From search engines to social influence: a stimulus–organism–response model of travel influencers on TikTok

In the context of the growing use of social media platforms as search engines, this study examines the role of travel influencers on TikTok as persuasive agents shaping tourism-related attitudes and intentions among young users in Chile. Based on the Stimulus–Organism–Response (S-O-R) framework, it is proposed that the dimensions of the influencer construct (attractiveness, expertise, trustworthiness, authenticity, and inspiration) serve as stimuli that shape users’ attitudes toward the influencer (organism), which in turn influences three behavioral responses: the intention to follow the influencer, the intention to visit promoted destinations, and electronic word of mouth. To this end, the study aims to analyze how perceived characteristics of travel influencers shape users’ attitudes and influence their behavioral intentions. Specifically, it seeks to: (1) analyze how social media users perceive and evaluate travel influencers on TikTok, particularly focusing on how influencer attributes shape user attitudes and behavioral intentions; (2) evaluate the effects of attitudes toward these influencers on behavioral intentions toward them, the promoted destination, and electronic word-of-mouth; and (3) propose digital content strategies for tourism brands, influencers, and agencies based on attributes that effectively generate positive attitudes and intentions. This research employed a cross-sectional quantitative design with a sample of 237 TikTok users aged between 18 and 44 years, analyzed through structural equation modeling (PLS-SEM). The findings indicate that visual attractiveness, content expertise, and trustworthiness are the main predictors of a positive attitude toward influencers, whereas authenticity and inspiration were found to be non-significant. Furthermore, attitudes toward influencers strongly predicted all three behavioral outcomes. This study offers relevant implications for both academia and the tourism industry, highlighting the strategic value of visual, trustworthy, and professional content. Additionally, a multi-group analysis revealed significant generational differences in how attitudes toward influencers translate into behavioral intentions.

1 Introduction

Social media influencer marketing has experienced exponential growth in recent years, profoundly transforming the way consumers access information and make purchasing decisions, particularly in experiential sectors, such as tourism. According to the Digital Global Overview Report (Kemp, 2025), more than 5 billion people use social media worldwide, representing 62.3% of the global population. Among these platforms, TikTok has solidified its position as one of the fastest-growing, surpassing 1.5 billion active users and achieving 1 trillion unique monthly visits (Magnet ABA, 2025). Additionally, Statista (2024b) indicated that 37.9% of users aged between 16 and 64 utilize social media as a source of inspiration for travel planning, turning platforms such as TikTok and Instagram into highly persuasive alternative search engines. In this context, social media influencers (SMIs) assume a prominent role and are perceived as credible, relatable, and emotionally resonant sources capable of shaping attitudes and behavioral intentions regarding destination choices (Popşa, 2024).

Currently, social media is profoundly reshaping travel information search processes, especially among younger users who prioritize platforms such as TikTok and Instagram over traditional search engines because of their ability to offer more personalized, authentic, and visually appealing content (Popşa, 2024; Rahman and Mia, 2025). This phenomenon is partly explained by the prominence of SMIs, whose credibility, perceived expertise, charisma, and emotional connection with their audiences significantly influence every stage of the travel decision-making process from need recognition to post-visit behavior (Babu and Philip, 2025; Chen and Lin, 2024; Han and Chen, 2022; Manthiou et al., 2024). In contrast to traditional search methods based on impersonal algorithms, users perceive social media as offering them more relatable and relevant experiential content (Saini et al., 2023). This shift in search preferences reflects not merely technological change, but also a deeper cultural transformation where peer-shared information or influencer-generated content is deemed more trustworthy and useful for travel planning (Ong et al., 2024; Pop et al., 2022). Despite this trend, a knowledge gap persists regarding how this new influencer-mediated search behavior is structured and what factors truly determine effective influence in specific contexts, such as tourism in developing countries, underscoring the need for systematic research into the impact of influencer marketing on informational habits related to travel and destination choices.

Building on Manthiou et al. (2024), who conceptualized the Travel Influencer Construct (TIC) as a multidimensional set of influencer cues (attractiveness, expertise, trustworthiness, authenticity, and inspiration), we propose to position the TIC as the “stimulus” within an S–O–R model and to test it in TikTok’s ultra-short video environment. TikTok’s algorithm-driven “For You” feed and rapid consumption format may shift the relative salience of these TIC dimensions compared to longer-form or image-based platforms. Prior applications of the S–O–R framework have focused on influencer effects in contexts such as Instagram (Zhang et al., 2021) and live-stream marketing (Matiza and Slabbert, 2024), but the TIC needs to be explored within TikTok’s distinctive short-video ecosystem, given its unique content dynamics and user engagement patterns, thus presenting a theoretical opportunity that the present study addresses.

While our study draws on the theoretical and measurement framework of Manthiou et al. (2024), its contribution lies in the contextual application and empirical contrast of the TIC model within TikTok’s unique media ecosystem and a Latin American youth demographic. Unlike prior studies that validated the TIC in broader or image-based platforms, this research examines how each TIC dimension performs in a hyper-visual, short-form video setting among Chilean Gen Z and Millennial users. In doing so, it tests the cross-platform robustness of the TIC and highlights contextual differences in the salience of influencer attributes. For example, as our findings later reveal, inspiration and authenticity, which were significant in earlier applications, did not exert meaningful effects in this specific environment. These divergences offer practical insights and advance theoretical understanding of how platform-specific dynamics and cultural context shape the persuasive power of influencer attributes.

To ground this theoretical proposal in the empirical context of TikTok, we briefly review the platform’s key usage and content dynamics. TikTok now exceeds 1.5 billion active users and generates over one trillion monthly unique visits, with adults spending an average of 53.8 min per day on the app (Backlinko, 2025). This hyper-visual, algorithm-driven context may amplify or attenuate the relative importance of the five TIC dimensions compared to longer-form or image-based platforms (Du et al., 2022; Liu et al., 2023). By situating the TIC within TikTok’s distinctive short-video ecosystem, the present study fills a critical theoretical gap and offers new insights into the mechanisms of travel influencer persuasion among Millennials and Gen Z in Chile.

This study aims to analyze how perceived characteristics of travel influencers on TikTok shape users’ attitudes and, consequently, influence their behavioral intentions related to tourism. It focuses on the cognitive and affective responses elicited by influencer attributes, such as attractiveness, trustworthiness, and content expertise, and how these internal evaluations impact decisions such as following recommendations, visiting promoted destinations, and sharing content. To achieve this, three specific objectives are proposed: (1) analyze how social media users perceive and evaluate travel influencers on TikTok, particularly focusing on how influencer attributes shape user attitudes and behavioral intentions; (2) evaluate the effects of attitudes toward these influencers on behavioral intentions toward them, the promoted destination, and electronic word-of-mouth; and (3) propose digital content strategies for tourism brands, influencers, and agencies based on attributes that effectively generate positive attitudes and intentions among users. In addition to its primary objectives, the study includes an exploratory comparison between Generation Z and Millennials to assess whether generational differences shape the dynamics between influencer attributes, attitudes, and behavioral responses.

2 Literature review

2.1 Stimulus–organism–response

The stimulus–organism–response (S-O-R) model proposed by Mehrabian and Russell (1974), has been widely adopted to explain how consumers process stimuli in digital environments, including tourism contexts. In this framework, external stimuli (such as visual or narrative content from an influencer) evoke internal responses in the organism (emotions, attitudes, and perceptions), which subsequently lead to behavioral responses, such as the intention to travel or share information online.

Liu et al. (2023) applied the S-O-R model to examine how destination marketing using short videos influences travel intentions. In their study, audiovisual stimuli activated internal mechanisms, such as telepresence, perceived enjoyment, and perceived value, which mediated the relationship between the content and the intention to visit the destination. These results empirically validate the role of internal states in tourists’ behavioral responses. Zhang et al. (2021) similarly utilized the S-O-R model in the context of influencer marketing via live streaming, identifying stimuli such as source attractiveness, content utility, perceived social norms, and virtual enjoyment. These stimuli affect the user’s organism, measured by attitudes toward the influencer and impulsive buying tendencies, ultimately determining offline purchase intentions. Their findings demonstrated that intermediate affective and cognitive mechanisms are crucial for understanding the impact of influencers.

Complementarily, Matiza and Slabbert (2024) employed the S-O-R model to explain how celebrity-generated social media content influences factors such as trust, safety perception, and country image evaluation. These factors, which represent the organism, mediate the effect of stimuli (attributes of the influencer) on travel intentions. Collectively, these studies underscore that the S-O-R model provides a robust explanatory framework for analyzing how influencer-generated digital content influences travel decisions, enabling the sequential mapping of stimulus impacts on internal user states and behavioral responses.

2.2 Travel influencer construct

The Travel Influencer Construct (TIC) proposed by Manthiou et al. (2024) offers a multidimensional and context-sensitive framework that integrates five perceptual dimensions—attractiveness, expertise, trustworthiness, authenticity, and inspiration—to explain how users form attitudes toward tourism content creators. This model addresses conceptual limitations in previous literature, which tended to rely on fragmented constructs such as source credibility or parasocial interaction without fully capturing the experiential and affective nature of tourism marketing on social media (Djafarova and Rushworth, 2017; Lou and Yuan, 2019). Unlike earlier models, the TIC was empirically validated using both qualitative and Bayesian quantitative methods in highly visual and interactive tourism contexts, making it especially relevant for platforms such as TikTok (Manthiou et al., 2024).

Moreover, the TIC incorporates dimensions, such as authenticity and inspiration, that have proven particularly salient in digital tourism environments shaped by emotional engagement and visual storytelling. For example, inspiration operates as an aspirational cue that allows users to mentally project themselves into narrated travel experiences and motivates future behavior (Pop et al., 2022; Saini et al., 2023). Authenticity, in turn, reinforces identification and credibility, especially when influencers convey consistency and alignment with their audiences’ values (Matiza and Slabbert, 2024). While these attributes have been discussed in prior studies, they have seldom been systematically integrated into formal conceptualizations of influencer impact.

Given the growing relevance of short-form, algorithmically curated platforms in shaping travel perceptions, especially among younger users, there is increasing interest in frameworks that reflect the emotional, symbolic, and social dynamics of such environments (Cao et al., 2021; Liu et al., 2023). In this context, the TIC offers a more comprehensive and theoretically coherent approach for understanding influencer effectiveness in the tourism domain.

While this study adopts the TIC framework proposed by Manthiou et al. (2024), its primary contribution lies in applying this model to a distinct sociocultural and platform-specific context. Rather than focusing on scale validation, the study examines the TIC’s conceptual utility within TikTok’s short-form, algorithm-driven video ecosystem and among young Chilean users. This approach enables an exploration of how each dimension of the TIC operates in an environment characterized by high visual intensity, rapid content consumption, and platform-specific engagement logics, thereby contributing to the broader understanding of the model’s adaptability and relevance across digital contexts marked by diverse technological and cultural dynamics. In light of this, each of the five dimensions is discussed below.

2.2.1 Inspiration

Inspiration refers to an influencer’s capacity to evoke desires to explore new destinations, engage in transformative experiences, and imagine aspirational scenarios. According to Manthiou et al. (2024), this dimension is activated when visual and narrative content enable users to project themselves into displayed experiences. Pop et al. (2022) reinforces this idea, indicating that influencers’ ability to generate vivid mental imagery is positively associated with behavioral intentions toward promoted destinations. Additionally, Saini et al. (2023) emphasized that users seek content enabling escape from daily routines, highlighting this emotional function as central to digital influence in tourism. This evidence suggests that inspiration functions as an aspirational stimulus, potentially initiating or reinforcing travel intention.

2.2.2 Authenticity

Authenticity, defined as the perception that the content creator presents themselves genuinely, honestly, and coherently, is crucial for evaluating travel influencers (Manthiou et al., 2024). According to Najar et al. (2024), perceived authenticity strengthens user trust and, significantly predicts intention to follow travel recommendations and influencer credibility. Studies by Matiza and Slabbert (2024) and Popşa (2024) suggest that authenticity fosters greater user identification with the influencer, particularly when there is congruence between the influencer’s and audience’s values, thereby enhancing the effectiveness of persuasive content on visual platforms such as Instagram or TikTok.

2.2.3 Attractiveness

Attractiveness refers to the esthetic and charismatic components of influencers, including attributes such as physical appearance, style, and likability that increase user interest and content engagement (Manthiou et al., 2024). Manthiou et al. (2024), suggest that attractiveness contributes integrally to social media credibility, as physical appeal and communication style foster emotional closeness. Babu and Philip (2025) confirm this association, noting that attributes such as personality, appearance, and style are positively related to international travel decisions, albeit less significantly than trustworthiness or expertise.

2.2.4 Content expertise

Content expertise refers to influencers demonstrated knowledge of aspects related to tourism destinations such as culture, gastronomy, or practical recommendations (Manthiou et al., 2024). This dimension correlates with higher trust and behavioral intentions. Manthiou et al. (2024) proposed that thematic expertise reinforces perceptions of content utility, a finding supported by Najar et al. (2024), who showed that influencer expertise significantly enhances destination trust. Rodriguez-Hidalgo et al. (2023) similarly identified that influencer expertise facilitates cognitive connections between users, enabling informed decisions.

2.2.5 Trustworthiness

Trustworthiness, understood as the perception of influencers’ honesty, ethical behavior, and consistency in recommendations, significantly affects purchase intentions and destination trust (Manthiou et al., 2024). Najar et al. (2024) found that influencer trustworthiness strongly predicts visit intention and destination brand trust. These findings align with those of Babu and Philip (2025), who identified trustworthiness and expertise as attributes with the most significant positive impact on international travel decisions.

2.3 Attitude toward a travel influencer

The attitude toward a travel influencer represents the consumer’s internal response resulting from exposure to stimuli such as the presenter’s attractiveness, the enjoyment derived from the content, and its perceived usefulness (Manthiou et al., 2024). This response manifests in behaviors such as purchase intention (Zhang et al., 2021). This evaluation comprises cognitive components, such as the perceived usefulness of the content, affective elements, such as emotional connection with the influencer, and behavioral aspects, such as the predisposition to follow their suggestions or share their content. Zhang et al. (2021) demonstrate that in the context of live streaming, attitude toward the influencer emerges as a key internal response influenced by source attractiveness, perceived usefulness, and virtual enjoyment, which in turn predicts offline purchase intention. This approach, based on the S-O-R model, posits attitude as the organism between digital environmental stimuli and consumer behavioral responses.

In tourism, Najar et al. (2024) provided empirical evidence that a favorable attitude toward an influencer increases destination trust, visit intention, and electronic word-of-mouth (eWOM). In their study, influencer attributes (such as authenticity, trustworthiness, and expertise) directly predicted users’ attitudes. Additionally, Pop et al. (2022) and Rodriguez-Hidalgo et al. (2023) emphasized that such attitudes are not formed in isolation; rather, they are shaped by perceived congruence between the influencer’s values and those of the user as well as thematic consistency across content. These conditions strengthen user identification with the source, fostering a more stable and positive attitude toward the content. Thus, attitude toward the travel influencer emerges as a central construct in explaining influencer marketing effectiveness, as it reflects the psychological link between the emitted content and the recipient’s decisions in digital tourism environments.

2.4 Behavioral intention regarding the travel influencer

Behavioral intention regarding a travel influencer refers to users’ willingness to act based on the influencer’s recommendations, encompassing behaviors such as seeking additional information, sharing content, or planning a trip (Purwandari et al., 2022). This variable is critical in assessing the actual impact of influencer marketing in the digital tourism context as it allows the estimation of the extent to which content exposure translates into concrete decisions. Multiple studies have shown that the perceived attributes of an influencer significantly influence users’ attitudes, which, in turn, predict behavioral intentions. For example, Purwandari et al. (2022) found that affective engagement generated through interactions with the influencer, along with the perceived informational and emotional value of the content, positively affects the intention to follow travel recommendations. Similarly, Sokolova and Kefi (2020) demonstrated that influencer credibility and parasocial interaction directly affect purchase intention, a finding that can be extrapolated to tourism when specific destinations are promoted via social media. In a similar manner, Pop et al. (2022) highlighted that trust in the influencer, derived from perceived similarity and authenticity, enhances the intention to visit the promoted destinations and share recommendations through eWOM. In this case, behavioral intention arises not solely as a rational response to content, but also as a result of a symbolic relationship connecting the user with both the message and the source.

Theoretically, the S-O-R model offers a robust framework for understanding this phenomenon. Zhang et al. (2021) applied this model and confirmed that influencer characteristics (stimuli), such as attractiveness or content usefulness, generate a positive attitude toward the influencer (organism), which then directly influences purchase intention (response). This framework has been validated in tourism contexts, reinforcing the role of attitude in the relationship between perceived influencer attributes and behavioral intentions regarding recommendations.

2.5 Behavioral intention to visit the recommended destination

Behavioral intention to visit the recommended destination refers to the user’s conscious willingness to visit a given location in the future, influenced by perceptions formed through exposure to digital content, particularly that generated by social media influencers. This variable has been widely validated as a behavioral outcome of influencer marketing in tourism, with a strong predictive value for actual travel decisions (Priyanga and Ashokkumar, 2023; Zhang and Xu, 2023). Several studies show that visit intention is significantly strengthened when information provided by influencers perceived as credible, attractive, or aligned with the recipient’s values (Meng Monroe et al., 2025; Pop et al., 2022). For example, followers have been shown to develop stronger travel intentions when they identify value, background, or attitudinal similarities with the influencer, thereby enhancing the perceived credibility and usefulness of the content (Pop et al., 2022).

In addition, the study by Meng Monroe et al. (2025) shows that congruence between the type of influencer (human or virtual) and the type of destination (natural or cultural) significantly affects visit intention. This effect is explained by differential perceptions of credibility and activation of the self-referencing mechanism, which mediates the relationship between influencer type and willingness to visit the destination. In summary, behavioral intention toward a destination is shaped not only by attributes of the place itself, but also by a complex network of symbolic stimuli, identity congruence, and perceived source credibility. Understanding these factors allows for the optimization of tourism promotion strategies through the strategic use of digital influencers.

2.6 Electronic word-of-mouth regarding the travel influencer

Electronic word-of-mouth (eWOM) has become an essential component of the dissemination of tourism content in digital environments. In the context of influencer marketing, eWOM refers to the voluntary transmission of opinions, experiences, and recommendations generated by users after interacting with the content posted by travel influencers. This form of communication has proven to be highly persuasive, particularly when it originates from sources that are perceived as trustworthy and relatable (Saini et al., 2023). Pop et al. (2022) emphasized that influencers who generate trust tend to foster active participation from their followers, who not only adopt recommendations, but also retransmit them through posts, comments, or interactions on social media. This dynamic transforms the consumer into a “prosumer” (both producer and consumer of content), thereby expanding the reach of tourism campaigns through horizontal social diffusion. Additionally, Rahman and Mia (2025) empirically confirms that perceived source credibility directly influences eWOM effectiveness, as users are more likely to trust recommendations from figures they perceive as authentic, competent, and emotionally connected to their audience. In this sense, the impact of eWOM lies not only in the content itself but also in how the recipient perceives the influencer as a source. Rodriguez-Hidalgo et al. (2023) highlighted that the perceived congruence between the influencer’s values and the user’s interests strengthens the latter’s willingness to share content, creating a cascading effect that amplifies the reach of the original message. Consequently, eWOM emerging from influencers does not merely entail direct recommendations, but also activates social and emotional processes that support the co-creation of tourism content on social media.

3 Hypotheses development

From the perspective of the Stimulus–Organism–Response (S-O-R) model, the stimulus is represented by the perceived attributes of the travel influencer, operationalized through the Travel Influencer Construct (TIC), which comprises five dimensions: inspiration, authenticity, attractiveness, thematic expertise, and trustworthiness. These attributes have been shown to be relevant in explaining the persuasive effect of tourism content creators on user perceptions and decisions (Manthiou et al., 2024). Each of these dimensions influences the formation of a favorable attitude toward the influencer. For instance, inspiration and authenticity have been identified as key drivers of emotional connection with content (Manthiou et al., 2024; Pop et al., 2022), while physical attractiveness and perceived expertise reinforce the recipient’s trust (Najar et al., 2024). Trustworthiness, understood as honesty and consistency, is one of the most relevant factors in source credibility and behavioral intention (Han and Chen, 2022; Najar et al., 2024). The following hypothesis was proposed:

H1: Inspiration has a direct and positive effect on attitude toward travel influencers.

H2: Authenticity of the influencer has a direct and positive effect on attitude toward the travel influencer.

H3: Attractiveness of an influencer has a direct and positive effect on attitude toward the travel influencer.

H4: Content expertise of the influencer has a direct and positive effect on attitude toward the travel influencer.

H5: Trustworthiness of the influencer has a direct and positive effect on attitude toward the travel influencer.

In this model, the “organism” corresponds to the user’s attitude toward the influencer, which is understood as a general evaluation based on affective and cognitive components. This attitude functions as a variable between the perceived attributes of the influencer and users’ expected behaviors. Recent studies have shown that a positive attitude toward the influencer increases the intention to visit the destination, follow recommendations, and share content (Dutta et al., 2021; Najar et al., 2024; Pop et al., 2022). The following hypotheses are proposed:

H6: Attitude toward the travel influencer has a direct and positive effect on the Behavioral intention regarding the Travel Influencer

H7: Attitude toward the travel influencer has a direct and positive effect on the Behavioral intention to visit the recommended destination

H8: Attitude toward the travel influencer has a direct and positive effect on the Electronic Word-of-Mouth regarding the Travel Influencer

In the S-O-R model, the response includes behavioral intentions such as seeking additional information, planning a trip, or sharing content, all of which are enhanced by a favorable attitude toward the source. Evidence suggests that these behaviors are mediated by content credibility and the emotional perception of the influencer (Han and Chen, 2022; Pop et al., 2022; Rahman and Mia, 2025). The proposed model is presented in Figure 1.

Figure 1

Figure 1. Proposed model.

4 Methodology

4.1 Sample and pre-test

This quantitative cross-sectional study analyzed how social media users, particularly TikTok, modify their information-seeking behaviors related to tourism. The target population focused on young Chilean users, primarily Generation Z and Millennials, who represent the most active TikTok users in the country (Statista, 2024a). According to The Social Shepherd (2025), TikTok was the most downloaded app globally in 2024, with 773 million downloads. Additionally, Backlinko (2025) reported that 55% of the platform’s weekly active users were aged between 18 and 34, and adults spent, on average, 53.8 min daily on the app. However, regional data suggest much higher engagement levels: Chile ranks fourth worldwide in average monthly TikTok usage, with users spending approximately 45 h and 30 min per month, or about 1.5 h per day, on the platform (Exploding Topics, 2025). This aligns with the usage profile of our sample, in which over 80% of respondents reported using TikTok for more than 1 h per day, and reinforces the study’s focus on intensively engaged users who are more likely to be exposed to and influenced by travel content on the platform.

The sample was selected using non-probabilistic convenience sampling, due to accessibility and alignment with the objectives of the study. Prior to the face-to-face data collection conducted by professional interviewers between August and November 2024, a pre-test was administered to 30 participants. A total of 237 valid responses were obtained, of which 66.2% corresponded to Generation Z and 33.8% to Generation Y. Regarding gender, 54.9% were identified as female, 44.3% as male, and 0.8% as other. The age distribution was concentrated within the 18–27 years age range (54.8% of the total), with an average age of 27 years. Geographically, 41.4% resided in the northern region, 28.7% in the central region, and 29.9% in the southern region of the country. In relation to TikTok usage, 30.4% indicated using the platform for 2 h per day, while 57.4% reported using it between one and 3 h daily. Regarding tourism mobility, 31.2% reported traveling for leisure once per year, followed by 26.6% who traveled less than once per year and 22.4% who traveled twice annually. The demographic data are summarized in Table 1.

Table 1

Table 1. Demographic characteristics of the sample.

4.2 Measurement scales

The measurement instrument consisted of a structured, self-administered questionnaire designed to assess the factors influencing the use of TikTok as a search engine for planning tourism-related travel. The scales employed were adapted from validated empirical literature and semantically adjusted to the Chilean context, with a specific focus on Generation Z and Generation Y.

The Travel Influencer Construct (TIC) was operationalized as a second-order variable composed of five dimensions: inspiration, authenticity, attractiveness, content expertise, and trustworthiness. These dimensions were measured using 17 items, each evaluated on a seven-point Likert scale (1 = “strongly disagree”; 7 = “strongly agree”), based on the model developed and validated by Manthiou et al. (2024). Sample items included statements such as: “Travel influencers inspire me to travel,” “Travel influencers are visually appealing,” “Travel influencers know what they are talking about,” and “I trust travel influencers.”

User behavioral intentions were incorporated into the model as dependent variables, following the framework proposed by Manthiou et al. (2024), who identified three key responses: (1) intention to follow the influencer’s recommendations, (2) intention to visit the promoted destination, and (3) intention to share content through social media. These variables were measured using seven-point Likert scales. Before the final implementation, the questionnaire was reviewed by experts in digital marketing and tourism to ensure content validity and contextual appropriateness. Subsequently, a pre-test was conducted with 30 participants to verify the semantic clarity, internal consistency, and overall functionality of the instrument.

4.3 Statistical tools

Data analysis was conducted using partial least squares structural equation modeling (PLS-SEM), a variance-based technique chosen for its flexibility and suitability in estimating complex models involving multiple latent constructs and observed variables. This methodology is particularly appropriate for explanatory and predictive research, where the modeling of composite relationships and assessment of explained variance are prioritized (Henseler, 2018; Sarstedt et al., 2017). Unlike covariance-based approaches, PLS-SEM allows for analyses with smaller sample sizes, non-normal data distributions, and both formative and reflective model structures (Henseler et al., 2016). Its application has been widely validated in studies on marketing, tourism, and consumer behavior.

Following methodological recommendations, the analysis was conducted in two stages: first, the evaluation of the measurement model, focusing on reliability, convergent validity, and discriminant validity, and second, the evaluation of the structural model, which examined path coefficients and the coefficient of determination (R²; Gudergan et al., 2008; Henseler et al., 2016). This analytical strategy enables an empirical assessment of the measurement quality and the robustness of the proposed theoretical model. The analysis was performed using the SmartPLS4 software (Ringle et al., 2022).

To examine potential differences between generational cohorts, a multi-group analysis (PLS-MGA) was conducted, comparing Generation Z (n = 157) and Generation Y (n = 80). This analysis followed the non-parametric procedure proposed by Henseler et al. (2016) and used 5,000 bootstrap resamples to test for significant differences in path coefficients across groups. Prior to conducting the multi-group comparison, measurement invariance was evaluated using the Measurement Invariance of Composite Models (MICOM) procedure, confirming configural and compositional invariance. The MGA results allowed us to assess whether the structural relationships varied significantly between generations, offering additional insight into audience heterogeneity.

5 Results

5.1 Measurement model evaluation

Measurement models were evaluated to verify the reliability and validity of the model’s latent constructs. Regarding internal reliability, all constructs exhibited satisfactory values for Cronbach’s alpha (CA), composite reliability (Rho_C), and Dijkstra–Henseler’s reliability (Rho_A), exceeding the recommended threshold of 0.70 established in the literature (J. F. Hair et al., 2022). In addition, the individual item loadings were above 0.70, indicating adequate internal consistency. Convergent validity was confirmed through Average Variance Extracted (AVE), with all values exceeding the minimum recommended threshold of 0.50 (Fornell and Larcker, 1981). This indicates that the items explained a substantial proportion of the variance in their respective constructs. Table 2 presents the results.

Table 2

Table 2. Reliability and validity of constructs.

5.2 Structural model evaluation

The structural model was assessed through the analysis of path coefficients, coefficients of determination (R²), and model fit index SRMR. SRMR yielded a value of 0.04, which is below the threshold of 0.08, indicating an acceptable model fit (Henseler et al., 2016; Table 3).

Table 3

Table 3. Discriminant validity—Fornell-Larcker criterion.

The model explained 75.1% of the variance in attitude toward travel influencers (R² = 0.751). Among the dimensions of the TIC construct, attractiveness had the strongest impact on attitude (β = 0.373, p < 0.001), followed by content expertise (β = 0.282, p < 0.001), and trustworthiness (β = 0.254, p < 0.001). Authenticity (β = −0.06, p = 0.364) and inspiration (β = 0.101, p = 0.094) were not significant in this context.

Attitude toward influencers showed a significant direct impact on all three dependent variables. It explained 70.4% of behavioral intention toward influencers (R² = 0.704; β = 0.839, p < 0.001), 63.8% of behavioral intention toward the destination (R² = 0.638; β = 0.799, p < 0.001), and 39.9% of electronic word-of-mouth (eWOM; R² = 0.399; β = 0.632, p < 0.001). These results underscore the importance of producing attractive, trustworthy, and professional content to enhance the influence of content creators on tourism-related decisions. The results are shown in Figure 2.

Figure 2

Figure 2. Structural model results.

The results of the hypothesis testing (Table 4) allowed for the evaluation of the structural relationships proposed in the model. Of the eight formulated hypotheses, six were statistically significant (p < 0.001), while two did not meet the required threshold (p > 0.05). First, H1, which posited a positive effect of the inspiration dimension on attitude toward travel influencers, was not supported (β = 0.101; p = 0.094). This suggests that, in this context, influencers’ capacity to evoke travel desires does not constitute a decisive factor in users’ attitudinal evaluations. Similarly, H2 was rejected, as influencer authenticity did not have a significant impact on attitude (β = −0.060; p = 0.364), contradicting prior literature and highlighting a potential loss of centrality for this attribute within certain digital environments. Conversely, H3 was confirmed, establishing influencer attractiveness as exerting the strongest effect on attitude (β = 0.373; p < 0.001), followed by content expertise (H4, β = 0.282; p < 0.001) and trustworthiness (H5, β = 0.254; p < 0.001), all of which demonstrated positive and significant effects. These three dimensions of the TIC construct jointly explained 75.1% of the variance in attitude toward influencers (R² = 0.751), evidencing their strong explanatory power.

Table 4

Table 4. Results.

Regarding behavioral outcomes, attitude toward influencers was positively associated with behavioral intention toward the influencers themselves (H6, β = 0.839; R² = 0.704; p < 0.001), intention to visit promoted destinations (H7, β = 0.799; R² = 0.638; p < 0.001), and willingness to share content via electronic word-of-mouth (H8, β = 0.632; R² = 0.399; p < 0.001). Collectively, these findings underscore the relevance of producing visually attractive, professionally crafted, and trustworthy content to enhance the influence of content creators on users’ travel decisions.

5.3 Multigroup results

Measurement invariance was assessed using the Measurement Invariance of Composite Models (MICOM) procedure, as described by Hair et al. (2017). In Step 1 (configural invariance), all constructs shared identical model specifications, indicators, and estimation settings across generational groups. In Step 2 (compositional invariance), all constructs showed non-significant permutation p-values (p > 0.05), confirming full compositional invariance. In Step 3 (equality of means and variances), most constructs demonstrated invariance; however, Authenticity and Electronic Word-of-Mouth (eWOM) presented significant differences (p < 0.05), indicating partial measurement invariance. The establishment of partial measurement invariance (i.e., configural and compositional invariance) is sufficient to proceed with multi-group comparisons of path coefficients using PLS-MGA (Hair et al., 2017). Therefore, the multi-group analysis was conducted, interpreting findings related to Authenticity and eWOM with caution.

To examine potential generational differences in the structural relationships of the model, a multi-group analysis (PLS-MGA) was conducted comparing participants from Generation Z (n = 157) and Generation Y (n = 80). The analysis aimed to test whether the path coefficients between constructs differed significantly across these two groups.

The results, presented in Table 5, indicate that no statistically significant differences were observed in the relationships between the five dimensions of the Travel Influencer Construct (TIC), inspiration, authenticity, attractiveness, content expertise, and trustworthiness, and attitude toward travel influencers (H1 to H5). This suggests that both generations evaluate the influencer attributes in a similar manner when forming their attitudes.

Table 5

Table 5. Multigroup results.

However, significant generational differences emerged in the paths from attitude toward travel influencers to the three behavioral outcome variables. Specifically, the path from attitude to behavioral intention regarding the influencer (H6) was significantly stronger for Generation Y (β = 0.929) than for Generation Z (β = 0.751), with a PLS-MGA p-value of 0.000. Likewise, the effect of attitude on intention to visit the promoted destination (H7) was higher among Generation Y participants (β = 0.894) compared to Generation Z (β = 0.703), with a p-value of 0.001. A similar pattern was observed in the path from attitude to electronic word-of-mouth (eWOM; H8), where Generation Y exhibited a stronger effect (β = 0.760) than Generation Z (β = 0.517), with a p-value of 0.003. These findings suggest that although both generations rely on similar criteria when forming attitudes toward travel influencers, the influence of those attitudes on behavioral intentions is significantly stronger among Millennials than among Gen Z participants.

6 Discussion

The results obtained provide deeper insights into how the perceived characteristics of TikTok travel influencers (stimulus) influence user attitudes (organism) and consequently their behavioral intentions (response), consistent with the Stimulus–Organism–Response (S–O–R) model (Mehrabian and Russell, 1974). The study focuses on the attitudinal and perceptual responses elicited by influencer attributes, rather than on direct interaction behaviors, offering a cognitive-affective understanding of how users process and respond to travel-related content. The stimulus was operationalized through the Travel Influencer Construct (TIC), comprising five dimensions: inspiration, authenticity, attractiveness, content expertise, and trustworthiness. The analysis revealed that three of these dimensions significantly influenced attitudes toward influencers: visual attractiveness, content expertise, and trustworthiness. Specifically, attractiveness had the strongest influence (β = 0.373, p < 0.001), followed by content expertise (β = 0.282, p < 0.001), and trustworthiness (β = 0.254, p < 0.001). In contrast, neither inspiration (β = 0.101, p = 0.094) nor authenticity (β = −0.060, p = 0.364) demonstrated statistically significant effects.

While this study builds on the TIC framework proposed by Manthiou et al. (2024), its analytical focus differs in scope and intent. Rather than revalidating the construct, the study examines how its five dimensions operate within TikTok’s short-form video environment and among Chilean Gen Z and Millennial users. This contributes to the broader discussion on how influencer-related constructs behave across cultural contexts and platform architectures. By applying the TIC in a new setting, this research highlights its conceptual utility while encouraging future studies to explore the influence of media format, audience characteristics, and content dynamics in shaping the effectiveness of specific influencer attributes.

These findings are consistent with those reported by Ao et al. (2023) who identified that influencers’ visual attractiveness, measured through esthetic design, content quality, and charisma, directly affects attitudes toward promoted content, especially in visually driven platforms such as TikTok. In a similar manner, Chen and Lin (2024) argued that content expertise enhances perceptions of influencer usefulness and professionalism, facilitating acceptance of their recommendations. Trustworthiness has also been highlighted as a key component of source credibility (Rahman and Mia, 2025), which explains its positive influence on user attitudes. Despite their significance in previous studies (Pop et al., 2022), the limited impact of authenticity and inspiration might be attributed to TikTok’s hyper-visual environment, where esthetic appeal and storytelling skills appear to be more decisive in shaping attitudes. This interpretation is supported by recent studies that emphasize the contextual variability in how users respond to influencer attributes across different platforms. For instance, Du et al. (2022) and Liu et al. (2023) show that short-form video environments, such as TikTok or Douyin, foster fragmented attention, favoring quick visual gratification over sustained engagement with narrative authenticity or aspirational content. Even Manthiou et al. (2024) acknowledge that the relative salience of TIC dimensions may vary depending on the platform’s architecture and content delivery format. Our findings reinforce this view by empirically demonstrating that, under the high visual saturation and algorithmic immediacy of TikTok, dimensions such as inspiration and authenticity lose explanatory strength in predicting user attitudes. This suggests that the TIC, although conceptually robust, may not exert uniform effects across all digital ecosystems. The present study contributes by validating the model in a new sociocultural context, but also by identifying potential platform-contingent boundaries to its effectiveness.

Regarding the organism component, attitude toward travel influencers explained a significant proportion of the variance in the three dependent variables analyzed: behavioral intention toward the influencer (R² = 0.704), intention to visit the destination (R² = 0.638), and electronic word-of-mouth (eWOM; R² = 0.399). This confirms the role of attitude in the influence process, as highlighted by Najar et al. (2024). Indeed, when users develop a positive evaluation of influencers, they are more likely to follow their recommendations, plan trips to promoted destinations, and share their content on social media. This comprehensive effect aligns with the S–O–R model, where attitude functions as an affective and cognitive response between perceived stimuli and observable behavior (Matiza and Slabbert, 2024).

To further explore potential audience heterogeneity, a multi-group analysis was conducted comparing Millennials (Generation Y) and Generation Z. While both groups evaluated influencer attributes similarly when forming attitudes, significant differences emerged in the behavioral pathways. Specifically, the effects of attitude toward the influencer on behavioral intentions, whether to follow recommendations, visit promoted destinations or share content via eWOM, were significantly stronger among Millennials. These results suggest that although Generation Z and Millennials construct comparable attitudinal responses based on perceived influencer characteristics, Millennials may be more behaviorally responsive to those attitudes in tourism contexts.

This finding is consistent with prior studies indicating that Millennials are more likely to engage with influencer content through peripheral processing, relying on cues such as trustworthiness and visual appeal, whereas Generation Z tends to adopt a more central processing route, evaluating content critically and placing higher value on authenticity and message quality (Ong et al., 2024; Popşa, 2024). Ong et al. (2024) specifically found that Millennials’ behavioral responses in tourism marketing were more influenced by emotional identification and social comparison, while Gen Z participants demonstrated more deliberate and cognitively filtered responses to similar content. These generational tendencies may help explain why, in the current study, the attitudinal evaluations were statistically similar, but their translation into behavioral intention differed significantly across groups.

Finally, the results have clear practical implications for brands, tourism destinations, and advertising agencies. Given that attractiveness, content expertise, and trustworthiness have emerged as the main predictors of attitude, collaborating with influencers proficient in digital esthetics, possessing thematic tourism expertise, and projecting honesty and professionalism is recommended. As suggested by Babu and Philip (2025), this combination of attributes not only facilitates immediate engagement, but also supports sustained marketing strategies. In contexts of high content saturation, such as TikTok, prioritizing these attributes could differentiate casual viewership from genuine behavioral intent.

From an academic perspective, this study contributes to consolidating the S–O–R model as a useful theoretical framework for understanding influencer marketing effects in digital tourism contexts. Unlike traditional approaches focused primarily on destination image, this research empirically validates that attitude toward the message source, in this case, the influencer, is a critical link between perceived stimuli and behavioral intentions. This finding reinforces Matiza and Slabbert (2024) proposal, emphasizing the role of affective and cognitive states in tourism decision-making mediated by experiential content. Furthermore, this study contributes to the contextual application of the TIC construct as a second-order variable, providing insights into how its structure operates within TikTok’s short-form video environment and among Chilean Gen Z and Millennial users, as initially proposed by Manthiou et al. (2024). These contributions open avenues for further research exploring interactions between influencer attributes and contextual variables, such as platform type, content format, and characteristics of promoted destinations.

Beyond the validation of the S–O–R model, this study contributes to advancing theoretical understanding of how influencers exert persuasive power in algorithmically mediated digital environments. The findings suggest that influencer attributes such as visual attractiveness, content expertise, and trustworthiness do not only function as static perceptual traits, but also act as persuasive cues that shape message reception and behavioral compliance. This reinforces source credibility theory, which posits that communicators perceived as both competent and trustworthy are more persuasive (Djafarova and Rushworth, 2017). In this sense, the influencers studied here operate as persuasive agents whose power lies in how their traits are cognitively processed under specific platform dynamics.

Conversely, the non-significant effects of inspiration and authenticity, despite their emphasis in prior literature (Pop et al., 2022; Saini et al., 2023), reveal a boundary condition for their persuasive impact. This limitation may be attributed to TikTok’s short-form, hyper-visual format, which favors esthetic immediacy over symbolic resonance or narrative depth (Du et al., 2022; Liu et al., 2023). The results support emerging perspectives that influencer persuasion is not solely determined by the communicator’s attributes, but also by platform affordances and user attention patterns.

Furthermore, the multigroup analysis provides additional theoretical nuance by suggesting that persuasion dynamics vary across generational cohorts. Millennials appeared more behaviorally responsive to influencer content than Gen Z, even when attitudes were comparable. This aligns with the elaboration likelihood model (Han and Chen, 2022; Najar et al., 2024; Ong et al., 2024), which suggests that peripheral cues such as appearance or trust are more influential when audiences engage in low elaboration, while Gen Z users may require deeper message relevance or authenticity to be persuaded. These insights contribute to a more contextualized and dynamic understanding of how persuasion unfolds in social media tourism settings.

7 Conclusion

This study empirically demonstrated how the perceived characteristics of travel influencers on TikTok influence users’ attitudes and, subsequently, their behavioral intentions toward promoted destinations and the dissemination of content through electronic word-of-mouth (eWOM). Applying the Stimulus-Organism-Response (S-O-R) model (Mehrabian and Russell, 1974), it was confirmed that the three dimensions of the TIC construct (attractiveness, content expertise, and trustworthiness) significantly explain attitudes toward influencers, highlighting the pivotal role of visual appeal and professional content quality in shaping positive attitudes. Attitude played a central explanatory role in the model, influencing the intention to follow recommendations, visit promoted destinations, and share tourism-related content, reinforcing the relevance of influencers as key actors in travel decision-making processes.

Nevertheless, these findings should be interpreted with consideration of at least three limitations. First, the cross-sectional design of the study prevents the establishment of robust causal relationships among the analyzed variables, restricting temporal inferences about the effects of influencer content. Second, the exclusive focus on TikTok as the analyzed platform may limit the generalizability of the results to other social networks with differing dynamics, such as Instagram, YouTube, and Facebook. Third, the sample was selected using non-probabilistic convenience sampling, which may introduce selection biases and limit the representativeness of the findings concerning the broader population of social media users interested in travel. Additionally, since the sample consisted predominantly of high-frequency TikTok users, consistent with national usage patterns in Chile, the findings should be interpreted with caution regarding their generalizability to less active users. This reflects the behaviors of the population most exposed to influencer content, but future studies could investigate whether usage intensity moderates the observed relationships.

Based on these limitations, several avenues for future research were proposed. First, longitudinal or experimental studies are recommended to identify temporal changes and establish causal effects between influencer attributes and user behavior. Second, expanding the analysis to other social platforms would be pertinent to assessing whether the observed effects are specific to TikTok or replicable across different digital environments. Third, future studies could explore the moderating roles of contextual variables, such as the type of promoted destination, users’ familiarity with the influencer, or personal travel motivations. Additionally, investigating the influence of micro-influencers or user-generated content compared to macro-influencers would be valuable for evaluating differences in perceptions, credibility, and persuasive impact. Moreover, future research could examine daily TikTok usage as a control or moderating variable to assess whether engagement intensity influences how users process and respond to influencer attributes and content.

In summary, this study provides a theoretical contribution by validating the TIC construct and reinforcing the utility of the S-O-R model within digital tourism marketing environments. Simultaneously, it offers relevant practical insights for designing more effective influencer-based communication strategies, emphasizing the importance of visual, narrative, and ethical attributes in creating persuasive content that enhances travel experience and decision-making.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by Universidad Católica del Norte. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

JS-M: Visualization, Resources, Project administration, Writing – original draft, Formal analysis, Funding acquisition, Methodology, Data curation, Validation, Investigation, Supervision, Conceptualization, Writing – review & editing, Software. FC-N: Writing – review & editing, Formal analysis, Writing – original draft, Methodology, Conceptualization. CV-S: Validation, Formal analysis, Conceptualization, Writing – original draft, Writing – review & editing. DV-A: Formal analysis, Writing – original draft, Writing – review & editing, Conceptualization. FZ-C: Project administration, Validation, Formal analysis, Methodology, Data curation, Supervision, Visualization, Writing – review & editing, Conceptualization, Software, Writing – original draft, Investigation. DA-G: Validation, Writing – review & editing, Project administration, Formal analysis, Supervision, Methodology, Data curation, Visualization, Software, Conceptualization, Investigation, Writing – original draft.

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 author(s) declare that Gen AI was used in the creation of this manuscript. This manuscript was conceptualized, written, and revised entirely by the authors. No generative AI tools were used for literature synthesis, data analysis, or drafting of core content. Language editing tools (e.g., Grammarly and ChatGPT) were employed solely to improve clarity, fluency, and grammar in selected passages, always under human supervision. All intellectual contributions, analytical interpretations, and final decisions reflect the authors' original work and academic responsibility.

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