation; CI = community identification motivation; SI_T = text-only sharing intention; SI_I = image + text sharing intention; SI_V = video sharing intention; MTTE = memorable theme park tourism experience.

, the R² values for the five sharing motivations ranged from 0.216 to 0.291, indicating that the servicescape (physical environment and social environment) explains approximately 21.6% to 29.1% of the variance in these motivations. The R² values for the three modal sharing intentions ranged from 0.403 to 0.466, suggesting that the five motivations explain about 40.3% to 46.6% of the variance in these intentions. Finally, the R² value for the memorable theme park tourism experience was 0.555, indicating that the three sharing intentions collectively explain approximately 55.5% of its variance. These results demonstrate that the SOBC model in this study exhibits moderate-to-strong explanatory power for the core endogenous variables.

5. Discussion

UGC on social media platforms is crucial for destination marketing. Many tourists share their travel experiences online. This study posits that servicescapes within theme parks activate specific sharing motivations, which, in turn, are associated with tourists’ preferences for different forms of social media sharing intention, therefore being linked to the formation of memorable theme tourism experiences.

Employing a mixed-method approach, this study identified five dimensions comprising 19 motivation items through interviews. Consistent with previous studies in the literature, altruism motivation reflects the user’s desire to assist others and share useful information, thereby facilitating digital co-creation and value sharing within their social networks [80]. Self-presentation motivation highlights the role of social media as a platform for crafting and managing one’s self-image [35], where sharing theme park content contributes to constructing a specific identity. Affective expression motivation highlights sharing as a channel for emotional communication, enabling users to convey joy, excitement, or nostalgia associated with their experiences [81]. Hedonic motivation captures the intrinsic pleasure derived from the act of sharing, serving as an extension of the enjoyment from the theme park visit [38]. Finally, community identification motivation signifies the desire to connect with a group, strengthen a sense of belonging, and participate in a shared cultural narrative built around the theme park brand. Altruism, self-presentation, and hedonic motivations are recognized drivers of social media use in general [35,38,80,81]. However, theme parks operate within a high-engagement, experience-driven tourism context, which places emotional and social connections at the core of the sharing process [82]. This finding aligns with prior research indicating that the emotional and social bonds experienced in theme parks foster positive recommendations and word-of-mouth [13]. Consequently, this study demonstrates that the intention to share on social media among theme park visitors is driven by a constellation of these motivations.

The tests of our hypothesis framework demonstrated that both the physical and social environments contribute to the enhancement of tourists’ social media sharing motivations. Specifically, the physical environment significantly stimulates motivations such as altruism, self-presentation, affective expression, and community identification, yet its impact on hedonic motivation is minimal. This suggests that tangible elements like design and facilities are perhaps perceived more as functional backdrops or symbols of status rather than direct sources of enjoyment. However, the non-significant link between the physical environment and hedonic motivation is theoretically notable. This suggests that in the immersive, activity-saturated context of a theme park, tangible design and facilities may be perceived more as a necessary stage or functional backdrop rather than a direct source of enjoyment. In contrast, the link of the social environment was more universal and significant, positively affecting all five motivational dimensions. The path coefficients for hedonic motivation and community identification motivation were particularly strong. In other words, staff–visitor interactions and service-related social cues play a critical role in shaping tourists’ motivations to share on social media. This finding aligns with the service-dominant logic, which emphasizes that value in theme parks is predominantly co-created through interactive service encounters between employees and visitors [31]. This result is consistent with the influence path from stimulus to organism within the SOBC framework [83].

Subsequently, we investigated how these social media sharing motivations are linked to sharing intentions. Moving beyond a simple link between motivations and general sharing intention, this study offers more nuanced and detailed insights into how specific motivations influence intentions towards specific sharing formats. We found that different motivations exert different associations with the three forms of social media sharing intention. First, text-only sharing intention was primarily associated with altruism motivation and affective expression motivation. Tourists driven by altruism motivation likely use text to provide detailed suggestions, practical tips, and comprehensive reviews, content best conveyed through descriptive language. Similarly, those motivated by affective expression utilize text to articulate complex emotional experiences, such as expressing both positive and negative feelings, narrating stories, and providing nuanced contextual information that visuals alone cannot capture. This highlights the unique role of text as a medium for cognitive and narrative elaboration [43]. The lack of significant association between text-only sharing and motivations like hedonic motivation and community identification is instructive. This suggests that the textual modality, with its lower sensory richness and less direct social signaling capability [18,19], may not be the preferred channel for expressing pure enjoyment or reinforcing group belonging, which are better served by richer media like images or video [45,46].

Image + text sharing, as a hybrid format, provides a flexible channel for multiple motivations. Its primary predictors are altruism motivation and community identification motivation. It strikes a balance between the informational depth of text and the symbolic power of images. While image sharing enables the curation of life and the construction of an ideal self-image [44], text allows for further elaboration [43]. This makes it particularly suitable for altruistic acts and for affirming community membership. Notably, self-presentation motivation is also significantly associated with this format, likely because image + text sharing allows for highly controlled curation of personal identity through visual esthetics and accompanying narratives [44,45]. However, the non-significant association with affective expression motivation is notable. This may indicate that for the immediate, visceral emotional release often sought in theme parks, the static nature of images paired with text might feel less immediate compared to the dynamic emotion capture of video or the deep narrative processing of pure text [43,49].

Video sharing emerged as the primary avenue for fulfilling self-presentation motivation and hedonic motivation. The dynamic nature of video makes it exceptionally effective at capturing the exciting and fun-filled moments of a theme park visit, thereby directly satisfying hedonic motivation. Furthermore, its immersive and rich sensory qualities provide a potent medium for self-presentation, enabling individuals to project themselves within the theme park context. This result aligns with prior research indicating that self-presentation motivation significantly influences vloggers’ perceived enjoyment [84]. The significant paths from community identification motivation and affective expression motivation indicate that video is also employed for sharing collective experiences and emotions [19]. While altruism strongly associated with text-only and image + text sharing, it did not extend to video. This may be because creating helpful, informative video content requires higher production effort [18,19] and is less suited for quick, actionable advice compared to text or static images.

Finally, this study examined the impact of sharing intentions on memorable theme park experiences. The results indicate that all three forms of sharing intention positively contributed to memorable theme park experiences, demonstrating that the willingness to share experiences on social media facilitates the formation of such memories. This finding extends beyond the conventional view of social media sharing as a post hoc behavior and redefines it as an integral component of the consumption process itself. While previous research has established that publishing eWOM positively influences revisit intention and experience memory [85], the current study can be viewed as an extension of this work. Going a step further, this research identified varying intensities in the impact of the three sharing forms on memorable theme park experiences.

6. Conclusions

6.1. Theoretical Innovations

Employing a mixed-method approach combining semi-structured interviews and questionnaire surveys, this study identified theme park tourists’ social media sharing motivations and further constructed a servicescape-sharing motivations–multimodal sharing intentions–memorable theme park experience model based on the SOBC framework to investigate the pathway effects. This study offers several key theoretical innovations.

First, by focusing on theme parks as the research context, this study investigated social media sharing motivations within this unique, high-engagement, experience-driven environment. The findings reveal that tourists’ social media sharing motivations in theme parks comprise five categories: altruism motivation, self-presentation motivation, affective expression motivation, hedonic motivation, and community identification motivation. This research deepens the study of social media sharing motivations. Although previous studies have established general classifications of social media motivations [61], our study further reveals how these motivations are specifically activated by theme park servicescapes. The results demonstrate that the social environment exhibits a more universal and powerful influence, significantly contributing to all five identified motivations. In contrast, the impact of the physical environment is more selective. More importantly, it demonstrates that these motivations do not uniformly drive a generic sharing intention. Instead, they form differential affinities with specific sharing modalities.

Second, and most significantly, this research introduces modality as a critical theoretical construct that explicates the “how” in the motivation–behavior–consequence chain. This study reveals the differential effects of social media sharing motivations on various modal sharing behaviors. While existing research has explored UGC sharing intentions, most studies focus on single modalities [13,15,34], overlooking the fundamental differences between text-only media, image + text media, and video media. Our findings indicate that text-only sharing intention is primarily associated with altruism motivation and affective expression motivation. Image + text sharing is associated with altruism motivation, community identification motivation, and self-presentation motivation. Video sharing serves as the primary channel for satisfying self-presentation motivation, hedonic motivation, community identification motivation, and affective expression motivation. Consequently, this study provides a theoretical mechanism for why and how different psychological drives translate into different behavioral expressions and, ultimately, lead to the formation of memorable experience. This addresses a key limitation in existing SOBC/SOR applications in tourism, which often treat behavior as a monolithic outcome variable.

Third, by validating a complete SOBC framework from servicescapes to memorable experience, this study demonstrates the role of these modality-specific behaviors. It shows that the sharing intention is not merely a post hoc reflection but an integral part of the experience construction process. Furthermore, grounded in the SOBC framework, this study examines the servicescape-sharing motivations–multimodal sharing intentions–memorable theme park experience model within the theme park context, thereby expanding the application scope of SOBC. Thus, the model expands the traditional view by incorporating the expressive form of behavior intention as a key variable that shapes the final experience.

6.2. Management Insights

This study offers both micro-level managerial guidance for theme park operations and, more importantly, macro-level strategic pathways for urban tourism destinations. By leveraging large-scale theme parks as engines of urban tourism, it demonstrates how stimulating individual visitors’ sharing behaviors can drive destination brand building, spatial vitality, and overall development.

First, the results demonstrate that social environment influences a wider range of sharing motivations (altruism, hedonism, community identification), while physical environment primarily stimulates self-presentation and affective expression. This differentiation suggests that theme park operators should strategically align servicescape elements with desired UGC modalities. For instance, designing spontaneous social interaction spaces (e.g., interactive parades, live character shows) may activate community-related motivations and foster image + text sharing, while immersive emotional zones (e.g., slow-paced thematic areas) may evoke stronger affective expression conducive to video-based storytelling. At the same time, highly esthetically pleasing installations like IP sculptures or landmark backgrounds still serve as important triggers for self-presentation through text-only or image + text formats. Therefore, managers should shift from generic beautification to modality-sensitive experience planning, transforming social and physical servicescapes into curated digital content generators that cater to distinct sharing preferences.

Second, based on the differential relationships between sharing motivations and modalities, theme park managers and marketers can guide visitors to co-create a digital urban image. Different motivations show differentiated effects on the three sharing modalities, enabling more precise content guidance strategies. For example, self-presentation shows stronger association with text-only sharing and video sharing, which implies that personalized experience spaces (e.g., “top 1% adventurer” badges, AR-based achievements) can enhance visibility and encourage detailed narration or high-effort video production. In contrast, altruism and community identification are more associated with image + text posts, which are ideal for disseminating park tips, reviews, or group interactions. Managers should thus develop modality-specific content campaigns, featuring, for example, “Quick Tips with a Pic”-type content to encourage image + text UGC for practical advice or “My Theme Park Journey” vlog competitions to inspire deeper engagement via videos. This modular approach allows for targeted amplification of desired user behaviors based on empirical model evidence.

Third, integrating sharing opportunities deeply into experience design can reinforce individual memories while fostering urban tourism development. While all three sharing modalities positively contribute to memorable experiences, text-only and video sharing intentions exhibit stronger effects, as they involve more effortful narrative reconstruction or immersive re-engagement. Accordingly, managers should match intervention designs with cognitive depth. For instance, digital guestbooks or memory prompts can nudge visitors to produce reflective text posts, while interactive filming zones or storyline-triggered AR cues can stimulate video creation. In contrast, image + text sharing, though easier, may require visual curation prompts (e.g., “spotlight shot” signage) to reinforce its memory contribution.

This strategic framework aligns micro-level visitor engagement with macro-level destination development, offering actionable insights for theme park operators and urban tourism authorities.

6.3. Shortcomings and Future Research Directions

First, while this study focused on two major theme parks in China—Beijing Universal Studios and Shanghai Disneyland—providing valuable insights into urban tourism contexts, the generalizability of the findings may be limited. Future research could extend the scope to a broader range of theme parks to enhance the external validity of the proposed model. In particular, park type (e.g., IP-driven versus locally themed parks) may serve as a grouping variable to examine contextual differences in tourists’ sharing motivations and behaviors.

Second, although this study validated the hypothesized relationships among servicescapes, sharing motivations, modality-specific sharing intentions, and memorable tourism experience within the SOBC framework, it did not explicitly test mediation or indirect effects, nor did it incorporate moderating variables. Future research could build on this framework by conducting formal mediation analyses, introducing moderators such as individual characteristics (e.g., visit frequency, fan engagement, or content creation skills) and integrating complementary theoretical perspectives (e.g., Uses and Gratifications or affordance theory) to further enrich the explanatory power of modality-specific sharing mechanisms.

Third, despite adopting a mixed-method approach with qualitative interviews and two stages of survey data collection, the empirical analysis remains cross-sectional in nature, which limits strong causal inference. Future studies could employ longitudinal or follow-up designs to track changes in motivations, sharing behaviors, and experiential outcomes over time, thereby better capturing the dynamic processes implied by the SOBC framework.