Visiting Intentions toward Theme Parks: Do Short Video Content and Tourists’ Perceived Playfulness on TikTok Matter?

Abstract

TikTok, along with other social media platforms, has emerged as one of the most important tools for many people, particularly millennials. Because the relationship between social media and customers’ behavioral intentions has long been a topic of discussion in the hospitality industry, the purpose of this study was to look into the potential determinants of customers’ visiting intentions toward Universal Studios Beijing on short video platforms such as TikTok. In addition, descriptive analysis was also conducted to show the demographic and other basic characteristics of the sample. The findings revealed that social interaction, informativeness, and trust had significant effects on perceived usefulness, as well as significant influences on the related visiting intentions from the perceived usefulness, ease of use, and playfulness. This study filled in the research gaps of the TikTok studies based on the extended technology acceptance model (TAM) and explored the effects of perceived playfulness on the theme park. This study can contribute to the formulation of operational and marketing strategies by theme park marketers, help internet vloggers with content creation and development, and provide suggestions to local governments for tourism destination management.

1. Introduction

In the tourism and recreation fields, TikTok plays an essential role in many areas, such as destination management, destinations’ images, and tourism marketing, especially among millennials [1,2]. This applies to theme park businesses as well, and to accommodate people’s preference for TikTok, theme parks have also shifted their marketing, promotion, and even sales services to the short video platform in order to increase awareness and boost the purchase of tickets and other souvenirs [3]. For instance, since opening in 2021, Universal Studios Beijing’s promotion and marketing on TikTok have significantly increased, with more than one billion clicks every half an hour [4].

The effects of social media platforms such as Facebook and YouTube have been widely discussed in the literature, and many studies on the tourism industry have also identified the significant influences of social media on people’s willingness to visit [5,6]. Theme parks constitute a growing sector in the tourism industry and the factors determining people’s preferences and visitation intentions are not only worthy of investigation but also contribute to the sustainable development of the tourism industry. Unlike the general tourism sector, the experiences of a theme park visitor comprise many factors. For instance, as discussed by Milman et al., the visitor’s perceived crowding and perceived popularity were two critical antecedents for satisfaction and behavioral intention [7]. However, studies from the theme park perspective have focused on exploring people’s experiences, satisfaction, or image-influenced visitation intentions [8,9], and they have neither addressed the effects of social media nor explored customers’ visiting intentions toward theme parks due to social media, especially short video platforms such as TikTok.

Therefore, in order to identify the potential determinants related to short video platforms and their content of the visiting intentions of customers, this study examines how people’s intentions to visit the Universal Studios Beijing theme park are affected by online social media and short video content. The technology acceptance model (TAM) has been utilized as the theoretical framework for investigating tourists’ visiting intentions. In addition to the two fundamental factors of the perceived usefulness and perceived ease of use, the current study also extended the TAM framework and took into consideration the factor of perceived playfulness, since people’s perceived playfulness has been systematically investigated and shown to have a significant influence on both people’s attitudes and further behavioral intentions in the existing literature [10,11,12]. Furthermore, three more determinants—social interaction, informativeness, and trust—are discussed, particularly aiming to explore their impact on TikTok video content because these factors have been suggested to have a significant influence on people’s perceived usefulness in the context of social media and short video platforms [13,14,15].

Data were collected through an online questionnaire and both confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to test the substantive framework and proposed model from the empirical data. According to the results, all the hypotheses were validated, in which the independent variables of social interaction (SI), informativeness (IF), and trust (TR) were indicated to have positive effects on perceived usefulness (PU), whereas perceived playfulness (PP) along with perceived ease of use (PE) and perceived usefulness (PU) from the TAM had positive effects on people’s attitudes (ATT) toward TikTok videos, which further identified with a positive influence on customer’s visiting intentions (VI) toward theme parks.

This current study fills a gap in the research on short-form video in theme park marketing and consumer behavior, with a focus on analyzing both short video content and evaluating its effects on people’s visiting intentions toward theme parks. The current study’s findings not only confirm the PU and PE of the TikTok platform and videos based on the TAM framework but also demonstrate the significant influence of theme park businesses’ special constructs of PP on people’s attitudes and future visiting intentions. The current study could contribute to the expanded use of the TAM framework in the theme park industry. Meanwhile, it rigorously examined the effects of many ascendants associated with TikTok’s short video content on PU from several angles, such as SI, IF, and TR. Furthermore, the current study’s practical consequences can assist theme park advertising, theme park owners, marketers, local governments, and even guests.

2. Literature Review

2.1. Visiting Intentions and Technology Acceptance Model (TAM)

In the tourism industry, people’s visiting intentions are usually defined as having specific plans to visit somewhere [16]. When people are determining their plans to visit a specific place, social media plays a vital role in this decision-making process [17,18]. Previously, social media and its corresponding effects on people’s intentions have been widely discussed in different areas such as tourism and destination management. For instance, Zulzilah et al. [19] investigated the influence of Instagram and determined how people’s visiting intentions toward specific destinations are affected by social media content from Instagram, whereas Sharif and Mura [20] also analyzed factors such as user-generated content (UGC) on Facebook that specifically affect people’s attitudes and visiting intentions concerning certain destinations.

However, with regard to theme park businesses specifically, although a few studies have examined topics such as people’s experiences, staff service quality, overall satisfaction levels, and brand quality [15,21,22], they have ignored the impact that social media has on all aspects of people’s lives nowadays, which leaves a research gap related to the impact of theme parks on social media platforms (TikTok) and social media content (TikTok videos). To explore people’s behavioral intentions due to social media and short video platforms such as TikTok, the TAM along with factors such as perceived usefulness and perceived ease of use was classically applied to explore the relationship between the factors and the visiting intentions [20,23,24].

The TAM has been widely used in consumer behavior research [25,26] to explain the decisive factors in the widespread acceptance of TikTok. The current study applied the TAM and explored how people’s attitudes and visitation intentions are affected by factors related to the use of social media and short video platforms. Developed by Davis [27], the two main determinants, perceived usefulness and perceived ease of use, were constituents of the original TAM framework. Both determinants were identified to have a significant influence on people’s attitudes toward the use of certain technologies, which can further impact people’s behavioral intentions to use [27].

Focusing on the context of social media, there are extensive studies investigating people’s future behaviors based on the TAM framework. According to the summary in

Table 1. Summary of future behavioral intention studies in social media context based on TAM since 2012.

Authors and Research Context	Method	Summary of Analysis
E-commerce
Al-Mowalad and Putit [34]	SEM	Examines how social media’s influence and perceptions of risk affect the relationship between intentions and actual online purchases.
Erkan and Evans [28]	Thematic analysis, multiple regression, SEM	Analyzes the impact of e-WOM and major social media factors on consumers’ online purchase intentions.
Arli [35]	CFA, SEM, ANOVA	Investigates how social media elements affect customers’ attitudes toward brands and intentions to buy.
Sharma and Bhatt [36]	Reliability analysis, multiple regression	Investigates the impact of perceived usefulness, perceived value, and perceived risk on purchase intentions.
Wong [37]	Pearson correlation, SEM, multiple linear regression	Investigates factors that may influence online purchasing intent in Hong Kong, including perceived risk, usefulness, trust, and e-WOM.
Xiao et al. [29]	Descriptive analysis	Combines the content features of the short video marketing model and analyzes the effects of these factors on online purchase intentions.
AI-Gasawneh et al. [38]	PLS-SEM	Examines the role of comprehensiveness as a moderating variable between social media and online shopping intentions.
Huang and Lu [39]	Descriptive analysis, SEM	Examines the relationship between the perceived value of short videos and the intent to purchase online.
Xu et al. [40]	PLS, SEM	Examines the impact of consumer flow, flow theory, and TAM on social media purchasing intentions.
Tourism, hospitality, and event industry
Di Pietro et al. [31]	SEM	Examines the significance of e-WOM communication on the impressions of usefulness and attitudes toward social networks in the selection of tourism sites.
Lee et al. [41]	ANOVA, descriptive analysis, SEM	Describes the technique by which social media marketing changes Facebook event page attitudes.
Amaro and Duarte [30]	PLS-SEM	Examines the various elements that influence internet travel booking intentions
Agag and EI-Masry [42]	SEM	Analyzes customers’ intentions to participate in an online travel community, purchase intentions, and positive WOM.
Agag and EI-Masry [43]	SEM	Examines how consumer intentions to book a hotel online are influenced by commitment, trust, and attitudes, as well as their antecedents.
Social media platform
Chang et al. [44]	PLS-SEM, descriptive analysis	Explores the impact of trust, subjective norm, perceived ease of use, and perceived usefulness on user intent to endorse multimedia content on mobile social networks.
Chun and Lee [32]	Experimental design	Investigates the effects of content type on individuals’ involvement and intentions to subscribe to a company’s SNS.
Florenthal [33]	SEM	Explains the aspects that influence the brand engagement intentions of young customers on social media websites.
Others
Zhao and Wang [7]	CFA, MLE, CMV	Discusses people’s approval and purchasing propensities for health-related short-form video advertisements.
Florenthal et al. [45]	PLS-SEM	Investigates the motivational drivers of millennials’ intentions to donate money to charities on social media sites.
Florenthal and Awad [46]	PLS-SEM	Evaluates how entertainment, interpersonal utility, and subjective norms impact participation with and donations to NPO among millennials.

Note: Word-of-mouth (WOM), Social Network Service (SNS), Non-profit organization (NPO), Technology Acceptance Model (TAM).

, analyses of previous studies can be mainly categorized into four perspectives, including general e-commence [28,29]; the tourism, hospitality, and event industries [30,31]; social media platforms [32,33]; and other industries [7,33]. In Table 1, it is explicitly indicated that the TAM framework plays a vital role in studying people’s future intentions to use vis-à-vis social media and short video platforms.

Therefore, to identify the determinants related to TikTok that affect people’s visiting intentions toward theme parks, the current study was established based on the TAM framework and it fundamentally evaluated the effects of people’s perceived usefulness, perceived ease of use, and attitudes on their visiting intentions. As a result, the following three hypotheses are proposed. The next sections address a number of additional particular considerations pertaining to both short video content and theme park-specific elements.

Hypothesis 1 (H1).

Perceived usefulness positively affects people’s attitudes toward videos on TikTok.

Hypothesis 2 (H2).

Perceived ease of use positively affects people’s attitudes toward videos on TikTok.

Hypothesis 3 (H3).

People’s attitudes toward videos on TikTok positively affect their visiting intentions.

2.2. Three Factors of Video Content

Rather than only focusing on the features of TikTok and mobile application usage, the current study was also curious about whether the content of the posts on TikTok also had an impact on people’s visiting intentions. According to previous studies, factors such as social interaction (SI), informativeness (IF), and trust (TR) have significant influences on people’s perceived usefulness of social media and short video content when making decisions [13,14].

Social interaction can be defined as interpersonal conversations among website users. People today seek guidance and relevant information on travel review websites to help them make decisions, and they communicate with each other by posing questions, responding to others, and voting [14]. The process of social interaction enables the formation of social relationships [47]. Based on Zhao and Wang’s study [7], social interaction in social media can influence people’s perceived usefulness. Consequently, it has become a crucial aspect of people’s acceptance of short video material. Based on the TAM framework, the effect of social interaction on the perceived usefulness of TikTok short video content was also explored in the current study.

Informativeness was regarded as another factor that affected perceived usefulness in the context of social media. Referring to useful content that can offer people a variety of alternatives for products or services, perceived informativeness can provide the necessary information to potential buyers before they make decisions [7,48]. Also identified in the previous literature, informativeness of the content on social media was confirmed to have a positive impact on people’s perceived usefulness [13,49]. Therefore, people’s perceived informativeness was the second factor considered in the current study that influences the perceived usefulness of TikTok’s video content related to Universal Studios Beijing.

In the context of social media, trust is critical in influencing customers’ perceived usefulness [50]. People’s trust in social media refers to the faith in and reliability of the information such as the video content or promotional advice posted on the platform. If people have greater trust in the content or advertisements, they will be more willing to select the product or service provided by the business [51]. As indicated by Cheunkamon et al. [52], trust exists between those who want accurate and useful information from content creators and various participating groups in online interactions. In the tourism industry, trust is known to influence perceived usefulness when people use Facebook and websites because trustworthy information about the destination and the various types of travel information can increase the credibility of not only social media platforms but also business organizations [50]. Therefore, based on the discussion above related to the three determinants of people’s perceived usefulness, the following hypotheses are posited.

Hypothesis 4 (H4).

Social interactions positively affect people’s perceived usefulness.

Hypothesis 5 (H5).

Informativeness positively affects people’s perceived usefulness.

Hypothesis 6 (H6).

Trust positively affects people’s perceived usefulness.

2.3. Perceived Playfulness

In addition to the fundamental perspectives of both usefulness and ease of use from the original TAM framework, the current study also considered people’s perceived playfulness (PP) as another essential independent variable of interest. Defined by Spence and Usher [53], people’s playfulness refers to their “cognitive spontaneity and sense of pleasure in undertaking a task.” Moon and Kim [12] indicated that people can embrace positive and optimistic beliefs about playfulness when interacting with websites. In addition, people’s perceived playfulness was also identified to have strong correlations with the development of their attitudes toward the Internet and technology usage intentions [10,11,12].

In the existing research developed based on the TAM framework, people’s perceived playfulness has been applied in a wide range of fields, such as general Internet websites and systems [12], online social media usage [54], and education technology implications [55], in order to facilitate further investigation into both the attitudes and behavioral intentions of people.

As discussed above, perceived playfulness is regarded as a critical factor that affects both attitudes and behavioral intentions when considering the adoption of technologies such as social media platforms and short video platforms such as TikTok; therefore, the variable of perceived playfulness is constructed in this study to explore its impacts on people’s attitudes toward videos on TikTok. Figure 1 illustrates the conceptual model of this study, which is generated from the preceding discussion.

Hypothesis 7 (H7).

Perceived playfulness positively affects customers’ attitudes toward videos on TikTok.

3. Methodology

3.1. Data Collection

To more precisely target clients influenced by TikTok promotions, the current study used Universal Studios Beijing as an example and performed a survey utilizing an online questionnaire. The questionnaire was drafted using the software Questionnaire Star and sent to a few people to make sure they could understand the questions and reduce the bias caused by the questions. After ensuring the quality of the questions, the questionnaires were sent out through WeChat and websites to ensure that the respondents were diverse enough and not concentrated on one group. In addition, the number of questionnaires collected was more than 400, which ensured that the sample was large and more representative. After the data were collected, incomplete questionnaires and questionnaires filled in by non-TikTok users or those who had not viewed videos related to Universal Studios Beijing on TikTok were screened out to ensure that the remaining study group was our target group.

An online questionnaire was sent using random selection. All variables measures were compiled using a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5). The constructs and variable items were taken from prior studies and adjusted for the questionnaire. Constructs applied in the questionnaire have been attached in Appendix A,

Table A1. Table of measurement scale constructs.

Construct	Items
SI	SI1: I like to give a “like”, comment, or reply to videos about Universal Studios on TikTok.
	SI2: Videos about Universal Studios on TikTok allowed me to interact with others.
	SI3: Videos about Universal Studios on TikTok enhance my social interaction with others.
IF	IF1: If you want to know about Beijing Universal Studios, TikTok short videos are a good source of information.
	IF2: If you want to know about Beijing Universal Studios, TikTok short videos can provide more accurate information.
	IF3: The release of TikTok short videos can help Universal Studios Beijing update the park in real time.
TR	TR1: I think most of TikTok’s short videos about Beijing Universal Studios are correct.
	TR2: I think most of TikTok’s short videos, photos, or videos about Beijing Universal Studios are consistent with the real situation.
	TR3: I think most of TikTok’s short videos and short video advertisements about Beijing Universal Studios are reliable.
PU	PU1: I think the videos about Universal Studios on TikTok can give me a deeper understanding of products or services.
	PU2: I think the videos about Universal Studios on TikTok can save me time in making travel plans.
	PU3: I think the videos about Universal Studios on TikTok can provide me with valuable information.
PE	PE1: It is easy for me to understand the functions of Tiktok including watching, clicking, and commenting.
	PE2: It is easy for me to use the app functions including watching, clicking, and commenting.
	PE3: It is easy for me to obtain information about Beijing Universal Studios on Tiktok.
	PE4: It is easy for me to enter universal Studios’ product-related pages on Tiktok.
PP	PP1: I feel more comfortable watching videos about Beijing Universal Studios on TikTok.
	PP2: I feel very happy about watching videos about Beijing Universal Studios on the TikTok platform.
	PP3: Watching videos about Beijing Universal Studios on TikTok can stimulate my imagination.
ATT	ATT1: I love the short videos about Beijing Universal Studios on Tiktok.
	ATT2: I hold positive views of the Universal Studios short video on Tiktok.
	ATT3: I like the style and concept of Tiktok short video advertising.
	ATT4: I would like to share the information about Beijing Universal Studios obtained from the short video on Tiktok with others.
VI	VI1: After watching the short video about Beijing Universal Studios on Tiktok, I would like to visit this scenic spot.
	VI2: After watching the short video about Beijing Universal Studios on Tiktok, I may plan to visit this attraction in the future.
	VI3: After watching the short video about Beijing Universal Studios on Tiktok, I would like to spread the information about the attraction to others.

.

A total of 432 surveys were collected initially, whereas 11 questionnaires were discarded because they could not be identified as TikTok users. Therefore, the total number of questionnaires available for analysis was 421, with 339 valid surveys (more than 78%) from participants who watched the promotional or introductory videos for Universal Studios Beijing on TikTok considered for the data analysis process.

3.2. Data Analysis

Structural equation modeling (SEM) was used to investigate the complex relationship between the dependent and independent variables and to test the model’s fit with the proposed study model. SEM analysis is adept at studying direct and indirect complex relationships among variables in a research model, which is not only superior to simple linear statistical testing methods such as regression analysis but also helps to incorporate measurable and non-measurable variables into the research model. AMOS 26 and SPSS 26 were used to examine the data as well as the model fit. The demographic features of the sample were subjected to descriptive analyses. Confirmatory factor analysis (CFA) was performed to assess the fitness and quality of the study’s model by examining the reliability and validity, as recommended by the research suggestions of Anderson and Gerbing [56].

4. Results

4.1. Profile of the Respondents

The demographic data and other basic characteristics of the sample were evaluated using descriptive analysis. As can be seen in

Table 2. Sample statistic results.

Items	Classification	Amounts	Percentage (%)
Gender	Male	234	54.17
	Female	198	45.83
Age	<18	6	1.39
	18–24	137	31.71
	25–30	181	41.90
	31–40	76	17.59
	41–50	21	4.86
	>50	11	2.55
Educational level	High school or below	79	18.29
	Bachelor’s	288	66.67
	Master’s	56	12.96
	Doctorate	9	2.08
TikTok user	Yes	421	97.45
	No	11	2.55
Years of TikTok use	0–1	63	14.58
	1–2	130	30.09
	2–3	162	37.50
	3–4	51	11.81
	>4	26	6.02
Hours of TikTok watching	0–1	71	16.44
	1–2	185	42.82
	2–3	116	26.85
	3–4	44	10.19
	>4	16	3.70
Total		432	100

, among the participants, the proportions of women and men were similar at 44% and 55.6%, respectively. The majority of participants were over the age of 18, with those aged 18–24 and 25–30 accounting for 37.93% and 40.09%, respectively. These figures are congruent with those reported by China Ecommerce Insights Hub, which show that the fundamental percentages of male and female users are nearly equal and that the largest user base is between the ages of 19 and 35. [57]. Furthermore, most of the participants had bachelor’s degrees, with the number of people with high school education ranking second, accounting for 66.67% and 18.29%, respectively; this means that most of the respondents were highly educated. In terms of the length of TikTok use and the hours spent using TikTok, most of the participants had used TikTok for 2–3 years and spent 2–3 h on TikTok per day, indicating that they were loyal users.

A Pearson correlation coefficient test was included in this study to evaluate whether there was a statistically significant correlation between the variables, and the results are presented with a coefficient matrix, mean, and standard deviation. According to

Table 3. Descriptive statistics and the correlation coefficients matrix.

Constructs	Mean	SD	1	2	3	4	5	6	7	8
1. VI	3.92	0.78	1
2. ATT	3.84	0.81	0.47 **	1
3. PE	3.94	0.77	0.17 **	0.38 **	1
4. PU	3.92	0.8	0.39 **	0.41 **	0.25 **	1
5. PP	3.86	0.84	0.11 *	0.21 **	0.11*	0.1	1
6. SI	3.9	0.8	0.21 **	0.19 **	0.07	0.38 **	0.1	1
7. IF	3.96	0.8	0.21 **	0.20 **	0.08	0.34 **	0.06	0.14 **	1
8. TR	3.83	0.84	0.26 **	0.17 **	0.05	0.31 **	0.03	0.19 **	0.12 *	1

** p < 0.01; * p < 0.05 (2-tailed).

, most of the variables significantly correlated with the others, except for the following relationships: PE with SI, IF, and TR; PP with SI, IF, and TR; PU with PP. Furthermore, all correlation effects were positive, which indicates that with an increase in one certain variable, there was also an increase in the others [36].

Visiting intentions (VI), Attitudes to the video on TikTok (ATT), Perceived ease of use (PE), Perceived usefulness (PU), Perceived playfulness (PP), Social interaction (SI), Informativeness (IF), Trust (TR)

4.2. Confirmatory Factor Analysis (CFA)

The measurement model’s reliability and validity were assessed in this study and the CFA findings showed that all standardized factor loadings were larger than 0.8, indicating that none of them needed to be excluded because the value was greater than 0.7 [58]. All of the composite reliabilities (CR) were higher than 0.7, which is considered satisfactory [58]. Reliability was a degree indicator of the veracity of the attributes being tested based on the consistency or stability of the test scale results.

When the value of Cronbach’s alpha surpasses 0.7, Tavakol and Dennick [59] conclude that the measuring scale’s internal consistency is high [60]. The values in

Table 4. Validity of the measurement model.

Latent Variance	Measured Variables	Items S.D.	Items Mean	Factor Loadings	Cronbach’s α	CR	AVE
VI	VIS(VI1)	0.93	3.88	0.81	0.85	0.83	0.61
	PLA(VI2)	0.94	3.95	0.77
	SPR(VI3)	0.89	3.94	0.76
ATT	VIE(ATT2)	0.94	3.80	0.83	0.85	0.88	0.66
	SAC(ATT3)	0.94	3.81	0.81
	SHA(ATT4)	0.96	3.90	0.81
	LOV(ATT1)	0.90	3.85	0.79
PE	ENT(PE4)	0.91	3.89	0.80	0.86	0.87	0.63
	USE(PE2)	0.99	4.04	0.80
	UND(PE1)	0.94	3.97	0.79
	OBT(PE3)	0.94	3.85	0.79
PU	VAL(PU3)	0.90	3.95	0.81	0.83	0.83	0.61
	TIM(PU2)	0.96	3.88	0.77
	POS(PU1)	0.92	3.94	0.76
PP	IMA(PP3)	0.94	3.79	0.87	0.86	0.89	0.72
	ENJ(PP1)	0.99	3.93	0.85
	PLE(PP2)	1.00	3.86	0.83
SI	OPP(SI2)	0.96	3.82	0.86	0.83	0.88	0.71
	INT(SI3)	0.93	3.88	0.83
	LOR(SI1)	0.91	4.00	0.83
IF	COR(IF2)	0.93	3.93	0.86	0.84	0.89	0.72
	UPD(IF3)	0.94	3.94	0.85
	SOU(IF1)	0.91	4.02	0.85
TR	MAT(TR2)	0.95	3.87	0.88	0.85	0.89	0.74
	REL(TR3)	0.99	3.74	0.85
	TRU(TR1)	0.94	3.86	0.84

Note: visit (VIS), plan (PLA), spread (SPR), view (VIE), style and concept (SAC), share (SHA), love (LOV), enter (ENT), use (USE), understand (UND), obtain (OBT), valuable (VAL), time (TIM), product and service (POS), imagination (IMA), enjoyment (ENJ), pleasure (PLE), opportunity (OPP), interaction (INT), like or reply (LOR), correct (COR), update information (UPD), source (SOU), match (MAT), reliable (REL), true (TRU).

ranged from 0.764 to 0.878, suggesting internal consistency in this study’s measuring structure. The amount of scale that may truly represent the construct under the survey is referred to as validity. A convergent validity test was carried out in this section. The extracted average variance (AVE) demonstrated convergent validity, which must be more than 0.5 to verify that the requirement had been met [61]. The results showed that the AVE was greater than 0.5, indicating that our study’s convergent validity was well attained.

4.3. Structural Evaluation Modeling

A total of 421 questionnaires were collected and AMOS 26 was used for the SEM. With reference to the recommended values in

Table 5. Fitting degree and discriminant validity.

Index	Criteria	Actual Value	Judgment
χ2/df	<3.00	1.424	Yes
GFI	>0.90	0.935	Yes
AGFI	>0.90	0.915	Yes
RMSEA	<0.05	0.025	Yes
NFI	>0.90	0.904	Yes
CFI	>0.90	0.969	Yes
TLI	>0.90	0.966	Yes

, the results show that the data had an acceptable fit to the model: χ²/df =1.424; goodness-of-fit index (GFI) = 0.935; adjusted goodness-of-fit index (AGFI) = 0.915; root-mean-square error of approximation (RMSEA) = 0.025; normed fit index (NFI) = 0.904; comparative fit index (CFI) = 0.969; Tucker–Lewis index (TLI) = 0.966. The values above demonstrate the study model can be statistically accepted.

The hypotheses were verified using SEM. As shown in

Table 6. Summary of hypotheses validation.

Hypothesis	Path	Estimate	β	S.E.	C.R.	p	Result
H1	PU→ATT	0.415	0.413	0.061	6.853	***	support
H2	PE→ATT	0.334	0.337	0.060	5.583	***	support
H3	ATT→VI	0.574	0.545	0.064	9.003	***	support
H4	SI→PU	0.376	0.370	0.063	5.935	***	support
H5	IF→PU	0.344	0.353	0.060	5.583	***	support
H6	TR→PU	0.253	0.269	0.056	4.553	***	support
H7	PP→ATT	0.159	0.173	0.052	3.062	**	support

Note: *** p < 0.001, ** p < 0.01.

, the results verified that PU and PE had a positive and significant influence on ATT (β = 0.413, p < 0.001; β = 0.337, p < 0.001). However, PP showed a lesser effect on ATT (β = 0.173, p = 0.002). In addition, the results indicated that ATT had a significant effect on VI (β = 0.545, p < 0.001). As a result, H1, H2, H3, and H7 were all supported. Furthermore, in the context of short video social media platforms, SI, IF, and TR were antecedents of PU. All three factors had a significant impact on PU, supporting H4, H5, and H6 (β = 0.370, p < 0.001; β = 0.353, p < 0.001; β = 0.269, p < 0.001). In summary, Figure 2 depicts the hypotheses’ outcomes; all hypotheses were supported.

5. Discussion

Using the TAM framework, this study evaluated customers’ intentions toward visiting Universal Studios Beijing. In addition to PU and PE, which are common in traditional studies, the analysis revealed that PP had a beneficial effect on customers’ attitudes toward Universal Studios Beijing’s videos on TikTok. These three independent variables had a positive effect on customers’ intentions to visit, similar to prior research on how PU, PE, and PP affect customers’ views based on the TAM [5,62]. There are numerous causes for these effects.

First, once people decide that videos can help them understand the products or help them save time in planning trips, they may think the video is valuable or useful for them, which creates a positive attitude toward the video they watch [63]. Second, the ease of use of the application can drive the willingness of the customers [64]. Lastly, perceived playfulness plays an essential role in social media marketing, as perceived playfulness arouses customers’ intentions, which can lead to an increase in the satisfaction rate [65]. Furthermore, consistent with the findings of Zhao and Wang [7] and Munoz-Leiva et al. [50], the findings of this study showed that social interaction, informativeness, and trust all had a significant impact on customers’ perceived usefulness.

The current study additionally investigated the influence of TikTok content on PU. SI had a substantial effect on PU (β = 0.370, p < 0.001) compared to other factors. These results are consistent with those of Seol et al. [6] and Zhao and Wang [7], suggesting that social interaction is an antecedent of perceived usefulness. SI had an impact on PU because social interaction enables users to “like” or respond to other people’s reviews, giving them the opportunity to receive feedback from others and assist one another in the virtual world [14]. Moreover, high-quality social interactions can assist individuals in achieving their objectives and increase customer satisfaction on social networking sites [6].

Apart from social interaction, IF and TR also showed significant effects on PU. IF had a positive impact on PU (β = 0.353, p < 0.001), As identified by Dehghani et al. [49] regarding the value of informativeness on YouTube, video content on TikTok can provide customers with timely information about Universal Studios Beijing. The amount of information might draw customers’ attention to products and increase their trust in purchasing online [13]. Although TR had a lower effect (β = 0.269, p < 0.001), it still positively influenced PU, which is consistent with the results of Mou et al. [66]. The results suggest that the greater a customer’s trust in TikTok’s videos, the more determined they will be to make travel decisions [67].

In terms of the overall model, the current study confirms the suitability of the TAM for short video platforms, especially TikTok. Both PU and PE had a positive influence on ATT and VI. The most influential factors affecting the visiting intentions were PU (β = 0.413, p < 0.001) and PE (β = 0.337, p < 0.001). The PU and PE of TikTok and its content encourage customers to be more attentive when watching the videos [68]. When a customer believes that the information in a short video will help him or her understand the product or service better, the customer will have a more positive attitude toward the video [69]. Regarding the relationship between ATT and VI, in line with the research of Al-Maroof et al. [5], ATT exerted a significant effect on VI (β = 0.545, p < 0.001). The effect of ATT on VI was found to be influenced by whether customers liked the style of the short video or were willing to share the video with others [70,71].

PP is a significant predictor of ATT (β = 0.173, p = 0.002) alongside PU and PE. Similar to the discussions by Moon and Kim [12] and Blasco and Virto [55], adding perceived enjoyment/playfulness to the TAM demonstrates a beneficial influence on customers’ attitudes. However, this finding differs from the results of Praveena and Thomas [62]. Although PP still had a significant impact on ATT, it was not as significant as PU and PE probably because TikTok’s platform features are different from those of other social media applications. The results indicate that the pleasure of short videos can alter people’s attitudes toward video material and, consequently, their willingness to visit.

6. Implications

6.1. Academic Implications

The current study makes significant academic contributions from the following perspectives. First, this study extends and enriches the existing technology acceptance model. A new independent variable (perceived playfulness) is introduced under the social media context, which extends the TAM and aligns it with current trends in communication and entertainment.

Second, the study fills the research gap in the application of the TAM in the field of short video social media platforms. In contrast to the majority of previous research that has focused on long-form video platforms [5,49], this study innovatively applied the TAM to short-form video platforms (e.g., Tik Tok). The frequency of social interaction has always been regarded as a reflection of the social influence of customers, which further impacts product purchasing decisions [72]. Both social interaction and informativeness contribute to online behavior in the theory of rational action (TRA) [73] and the theory of planned behavior (TPB) [74].

Third, this study explores the antecedents that influence perceived usefulness in the short video context. Three factors are shown to be most significant to the perceived usefulness by integrating numerous pieces of literature [7,66]: social interaction, informativeness, and trust. Furthermore, these three antecedents are consistent with social influence theory, which helps social influence theory’s use in short video platforms as well.

Moreover, the current study also enriches the trust theory [75]. As a key factor that influences continuance intentions in expectancy confirmation theory [70,76], perceived playfulness was also demonstrated to have a positive impact on customer attitudes. Therefore, the results of this study expand the application scenarios of the traditional trust theory by exploring the role of trust in marketing from a short video social media platform perspective.

Lastly, in addition to validating the relationship between the variables and filling the void in the research of short video social media platforms, this study also explored a new area by focusing on the case of theme parks, which have rarely been studied by others. In previous studies, researchers have not investigated how short video social media platforms influence visiting intentions toward theme parks; their research stops at the general factors that influence such intentions [77,78]. This study can contribute to the literature by providing new ideas to fill the gap in the research with regard to studying the impact of perceived playfulness on the entertainment industry.

6.2. Managerial Implications

Apart from the academic contributions, the current research also provides unique managerial implications. First, this research makes recommendations for producers of short-form video content who would like to focus on content marketing (e.g., individuals, key leaders, and PR agencies). Real information and interactivity have a positive effect on tourists’ visiting intentions. Thus, content creators can gain a clear understanding of the directions to follow when creating content based on this study.

Second, this research provides new ideas and strategies for the development and planning of short videos that theme parks post on social media. Based on this study, customers’ perceived usefulness influences their attitudes toward videos and their visiting intentions. This finding encourages theme park operations teams to focus on perceived customer usefulness when planning and producing short videos to attract potential tourists in a sustained approach.

Furthermore, this study also recommends new operational strategies for short video social media platforms. Due to the critical importance of social interaction in influencing perceived usefulness, short video social media platforms should strive to improve video interactivity (e.g., online live streaming) in the future to increase perceived usefulness in the future.

From the perspective of advertisements, public relations, entertainment companies, and individual vloggers, content creation and planning should be considered when they work on the copywriting for the videos. As indicated by the results, video content plays an important role in attracting customers’ attention; thus, providing accurate information and greater interactivity can be a practical way of improving the customer’s purchasing intentions. In the digital marketing industry, businesses should pay more attention to content marketing and copywriting ability, which may raise effectiveness in marketing, thus increasing revenue.

There are implications for both the government and the relevant agencies. Because the popularity of short video social media platforms has given rise to new concepts for online purchasing, the government and relevant ministries are responsible for fostering a safe online business environment. They can regulate merchant sales conduct and examine whether the operation of social media platforms conforms with legislation by revising applicable policies or laws, which can assist in protecting customers’ rights. Moreover, some preferential policies to support cultural and creative industries can also be provided to help those companies or individuals in need.

Finally, the findings of this study have several implications for customers to avoid losses and maximize benefits. Customers should try to interact with other people if they want to obtain real experiential feedback on products or services. Measuring the number of “likes” or evaluating the authenticity of reviews posted by others can help them gain a better understanding of the goods.

7. Limitations

There are still some limitations to our study. First, Universal Studios Beijing was selected as the research object, but because the theme park had just opened, some interviewees did not have a deep understanding of it. More importantly, this research only studied people’s travel intentions and did not delve into the actual travel, so the experimental results may deviate somewhat from the actual number of tourists. More time is needed to conduct longitudinal research to determine the actual visiting behavior of customers. Furthermore, our study only discussed the relationship between social media and customer behavioral intentions based on the Chinese market, and this is worth studying in other countries.

Consequently, a variety of future research directions can be identified. First, future research could be undertaken longitudinally on the same theme park over time to ensure that a greater number of visitors already have a comprehensive understanding of Universal Studios Beijing before visiting. Moreover, the research framework of this study can also be applied to other theme parks throughout the world (e.g., Disney Parks) to examine the impact of perceived playfulness on tourists’ visiting intentions. Lastly, further studies of the relationship between social media (especially short video platforms) and customers’ behavioral intentions could also be extended to cases in other countries outside of China.