Digital tourism communication: effects of influencer credibility, content quality, and e-WoM on emotions, FoMO, self-identification, and visit intentions of Gen Z travelers

Introduction: The rapid expansion of short-video platforms has transformed destination promotion, yet the psychological processes linking digital stimuli to behavioral intentions among young travelers remain underexplored.

Methods: Using the Stimulus-Organism-Response (S-O-R) framework and a Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, data were collected from 344 Generation Z respondents aged 21-27 years who had previously viewed Bali-related content on TikTok.

Results: The analysis reveals two main pathways: a direct effect of Influencer Credibility, TikTok Content Quality, and Electronic Word of Mouth on behavioral responses (β = 0.417), and an indirect path through the psychological Organism-Emotion, Fear of Missing Out (FoMO), and Self-Identification which also significantly influences responses (β = 0.149). TikTok Content Quality emerged as the most dominant stimulus (β = 0.760), while Self-Identification was the strongest psychological predictor within the Organism construct (β = 0.785). Intention to Visit showed the highest loading within the Response construct (β = 0.889), indicating the strong persuasive power of digital content.

Discussion: Although the model demonstrates high reliability at the lower-order construct level, limitations in convergent and discriminant validity were identified in higher-order constructs. The study extends the S-O-R framework in algorithm-driven short-video contexts and offers practical insights for tourism boards and digital strategists seeking to enhance cultural engagement and increase destination visit intentions among young travelers.

1 Introduction

Digital transformation has reshaped how individuals seek information and make decisions, including in the tourism sector. Within this shifting media landscape, TikTok has become one of the most influential platforms, particularly due to its rapid growth and its strong integration into Generation Z’s media habits (Khamis and Kılıç, 2025); (Rugrien and Funk, 2022). Reports from Business of Apps estimate that Indonesia now has approximately 109.9 million TikTok users, making it the country with the second-largest user base globally, dominated by users aged 18–24 (Haryanto et al., 2023). TikTok’s quick-paced format, interactive affordances, and algorithm-driven personalization allow tourism content to circulate efficiently and resonate emotionally with younger audiences (Vo Hoang Hoai and Klimecka, 2023).

Preisler (2025) explains that this phenomenon presents a major opportunity in the realm of digital tourism communication, where promotional strategies no longer rely on conventional media but depend on authentic and relatable visual narratives from influencers (Preisler, 2025). Influencers in the TikTok ecosystem play a key role as curators of experiences who shape public perceptions of tourist destinations (Ilieva, 2023). The credibility of influencers reflected in perceptions of expertise, trustworthiness, and personal appeal has been proven to act as a catalyst in building parasocial relationships between message deliverers and audiences (Nguyen and Borgel, 2024; Yuan and Lou, 2020). These relationships possess psychological strength in encouraging audiences to trust, relate to, and even imitate the lifestyles or destination choices portrayed (Santateresa-Bernat et al., 2023).

Despite the growing attention to TikTok’s role in tourism, empirical studies integrating influencer credibility, content quality, digital Word of Mouth (WoM), and Gen Z’s psychological mechanisms remain limited. Existing research tends to examine these elements in isolation, leaving unanswered how they interact to shape cultural curiosity and visit intentions in short-video environments. This study addresses that gap by analyzing how influencer credibility, TikTok content characteristics, and WoM jointly activate psychological responses including emotion, FOMO, cultural curiosity, and self-identification known to be especially salient for digitally immersed youth (Dinh and Lee, 2024; Ulucan, 2024; Zhang et al., 2023).

The study’s contribution lies in offering an integrated model that captures how these mechanisms operate simultaneously within algorithm-driven social media ecosystems. Within interactive social media environments, Word of Mouth (WoM) expressed through comments, content sharing, and user-generated reviews functions as an interpersonal communication channel that amplifies these psychological dynamics (Pillai, 2025; Berger, 2025; Santateresa-Bernat et al., 2023). Such digital WoM provides social validation that strengthens audience perceptions and enhances trust toward a destination.

The theoretical framework used in this study is the Stimulus–Organism–Response (S–O–R) model, developed by Mehrabian and Russell (1974), which is now increasingly popular in digital consumer behavior studies (Pahrudin et al., 2023). In this study’s theoretical implementation, the stimulus refers to influencer credibility, TikTok content characteristics, and WoM as external triggers. To explain these mechanisms, the study adopts the Stimulus–Organism–Response (S–O–R) framework, which is well suited to digital platforms where stimuli are delivered rapidly, repeatedly, and algorithmically (Pahrudin et al., 2023). Unlike rational decision models such as TRA or TPB, the S–O–R framework accommodates affect-driven, experiential, and socially reinforced processes that are characteristic of TikTok’s media environment (Abdalla et al., 2025; Serrano-Malebrán et al., 2025; Chin and Wong, 2022). In this study, influencer credibility, content characteristics, and WoM serve as the external stimuli; positive emotion, FOMO, cultural curiosity, and self-identification represent the internal organismic states (Peng and Kim, 2014; Yaqub et al., 2023; Seçilmiş et al., 2022; Alrawadieh et al., 2019); and intention to visit functions as the behavioral response. It is this organism that ultimately produces the response in the form of the intention to visit a tourist destination, in this case, Bali. The SOR framework provides a strong conceptual foundation for understanding how digital communication shapes behavioral intentions through measurable psychological and social processes.

Bali serves as a relevant empirical context because its cultural expressiveness and visual aesthetics make it highly compatible with TikTok’s algorithmic preferences (Dewa Mahendra, 2024; Subawa et al., 2021). Short videos depicting traditional ceremonies, landscapes, and everyday atmospheres frequently evoke emotional responses and strengthen destination imagery. Digital interactions such as comments and peer recommendations then extend these effects organically, contributing to social proof and heightened interest (Berger, 2025). By applying a PLS-SEM approach to data from Gen Z viewers of Bali-related TikTok content, this study examines the interconnected roles of influencer credibility, TikTok content quality, and WoM in shaping psychological responses and visit intention. The findings aim to advance theoretical understanding of digital tourism communication using the S-O-R lens, while offering practical insights for tourism boards, destination marketers, and digital strategists seeking to design content strategies that more effectively engage young travelers.

2 Methods

This study is an explanatory quantitative research that aims to explain causal relationships between variables using a specific theoretical approach (Mamuaya et al., 2025). The researcher employs the Stimulus–Organism–Response (S–O–R) framework as a grounded theory, supported by relevant constructs such as TikTok content, influencer credibility, word of mouth (WoM), self-identification, Fear of Missing Out (FoMO), and cultural curiosity to analyze their relationship in increasing travel intention. The sampling technique used is purposive sampling, which involves selecting samples based on specific criteria relevant to the research objective in this case, exposure to digital tourism content (Mamuaya et al., 2025).

The sample size in this study was determined based on statistical considerations to produce reliable estimates of the target population, namely active TikTok users from Generation Z in Indonesia. According to Indonesia’s population projection for 2025, Generation Z is estimated to number approximately 79.7 million people, with 90% of them identified as active TikTok users. Thus, the effective population for this study is around 72 million Gen Z users (IDN Research Institute, 2024). To obtain generalizable results, the margin of error (MoE) formula for proportion estimation was used, with a 95% confidence level and an assumed proportion of 0.5 (to yield the maximum margin value) (Fujihasa et al., 2023). A minimum sample size of 300 respondents yields a maximum sampling error of ±5.66%. This value remains within the statistically acceptable range, especially for social research based on surveys using a quantitative approach such as Partial Least Squares Structural Equation Modeling (PLS-SEM) (Hair Jr., et al., 2021) (see Table 1).

Table 1

Table 1. Construct item.

Within the framework construct of the Stimulus–Organism–Response (S–O–R) theory, the variables in this study are classified into three main components. The first component is Stimulus, which includes external factors influencing individuals, such as Influencer Credibility, TikTok Content Quality, and Electronic Word of Mouth (e-WoM) (Faisal and Dhusia, 2022; Guo et al., 2025; Nanggong and Mohammad, 2024). Influencer credibility refers to the extent to which users perceive influencers as experts, honest, and appealing in conveying tourism-related information. Meanwhile, TikTok content quality is assessed based on visual appeal, informational usefulness, ease of understanding, and the extent to which the content is enjoyable to watch. Electronic Word of Mouth pertains to individuals’ perceptions of online reviews and travel recommendations shared by other users, either through comments or social media platforms.

The second component is Organism, which refers to the internal responses that emerge after individuals are exposed to stimuli. In this context, three main dimensions are identified: Destination Emotion, FoMO (Fear of Missing Out), and Self-Identification (Przybylski et al., 2013; Hosany et al., 2015; Cao et al., 2023). Destination emotion reflects feelings of joy, excitement, and emotional engagement toward Bali after being exposed to digital content. FoMO refers to the anxiety or fear of being left out when not participating in popular travel trends followed by others. Self-identification, on the other hand, represents a personal connection with tourism content, where individuals feel that the promoted destination reflects who they are or their lifestyle.

Lastly, Response represents the final outcome of this psychological process, in the form of tangible actions or intentions. In this study, the response is captured through Cultural Curiosity and Visit Intention (Davari, 2022; Kurniawan et al., 2023). Cultural curiosity reflects the desire to understand Bali’s local culture, including its customs and traditions. Visit intention refers to one’s actual intention to travel to Bali, such as the willingness to plan a vacation or the likelihood of visiting the destination. Thus, the S-O-R model in this research provides a comprehensive understanding of how external factors can influence individual psychology and ultimately shape tourism visit intentions.

3 Result

3.1 Descriptive statistics

A total of 344 respondents aged 21–27 years participated in this study, representing Generation Z individuals actively engaged with TikTok. Female participants made up 58.4% (n = 201), while males comprised 41.6% (n = 143). The age distribution was balanced, with the largest groups aged 22 (17.2%) and 24 (16.0%), followed by those aged 21 (14.8%) and 25 (14.5%). Most respondents reported spending between one to 2 h per day on social media (43.9%), while about one-third (31.1%) spent 3 to 4 h. A smaller group (19.5%) were heavy users with more than 4 h of daily activity, and only 5.5% used social media for less than an hour. All participants confirmed having encountered TikTok content about Bali, ensuring the relevance of their responses to the research context (see Table 2).

Table 2

Table 2. Respondent.

3.2 Measurement model

The results of the structural model analysis illustrate the relationships among the Stimulus–Organism variables, which explain the influence of influencer credibility, content quality, and Electronic Word of Mouth (e-WoM) on destination emotion, Fear of Missing Out (FoMO), and self-identification among social media users. Based on the estimation results, Influencer Credibility (IC) shows a negative effect on Destination Emotion (EM) with a coefficient of −0.350, indicating that higher influencer credibility does not necessarily increase positive emotional responses toward the destination. However, influencer credibility demonstrates a positive and fairly strong effect on FoMO (0.354), suggesting that audiences tend to feel more intrigued and afraid of being left out when the influencer is perceived as credible. The effect of IC on Self-Identification (SI) is relatively small (0.058), implying that influencer credibility alone is insufficient to shape users’ identification with the promoted content.

Meanwhile, Content Quality (QC) also shows a very small negative effect on Destination Emotion (−0.046) but exhibits a positive relationship with FoMO (0.357), meaning that the more appealing and high-quality the content, the greater the audience’s tendency to experience the Fear of Missing Out. The influence of QC on Self-Identification (0.007) is negligible, indicating that content quality does not directly drive audiences to associate themselves with the content. On the other hand, Electronic Word of Mouth (EW) has a positive influence on Self-Identification (0.343), signifying that online interactions and recommendations play a key role in shaping users’ sense of connection or identification with shared tourism experiences.

The R² values of the endogenous variables reveal that Destination Emotion (EM) is explained by IC and QC at 12.8%, FoMO (FO) at 27.8%, and Self-Identification (SI) at 11.9% by IC, QC, and EW. These values indicate that the model has a relatively low to moderate explanatory power, with the most substantial effect observed on the FoMO variable. Overall, the findings suggest that in the context of tourism destination promotion through social media, audiences are more emotionally influenced by the feeling of being left out (FoMO) than by the formation of destination emotion or self-identification. Thus, influencer credibility and content quality appear to be more effective in stimulating curiosity and a desire to participate (Fear of Missing Out) rather than in fostering a deep emotional attachment to the promoted destination.

The figure above displays the results of Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis, which illustrates the relationship between the Organism variables consisting of Destination Emotion (EM), Fear of Missing Out (FO), and Self-Identification (SI) and the Response variables consisting of Cultural Curiosity (CC) and Intention to Visit (IV). This model is a continuation of the previous stage, which examined the influence of Stimulus on Organism. In this stage, the focus is directed to examining how internal psychological factors (emotion, FoMO, and self-knowledge) influence audience behavior and cognitive responses to tourism destination promotions.

In general, the model shows that Self-Identification (SI) has a positive influence on Cultural Curiosity (CC) with a coefficient of 0.207. This indicates that the stronger a person feels connected to or reflects the values displayed in tourism content (e.g., through influencers or a courageous community), the greater their desire to explore and understand the culture of the promoted destination. However, the effect of SI on Intention to Visit (IV) is negative, albeit very small (−0.027), indicating that although individuals feel close to the content, this does not directly increase their intention to visit. This phenomenon could mean that self-knowledge is more powerful in triggering curiosity than in driving actual behavior.

Furthermore, Fear of Missing Out (FO) has a small effect on Cultural Curiosity (0.040) and a slightly larger effect on Visit Intention (0.134). This means that individuals who fear missing out on social trends or popular experiences on social media are more likely to have the intention to visit the destination, even though their cultural curiosity does not significantly increase. FOMO here acts as a trigger for impulsive behavior driving action (intention to visit) without a corresponding increase in cultural interest.

Meanwhile, the Destination Emotion (EM) variable shows an interesting direction of the relationship: its effect on Cultural Curiosity is negative and very small (−0.030), but it has a fairly strong positive effect on Visit Intention (0.410). These results suggest that positive emotions toward an inspiring destination do not necessarily lead to greater curiosity about the local culture, but are more effective in driving intention. Concrete motivation to visit. In other words, emotional appeals are more powerful in shaping behavioral responses than cognitive curiosity.

The R² value for Cultural Curiosity of 0.083 means that the three variables (EM, FO, and SI) together explain approximately 8.3% of the variation in cultural curiosity, indicating that other factors outside the model likely play a greater role in influencing audience interest. Meanwhile, the R² value for Visit Intention of 0.158 indicates that this model can explain approximately 15.8% of the variation in visit intention, which can be classified as a low to medium level of explanation. Overall, it can be concluded that the Destination Emotion (EM) variable is the Organism factor that most strongly influences Responses, particularly Visit Intention, compared to Self-Identification and FoMO. This confirms that in the social context of media-based tourism promotion, emotional elements play the largest role in building visit intention, while psychological aspects such as FoMO and self-identification act more as mediators that strengthen feelings of cultural involvement and curiosity.

To visually support the quantitative findings of this study, the following figures present the output of the structural model analysis using the PLS-SEM approach. Figure 1 illustrates the overall path diagram of the S–O–R framework, showing the relationships between Stimulus, Organism, and Response constructs. Figure 2 displays the p-values associated with each hypothesized path, indicating the statistical significance of the relationships. Figure 3 presents the corresponding t-value, further validating the strength and reliability of each causal path within the model (see Table 3).

Figure 1

Figure 1. PLS-SEM path model between stimulus and organism constructs.

Figure 2

Figure 2. PLS-SEM path model between organism and response constructs.

Figure 3

Figure 3. Graphic output outer loading high order construct.

Table 3

Table 3. Construct reliability (Cronbach’s alpha, composite reliability ≥ 0.7).

In this study, the Stimulus, Organism, and Response constructs are higher-order constructs explained by several first-order constructs. The Stimulus construct comprises Influencer Credibility (IC), TikTok Content Quality (TC), and Electronic Word of Mouth (eWOM). These three constructs demonstrate good reliability and convergent validity, with all Cronbach’s Alpha values exceeding 0.7 and Average Variance Extracted (AVE) values above 0.5. However, the AVE value for the combined Stimulus construct is only 0.259, which falls below the ideal threshold of > 0.5. This indicates that overall, the indicators within the Stimulus construct are not sufficiently strong in comprehensively explaining the construct. Meanwhile, the Organism construct is explained by three variables: Destination Emotion (EM), Fear of Missing Out (FoMO or FO), and Self-Identification (SI). Each of these underlying constructs exhibits high reliability, with Composite Reliability (CR) values > 0.8 and AVE values > 0.6. However, the combined Organism construct has an AVE value of 0.354, which is also below the recommended threshold. This suggests that although the individual constructs are valid and reliable, their combination is not optimal in explaining the overall Organism construct. Furthermore, the Response construct consists of Cultural Curiosity (CC) and Intention to Visit (IV). Both constructs show strong reliability performance, with AVE values of 0.661 and 0.684, respectively. Nevertheless, the combined Response construct also presents a low AVE value of 0.439. This indicates that the combined Response construct does not adequately reflect the overall variance explained by its underlying variables (see Table 4).

Table 4

Table 4. Heterotrait-monotrait ratio.

Based on the HTMT (heterotrait–monotrait ratio) results, most inter-construct correlations were below the 0.90 threshold, indicating that discriminant validity was generally established. However, several pairs of constructs exhibited HTMT values that approached or exceeded the recommended limit, particularly between Organism–FoMO (0.954), Organism–SI (0.968), and Response–IV (1.058). These values indicate a degree of conceptual overlap, suggesting that participants may have perceived these psychological constructs as closely related experiences. Such high correlations imply that the emotional and motivational components of Organism are not fully distinguishable from the behavioral intentions captured in Response, particularly within the highly immersive and affect-driven context of TikTok travel content. This pattern aligns with previous findings in digital behavior research, where affective engagement (e.g., FoMO and social identification) tends to manifest simultaneously with behavioral impulses rather than sequentially.

Although discriminant validity is generally acceptable, these findings call for cautious interpretation of the structural model. The overlap between constructs may stem from theoretical proximity within the S–O–R framework, as well as the use of higher-order constructs (Stimulus, Organism, Response) that aggregate several first-order dimensions. The relatively low AVE values of these higher-order constructs further indicate that the shared variance among their indicators is limited, thus weakening convergent validity at the second-order level. Therefore, while the overall reliability and internal consistency of individual constructs remain adequate, the combined model should be interpreted as capturing interrelated psychological processes rather than strictly independent constructs. Future research is encouraged to refine the measurement model either by using first-order constructs or by re-specifying Organism and Response to enhance discriminant validity and theoretical clarity.

3.3 Structural model evaluation

Table 5 presents the outer loading values for all indicators on their respective constructs, along with the coefficient of determination (R²) for each latent variable. Most indicators show strong outer loadings above 0.70, indicating that individual indicators reliably contribute to their constructs. Only a few indicators fall slightly below 0.70, such as EW3 (0.680) and FO1 (0.656), yet they remain within acceptable bounds and do not materially compromise construct reliability. For the Stimulus construct, the first-order components display R² values of Influencer Credibility (IC) = 0.236, TikTok Content Quality (QC) = 0.577, and Electronic Word of Mouth (EW) = 0.420. These results indicate that content quality plays the most significant role in shaping Gen Z users’ perceptions and experiences with Bali-related TikTok content, followed by EW and IC. This underscores the importance of high-quality digital content in influencing users’ initial perceptions.

Table 5

Table 5. Outer loading and coefficient of determination.

The Organism construct, capturing Gen Z’s internal psychological states related to visit intention to Bali, exhibits a low R² of 0.024. This indicates that the Stimulus construct explains only a small proportion of the variance in Organism. Despite this low R², the first-order constructs reveal important insights: Self-Identification (SI) R² = 0.616, FoMO (FO) R² = 0.572, and Emotion (EM) R² = 0.422. These findings suggest that self-identification is the dominant internal factor driving psychological engagement, followed by FoMO and emotional responses.

The low explanatory power of Stimulus on Organism can be interpreted in several ways. First, Gen Z’s internal psychological responses toward visiting Bali may be shaped by unmeasured individual factors, such as personal travel motivations, prior experiences with tourism, personality traits, or social influences beyond TikTok content. Second, the limited scope of the Stimulus indicators focused only on IC, QC, and EW may not fully capture the broader range of digital or offline experiences affecting internal states. Third, given the complex nature of internal psychological constructs, even statistically significant paths may have small effect sizes, reflecting that internal states are inherently multifaceted and influenced by a variety of situational and dispositional factors.

The Response construct, representing behavioral outcomes, has an R² of 0.216. Within this construct, Visit Intention (IV) is dominant (R² = 0.790), while Cultural Curiosity (CC) shows moderate explanatory power (R² = 0.465). This indicates that visit intention is the primary behavioral manifestation of Gen Z engagement with Bali content, supported partially by curiosity about Balinese culture. Overall, these results highlight that while first-order construct relationships are statistically sound and interpretable, the limited explanatory power of Stimulus on Organism points to an area for future refinement. Researchers should consider incorporating additional mediators or moderators such as social norms, prior travel experiences, or personality dimensions to better capture the internal psychological processes of Gen Z tourists. By transparently reporting these limitations and providing theoretical explanations, the model maintains scientific rigor while acknowledging the complexity of human behavior in the context of digital stimuli and travel intentions (see Table 6).

Table 6

Table 6. Path coefficient and hypothesis testing results.

Based on the path coefficients, p-value, and t-value above, and by adopting the Stimulus–Organism–Response (S–O–R) framework, this study illustrates how exposure to digital tourism content particularly on social media platforms like TikTok can influence the psychological aspects of Generation Z and ultimately shape their behavioral responses in the context of tourism in Bali (Figures 4, 5). In general, the model outlines two primary influence pathways: a direct path from Stimulus to Response, and an indirect path through the mediating variable Organism.

Figure 4

Figure 4. Graphic output p-value high order construct.

Figure 5

Figure 5. Graphic output t-value high order construct.

In the direct path, it was found that the Stimulus has a significant and strong effect on the Response (β = 0.417; p < 0.001; t = 7.672), indicating that the more intense the exposure to digital stimuli such as influencers, TikTok content, and Electronic Word of Mouth the greater the interest and attraction of Gen Z toward Bali. This suggests that visual and public opinion–based digital marketing strategies have a direct and effective impact on tourism-related behavior.

In the indirect path, the Stimulus also significantly influences the Organism (β = 0.154; p = 0.012; t = 2.505), albeit with a smaller effect size. This implies that exposure to stimuli not only has a direct effect but also helps shape internal psychological states such as emotion, FoMO (Fear of Missing Out), and self-identification. Furthermore, the Organism has a significant impact on the Response (β = 0.149; p = 0.004; t = 2.915), demonstrating that the psychological conditions formed through digital stimuli further motivate individuals in making travel decisions, although this effect is not as strong as the direct path. Thus, the model emphasizes that both direct and indirect psychological mediation paths play important roles in shaping Gen Z’s travel intentions toward Bali.

A deeper analysis of the constructs reveals that within the Stimulus component, the most dominant factor is TikTok Content (QC) with the highest influence (β = 0.760), followed by Electronic Word of Mouth (EW) (β = 0.648), and Influencer Credibility (IC) (β = 0.485). This underscores that visual, creative, and narrative aspects on platforms like TikTok are the strongest attractions influencing Gen Z’s perception and interest. Within the Organism component, the three key constructs significantly shaped by digital stimuli are Self-Identification (SI) (β = 0.785), Fear of Missing Out (FO) (β = 0.757), and Emotion (EM) (β = 0.650). This indicates that Gen Z does not simply receive information passively, but rather internalizes content as part of their identity, experiences anxiety about missing trends, and engages emotionally with the destination.

Finally, within the Response component, the two main indicators are Intention to Visit (IV) (β = 0.889) and Cultural Curiosity (CC) (β = 0.682). Intention to Visit emerges as the strongest response, demonstrating that digital stimuli can shape concrete decisions regarding travel intentions, while Cultural Curiosity reinforces that Gen Z is also driven by a genuine desire to learn about local cultures. Overall, these findings confirm that digital tourism communication is highly relevant and effective in influencing the travel behavior of young tourists. It not only generates direct responses but also mediates the development of internal psychological aspects that strengthen the decision-making process in tourism.

4 Discussion

4.1 Interpreting the dominance of the direct stimulus–response path

The results show that the direct effect of Stimulus on Response (β = 0.417, p < 0.001) is stronger than the indirect effect through Organism (β_indirect = 0.154 × 0.149 = 0.023). This finding can be explained by the digital behavioral characteristics of Generation Z, who tend to be impulsive, visually oriented, and fast in decision-making.

On platforms such as TikTok, tourism-related content is presented in short video formats with attractive visuals and emotional storytelling. These features create an immediate emotional arousal that directly triggers interest or visit intention (Response) without requiring a deeper process of cognitive or affective reflection (Organism). In this study, the Stimulus dimension consisted of Influencer Credibility (IC), Content Quality (CQ), and Electronic Word of Mouth (e-WoM). Each of these constructs provides an external stimulus that directly enhances user engagement and curiosity about Bali as a tourism destination. For instance, Influencer Credibility (Faisal and Dhusia, 2022) and Content Quality (Guo et al., 2025) create immediate trust and enjoyment, while e-WoM (Nanggong and Mohammad, 2024) reinforces social validation from peers. Together, these first-order constructs elicit fast emotional reactions that bypass the internal organismal process of Destination Emotion, FoMO, or Self-Identification.

This phenomenon aligns with Preisler (2025) and Tian et al. (2022), who found that Generation Z is more strongly influenced by immediate visual gratification and peer validation rather than deep internalization of symbolic meanings. Therefore, the direct path (S–R) represents a spontaneous and affect-driven response, while the mediated path (S–O–R) requires a more reflective psychological process that is less likely to occur in the fast-paced TikTok environment. Moreover, Influencer Credibility and Content Quality appear to activate FoMO (Fear of Missing Out) more effectively than Self-Identification. FoMO functions as a quick affective trigger that motivates behavioral intentions such as the intention to visit without requiring a complex process of self-identification. Consequently, the stronger direct effect of Stimulus on Response suggests that Generation Z perceives and reacts to digital tourism content as emotional impulses rather than reflective identity expressions.

4.2 Implications of the low R² of organism for the S–O–R model

The value of R² for the Organism construct (0.024) indicates that only about 2.4% of the variance in psychological states comprising emotional responses, FoMO (Fear of Missing Out), and self-identification is explained by the Stimulus variables. Although this relationship is statistically significant (p = 0.012), the small proportion of explained variance reflects a very limited mediating effect of Organism within the S – O - R framework. Theoretically, this finding holds important implications for applying the Stimulus–Organism–Response (S–O–R) model (Mehrabian and Russell, 1974) in the context of fast-paced and visually driven media platforms such as TikTok. The classical S–O–R model assumes that behavioral responses are preceded by internal cognitive and affective processes, through which external stimuli are interpreted before producing behavioral intentions. However, among Generation Z audiences, the Organism component represented by emotional engagement, FoMO, and self-identification appears to function only as a minor intermediary rather than a central mediator.

This pattern can be attributed to several psychological and contextual factors. The extremely brief exposure time characteristic of TikTok limits users’ cognitive capacity to engage in deeper emotional or reflective processing. Instead, users’ reactions are primarily shaped by immediate affective experiences, driven by the platform’s visual, auditory, and narrative appeals. Furthermore, the built-in system of instant social validation through likes, comments, and shares encourages spontaneous and impulsive responses rather than deliberate or reflective ones. These dynamics suggest that in digital environments dominated by short-form content and peer interaction, the Organism operates as a rapid affective filter rather than a full mediating channel.

The findings support a conceptual adaptation of the traditional S–O–R. In this modified framework, the mediating function of the Organism is only partial, and the direct pathway from Stimulus to Response becomes the dominant mechanism. Importantly, the low R² value does not invalidate the S–O–R theory; rather, it signifies a structural shift in how internal psychological states contribute to behavioral outcomes in high-speed digital contexts. The Organism thus transitions from being the primary mediating pathway to serving as a secondary amplifier that subtly enhances but does not fundamentally determine user behavior. For future studies, this result highlights the need to refine the S–O–R model for digital tourism and social media research. Researchers should consider incorporating social-hedonic stimuli, such as community engagement, influencer–follower interaction, and social rewards, which better reflect the interactive nature of digital platforms. In addition, integrating new mediating variables such as emotional contagion or social validation could more accurately capture the affective and social psychological mechanisms underlying Generation Z’s engagement with short-form tourism content on platforms like TikTok.

4.3 Key findings in the S–O–R framework and behavior gen-Z

This study adopts the Stimulus–Organism–Response theoretical framework to explore how digital tourism content influences Generation Z’s travel behavior, particularly their intention to visit Bali. The findings reveal that Stimuli (S) including TikTok content, influencer credibility, and Electronic Word of Mouth (eWOM) exert a strong and statistically significant direct effect on the Response (R), which consists of Intention to Visit and Cultural Curiosity. Notably, TikTok content emerged as the most dominant stimulus, underscoring the growing influence of short-form, visually engaging media in shaping destination preferences. This is consistent with previous studies by Joseph et al., 2024, who found that social media content significantly affects young travelers’ perceptions and decisions due to its immediacy and emotional appeal.

Beyond this direct pathway, the study also identifies an indirect route where Stimuli influence the Organism (O) a set of internal psychological states comprising Emotion, Fear of Missing Out (FoMO), and Self-Identification. These organismic responses, in turn, significantly mediate the relationship between stimuli and response, albeit with a weaker effect compared to the direct path. This finding echoes insights from Tian et al. (2022) and Aslam and Luna (2021), who argue that emotional and cognitive engagement with digital content acts as a psychological driver of consumer behavior, particularly among younger demographics who are more prone to personalization and social validation (Tian et al., 2022; Aslam and Luna, 2021).

This reinforces the relevance of the S–O–R model in explaining digital tourism behavior and aligns with the theoretical propositions of Mehrabian and Russell (1974), who first introduced the S–O–R framework to describe emotional mediation in stimulus–response relationships (Chen et al., 2025). The dual-path model confirms that while direct digital exposure; watching a TikTok video or reading a peer review has an immediate effect on travel intention, the formation of internal psychological constructs adds a meaningful layer to how these intentions are shaped. It suggests that Generation Z is not only responsive to digital stimuli but also processes this content in relation to their self-concept, emotional state, and social identity.

Importantly, the patterns identified in this study are consistent with digital tourism trends across the broader ASEAN region. This finding studies from Liu et al. (2023) and Zhao et al. (2022) recent evidence from Vietnam and Thailand demonstrates that visually driven, algorithm-curated short videos strongly shape Gen Z’s destination perceptions and impulsive travel intentions, with Stimulus–Response effects dominating over reflective organismic processing (Liu et al., 2023; Zhao et al., 2022). These studies highlight that emotionally charged cues, influencer-driven narratives, and peer interactions in the comment section serve as rapid triggers of travel interest paralleling the direct S–R pathway observed in the present study. This suggests that Indonesian Gen Z travelers’ responsiveness to TikTok content aligns closely with regional patterns in which short-form media environments promote rapid, affective decision-making.

Comparable dynamics emerge in the broader global context. Research from Han et al. (2022) and Kim (2023) in China and South Korea shows that parasocial interaction, emotional contagion, and FoMO induced by short-form travel videos significantly influence young audiences’ travel intention. Recent evidence from Serrano-Malebrán et al. (2025) in Chile similarly shows that TikTok travel influencers function as strong S–R drivers, where visually appealing, trustworthy, and expert-driven content directly shapes young users’ attitudes and behavioral intentions, further reinforcing the global pattern of stimulus-dominant digital tourism behavior (Serrano-Malebrán et al., 2025). These international insights point to a global trend in which short-form video platforms reduce cognitive elaboration and strengthen emotionally driven responses-explaining the relatively weak mediating effect of Organism in this study. Thus, the findings not only contribute to Indonesian digital tourism scholarship but also align with regional and global evidence of an emergent shift toward experiential, stimulus-dominated travel behavior in Gen Z.

4.4 Theoretical implications

This study reinforces the applicability and validity of the S–O–R model in the context of digital tourist behavior, particularly among Gen Z. It affirms that the influence of digital stimuli extends beyond mere informational exposure and includes psychological internalization, which ultimately drives behavioral responses. These findings are consistent with earlier research by Gao et al. (2022), who demonstrated that emotionally charged media can trigger organismic states such as arousal and identification, significantly shaping consumer intentions. Similarly, Yuksel et al. (2010) and Zhao (2019) showed that the emotional dimension of tourism marketing, such as vivid imagery and storytelling, contributes to stronger behavioral intentions when internalized psychologically (Gao et al., 2022; Zhao, 2019).

However, one notable finding in this study is the greater strength of the direct Stimulus–Response path compared to the mediated path through the Organism, which contrasts with cognitive-heavy models that emphasize internal reflection or evaluation as central to decision-making. This may reflect the reactive and fast-paced nature of Gen Z when engaging with digital content especially on platforms like TikTok where decisions are made rapidly and based on visual or emotional stimuli rather than extended cognitive processing. This aligns with findings by Preisler (2025), who noted that Gen Z tends to rely more on visual content and peer influence for purchase or travel-related decisions (Ilieva, 2023). Furthermore, Self-Identification (SI) emerged as the most influential psychological construct in this model, emphasizing the importance of personal relevance and social alignment in shaping young travelers’ intentions. Social identity and perceived similarity with influencers significantly enhance message acceptance and behavioral alignment among younger users in social media environments.

4.5 Practical implications

This study provides several important implications for digital tourism communication strategies, particularly on platforms like TikTok: first, the findings underscore that TikTok content is the most effective stimulus, suggesting that tourism promotions should focus on creating engaging, emotional, and culturally resonant content tailored to Gen Z’s preferences; second, Influencers still play a significant role, but their effectiveness heavily depends on the perceived credibility among the target audience. Therefore, selecting influencers who exhibit authenticity and relatability is crucial for connecting with Gen Z consumers; third, while eWOM is not as influential as TikTok content, it still contributes to initial perception-building and social validation. Digital strategies should not only focus on professionally produced content but also encourage user-generated content to stimulate eWOM and enhance credibility through peer sharing.

4.6 Limitations and future research

This study has several limitations that should be acknowledged to guide future research directions. First, the respondents were limited to Generation Z individuals who are active users of social media platforms. This sampling focus may restrict the generalizability of the findings to other age groups or demographic segments that may exhibit different digital consumption behaviors. Moreover, the study specifically examined interest in visiting Bali, which may not fully represent the dynamics present in other tourism destinations. Applying the same research model to different cultural or geographical contexts may therefore yield varying outcomes.

Second, the study employed a purely quantitative approach using Partial Least Squares Structural Equation Modeling (PLS-SEM). While this method allows for robust testing of statistical relationships, it does not capture the depth and nuance of individual perceptions, emotions, or motivations that underlie online engagement. Future research is encouraged to adopt a mixed-methods design combining quantitative and qualitative approaches to better understand the “why” behind the weak statistical relationship observed between the Stimulus and Organism constructs. Qualitative methods such as in-depth interviews, focus groups, or digital ethnography could provide richer insights into how users emotionally process tourism content and form behavioral intentions.

Third, the scope of this study was confined to TikTok as the primary social media platform. Considering that digital behaviors vary significantly across platforms, future studies could replicate this model across different short-video environments such as Instagram Reels, YouTube Shorts, or SnackVideo. Comparative analyses among these platforms may reveal how specific content algorithms, user demographics, or engagement mechanisms shape the strength of the S–O–R relationships.

In addition, future research should explore other variables that may serve as stronger predictors of Organism, such as attachment to influencers, parasocial relationships, personal values, or emotional attachment to destination brands. These variables may better represent the affective and cognitive processes underlying users’ reactions to digital tourism content. Incorporating such constructs could also enhance the explanatory power of the S–O–R framework, especially in understanding why internal psychological states (Organism) exert a weaker mediating effect in high-speed digital contexts.

Finally, all participants in this study were adults aged 21–27 who voluntarily participated in an online survey. Written informed consent was obtained directly from each participant before completing the questionnaire. Because this study was non-interventional and only collected data on perceptions and behavioral intentions through anonymous self-report measures, formal ethical clearance was not required under Sahid University’s ethics policy. Nevertheless, all research procedures strictly adhered to basic principles of research ethics, which guarantee participant autonomy, confidentiality, and data protection.

5 Conclusion

This study examined how digital tourism content operationalized through TikTok content quality, influencer credibility, and Electronic Word of Mouth (eWOM) shapes Generation Z’s intention to visit Bali by activating internal psychological mechanisms within the Stimulus–Organism–Response (S–O–R) framework. Using PLS-SEM, the findings demonstrate three key insights. First, digital stimuli exert a strong and direct influence on behavioral responses, with TikTok content emerging as the most dominant predictor of visit intention. Second, stimuli significantly shape internal psychological states, including Emotion, FoMO, and Self-Identification, which partially mediate the relationship between digital cues and visit intention. Although this mediation is weaker than the direct paths, its statistical significance highlights the importance of affective and identity-driven processes in short-video environments. Third, the Response construct reveals that Intention to Visit is more strongly formed than Cultural Curiosity, suggesting that well-crafted short videos can directly translate into concrete behavioral motivation among Gen Z audiences.

Theoretically, the findings reinforce the applicability of the S-O-R model in algorithm-driven social media contexts, offering empirical support that affect-driven, experiential, and socially reinforced mechanisms remain central to digital tourism behavior. This contributes to ongoing scholarly discourse by demonstrating how S–O–R can integrate multiple psychological states. While this study deepens the understanding of Gen Z’s digital tourism psychology, future research should explore AI-generated virtual influencers, immersive metaverse-based cultural experiences, and cross-platform behavioral analytics. These emerging technologies may reshape how cultural curiosity and travel intentions are formed in hyper-digital environments, opening new pathways for theory development and digital tourism practice.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Ethics statement

The studies involving human participants were reviewed and approved by the Research Ethics Committee of the Postgraduate School, Sahid University, Jakarta, Indonesia, and the Faculty of Communication, Dian Nusantara University, Jakarta, Indonesia. The studies were conducted in accordance with local legislation and institutional requirements. Written informed consent for participation in this study was obtained from all participants. No identifiable human images were collected or used in this research.

Author contributions

TW: Conceptualization, Supervision, Validation, Writing – original draft, Writing – review & editing. AP: Investigation, Resources, Software, Validation, Writing – original draft, Writing – review & editing.

Funding

The author(s) declare that no financial support was received for the research and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that no Gen AI was used in the creation of this manuscript.

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Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Abbreviations

S–O–R, Stimulus–Organism–Response; IC, Influencer credibility; QC, TikTok content quality; EW, Electronic Word of Mouth; EM, Emotion; FO, Fear of Missing Out/FoMO; SI, Self-identification; CC, Cultural curiosity; IV, Intention to visit; PLS-SEM, Partial least squares–structural equation modeling; AVE, Average variance extracted; CR, Composite reliability; HTMT, Heterotrait–monotrait ratio; R2, Coefficient of determination.

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