Research Article

Factors Affecting Tourists’ Destination Selection Behavior: The Moderating Role of Travel Video Experience

Phuong Nguyen
Van Lang University, Ho Chi Minh City, Vietnam
* Corresponding author
Thao Thi Nguyen
Van Lang University, Ho Chi Minh City, Vietnam
Hieu Minh Nguyen
Van Lang University, Ho Chi Minh City, Vietnam
DOI icon 10.24018/ejbmr.2025.10.4.2764

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Submitted 2025-06-25
Published 2025-08-11

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Table of Contents

Article Main Content

This study investigates the factors influencing tourists’ destination selection behavior, with a focus on the moderating role of travel video experience. Grounded in the theory of planned behavior (TPB) and cultivation theory, the research examines how attitudes, subjective norms (SN), and perceived behavioral control (PBC) shape travel intentions, which in turn affect destination selection behavior. Additionally, the study explores how the frequency of travel video consumption moderates the relationship between travel intentions and destination selection behavior. Data were collected from 413 foreign tourists in Vietnam who had watched travel videos about the country prior to their visit. Using partial least squares analysis, the findings reveal that attitudes, SN, and PBC significantly influence travel intentions, which subsequently impact destination selection behavior. Notably, travel videos experience strengthens the link between intentions and behavior, highlighting their role in authenticating destination images and reducing perceived risks. The study provide practical implication that contributes to the Vietnamese tourism industry.

Keywords: destination selection behavior theory of planned behavior travel video

Introduction

The rise of mobile technology and the growing popularity of video-sharing platforms have made online video content the most widely consumed and accessible medium (Ma & Gu, 2022). Research indicates that Instagram videos generate twice the engagement of static images (Aslam, 2023), and 65% of travelers use video content when planning trips (Think With Google, 2016). Moreover, 59% of travelers report that YouTube videos influence their travel decisions (Drift, 2024). These videos not only enhance destination appeal but also promote surrounding services, supporting local economies (Arora & Lata, 2020). For example, a viral TikTok video featuring a performer in traditional attire attracted over 230 million views and significantly boosted tourism in Xi’an Datang Yongming City (Duet al., 2022). Video content has therefore emerged as a valuable tool for tourism marketing, benefiting tourism boards, businesses, and digital creators alike (Silabanet al., 2022).

Despite the global trend, research on the role and impact of tourism videos remains limited, particularly in Vietnam, where tourism is a national priority (Danget al., 2025). While the theory of planned behavior (TPB) has been widely used in tourism research (Ulker-Demirel & Ciftci, 2020; Nguyenet al., 2023), most studies focus either on travel intention or behavior separately, without exploring the transition between the two (Yuzhanin & Fisher, 2016). This has limited the explanatory power of TPB in understanding how travelers move from intention to action.

Ajzen (1991) and Song and Witt (2012) note that travel intentions often do not result in actual travel due to intervening barriers, including financial constraints, time, or unforeseen circumstances. Tourism, unlike other consumer behaviors, requires physical movement to the service location, creating a time gap that invites additional influences. Moreover, tourism services are intangible and cannot be evaluated before consumption, increasing the perceived risk (Jalilvand & Samiei, 2012). TPB alone does not account for factors such as authenticity and risk perception that can affect this decision-making gap.

Travel videos, however, offer an authentic and visual preview of destinations, helping travelers assess risks and make informed decisions (Lamet al., 2020). As such, they may not only shape travel intentions but also facilitate the progression from intention to behavior, warranting further investigation into their role within the TPB framework and their impact on tourism decision-making processes.

Therefore, to address the above gaps, this study extends the TPB by adding a factor related to the frequency of using travel videos. At the same time, based on the cultivation theory (CT) introduced by Gerbner (1966), this study argues that the use of travel videos can moderate the relationship between tourists’ intentions and behaviors. The addition of the moderating role of experiencing travel videos not only provides a strong theoretical basis in demonstrating the ability to promote tourists’ intentions to behavior but also responds to the call of previous studies for additional empirical studies on the process of converting intentions into behavior. In addition, this addition also highlights the role and benefits of travel videos in tourists’ travel decision-making process, providing a basis for tourism practitioners to consider choosing them as a potential marketing tool. Even tourism practitioners can refer to the research results to consider solutions to develop effective marketing strategies.

Literature Review

Studies across multiple disciplines have shown that an individual’s attitude—their general positive or negative assessment of performing a particular behavior—plays a key role in shaping their intention to act (Chenget al., 2006). In TPB, attitudes is referred to an individual’s positive or negative evaluation of performing a particular action (Ajzen, 1991). When deciding whether to engage in a behavior, people tend to weigh the potential advantages and disadvantages associated with it (Ajzen, 1991; Chenget al., 2006). If the perceived outcomes are positive, they are more inclined to proceed with the action. Conversely, if the anticipated results are unfavorable, they are less likely to follow through. Essentially, one’s attitude toward a behavior reflects their belief that engaging in it will lead to a beneficial outcome, which in turn reinforces their intention to perform that behavior (Ajzen, 1991). Based on these arguments, the authors propose hypothesis H1:

• H1: Attitude positive influence on travel intention.

SN reflects one’s perception of social pressure from significant others regarding the behavior (Ajzen, 1991). Research has extensively demonstrated that SN significantly influence behavioral intention, particularly in contexts where the behavior offers clear and advantageous outcomes for consumers (Taylor & Todd, 1995). According to Hunget al. (2003), peer pressure and broader social influences shape these norms. The SN impact users’ decisions in various online activities, including tourism selection (Al Ziadat, 2015), adopting blogs (Hsu & Lin, 2008), and utilizing advanced mobile services (López-Nicoláset al., 2008). Additionally, Liet al. (2008) found that SN play a crucial role in fostering trust in organizational information systems. Similarly, Zhou (2011) observed that these norms strongly influence users’ willingness to participate in online communities. Based on these arguments, the authors propose hypothesis H2:

• H2: SN positive influence on travel intention.

PBC refers to an individual’s perceived ability to perform a behavior based on available resources, time, and opportunities (Ajzen, 1991). It reflects one’s capacity to manage factors that support or hinder behavior in specific contexts (Verma & Chandra, 2018). PBC is strongest when individuals have easy access to necessary resources (Abbasiet al., 2021). In tourism, PBC influences travelers’ perceptions of their ability to visit a destination and their confidence in doing so. Studies show PBC significantly affects travel intentions (Martinet al., 2011), halal food purchases (Shah Alam & Mohamed Sayuti, 2011), soft drink consumption (Kassemet al., 2003), and technology adoption (Mathieson, 1991), highlighting its central role in shaping behavior. Based on these arguments, the authors propose hypothesis H3:

• H3: PBC positive influence on travel intention.

Ajzen and Fishbein (1977) identify behavioral intention as the strongest predictor of actual behavior. Ajzen (1985) emphasizes that intentions lead to actions when individuals have the opportunity to act. Stronger intentions significantly increase the likelihood of performing a behavior (Mafabiet al., 2017). In tourism, this relationship is well-supported. Hasanet al. (2023) found that tourists’ perceptions influence how marketing efforts translate into actual travel. Naziret al. (2021) showed that destination exposure through media fosters positive attitudes, increasing visit likelihood. Al Ziadat (2015) reported that stronger intentions to revisit Jordan led to higher visit attempts. Similarly, Ali (2025) found that tourists visit Pakistan primarily because of strong intentions to do so. Based on these arguments, the authors propose hypothesis H4:

• H4: Travel intention positive influence on destination selection behavior.

Behavioral intention has been widely acknowledged as a key factor that influences the connection between behavior and PBC (Ajzen, 1991). When individuals believe they have control over a behavior, they are more likely to form strong intentions and persist in performing it (Ajzen, 2002). Thus, PBC influences behavior indirectly through intention. In tourism, Hsu and Huang (2010) found that access to travel resources strengthens travel intentions and motivates behavior. Sentosa and Mat (2012) also noted that perceptions of destination accessibility enhance visit intentions, leading to actual travel. Recently, Hooet al. (2024) confirmed that in hotel selection, intention mediates the relationship between PBC and behavior, reinforcing the importance of intention as a bridge between perceived control and action. Based on these arguments, the authors propose hypothesis H5:

• H5: Travel intention mediates the relationship between PBC and destination selection behavior.

As a social media variant, travel videos enable users to create and share short, user-generated travel narratives. These videos have become vital tools for travel planning, offering authentic visual experiences that support informed decision-making (Liaoet al., 2020). Tourists increasingly rely on such content to guide their choices (Huertaset al., 2017), and social media platforms provide valuable reference points that enhance the quality of these decisions (Adeloyeet al., 2022). To explain how videos influence destination choices, this study applies CT. CT explores how repeated exposure to mass media messages—originally television—shapes viewers’ perceptions and beliefs (Gerbner, 1966). In the social media era, the more time individuals spend engaging with content, the greater its influence on their decision-making (Morgan & Shanahan, 2010). Research shows that repeated exposure to social media content can reinforce brand recognition, reduce uncertainty, and increase purchase likelihood (Luet al., 2023). Similarly, consumers are more likely to act when product-related content appears consistently on their feeds (Caoet al., 2021).

In tourism, social media presence is essential for shaping destination image (Tiagoet al., 2019). Videos, in particular, effectively capture attention and reduce perceived risks by authenticating the travel experience (Lamet al., 2020). Tourists with travel intentions may hesitate due to potential risks (Shinet al., 2022), but repeated exposure to travel videos can mitigate these fears and guide them toward action. Thus, video content may bridge the gap between intention and actual travel behavior. Based on these arguments, the authors propose hypothesis H6:

• H6: The link between travel intention and destination selection behavior is moderated by travel video experience, such that the relationship is stronger when tourists experience more travel videos.

The applied proposed model is visually presented in Fig. 1.

Fig. 1. Proposed theoretical model.

Methodology

To experiment, this study determined the measurements for the research variables. The measurement model was measured using a Likert-7 scale (1-strongly disagree, 7-strongly agree). Specifically, the scales of attitude (six items), SN (three items), PBC (five items), and travel intention (four items) were inherited and adjusted from the study of Lam and Hsu (2004). Next is the travel videos experience, which has seven observed variables and is inherited and adjusted from the study of Zhanget al. (2024). Finally, destination selection behavior is inherited and adjusted from the study of Bui (2024) with four observed variables.

This study surveyed foreigners who were traveling in Vietnam and had watched travel videos about Vietnam before coming to Vietnam. The study used a convenience sampling method. However, to ensure that participants had watched travel videos about Vietnam before coming to Vietnam, the authors added some screening questions, including: (1) Have you ever watched travel videos about Vietnam? (2) Where were the videos posted? (3) Have you visited specific destinations mentioned in travel videos about Vietnam? (4) Which destinations were they?

This study conducted a face-to-face and online survey for three months, from March 2025 to June 2025. After three months, 438 responses were collected, of which 413 were valid. Descriptive analysis of the 413 survey results showed that the proportion of female respondents was higher than that of male respondents (54.19% vs. 46.91%). In addition, respondents aged 25–35 years old were the largest group (45.76%). The majority of respondents were single (62.41%).

Results

To assess the measurement model, this research followed the methodology outlined by Hairet al. (2019). The analysis began by examining the scale’s reliability using Cronbach’s alpha (α), composite reliability (CR), and outer loadings. These indicators reflect the internal consistency of the measurement items, with acceptable thresholds exceeding 0.7 (Hairet al., 2023). As presented in Table I, all items demonstrated outer loadings above 0.7, while Cronbach’s α, CR, and average variance extracted (AVE) for each construct also surpassed this benchmark. Based on these findings, the measurement model can be considered reliable.

Variables Outer loadings Cronbach’s α Composite reliability AVE
Attitude 0.738~0.902 0.892 0.918 0.651
SN 0.798~0.926 0.836 0.902 0.754
PBC 0.863~0.890 0.927 0.945 0.774
Travel intention 0.924~0.945 0.949 0.963 0.868
Destination selection behaviour 0.782~0.889 0.837 0.892 0.674
Travel videos experience 0.865~0.903 0.956 0.963 0.790
Table I. Reliability Assessment of the Measurement Model

Next, the study evaluated validity through the AVE approach. AVE quantifies the variance explained by a latent construct compared to measurement error, where values exceeding 0.5 indicate adequate convergent validity (Fornell & Larcker, 1981). Table I reveals that the AVE scores for all constructs fell between 0.730 and 0.852, demonstrating strong convergent validity for the measurement scales.

Discriminant validity was subsequently assessed using Fornell and Larcker’s (1981) guidelines, which require that the square root of the AVE for each construct exceed its correlation with other constructs. As evidenced in Table II, all constructs met this criterion, confirming adequate discriminant validity.

ATT DSB PBC STN TIT TVE
ATT 0.807
DSB 0.383 0.821
PBC 0.330 0.764 0.880
STN 0.448 0.639 0.578 0.869
TIT 0.566 0.489 0.456 0.542 0.932
TVE 0.015 0.278 0.202 0.07 0.079 0.889
Table II. Fornell–Larcker Criterion for Discriminant Validity

Structural Model Evaluation

Consistent with Hairet al.’s (2011) methodological guidelines, the research utilized a bootstrapping analysis with 5000 resamples to evaluate the structural relationships. The findings presented in Table IV indicate statistically significant positive effects of ATT (p < 0.001), STN (p < 0.001), and PBC (p < 0.01) on TIT, providing empirical support for hypotheses H1, H2 and H3. The research results also showed a positive effect of TIT on DSB (p < 0.001), thus accepting hypothesis H4. The results from Table III also show that TIT mediates the relationship between PBC and DSB. Therefore, hypothesis H5 is confirmed.

Hypotheses Relationships ß t-values p-values Decision
H1 ATT→TIT 0.389 6.829 0.000 Supported
H2 STN →TIT 0.268 4.404 0.000 Supported
H3 PBC →TIT 0.172 2.980 0.003 Supported
H4 TIT →DSB 0.178 4.806 0.000 Supported
H5 PBC →TIT DSB 0.335 2.653 0.008 Supported
H6 TVE*TIT→ DSB 0.189 4.334 0.000 Supported
Table III. Hypothesis Testing Results
Hypo Relationship Indirect effect coefficients Direct effect coefficients Total effect coefficients VAF Mediation type
H5 PBC TIT DSB 0.335 0.075 0.410 81.71% Full mediation
Table IV. Analysis of the Mediation Type of Travel Intention

Finally, the results of the analysis of the moderating role of TVE also show that TVE moderates the relationship between TIT and DSB (p < 0.001). Specifically, tourists who intend to travel to Vietnam will choose Vietnam as their actual tourist destination the more they watch travel videos about Vietnam. Therefore, hypothesis H6 is accepted.

To propose further valuable contributions, this study further analyzes the mediating effect type of TIT. This study adopted the analytical methodologies proposed by Zhaoet al. (2010) and Nitzlet al. (2016), employing variance accounted for (VAF) metrics to assess mediation effects. As shown in Table IV, VAF results revealed that the indirect effects of PBC on DSB demonstrated a VAF of 81.71%, exceeding the 80% threshold and thus confirming full mediation (Hairet al., 2016).

Finally, the research assessed the structural model’s predictive validity through two key metrics: R2 and Q2. As displayed in Table V, the analysis yielded R2 values of 0.444 for TIT and 0.651 for DSB. According to Chin (1998), such results indicate that the explanatory power of the independent variables on TIT is moderate (0.2 < R2 < 0.5) and on DSB is significant (R2 > 0.5). Furthermore, the Q2 statistics for both constructs ranged from 0.25 to 0.5, confirming their moderate predictive power according to the established benchmark of Hairet al. (2019).

Variables R2 Q2
TIT 0.444 0.380
DSB 0.651 0.431
Table V. Analysis Result of R2 and Q2 Values

Conclusion and Discussion

The main purpose of this study is to investigate the moderating role of experiencing travel videos on tourists’ decision-making process of choosing a tourist destination. By applying TPB, the study identified three main antecedents to tourists’ decision-making process including attitude, SN and PBC. At the same time, by applying CT, the study confirmed the moderating role of experiencing travel videos on the relationship between travel intention and tourist destination choice behavior. The study used a convenience sampling method and surveyed 413 international tourists to Vietnam for 3 months to test the research model.

The results from this study confirm the positive influence of ATT, STN and PBC on TIT. with the strongest influence on TIT is ATT. The result of the current study also emphasizes the full mediating role of TIT on this relationship between PCB and DSB. Finally, while existing studies have found that intentions have no influence or a negligible influence on actual behavior, the current study found that this relationship is statistically significant. Furthermore, the findings also suggest that tourists with travel intentions are more likely to engage in destination choice behavior, the more travel videos they experience. Such results highlight the role of travel videos in tourists’ travel decision-making process.

Contributions

The study presents several practical implications for enhancing Vietnam’s tourism sector. Social influence from other tourists significantly shapes travel intentions, highlighting the need for coordinated efforts among the government, tourism authorities, educational institutions, and airport management to improve visitor satisfaction. Positive experiences can turn tourists into ambassadors who promote Vietnam through word-of-mouth. The government should promote public education to encourage hospitality and enforce laws against scams. Tourism boards can establish service standards to ensure consistent quality, while hospitality schools should include customer satisfaction training in their curriculum. Strengthening cultural and social values at destinations and promoting them through media can further shape positive attitudes among potential tourists.

Given the importance of PBC, marketing campaigns should highlight how convenient and accessible Vietnam is for international travelers. The study also confirms the moderating role of travel videos in converting intention into actual behavior. Tourism businesses and management agencies should invest in creating engaging, authentic travel videos to promote destinations. Collaborations with content creators can amplify reach, and branding strategies—such as adding logos, supporting creator costs, and encouraging user-generated content—can further enhance Vietnam’s image. These actions can encourage stronger destination approach behaviors, leading to increased tourism and improved business performance.

Limitations and Future Research

The results of this study highlight the theoretical model’s ability to shape destination selection behavior. Nevertheless, the research has some limitations. First, the data was gathered between March and June 2025, meaning it may not reflect seasonal differences in travel decisions. Future studies should explore these trends across various seasons to strengthen the model. Second, alternative data collection techniques could improve the study’s validity and sampling reliability. In this aspect, the reliance on convenience sampling in this study may lead to biased results and limit how broadly the findings can be applied. To better analyze domestic tourists’ destination preferences, future studies should explore alternative survey methods for more accurate and representative insights. Lastly, it should be recognized that additional unexamined factors may influence destination selection. Future studies could explore integrating other latent variable constructs to deepen the understanding of tourist decision-making complexities.

This research is funded by Van Lang University, Vietnam under grant number VLU-2503-DT-KDL-GV-0093.

Conflict of Interest

Conflict of Interest: The authors declare that they do not have any conflict of interest.

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