# Exploring the Impacts of Students in Hospitality Programs of Vocational High Schools Watching YouTubers’ Travel Programs on Travel Intention from the Perspective of Digital Business Opportunities in the Postpandemic Era

Authors: Yi-Ta Tsou; Hsiao-Hsien Lin; Wei-Cheng Chen; Chao-Chien Chen; Rui-Wen Fang; Chin-Hsien Hsu
Journal: Mobile Information Systems
 (2022)

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## Abstract

The purpose of this study is to explore the impacts of students in the hospitality programs of vocational high schools watching YouTubers’ travel programs on their travel intentions, as viewed from the perspective of digital business opportunities in the postpandemic era. Students in the hospitality programs of vocational high schools were taken as the research subjects, and a questionnaire survey was conducted with convenience sampling. A total of 350 questionnaires were distributed, and 320 questionnaires were recovered for a recovery rate of 91%. After 35 invalid questionnaires were excluded, there were 285 valid questionnaires for an effective recovery rate of 89%. The software, Statistical Package for the Social Sciences and Analysis of Moment Structures, was used for statistical analysis. The research results show that (1) there was no significant difference between different background variables in travel intention; (2) the degree of involvement had a significant impact on travel intention; (3) trust had a significant impact on travel intention; (4) perceived value had a significant impact on travel intention; and (5) destination image had a significant impact on travel intention. Finally, based on the results of this study, relevant suggestions were provided for practical application.


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## Body

## 1. Introduction

Tourism industries, service industries, and medical industries all over the world have been hit hard since COVID-19 ravaged the world in 2020. In order to curb the spread of the pandemic, relevant management units in various countries successively implemented pandemic prevention measures, such as maintaining social distance or initiating lockdowns in cities to reduce the risk of clustering and increase the infection rate. As of February 15, 2022, the number of confirmed cases globally reached 411,721,356, the number of confirmed cases in Taiwan reached 19,621, and the cumulative number of deaths in Taiwan reached 851. The current vaccine coverage rate in Taiwan has reached 82.29% [1]. With the development of the pandemic, the vaccination rate has greatly reduced the number of patients with severe disease and mortality caused by COVID-19, and how to coexist with COVID-19 has become a global concern in the postpandemic era; for example, the Tokyo Olympics was held in 2021 despite the difficult circumstances of the pandemic and, thus, can be regarded as a demonstration of the new norm of coexisting with the virus in the postpandemic era, which also opens up new business opportunities. As pointed out by Hsu and Chen [2], in the service industry, the rise of multifunctional complexes and large-scale leisure shopping malls has driven group warfares through cross-industry and cross-channel cooperation.Digital transformation has reshaped business models, while microbusiness districts and the M-shape development of retail stores are moving toward refined and community-based precision marketing. During the postpandemic era, the demand for zero-contact products and services is gradually increasing, and digital business opportunities are booming. A digital economy encompasses economic activities with digital data as the main factor of production, while a large amount of digital data is processed and the analysis results are evaluated. There have been changes in technology, equipment, storage, and sales in various industries under the digital economy compared with the traditional management form. Yang [3] pointed out that the digital economy is changing the relationship and engagement model between producers and consumers, making multinational companies redesign their processes and go-to-market routes and redefining the governance model of global production networks. Under the digital transformation, “virtual multinational enterprises (MNEs)” and “digital MNEs” with diversified business models have emerged, including Internet platforms (such as Yahoo, Alphabet (Google), and Facebook), e-commerce (such as Alibaba and Amazon), digital solutions (such as PayPal and First Data), and digital content (such as Comcast, Tencent, and Thomson Reuters). On the other hand, people have been under the restrictions of social distancing for a long time, and as the pandemic gradually eases, they have a higher willingness to go outdoors; thus, relevant government departments also take corresponding measures. For example, the Tourism Bureau [4] pointed out that with the tourism industry affected by the pandemic, the Tourism Bureau has adhered to the concept of “domestic tourism goes ahead of postpandemic transformation” and actively implemented the “Tourism 2025—Taiwan Tourism 2025 Plan” to promote the sustainable development of tourism through the five major strategies of “creating charming attractions, preparing theme tourism, optimizing industrial environment, promoting digital experience, and expanding tourist sources.” At the same time, the Tourism Bureau also used Taiwanese brands as the best international marketing, strived for the recovery and growth opportunities of the international market in Taiwan, and polished the new image of the Taiwanese tourism brand of “Taiwan, the first choice of safe travel.” In other words, Taiwan is vigorously promoting relevant policies to revive the tourism industry in the postpandemic era and is striving to promote such policies by promoting both national tourism and attracting international tourists.With the continuous development of network technology, the public’s network usage habits are also changing. A report on the network usage of Taiwanese people in 2020 by the Taiwan Network Information Center [5] found that, among the people observed regarding Internet usage, “real-time communication” (14.2%), “social media” (13.0%), and “video entertainment” (11.1%) are three of the top five network services they used. As can be seen from this data, in addition to the public’s usage of communication software to maintain connections with people around them, audio-visual entertainment also accounts for a certain proportion of the time spent using smartphones. The YouTube channel has long served as a platform for various types of information for users to search and learn. Coupled with the popularity of mobile devices, users’ reliance on YouTube is different; some are purely audience, while others are content providers. Chen et al. [6] held a related point of view and pointed out that the popularity of the YouTube platform has led to the emergence of a rare profession in recent years, YouTubers, meaning those who take operating their own YouTube platform as a profession to express themselves by uploading videos, thus increasing their popularity and income and becoming Internet celebrities widely seen by the public. Certainly, there are natural incentives to regard the YouTube platform as a profession. Su and Wang [7] pointed out that there are three common ways for YouTubers to make profits through the partner program. (1) Advertising: YouTubers agree that YouTube can place advertisements on their channels, and they can share advertising profits with YouTube afterwards. (2) Channel membership: a YouTuber creates a paid channel, then fans become paid members, they can receive member-exclusive rewards or video experiences, and YouTube will share revenue with YouTubers according to the number of subscribers. (3) Enabling the YouTube Premium function: if viewers subscribe to YouTube Premium and watch a YouTuber’s channel content, the YouTuber can receive a share of the subscription fees from YouTube Premium users. According to the abovementioned profit-making methods, it is possible to understand why YouTubers continue to release content that attracts viewers, as this represents not only a digital business opportunity but also the establishment of their own brands. Standing out among the vast contents of many channels means that its content or word of mouth has been affirmed. According to [8] data on “the survey on YouTube listening habits—Young people, what are you watching?,” which targets young people aged 18 to 24 in Taiwan, video content related to travel and food was the fourth most popular type of video content among young people. In relation to the impact of YouTube on the tourism industry, Li [9] pointed out that YouTube travel video elements have a positive impact on travel intention. Li also noted that in the case of developing local tourism, if one wants to promote local tourism through audio-visual media to encourage tourists to travel to the destination, then it will be beneficial to present relevant elements of the film (informative aspect) in the video. However, it is worthy of further exploration whether young people’s travel intentions will be influenced by YouTubers’ travel channel content. As learned from relevant literature, the research on travel intention is diversified; for example, Lee [10] took the members of the Facebook travel discussion group as the research subjects and conducted an online questionnaire survey with the marketing video for Korea Tourism Organization 2019 as the stimuli to construct and verify the relationship model of “idol identity, idol worship, and tourism intention.” Chen et al. [11] took the film “Your Love Song” as an example to explore the impact of the placement of tourist attractions in film and television programs on involvement, place attachment, and tourism intention. Cheng et al. [12] aimed to understand customers’ watching experience with travel vlogs and its impacts on one of the most prominent manifestations of customer engagement behaviors (CEBs)—word of mouth (WOM)—and their travel intention. Yılmazdoğan et al. [13] conducted a study taking the social network of Instagram as an example, where the primary objective was to determine the impact of the subdimensions of source credibility (attractiveness, trustworthiness, and expertise), and its secondary objective was to investigate the mediating role of parasocial interactions on the effect of the subdimensions of source credibility on travel intention. As can be seen from the above related literature, research on travel intentions mainly based on YouTubers’ travel channels is relatively rare. However, there are many factors affecting travel intention, such as the degree of involvement [14], trust [15], perceived value [16, 17], and destination image [18, 19]. Therefore, through empirical research, this article further explored the influence of the degree of involvement, trust, perceived value, and destination image on travel intention.With the trend of digitalization moving to the tourism industry, under multimarketing channels, the power of the community is combined with the integration of virtual and real channels, and even the customer travel service experience is optimized with digital technology, thereby enhancing the competitiveness of this industry. According to data from the Market Intelligence & Consulting Institute (MIC) of the Institute for Industrial Information (2021), the top five applications related to tourist attractions that tourists are interested in are “electronic tickets, sensor bracelets, AR/VR somatosensory facilities, queuing systems, and multi-payment.” On the other hand, consumers focus on optimizing digital tools for accommodation and an integrated app that can meet all transportation needs in one stop. The impacts of digital business opportunities on the tourism industry can thus be seen.As mentioned above, today’s young people tend to prefer videos related to travel and food when they are browsing YouTube. In other words, their behaviors of watching YouTube channel travel programs and their perceptions of the contents of these programs may affect their intentions of getting engaged in travel or not. In addition, for a YouTuber (a celebrity with a travel program channel), the perception and attitude of these young groups to the travel programs that the YouTuber has made are also issues that need to be studied under digital business opportunities. There is more room for development in applying digital business opportunities in the tourism industry, which is the value of this study.


## 2. Literature Review

Involvement refers to different levels of investment produced due to the attributes of activities and products, as well as personal preferences, when individuals engage in activities or consumption. Specific stimuli or situational influences can drive people to specific behaviors, and this can also explain why the concept of involvement is gradually used in the research on consumer behaviors and leisure issues. Houston and Rothschild [20] divided involvement into three specific types. (1) Situational involvement refers to an individual’s temporary perception of matters or things due to personal needs in a specific situation, which in turn affects the individual’s behavior, meaning that situational involvement is a temporary impact. (2) Continuous involvement refers to persistent concerns about a matter due to personal needs, values, and interests, meaning that it is not easy to change the degree of continuous involvement in a commodity due to the external environment. (3) Response involvement refers to the psychological state of something due to the combination of the effects of situational involvement and continuous involvement. There are different ways to measure involvement. Chen and Chen [21] suggested that the dimensions proposed by the following two scholars are most commonly used by other researchers to measure involvement according to multiple dimensions, namely, the consumer involvement profile (CIP) proposed by Laurent and Kapferer (1985) and the personal involvement inventory (PII) proposed by Zaichkowsky (1985).Trust fosters belief, meaning that a person will not engage in speculative behavior or focus solely on their own interest and will have faith in consistent values [22]. However, the concept of trust is not the same in the East and the West. Chen et al. [23] argued that there are different views on trust in the research between the East and the West and pointed out that the research perspectives regarding the ideal type of trust in Western social science research are always based on society versus individual (macro versus macro), space versus time, structure versus process, universal versus particular, and trust versus distrust (the degree of high versus low). While various dualistic distinction frameworks at the logical level (with continuous internal subdivision) are constantly being constructed, such concise and clear theoretical segmentations cannot actually achieve the intended empirical results. Chinese research on trust issues is mostly related to “relationships,” meaning the discussion of the internal structure and operational processes of relationship trust. It can be seen from the above classifications that consumers purchasing a certain product or accepting a certain service are based on the point of view of Western social sciences, that is, the basis for choosing between high or low levels of trust. Kim et al. [24] established an initial trust model (ITM) and formulated four key antecedents of initial trust, namely, Relative Benefits (RB), Structural Assurances (SA), Propensity to Trust (PT), and Firm Reputation (FR).When consumers have an overall subjective evaluation toward a product or service, value is generated. Zeithaml [25] pointed out that perceived value is a higher-level attribute that refers to the overall evaluation of the cost of a product and the perceived utility of the product; thus, it represents a trade-off between pay and gain. Value is divided into the following four types: (1) low price provides value, (2) value is the product that customers want, (3) value is the quality of goods at the price paid by customers, and (4) value is what customers obtain after paying. The above classifications show that different consumers do not necessarily have the same perceived value for the same service; for example, in tourism, the value pursued by the elderly may be physical and psychological security, while for the young, the pursued value may be biased toward adventure and stimulation. The tourism research of Petrick [26] pointed out that for tourists, perceived value is the relative value of the travel experience service one obtains from paying. After reviewing relevant literature and previous empirical research, Petrick [27] argued that the connotations of perceived value should include five aspects, quality, emotional response, monetary price, behavioral price, and reputation, in which quality refers to consumers’ judgment of the overall superiority of the product/service; emotional response refers to the descriptive judgment of the pleasure that a product/service gives the buyer; monetary price refers to the consumer’s perceived price for the product/service; behavioral price refers to the costs of time and effort required to obtain the product/service; reputation refers to the repute that consumers perceive based on the image of the supplier’s products/services.Destination images are often regarded as an entry point in the discussion of tourists’ tourism behaviors. Gunn [28] suggested that the destination image is generated after seven stages: (1) generating images in mind from past life experiences; (2) further revising the image of the destination after obtaining information; (3) determining the destination to visit after comparing the images; (4) arriving at the destination; (5) generating destination images from personal experience; (6) the process of leaving the destination and returning home; (7) modifying and generating new destination images based on actual experience. According to related research, the concepts of destination images tend to be diversified. Fakeye and Crompton [29] argued that destination image is a hot topic in the field of tourism research; however, many scholars have divergent views on the conceptual structure of destination image. By reviewing previous literature regarding tourist destination images, Echtner and Ritchie [30] concluded that a tourist destination should have two main components: an attribute-based destination image and a nonattribute-based overall destination image, as these two main components have more specific functional characteristics and more abstract psychological characteristics.Travel intention refers to the possibility of purchasing a tourism product and the concept of readiness-to-buy [31]. Relevant research shows that the factors influencing consumers’ intention to travel to a certain place include both internal and external factors. The internal factors refer to the images, perceptions, attitudes, and trust of the local place itself, while the external factors are the tourists’ own motivation, satisfaction, time, perception of destination attributes, tourism costs, buyer characteristics, and benefits obtained [32–34].In terms of the relationship between variables, relevant studies have confirmed the causal relationship between each other. The degree of involvement has a positive impact on travel intention [35–37], trust has a positive effect on travel intention [38, 39], perceived value has a positive effect on travel intention [40–42], and destination image has a positive impact on travel intention [43, 44].As the relationships among the above variables have all been verified by relevant studies, this study formulated research hypotheses and collected data through questionnaires based on this information. This study aims to further explore the impact on the travel intentions of students watching YouTube travel programs under the digital business opportunities in the postpandemic era.


## 3. Research Method

### 3.1. Research Structure

The following hypotheses of this study are based on the literature review, research purpose, and research structure, and the research structure is shown in Figure1.Figure 1
Research structure.


### 3.2. Research Hypotheses

(1)
Different demographic variables have a significant impact on travel intention.(2)
The degree of involvement of students in hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.(3)
The trust of students in hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.(4)
The perceived value of students in hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.(5)
The destination image of students in hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.


### 3.3. Research Questions

(1)
Discuss the differences in the travel intentions of various demographic variables of students in hospitality programs of vocational high schools watching YouTube travel programs.(2)
Discuss the influence of the degree of involvement on the travel intentions of students in hospitality programs of vocational high schools watching YouTube travel programs.(3)
Discuss the influence of trust on the travel intentions of students in hospitality programs of vocational high schools watching YouTube travel programs.(4)
Discuss the influence of the perceived value on the travel intentions of students in hospitality programs of vocational high schools watching YouTube travel programs.(5)
Discuss the influence of the destination image on the travel intentions of students in hospitality programs of vocational high schools watching YouTube travel programs.


### 3.4. Research Subjects

The convenience sampling method was adopted to distribute the questionnaires of this study. The students who had watched YouTube travel programs were selected as the research subjects, and the questionnaires were distributed and filled out on the spot from March 1 to May 1, 2021. A total of 350 questionnaires were distributed, 320 questionnaires were recovered, there were 285 valid questionnaires after invalid questionnaires, and those with incomplete answers were excluded.


### 3.5. Research Tools

The content of the questionnaire was compiled and modified with reference to the relevant literature and questionnaires of Chen et al. [11]; Chen [17]; Liu [14]; and Li [15]. The questionnaire is divided into six parts, with a total of 35 items. There are 5 items on basic personal information, 5 items on the degree of involvement, 3 items on trust, 15 items on destination image, 4 items on perceived value, and 3 items on travel intention. The scoring was made on a scale of 1 to 5, from “strongly disagree” to “strongly agree.”


### 3.6. Data Processing and Analysis

In this study, after the valid questionnaires were collected and the invalid questionnaires were excluded, the data were archived with SPSS 24.0 statistical software, and the correlation between variables was analyzed with AMOS 24.0 statistical software.


## 3.1. Research Structure

The following hypotheses of this study are based on the literature review, research purpose, and research structure, and the research structure is shown in Figure1.Figure 1
Research structure.


## 3.2. Research Hypotheses

(1)
Different demographic variables have a significant impact on travel intention.(2)
The degree of involvement of students in hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.(3)
The trust of students in hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.(4)
The perceived value of students in hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.(5)
The destination image of students in hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.


## 3.3. Research Questions

(1)
Discuss the differences in the travel intentions of various demographic variables of students in hospitality programs of vocational high schools watching YouTube travel programs.(2)
Discuss the influence of the degree of involvement on the travel intentions of students in hospitality programs of vocational high schools watching YouTube travel programs.(3)
Discuss the influence of trust on the travel intentions of students in hospitality programs of vocational high schools watching YouTube travel programs.(4)
Discuss the influence of the perceived value on the travel intentions of students in hospitality programs of vocational high schools watching YouTube travel programs.(5)
Discuss the influence of the destination image on the travel intentions of students in hospitality programs of vocational high schools watching YouTube travel programs.


## 3.4. Research Subjects

The convenience sampling method was adopted to distribute the questionnaires of this study. The students who had watched YouTube travel programs were selected as the research subjects, and the questionnaires were distributed and filled out on the spot from March 1 to May 1, 2021. A total of 350 questionnaires were distributed, 320 questionnaires were recovered, there were 285 valid questionnaires after invalid questionnaires, and those with incomplete answers were excluded.


## 3.5. Research Tools

The content of the questionnaire was compiled and modified with reference to the relevant literature and questionnaires of Chen et al. [11]; Chen [17]; Liu [14]; and Li [15]. The questionnaire is divided into six parts, with a total of 35 items. There are 5 items on basic personal information, 5 items on the degree of involvement, 3 items on trust, 15 items on destination image, 4 items on perceived value, and 3 items on travel intention. The scoring was made on a scale of 1 to 5, from “strongly disagree” to “strongly agree.”


## 3.6. Data Processing and Analysis

In this study, after the valid questionnaires were collected and the invalid questionnaires were excluded, the data were archived with SPSS 24.0 statistical software, and the correlation between variables was analyzed with AMOS 24.0 statistical software.


## 4. Research Results

### 4.1. Sample Characteristics

This study collected 285 valid samples, and the sample characteristics are shown in Table1.Table 1
Sample characteristics.
Background variableClassification criteriaSample numberPercentage (%)Cumulative percentage (%)GenderMale8228.828.8Female20371.2100.0GradeGrade 17024.624.6Grade 27827.451.9Grade 313748.1100.0Average weekly spending on leisure activitiesNTD 200 or less1043736.5NTD 201–400853066.3NTD 401–600411480.7NTD 601–80018687.0NTD 801–100021794.4NTD 1001or more166100.0Time spent in after-school leisure activities per week2 hours or less5519.319.33–5 hours13045.664.96–8 hours6121.486.39–11 hours134.690.912 hours or more269.1100.0Number of times watching YouTubers’ travel programs per week1 time or less7225.325.32–3 times10737.562.84–5 times4917.280.06–7 times165.685.68 times or more4114.4100.0


### 4.2. Analysis of the Differences in Demographic Variables

#### 4.2.1. Analysis of the Differences in the Travel Intentions of Different Genders of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs

The independent sampleT-test analysis results show that the T-value was 1.412, and the test result was not significant, indicating that there was no significant difference in the travel intentions between different genders of students in the hospitality programs of vocational high schools watching YouTube travel programs, as shown in Table 2.Table 2
Analysis of the differences in the travel intentions of different genders of students in the hospitality programs of vocational high schools watching YouTube travel programs.
NMeanMale823.991Female2034.156T-value1.412


#### 4.2.2. Analysis of the Differences in the Travel Intentions of Different Grades of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs

The independent sampleT-test analysis results show that the F value was 1.613, and the test result was not significant, indicating that there was no significant difference in the travel intentions among different grades of students in the hospitality programs of vocational high schools watching YouTube travel programs, as shown in Table 3.Table 3
Analysis of the differences in the travel intentions of different grades of students in the hospitality programs of vocational high schools watching YouTube travel programs.
NMeanGrade 1703.966Grade 2784.175Grade 31374.143F value1.613


#### 4.2.3. Analysis of the Differences in the Travel Intentions of Students in the Hospitality Programs of Vocational High Schools Watching YouTubers’ Travel Programs with Different Average Weekly Spending on Leisure Activities

The independent sampleT-test analysis results show that the F value was 2.262, and the test result was not significant, indicating that there was no significant difference in the travel intentions among students in the hospitality programs of vocational high schools watching YouTube travel programs with different average weekly spending on leisure activities, as shown in Table 4.Table 4
An analysis of the differences in the travel intentions of students in the hospitality programs of vocational high schools watching YouTube travel programs with different average weekly spending on leisure activities.
NMeanNTD 200 or less1043.974NTD 201–400854.321NTD 401–600414.008NTD 601–800184.074NTD 801–1000214.222NTD 1001or more164.000F value2.262


#### 4.2.4. Analysis of the Differences in the Travel Intentions of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs with Different Time Spent in After-School Leisure Activities per Week

The independent sampleT-test analysis results show that the F value was 0.335, and the test result was not significant, indicating that there was no significant difference in the travel intentions among the students in the hospitality programs of vocational high schools watching YouTube travel programs with different time spent in after-school leisure activities per week, as shown in Table 5.Table 5
Analysis of the differences in the travel intentions of students in the hospitality programs of vocational high schools watching YouTube travel programs with different time spent in after-school leisure activities per week.
NMean2 hours or less554.0543–5 hours1304.1356–8 hours614.0499–11 hours134.25612 hours or more264.153F value0.335


#### 4.2.5. Analysis of the Differences in the Travel Intentions of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs with Different Number of Times of Watching YouTube Travel Programs per Week

The independent sampleT-test analysis results show that the F value was 2.007, and the test result was not significant, indicating that there was no significant difference in the travel intentions among students in the hospitality programs of vocational high schools watching YouTube travel programs with different numbers of times of watching YouTube travel programs per week, as shown in Table 6.Table 6
Analysis of the differences in the travel intentions of students in the hospitality programs of vocational high schools watching YouTube travel programs with a different number of times of watching YouTube travel programs per week.
NMean1 time or less723.9532–3 times1074.0994–5 times494.1496–7 times164.0628 times or more414.374F value2.007


### 4.3. Measurement Mode Analysis and Verification of Convergent Validity

This study used confirmatory factor analysis to test and analyze the reliability and validity of the questionnaire, and the items were revised with reference to Modification Indices (MI) [45]. The items deleted by this study include Image 1, Image 3, Image 4, Image 6, Image 7, Image 10, Image 11, Image 12, and Image 14 of the Destination Image Scale.This study conducted convergent validity tests on the dimensions of the degrees of involvement, trust, perceived value, destination image, and travel intention. The test results indicate that the factor loadings of all the dimensions were between 0.65 and 0.94, the values of the composite reliability were between 0.80 and 0.94, and the values of average variance extracted were between 0.58 and 0.84, indicating that the research on watching YouTube travel programs had convergent validity, and the details are shown in Tables712.Table 7
Variables and item contents.
Degree of involvementInvolvement 1I am pretty focused when watching YouTubers’ travel programs.Involvement 2I am engrossed in every detail of the video when watching YouTubers’ travel programs.Involvement 3The content of YouTubers’ travel programs intrigues me.Involvement 4I take the time to recall the content of the YouTubers’ travel programs.Involvement 5Relevant thoughts come to my mind when recalling the content of a YouTuber’s travel program.TrustTrust1I would like to trust the viewing services provided by YouTubers’ travel programs.Trust2I would like to trust the travel information provided by YouTubers’ travel programs.Trust3I have confidence in the travel information provided by YouTubers’ travel programs and will make travel plans accordingly.Destination imageImage 1The travel contents, environments, and places introduced by YouTubers’ travel programs are diverse.Image 2The tourist attractions and activities introduced by YouTubers’ travel programs are diverse.Image 3There are plenty of natural tourist attractions introduced by YouTubers’ travel programs.Image 4The tourist shopping facilities introduced by YouTubers’ travel programs are perfect.Image 5The travel consulting service introduced by YouTubers’ travel programs is developed well.Image 6The tourist attractions introduced by YouTubers’ travel programs are convenient and easy to reach.Image 7There are various accommodation options for the tourist attractions introduced by YouTubers’ travel programs.Image 8The architecture of the tourist attractions introduced by YouTubers’ travel programs is featured.Image 9The tourist attractions introduced by YouTubers’ travel programs have a pleasant climate and are suitable for travel.Image 10The economic development of the tourist attractions introduced by YouTubers’ travel programs is sound.Image 11The tourist attractions introduced by YouTubers’ travel programs are in good order, and people can travel with peace of mind.Image 12The customs and cultures of the tourist attractions introduced by YouTubers’ travel programs are distinctive.Image 13The local residents of the tourist attractions introduced by YouTubers’ travel programs are amicable and friendly.Image 14The tourist attractions introduced by YouTubers’ travel programs do not cost much.Image 15The tourist attractions introduced by YouTubers’ travel programs have a special local atmosphere.Perceived valuePerceivingness 1The travel information presented by YouTubers’ travel programs exhibits high quality.Perceivingness 2Overall, watching YouTubers’ travel programs is convenient.Perceivingness 3YouTubers’ travel programs are practical.Perceivingness 4The value I get from the content of YouTubers’ travel programs is worth my time and effort.Travel intentionIntention 1I am willing to travel to other countries for sightseeing.Intention 2I am willing to travel to other countries again for sightseeing again.Intention 3I would like to recommend others to travel to other countries.Table 8
Convergent validity and construct reliability summary table—degree of involvement.
Item no.Standardized factor loadingsUnstandardized factor loadingsS.E.C.R. (t-value)PSMCC.R.AVEInvolvement 2<---degree of involvement0.691.000.480.800.58Involvement 4<---degree of involvement0.851.380.1310.22∗∗∗0.72Involvement 5<---degree of involvement0.741.050.1010.29∗∗∗0.54Source: Compiled by this study.Table 9
Convergent validity and construct reliability summary table—trust.
Item no.Standardized factor loadingsUnstandardized factor loadingsS.E.C.R. (t-value)PSMCC.R.AVETrust 1<---trust0.941.000.480.840.65Trust 2<---trust0.770.900.0713.06∗∗∗0.60Trust 3<---trust0.690.670.0611.89∗∗∗0.88Source: Compiled by this study.Table 10
Convergent validity and construct reliability summary table—perceived value.
Item no.Standardized factor loadingsUnstandardized factor loadingsS.E.C.R. (t-value)PSMCC.R.AVEPerceivingness 1<---perceived value0.761.000.570.860.62Perceivingness 2<---perceived value0.821.100.0813.61∗∗∗0.68Perceivingness 3<---perceived value0.841.080.0813.24∗∗∗0.70Perceivingness 4<---perceived value0.731.010.0811.95∗∗∗0.53Source: Compiled by this study.Table 11
Convergent validity and construct reliability summary table—destination image.
Item no.Standardized factor loadingsUnstandardized factor loadingsS.E.C.R. (t-value)PSMCC.R.AVEImage 2<--- destination image0.761.000.580.900.58Image 5<--- destination image0.771.060.0813.36∗∗∗0.59Image 7<--- destination image0.751.030.0812.88∗∗∗0.57Image 8<--- destination image0.821.090.0814.40∗∗∗0.68Image 9<--- destination image0.741.030.0812.74∗∗∗0.55Image 13<--- destination image0.771.090.0813.42∗∗∗0.59Image 15<--- destination image0.761.050.8013.11∗∗∗0.58Source: Compiled by this study.Table 12
Convergent validity and construct reliability summary table—travel intention.
Item no.Standardized factor loadingsUnstandardized factor loadingsS.E.C.R. (t-value)PSMCC.R.AVEIntention 1<---travel intention0.941.000.780.940.84Intention 2<--- travel intention0.931.030.0427.22∗∗∗0.86Intention 3<--- travel intention0.880.950.0424.09∗∗∗0.88Source: Compiled by this study.


### 4.4. Structural Model Analysis

The structural model analysis of this study referred to the opinions of Bagozzi and Yi [46], Benter (1992), Wu (2009), and Hair et al. (1998), and the seven indicators of the χ2 test, the ratio of χ2 to degrees of freedom, GFI, AGFI, RMSEA, CFI, and PCFI were used to evaluate the overall goodness of fit. Table 7 shows that the corrected χ2 was 353.54, the ratio of χ2 to degrees of freedom was 2.21, the value of GFI was 0.90 (equal to 0.9), the value of AGFI was 0.90 (equal to 0.8), the value of RMSEA was 0.07 (less than.08), the value of CFI was 0.95 (more than 0.8), and the value of PCFI was 0.80 (more than 0.5). The research results show that this model is acceptable, as shown in Table 13.Table 13
Analysis of research model overall goodness of fit.
Fit indexAllowable standardModel correctedGoodness of fit judgmentχ2 (chi-square)The smaller, the better353.54Ratio ofχ to degrees of freedom<32.21AcceptableGFI>0.900.90AcceptableAGFI>0.800.90AcceptableRMSEA<0.080.07AcceptableCFI>0.800.95AcceptablePCFI>0.500.80AcceptableSource: Compiled by this study.H1 was not supported; that is, different demographic variables did not have a significant impact on travel intention. The results of this study are different from the research conclusions of Chen [45]; the possible reason is that many travel restrictions or obstacles have led to a decrease in the travel intentions of students in the hospitality programs of vocational high schools due to the current pandemic. H2 was supported; that is, the degree of involvement of students in the hospitality programs of vocational high schools watching YouTube travel programs significantly impacted travel intention. As shown in Table 14 and Figure 2, the results of this study are the same as the research findings of Hasan and Khandakar (2021), and the possible reason is that more students in hospitality programs of vocational high schools pay attention to or follow up on YouTube travel programs, the more likely their travel intention is to be increased. H3 was supported; that is, the trust of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. This research result is consistent with the research conclusion of Weng [39]; and the possible reason might be that students in the hospitality programs of vocational high schools may think that a channel or a YouTuber is more trustworthy when they have a high number of subscribers or are discussed more, which should gradually improve travel intentions. H4 was supported; that is, the perceived value of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. This research result is similar to the research conclusion of Uslu and Karabulut [42], which is possible because students in the hospitality programs of vocational high schools find that watching YouTube travel programs brings knowledge, information, or aesthetic value, which may trigger their travel intentions. H5 was supported; that is, the destination image of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. The results of this study are the same as the research conclusions of Chaulagain et al. [43]; and the possible reason is that after watching YouTube travel programs, students in the hospitality programs of vocational high schools have a better impression of the destination image, which increases their travel intentions, as travel programs provide relevant travel information.Table 14
Summary of research hypotheses and test results.
Research hypothesesPath valueTest resultsH1: Different demographic variables have a significant impact on travel intention.Not supportedH2: The degree of involvement of students in the hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.0.14SupportedH3: The trust of students in the hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.0.10SupportedH4: The perceived value of students in the hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.0.33SupportedH5: The destination image of students in the hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.0.22Supported∗P < 0.05.Figure 2
Model diagram of the degree of involvement, trust, perceived value, destination image, and travel intentions of students in the hospitality programs of vocational high schools watching YouTube travel programs.


## 4.1. Sample Characteristics

This study collected 285 valid samples, and the sample characteristics are shown in Table1.Table 1
Sample characteristics.
Background variableClassification criteriaSample numberPercentage (%)Cumulative percentage (%)GenderMale8228.828.8Female20371.2100.0GradeGrade 17024.624.6Grade 27827.451.9Grade 313748.1100.0Average weekly spending on leisure activitiesNTD 200 or less1043736.5NTD 201–400853066.3NTD 401–600411480.7NTD 601–80018687.0NTD 801–100021794.4NTD 1001or more166100.0Time spent in after-school leisure activities per week2 hours or less5519.319.33–5 hours13045.664.96–8 hours6121.486.39–11 hours134.690.912 hours or more269.1100.0Number of times watching YouTubers’ travel programs per week1 time or less7225.325.32–3 times10737.562.84–5 times4917.280.06–7 times165.685.68 times or more4114.4100.0


## 4.2. Analysis of the Differences in Demographic Variables

### 4.2.1. Analysis of the Differences in the Travel Intentions of Different Genders of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs

The independent sampleT-test analysis results show that the T-value was 1.412, and the test result was not significant, indicating that there was no significant difference in the travel intentions between different genders of students in the hospitality programs of vocational high schools watching YouTube travel programs, as shown in Table 2.Table 2
Analysis of the differences in the travel intentions of different genders of students in the hospitality programs of vocational high schools watching YouTube travel programs.
NMeanMale823.991Female2034.156T-value1.412


### 4.2.2. Analysis of the Differences in the Travel Intentions of Different Grades of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs

The independent sampleT-test analysis results show that the F value was 1.613, and the test result was not significant, indicating that there was no significant difference in the travel intentions among different grades of students in the hospitality programs of vocational high schools watching YouTube travel programs, as shown in Table 3.Table 3
Analysis of the differences in the travel intentions of different grades of students in the hospitality programs of vocational high schools watching YouTube travel programs.
NMeanGrade 1703.966Grade 2784.175Grade 31374.143F value1.613


### 4.2.3. Analysis of the Differences in the Travel Intentions of Students in the Hospitality Programs of Vocational High Schools Watching YouTubers’ Travel Programs with Different Average Weekly Spending on Leisure Activities

The independent sampleT-test analysis results show that the F value was 2.262, and the test result was not significant, indicating that there was no significant difference in the travel intentions among students in the hospitality programs of vocational high schools watching YouTube travel programs with different average weekly spending on leisure activities, as shown in Table 4.Table 4
An analysis of the differences in the travel intentions of students in the hospitality programs of vocational high schools watching YouTube travel programs with different average weekly spending on leisure activities.
NMeanNTD 200 or less1043.974NTD 201–400854.321NTD 401–600414.008NTD 601–800184.074NTD 801–1000214.222NTD 1001or more164.000F value2.262


### 4.2.4. Analysis of the Differences in the Travel Intentions of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs with Different Time Spent in After-School Leisure Activities per Week

The independent sampleT-test analysis results show that the F value was 0.335, and the test result was not significant, indicating that there was no significant difference in the travel intentions among the students in the hospitality programs of vocational high schools watching YouTube travel programs with different time spent in after-school leisure activities per week, as shown in Table 5.Table 5
Analysis of the differences in the travel intentions of students in the hospitality programs of vocational high schools watching YouTube travel programs with different time spent in after-school leisure activities per week.
NMean2 hours or less554.0543–5 hours1304.1356–8 hours614.0499–11 hours134.25612 hours or more264.153F value0.335


### 4.2.5. Analysis of the Differences in the Travel Intentions of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs with Different Number of Times of Watching YouTube Travel Programs per Week

The independent sampleT-test analysis results show that the F value was 2.007, and the test result was not significant, indicating that there was no significant difference in the travel intentions among students in the hospitality programs of vocational high schools watching YouTube travel programs with different numbers of times of watching YouTube travel programs per week, as shown in Table 6.Table 6
Analysis of the differences in the travel intentions of students in the hospitality programs of vocational high schools watching YouTube travel programs with a different number of times of watching YouTube travel programs per week.
NMean1 time or less723.9532–3 times1074.0994–5 times494.1496–7 times164.0628 times or more414.374F value2.007


## 4.2.1. Analysis of the Differences in the Travel Intentions of Different Genders of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs

The independent sampleT-test analysis results show that the T-value was 1.412, and the test result was not significant, indicating that there was no significant difference in the travel intentions between different genders of students in the hospitality programs of vocational high schools watching YouTube travel programs, as shown in Table 2.Table 2
Analysis of the differences in the travel intentions of different genders of students in the hospitality programs of vocational high schools watching YouTube travel programs.
NMeanMale823.991Female2034.156T-value1.412


## 4.2.2. Analysis of the Differences in the Travel Intentions of Different Grades of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs

The independent sampleT-test analysis results show that the F value was 1.613, and the test result was not significant, indicating that there was no significant difference in the travel intentions among different grades of students in the hospitality programs of vocational high schools watching YouTube travel programs, as shown in Table 3.Table 3
Analysis of the differences in the travel intentions of different grades of students in the hospitality programs of vocational high schools watching YouTube travel programs.
NMeanGrade 1703.966Grade 2784.175Grade 31374.143F value1.613


## 4.2.3. Analysis of the Differences in the Travel Intentions of Students in the Hospitality Programs of Vocational High Schools Watching YouTubers’ Travel Programs with Different Average Weekly Spending on Leisure Activities

The independent sampleT-test analysis results show that the F value was 2.262, and the test result was not significant, indicating that there was no significant difference in the travel intentions among students in the hospitality programs of vocational high schools watching YouTube travel programs with different average weekly spending on leisure activities, as shown in Table 4.Table 4
An analysis of the differences in the travel intentions of students in the hospitality programs of vocational high schools watching YouTube travel programs with different average weekly spending on leisure activities.
NMeanNTD 200 or less1043.974NTD 201–400854.321NTD 401–600414.008NTD 601–800184.074NTD 801–1000214.222NTD 1001or more164.000F value2.262


## 4.2.4. Analysis of the Differences in the Travel Intentions of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs with Different Time Spent in After-School Leisure Activities per Week

The independent sampleT-test analysis results show that the F value was 0.335, and the test result was not significant, indicating that there was no significant difference in the travel intentions among the students in the hospitality programs of vocational high schools watching YouTube travel programs with different time spent in after-school leisure activities per week, as shown in Table 5.Table 5
Analysis of the differences in the travel intentions of students in the hospitality programs of vocational high schools watching YouTube travel programs with different time spent in after-school leisure activities per week.
NMean2 hours or less554.0543–5 hours1304.1356–8 hours614.0499–11 hours134.25612 hours or more264.153F value0.335


## 4.2.5. Analysis of the Differences in the Travel Intentions of Students in the Hospitality Programs of Vocational High Schools Watching YouTube Travel Programs with Different Number of Times of Watching YouTube Travel Programs per Week

The independent sampleT-test analysis results show that the F value was 2.007, and the test result was not significant, indicating that there was no significant difference in the travel intentions among students in the hospitality programs of vocational high schools watching YouTube travel programs with different numbers of times of watching YouTube travel programs per week, as shown in Table 6.Table 6
Analysis of the differences in the travel intentions of students in the hospitality programs of vocational high schools watching YouTube travel programs with a different number of times of watching YouTube travel programs per week.
NMean1 time or less723.9532–3 times1074.0994–5 times494.1496–7 times164.0628 times or more414.374F value2.007


## 4.3. Measurement Mode Analysis and Verification of Convergent Validity

This study used confirmatory factor analysis to test and analyze the reliability and validity of the questionnaire, and the items were revised with reference to Modification Indices (MI) [45]. The items deleted by this study include Image 1, Image 3, Image 4, Image 6, Image 7, Image 10, Image 11, Image 12, and Image 14 of the Destination Image Scale.This study conducted convergent validity tests on the dimensions of the degrees of involvement, trust, perceived value, destination image, and travel intention. The test results indicate that the factor loadings of all the dimensions were between 0.65 and 0.94, the values of the composite reliability were between 0.80 and 0.94, and the values of average variance extracted were between 0.58 and 0.84, indicating that the research on watching YouTube travel programs had convergent validity, and the details are shown in Tables712.Table 7
Variables and item contents.
Degree of involvementInvolvement 1I am pretty focused when watching YouTubers’ travel programs.Involvement 2I am engrossed in every detail of the video when watching YouTubers’ travel programs.Involvement 3The content of YouTubers’ travel programs intrigues me.Involvement 4I take the time to recall the content of the YouTubers’ travel programs.Involvement 5Relevant thoughts come to my mind when recalling the content of a YouTuber’s travel program.TrustTrust1I would like to trust the viewing services provided by YouTubers’ travel programs.Trust2I would like to trust the travel information provided by YouTubers’ travel programs.Trust3I have confidence in the travel information provided by YouTubers’ travel programs and will make travel plans accordingly.Destination imageImage 1The travel contents, environments, and places introduced by YouTubers’ travel programs are diverse.Image 2The tourist attractions and activities introduced by YouTubers’ travel programs are diverse.Image 3There are plenty of natural tourist attractions introduced by YouTubers’ travel programs.Image 4The tourist shopping facilities introduced by YouTubers’ travel programs are perfect.Image 5The travel consulting service introduced by YouTubers’ travel programs is developed well.Image 6The tourist attractions introduced by YouTubers’ travel programs are convenient and easy to reach.Image 7There are various accommodation options for the tourist attractions introduced by YouTubers’ travel programs.Image 8The architecture of the tourist attractions introduced by YouTubers’ travel programs is featured.Image 9The tourist attractions introduced by YouTubers’ travel programs have a pleasant climate and are suitable for travel.Image 10The economic development of the tourist attractions introduced by YouTubers’ travel programs is sound.Image 11The tourist attractions introduced by YouTubers’ travel programs are in good order, and people can travel with peace of mind.Image 12The customs and cultures of the tourist attractions introduced by YouTubers’ travel programs are distinctive.Image 13The local residents of the tourist attractions introduced by YouTubers’ travel programs are amicable and friendly.Image 14The tourist attractions introduced by YouTubers’ travel programs do not cost much.Image 15The tourist attractions introduced by YouTubers’ travel programs have a special local atmosphere.Perceived valuePerceivingness 1The travel information presented by YouTubers’ travel programs exhibits high quality.Perceivingness 2Overall, watching YouTubers’ travel programs is convenient.Perceivingness 3YouTubers’ travel programs are practical.Perceivingness 4The value I get from the content of YouTubers’ travel programs is worth my time and effort.Travel intentionIntention 1I am willing to travel to other countries for sightseeing.Intention 2I am willing to travel to other countries again for sightseeing again.Intention 3I would like to recommend others to travel to other countries.Table 8
Convergent validity and construct reliability summary table—degree of involvement.
Item no.Standardized factor loadingsUnstandardized factor loadingsS.E.C.R. (t-value)PSMCC.R.AVEInvolvement 2<---degree of involvement0.691.000.480.800.58Involvement 4<---degree of involvement0.851.380.1310.22∗∗∗0.72Involvement 5<---degree of involvement0.741.050.1010.29∗∗∗0.54Source: Compiled by this study.Table 9
Convergent validity and construct reliability summary table—trust.
Item no.Standardized factor loadingsUnstandardized factor loadingsS.E.C.R. (t-value)PSMCC.R.AVETrust 1<---trust0.941.000.480.840.65Trust 2<---trust0.770.900.0713.06∗∗∗0.60Trust 3<---trust0.690.670.0611.89∗∗∗0.88Source: Compiled by this study.Table 10
Convergent validity and construct reliability summary table—perceived value.
Item no.Standardized factor loadingsUnstandardized factor loadingsS.E.C.R. (t-value)PSMCC.R.AVEPerceivingness 1<---perceived value0.761.000.570.860.62Perceivingness 2<---perceived value0.821.100.0813.61∗∗∗0.68Perceivingness 3<---perceived value0.841.080.0813.24∗∗∗0.70Perceivingness 4<---perceived value0.731.010.0811.95∗∗∗0.53Source: Compiled by this study.Table 11
Convergent validity and construct reliability summary table—destination image.
Item no.Standardized factor loadingsUnstandardized factor loadingsS.E.C.R. (t-value)PSMCC.R.AVEImage 2<--- destination image0.761.000.580.900.58Image 5<--- destination image0.771.060.0813.36∗∗∗0.59Image 7<--- destination image0.751.030.0812.88∗∗∗0.57Image 8<--- destination image0.821.090.0814.40∗∗∗0.68Image 9<--- destination image0.741.030.0812.74∗∗∗0.55Image 13<--- destination image0.771.090.0813.42∗∗∗0.59Image 15<--- destination image0.761.050.8013.11∗∗∗0.58Source: Compiled by this study.Table 12
Convergent validity and construct reliability summary table—travel intention.
Item no.Standardized factor loadingsUnstandardized factor loadingsS.E.C.R. (t-value)PSMCC.R.AVEIntention 1<---travel intention0.941.000.780.940.84Intention 2<--- travel intention0.931.030.0427.22∗∗∗0.86Intention 3<--- travel intention0.880.950.0424.09∗∗∗0.88Source: Compiled by this study.


## 4.4. Structural Model Analysis

The structural model analysis of this study referred to the opinions of Bagozzi and Yi [46], Benter (1992), Wu (2009), and Hair et al. (1998), and the seven indicators of the χ2 test, the ratio of χ2 to degrees of freedom, GFI, AGFI, RMSEA, CFI, and PCFI were used to evaluate the overall goodness of fit. Table 7 shows that the corrected χ2 was 353.54, the ratio of χ2 to degrees of freedom was 2.21, the value of GFI was 0.90 (equal to 0.9), the value of AGFI was 0.90 (equal to 0.8), the value of RMSEA was 0.07 (less than.08), the value of CFI was 0.95 (more than 0.8), and the value of PCFI was 0.80 (more than 0.5). The research results show that this model is acceptable, as shown in Table 13.Table 13
Analysis of research model overall goodness of fit.
Fit indexAllowable standardModel correctedGoodness of fit judgmentχ2 (chi-square)The smaller, the better353.54Ratio ofχ to degrees of freedom<32.21AcceptableGFI>0.900.90AcceptableAGFI>0.800.90AcceptableRMSEA<0.080.07AcceptableCFI>0.800.95AcceptablePCFI>0.500.80AcceptableSource: Compiled by this study.H1 was not supported; that is, different demographic variables did not have a significant impact on travel intention. The results of this study are different from the research conclusions of Chen [45]; the possible reason is that many travel restrictions or obstacles have led to a decrease in the travel intentions of students in the hospitality programs of vocational high schools due to the current pandemic. H2 was supported; that is, the degree of involvement of students in the hospitality programs of vocational high schools watching YouTube travel programs significantly impacted travel intention. As shown in Table 14 and Figure 2, the results of this study are the same as the research findings of Hasan and Khandakar (2021), and the possible reason is that more students in hospitality programs of vocational high schools pay attention to or follow up on YouTube travel programs, the more likely their travel intention is to be increased. H3 was supported; that is, the trust of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. This research result is consistent with the research conclusion of Weng [39]; and the possible reason might be that students in the hospitality programs of vocational high schools may think that a channel or a YouTuber is more trustworthy when they have a high number of subscribers or are discussed more, which should gradually improve travel intentions. H4 was supported; that is, the perceived value of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. This research result is similar to the research conclusion of Uslu and Karabulut [42], which is possible because students in the hospitality programs of vocational high schools find that watching YouTube travel programs brings knowledge, information, or aesthetic value, which may trigger their travel intentions. H5 was supported; that is, the destination image of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. The results of this study are the same as the research conclusions of Chaulagain et al. [43]; and the possible reason is that after watching YouTube travel programs, students in the hospitality programs of vocational high schools have a better impression of the destination image, which increases their travel intentions, as travel programs provide relevant travel information.Table 14
Summary of research hypotheses and test results.
Research hypothesesPath valueTest resultsH1: Different demographic variables have a significant impact on travel intention.Not supportedH2: The degree of involvement of students in the hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.0.14SupportedH3: The trust of students in the hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.0.10SupportedH4: The perceived value of students in the hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.0.33SupportedH5: The destination image of students in the hospitality programs of vocational high schools watching YouTube travel programs has a significant impact on travel intention.0.22Supported∗P < 0.05.Figure 2
Model diagram of the degree of involvement, trust, perceived value, destination image, and travel intentions of students in the hospitality programs of vocational high schools watching YouTube travel programs.


## 5. Conclusion and Suggestions

### 5.1. Conclusion

The conclusion of this study presents the impacts of YouTubers’ travel programs on the students in the hospitality programs of vocational high schools. The higher the degree of involvement and trust when watching YouTubers’ travel programs, the greater their travel intentions. On the other hand, the higher the perceived value and the better the destination image for the students in the hospitality programs of vocational high schools who watched YouTubers’ travel programs, the higher their travel intention.From this conclusion, it can be seen that YouTuber travel program providers, the audience, and the tourism industry have created a mutually beneficial and win-win industrial structure with digital business opportunities. Under the value creation method, the audience can gain unique travel experiences and values by watching trusted travel programs and realize different interpretations of the destination image as well [47–53].


### 5.2. Suggestions

Some suggestions were put forward by this article for reference based on the above research results:


#### 5.2.1. For Students in Hospitality Programs of Vocational High Schools

The conclusions of this study showed that the degree of involvement of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. Therefore, it is suggested that students in the hospitality programs of vocational high schools should have the perception ability for self-subscribed YouTube travel channels or YouTubers in the travel category to avoid bad consequences due to the incorrect information provided by travel channels. It can be seen that the students in the hospitality programs of vocational high schools are at an age when they are easily influenced by opinion leaders. If the students in the hospitality programs of vocational high schools do not have the ability to judge the travel information provided by YouTubers and become blindly involved, although the degree of involvement will gradually increase and their travel intentions are improved, they may end up with a poor travel experience. Therefore, it is recommended that students in the hospitality programs of vocational high schools should choose YouTube travel channels or travel YouTubers very carefully. The results of this study show that the destination image of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. Therefore, it is recommended that students in the hospitality programs of vocational high schools pay attention to the practicability and correctness of the information when receiving information from YouTube travel programs. For example, in order to gain views or network volume, some YouTubers in the travel category may wear inappropriate outdoor gear to pursue secret realms in the mountains, such as setting off to shoot a channel video wearing sneakers and jeans. This approach may make students in the hospitality programs of vocational high schools have a false image, meaning that “if YouTubers can do that, of course, I can, too,” which can result in the travel intention but may greatly reduce the destination image of students due to referring to YouTubers’ wrong information.


#### 5.2.2. For Travel Programs on YouTube

According to the results of this study, the trust of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intentions. Therefore, it is suggested that travel program YouTubers should appropriately improve their professional knowledge and image to build a higher degree of trust. For example, some travel program YouTubers can hold lectures on the purchase of air tickets and lectures relevant to air ticketing from time to time. Through these lectures, they can share and pass on the matters that should be paid attention to when purchasing air tickets or how to accumulate miles to upgrade the class and other practical information through personal practical experience. Travel program YouTubers can also release air ticketing-related videos and discount information on board and lodging at the same time. Such activities have improved their brand images and given the public a higher sense of trust in the YouTube travel channel because of the exposure to news media. On the other hand, it is suggested that YouTubers in travel programs should build trust through their social responsibility efforts, such as maintaining the originality of channel content and programs and avoiding plagiarism and infringing content. At the same time, they should avoid overriding moral conscience and establish a good media reading environment, which can enhance the professional image of YouTubers in travel programs and deepen the trust of subscribers. The results of this study show that the perceived value of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intentions. Therefore, it is suggested that the travel program production of YouTubers should consider the number of viewers and make the program content rewarding and inspiring; for example, some YouTubers in travel programs organize their overseas travel experience according to pre-travel, during travel, and post-travel experience and offer tool kits or lazy bags for various topics, such as food, clothing, housing, and transportation. Through such arrangements, readers can feel that YouTubers in travel programs are reliable and offer more specific information, which gives them a deeper understanding of the destination image. In other words, the YouTuber’s adopting such an approach in their travel programs can present the aspects of quality, emotional response, and reputation in the connotation of perceived value.


#### 5.2.3. For Future Research

The results of this study show that different demographic variables had no significant impact on travel intentions. As discussed in the above literature, it can be seen that the factors influencing consumers’ intention to travel to a certain place include external factors and internal factors. In other words, the factors influencing the travel intentions of students in the hospitality programs of vocational high schools are very diverse, and many travel program YouTubers present various qualities. This study recommended future related research include the demographic variables of different age groups and discuss other variables, such as program type, program quality, and hosting style of YouTubers in travel programs. By exploring related variables, a better understanding can be obtained regarding how YouTubers of travel programs can build positive psychological capital with the audience in terms of popularity, credibility, and exposure and, thus, resonate with and promote the satisfaction of audience members. In addition, it is recommended to include the audience’s lifestyle for analysis. After all, some people are content with the status quo, while others have the courage to get out of their comfort zone, and analysis will help to understand whether different lifestyles affect the choice of YouTubers in travel programs when constructing the pursued destination image.


## 5.1. Conclusion

The conclusion of this study presents the impacts of YouTubers’ travel programs on the students in the hospitality programs of vocational high schools. The higher the degree of involvement and trust when watching YouTubers’ travel programs, the greater their travel intentions. On the other hand, the higher the perceived value and the better the destination image for the students in the hospitality programs of vocational high schools who watched YouTubers’ travel programs, the higher their travel intention.From this conclusion, it can be seen that YouTuber travel program providers, the audience, and the tourism industry have created a mutually beneficial and win-win industrial structure with digital business opportunities. Under the value creation method, the audience can gain unique travel experiences and values by watching trusted travel programs and realize different interpretations of the destination image as well [47–53].


## 5.2. Suggestions

Some suggestions were put forward by this article for reference based on the above research results:


### 5.2.1. For Students in Hospitality Programs of Vocational High Schools

The conclusions of this study showed that the degree of involvement of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. Therefore, it is suggested that students in the hospitality programs of vocational high schools should have the perception ability for self-subscribed YouTube travel channels or YouTubers in the travel category to avoid bad consequences due to the incorrect information provided by travel channels. It can be seen that the students in the hospitality programs of vocational high schools are at an age when they are easily influenced by opinion leaders. If the students in the hospitality programs of vocational high schools do not have the ability to judge the travel information provided by YouTubers and become blindly involved, although the degree of involvement will gradually increase and their travel intentions are improved, they may end up with a poor travel experience. Therefore, it is recommended that students in the hospitality programs of vocational high schools should choose YouTube travel channels or travel YouTubers very carefully. The results of this study show that the destination image of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. Therefore, it is recommended that students in the hospitality programs of vocational high schools pay attention to the practicability and correctness of the information when receiving information from YouTube travel programs. For example, in order to gain views or network volume, some YouTubers in the travel category may wear inappropriate outdoor gear to pursue secret realms in the mountains, such as setting off to shoot a channel video wearing sneakers and jeans. This approach may make students in the hospitality programs of vocational high schools have a false image, meaning that “if YouTubers can do that, of course, I can, too,” which can result in the travel intention but may greatly reduce the destination image of students due to referring to YouTubers’ wrong information.


### 5.2.2. For Travel Programs on YouTube

According to the results of this study, the trust of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intentions. Therefore, it is suggested that travel program YouTubers should appropriately improve their professional knowledge and image to build a higher degree of trust. For example, some travel program YouTubers can hold lectures on the purchase of air tickets and lectures relevant to air ticketing from time to time. Through these lectures, they can share and pass on the matters that should be paid attention to when purchasing air tickets or how to accumulate miles to upgrade the class and other practical information through personal practical experience. Travel program YouTubers can also release air ticketing-related videos and discount information on board and lodging at the same time. Such activities have improved their brand images and given the public a higher sense of trust in the YouTube travel channel because of the exposure to news media. On the other hand, it is suggested that YouTubers in travel programs should build trust through their social responsibility efforts, such as maintaining the originality of channel content and programs and avoiding plagiarism and infringing content. At the same time, they should avoid overriding moral conscience and establish a good media reading environment, which can enhance the professional image of YouTubers in travel programs and deepen the trust of subscribers. The results of this study show that the perceived value of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intentions. Therefore, it is suggested that the travel program production of YouTubers should consider the number of viewers and make the program content rewarding and inspiring; for example, some YouTubers in travel programs organize their overseas travel experience according to pre-travel, during travel, and post-travel experience and offer tool kits or lazy bags for various topics, such as food, clothing, housing, and transportation. Through such arrangements, readers can feel that YouTubers in travel programs are reliable and offer more specific information, which gives them a deeper understanding of the destination image. In other words, the YouTuber’s adopting such an approach in their travel programs can present the aspects of quality, emotional response, and reputation in the connotation of perceived value.


### 5.2.3. For Future Research

The results of this study show that different demographic variables had no significant impact on travel intentions. As discussed in the above literature, it can be seen that the factors influencing consumers’ intention to travel to a certain place include external factors and internal factors. In other words, the factors influencing the travel intentions of students in the hospitality programs of vocational high schools are very diverse, and many travel program YouTubers present various qualities. This study recommended future related research include the demographic variables of different age groups and discuss other variables, such as program type, program quality, and hosting style of YouTubers in travel programs. By exploring related variables, a better understanding can be obtained regarding how YouTubers of travel programs can build positive psychological capital with the audience in terms of popularity, credibility, and exposure and, thus, resonate with and promote the satisfaction of audience members. In addition, it is recommended to include the audience’s lifestyle for analysis. After all, some people are content with the status quo, while others have the courage to get out of their comfort zone, and analysis will help to understand whether different lifestyles affect the choice of YouTubers in travel programs when constructing the pursued destination image.


## 5.2.1. For Students in Hospitality Programs of Vocational High Schools

The conclusions of this study showed that the degree of involvement of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. Therefore, it is suggested that students in the hospitality programs of vocational high schools should have the perception ability for self-subscribed YouTube travel channels or YouTubers in the travel category to avoid bad consequences due to the incorrect information provided by travel channels. It can be seen that the students in the hospitality programs of vocational high schools are at an age when they are easily influenced by opinion leaders. If the students in the hospitality programs of vocational high schools do not have the ability to judge the travel information provided by YouTubers and become blindly involved, although the degree of involvement will gradually increase and their travel intentions are improved, they may end up with a poor travel experience. Therefore, it is recommended that students in the hospitality programs of vocational high schools should choose YouTube travel channels or travel YouTubers very carefully. The results of this study show that the destination image of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intention. Therefore, it is recommended that students in the hospitality programs of vocational high schools pay attention to the practicability and correctness of the information when receiving information from YouTube travel programs. For example, in order to gain views or network volume, some YouTubers in the travel category may wear inappropriate outdoor gear to pursue secret realms in the mountains, such as setting off to shoot a channel video wearing sneakers and jeans. This approach may make students in the hospitality programs of vocational high schools have a false image, meaning that “if YouTubers can do that, of course, I can, too,” which can result in the travel intention but may greatly reduce the destination image of students due to referring to YouTubers’ wrong information.


## 5.2.2. For Travel Programs on YouTube

According to the results of this study, the trust of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intentions. Therefore, it is suggested that travel program YouTubers should appropriately improve their professional knowledge and image to build a higher degree of trust. For example, some travel program YouTubers can hold lectures on the purchase of air tickets and lectures relevant to air ticketing from time to time. Through these lectures, they can share and pass on the matters that should be paid attention to when purchasing air tickets or how to accumulate miles to upgrade the class and other practical information through personal practical experience. Travel program YouTubers can also release air ticketing-related videos and discount information on board and lodging at the same time. Such activities have improved their brand images and given the public a higher sense of trust in the YouTube travel channel because of the exposure to news media. On the other hand, it is suggested that YouTubers in travel programs should build trust through their social responsibility efforts, such as maintaining the originality of channel content and programs and avoiding plagiarism and infringing content. At the same time, they should avoid overriding moral conscience and establish a good media reading environment, which can enhance the professional image of YouTubers in travel programs and deepen the trust of subscribers. The results of this study show that the perceived value of students in the hospitality programs of vocational high schools watching YouTube travel programs had a significant impact on travel intentions. Therefore, it is suggested that the travel program production of YouTubers should consider the number of viewers and make the program content rewarding and inspiring; for example, some YouTubers in travel programs organize their overseas travel experience according to pre-travel, during travel, and post-travel experience and offer tool kits or lazy bags for various topics, such as food, clothing, housing, and transportation. Through such arrangements, readers can feel that YouTubers in travel programs are reliable and offer more specific information, which gives them a deeper understanding of the destination image. In other words, the YouTuber’s adopting such an approach in their travel programs can present the aspects of quality, emotional response, and reputation in the connotation of perceived value.


## 5.2.3. For Future Research

The results of this study show that different demographic variables had no significant impact on travel intentions. As discussed in the above literature, it can be seen that the factors influencing consumers’ intention to travel to a certain place include external factors and internal factors. In other words, the factors influencing the travel intentions of students in the hospitality programs of vocational high schools are very diverse, and many travel program YouTubers present various qualities. This study recommended future related research include the demographic variables of different age groups and discuss other variables, such as program type, program quality, and hosting style of YouTubers in travel programs. By exploring related variables, a better understanding can be obtained regarding how YouTubers of travel programs can build positive psychological capital with the audience in terms of popularity, credibility, and exposure and, thus, resonate with and promote the satisfaction of audience members. In addition, it is recommended to include the audience’s lifestyle for analysis. After all, some people are content with the status quo, while others have the courage to get out of their comfort zone, and analysis will help to understand whether different lifestyles affect the choice of YouTubers in travel programs when constructing the pursued destination image.



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*Source: 6193685-2022-09-02.xml*