1 Introduction

With the development of information technology, travel-related consumer generated media (CGM)—platforms for users to share information through voluntary participation [1]—have become increasingly significant in the travel planning and decision-making process [2, 3]. The number of related studies is growing in parallel with the popularity of travel-related CGM, as represented by Tripadvisor. Examples include the perceived impact of CGM on the decision-making process of travelers [4], users’ intention to continue using CGM [5], methods to reduce the switching intention of Generation Z users [6], and credibility measures of CGM [7].

However, very few studies have explored content creation. Yoo and Gretzel [2] and Gretzel and Yoo [8] investigated the relationships between the personal characteristics (e.g. age and gender) of the creator, their personality, and content creation, noting that the content was mainly provided by a few users. Yoo and Gretzel [3] explored users’ motivations for commenting online. User-provided content is the basis of travel-related CGM [1], because millions would not visit Tripadvisor without the tips, recommendations, and advice from fellow travelers [9]. Moreover, as the impact of COVID-19 has subsided after two years, the number of planned trips in 2022 is expected to exceed that of actual trips in 2019 [10], and therefore, the use of travel-related CGM may significantly increase. Additionally, reviews of travel-related CGM, particularly long-form reviews, are helpful to potential travelers [11] to ascertain the destination’s COVID-19-related safety, security, and cleanliness standards [12]. Therefore, it is necessary to determine the factors that influence users’ intentions to use travel-related CGM to create and share content.

2 Theoretical Background and Research Hypotheses

2.1 Content Sharing

In this study, content sharing refers to the behavior of users posting word-of-mouth, reviews, and tips, based on their travel experiences and knowledge rather than the behavior of forwarding others’ content. Several studies have explored the motivations for content sharing. Yoo and Gretzel [3] examined whether helping service providers, concern for other consumers, the need for enjoyment/positive self-improvement, and venting negative feelings were motivations for users to post online travel reviews. However, the four aforementioned factors do not adequately cover all motivations; additional factors may also impact content sharing intention. Shao [13] suggested that users continue to use CGM because of its utility. Gagné [14] confirmed that ease of sharing may influence people’s intention to share. Therefore, the technology acceptance model (TAM) was chosen, which considers the relationships between perceived usefulness and ease of use of information technology and continued use [15]. Additionally, Park and Lee [16] argued that motivations for content sharing were divided into personal and social purposes. The uses and gratifications theory (U&G) describes the reasons why individuals use media from the perspective of gratification or psychological needs [17]. The theory of planned behavior (TPB) considers the influence of social and psychological factors on consumer behavior [18]. Both theories include factors related to personal and social purposes. Therefore, we constructed a research model using three theories; the possibility of their combination has been tested by a few studies [19, 20]. The combination of these three theories provides a more comprehensive understanding of the determinants of content sharing intention in travel-related CGM and how these factors influence users’ sharing intentions.

2.2 Technology Acceptance Model (TAM)

The TAM was proposed by Davis [15] based on the theory of reasoned action (TRA). Its purpose is to analyze the motivations of users of information systems to use new technologies; it has five components: perceived usefulness, perceived ease of use, attitude, behavioral intention, and system use. Perceived usefulness refers to the extent to which individuals believe their performance will improve by using a particular system [15]. Perceived ease of use implies the extent to which individuals believe they can effortlessly use a particular system [15]. Attitude is influenced by perceived usefulness and ease of use. The intention to use is influenced by perceived usefulness and attitude, and perceived ease of use also directly influences perceived usefulness. The TAM views information systems such as the Internet as a tool for improving user performance [21]. Fari [22] noted that despite the complexity of information sharing and knowledge sharing activities and processes, the TAM is a strong guide for knowledge sharing research. Using the TAM, this study intended to determine whether travel-related CGM would facilitate the sharing of travel-related information by users and increase their efficiency. Therefore, we propose the following hypotheses:

  • H1: Perceived usefulness positively influences users’ intention to share travel content.

  • H2: Perceived usefulness positively influences users’ attitude.

  • H3: Perceived ease of use positively influences users’ attitude.

  • H4: Perceived ease of use positively influences users’ perceived usefulness.

2.3 Uses and Gratifications Theory (U&G)

The U&G, proposed by Katz et al. [17], is primarily used to examine why and how individuals use media to meet their requirements. This theory propounds that individuals possess the ability to select media use [23]. Moreover, differences in media and information environments can result in different user gratifications [23]. Consequently, each study selects different dimensionalities to examine the factors that influence media use, depending on the nature of the media and purpose of the study. To examine users’ information sharing intention, Lee and Ma [24] investigated the effects of information seeking, socializing, status seeking, and entertainment on college students’ intentions to share the news on social media. Based on Lee and Ma [24], Thompson et al. [25] added the factor of passing time and modified information seeking to information sharing to examine whether the role of those gratifications differed across contexts, using ordinary social media users as subjects [25]. Additionally, Park and Lee [16] confirmed that reward is a powerful tool to motivate users to post content. However, these studies have only examined the relationship between gratifications and sharing intention; few studies have considered the relationship between gratifications and attitude. Wu and Kuang [23] confirmed that status seeking, social interaction, the norm of reciprocity, and information needs have a positive effect on attitude toward sharing health information using WeChat. They also noted that users with positive attitudes are more likely to share information [23]. On the basis of the aforementioned studies, and considering the characteristics of travel-related CGM, we hypothesized the following:

  • H5: Status seeking positively influences users’ attitude.

  • H6: Socializing positively influences users’ attitude.

  • H7: Entertainment positively influences users’ attitude.

  • H8: Information sharing positively influences users’ attitude.

  • H9: Passing time positively influences users’ attitude.

  • H10: Reward positively influences users’ attitude.

2.4 Theory of Planned Behavior (TPB)

The TPB, also a derivative theory of the TRA, was first introduced by Ajzen [26] as a psychological theory linking beliefs to behavior. There are five components of the TPB: attitude, subjective norm, perceived behavioral control, intention, and behavior. Subjective norm refers to the social pressure that individuals perceive when engaging in a particular behavior [27]. Perceived behavioral control implies an individual’s perception of the ease of engaging in a particular behavior [27].

To date, the TPB has been widely applied to explore information sharing behavior. Chen et al. [28] categorized perceived behavioral control into knowledge creation and web-specific self-efficacy. Finally, attitude, subjective norm, and web-specific self-efficacy were confirmed to have a positive effect on the intention to share knowledge [28]. Kuo and Young [29] examined how the TRA, TPB, decomposed TPB, and revised TPB predicted knowledge sharing behavior. It was shown that in the model, which had applied the TPB, all three concepts positively influenced the intention to practice knowledge sharing behavior [29]. However, the factors that influence users’ behavioral intentions vary across media and topics. Therefore, this study explores the relationships between attitude, subjective norm, perceived behavioral control, and intention to share travel-related content. The following hypotheses are thus proposed:

  • H11: Attitude positively influences users’ intention to share travel content.

  • H12: Subjective norm positively influences users’ intention to share travel content.

  • H13: Perceived behavioral control positively influences users’ intention to share travel content.

Hypothetical relationships in this study are shown in Fig. 1.

Fig. 1.
figure 1

Research model

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3 Methodology

3.1 Data Collection Procedures and Respondents

This study was conducted in Japan—a key market for Tripadvisor [10]. A screening questionnaire was distributed to 6,000 Japanese people by the Japanese research company FREEASY in August 2022. Based on data screening, we observed that although the largest proportion of respondents had posted travel content on Tripadvisor, there were also a certain number of users of local Japanese travel-related CGM. A total of 484 respondents who posted travel-related content on travel-related CGM in the past year were selected and surveyed. A total of 410 samples were collected, and after filtering out outliers and pattern answers, 355 valid responses were retained.

3.2 Measurement

This study used the scales validated in previous studies and modified them to fit the research scenario of travel content sharing on travel-related CGM. The original scales, in English, were translated into Japanese and reviewed by several scholars (including native Japanese speakers) who were familiar with both English and Japanese to ensure content validity, equivalence of meaning, and authenticity of expression. The TAM and TPB scales were adapted from Wu and Kuang [23], Davis [15], Park et al. [30], and Thompson et al. [25]. The items for the U&G were adapted from Wu and Kuang [23], Park and Lee [16], and Thompson et al. [25]. These items were rated on a 7-point Likert scale, ranging from “Strongly Disagree” to “Strongly Agree.”

3.3 Data Analysis

This study used SPSS Statistics version 26.0 for descriptive analysis. A partial least squares structural equation modeling (PLS-SEM) analysis using SmartPLS was then conducted to test the proposed hypotheses and model fit. The measurement and structural models were evaluated using the PLS algorithm and bootstrapping (5000 subsamples), respectively. As the research model in this study is complex and predictive, PLS-SEM is more flexible in dealing with complex models, small sample sizes, and non-normal data for predictive research [31]. Therefore, PLS-SEM is a more appropriate analytical tool in this study.

4 Results

4.1 Respondents’ Profiles

The respondents’ demographic characteristics are listed in Table 1. There were approximately 20% more male (60.28%) than female respondents (39.72%). Respondents were spread across a wide age-range, with a clear majority between the ages of 20 and 49 years. The frequency of using travel-related CGM to post content also varied from person to person, with 83.38% of the respondents posting content no more frequently than every 2–3 months. They also used a variety of websites, Tripadvisor being the most popular. The content posted by the respondents on the website was also highly informative (for content options, we referred to Yoo and Gretzel [2]). Commonly posted content includes personal experiences, local people, food and culture, practical travel information about destination, and general destination facts.

Table 1. Demographic characteristics of respondents (n = 355)
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4.2 Evaluation of the Measurement Model

First, Cronbach’s α and composite reliability (CR) were used to assess the reliability. As shown in Table 2, Cronbach’s α, CR values, and factor loadings were above the recommended threshold of .70 [31], ensuring internal consistency across all the constructs. Convergent validity of the model was also tested. All average variance extracted (AVE) values were greater than .50 [32], indicating no problems with convergent validity. However, when examining discriminant validity, the correlation coefficients for information sharing (IS) and socializing (SO) (.848) were higher than the square root of the AVE for IS (.832) and SO (.841); therefore, the discriminant validity was not satisfactory [32]. It is likely that the respondents were confused when answering because the two factors were conceptually proximate. Therefore, we conducted a chi-square difference test using AMOS [33] to assess the discriminant validity between IS and SO. The results showed that Δχ2 = 8.372, p < .01. Therefore, the discriminant validity can be reasonably accepted.

Table 2. Measurement model for constructs
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4.3 Structural Model and Hypotheses Testing

Before testing the structural model, the inner and outer variance inflation factors (VIF) were calculated and found to be less than four (1.488 –2.446), indicating no issues with multicollinearity [34]. The structural model was then assessed. The value of standardized root mean squared residual (SRMR) was .047, which was lower than the threshold of .05 [35]. Furthermore, all Q2 (predictive relevance) values were greater than zero (PU:0.518, ATT:0.520, INT:0.518), indicating that the exogenous latent variables had good predictive relevance [36]. Moreover, the proposed research model accounted for 69.9% of the variance in perceived usefulness, 69.3% in attitude, and 69.5% in the intention to share on travel-related CGM, signifying substantial R2 (explained variance) values [37]. This indicates that the goodness-to-fit of the structural model was good.

The results of hypotheses testing are shown in Fig. 2. Thirteen hypothesis paths were proposed in this study, of which five proved to be insignificant. Regarding the TAM’s component concepts, perceived usefulness (β = .084, p > .05) and perceived ease of use (β = -.103, p > .05) had no effect on attitude, thus, not supporting Hypotheses 2 and 3. Status seeking (β = -.001, p > .05), socializing (β = .022, p > .05), and passing time (β = .104, p > .05) in the U&G also had no effect on attitude, thus not supporting Hypotheses 5, 6, and 9.

Fig. 2.
figure 2

Results of structural equation model

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5 Discussion

Based on the analysis in the previous section, we obtained the following results: among the constituent concepts of the TAM, perceived usefulness significantly and positively influenced users’ intention to share. Perceived ease of use also had a significant impact on perceived usefulness and had the strongest influence of all paths—that is, the easier it was for users to operate, the more likely they were to perceive travel-related CGM as useful when sharing travel content. This makes travelers more likely to continue using websites to share content. However, perceived usefulness and perceived ease of use did not significantly affect attitude—a result that differed from expectations. In this era of information technology, most people have posted information online at some point of time, be it in the form of text or images. Therefore, the usefulness and ease of use perceived by users may not be strong enough to influence their attitudes toward using travel-related CGM to share content.

Among the six paths associated with the U&G, entertainment, information sharing, and rewards directly influenced users’ attitudes. Furthermore, the relationships between status seeking, socializing, passing time, and attitude were insignificant. This suggests four things. First, users can gain pleasure from content sharing. Second, they are willing to express themselves by sharing content and obtaining useful information from others’ feedback. Third, they want to receive some financial benefits from sharing content. Fourth, gaining reputation and visibility, acquiring social satisfaction, and alleviating boredom are not significant influencing factors for users’ attitudes. Probably the main reason for this result is that the majority of respondents do not post content through travel-related CGM very frequently, which makes it difficult to achieve higher status and find communication opportunities with others. Meanwhile, it hardly provides the effect of passing time in daily life. Another possible reason for the differences is the cultural background. When Liu et al. [38] used the New Orleans dataset for analysis, it indicated that when Tripadvisor members were at a lower status, they were eager to improve their rank and gain knowledge as they communicated with others. This differs from the results of our study, which necessitates further research.

Attitude, subjective norm, and perceived behavioral control in the TPB have all shown to significantly and positively influence users’ intention to share. These results are consistent with those of previous studies. This implies that those who hold a positive attitude toward content sharing are more likely to share information on travel-related CGM. Those who are supported by the people around them, particularly those who are confident of their abilities, also tend to share information.

6 Conclusion

6.1 Implications for Theory

This study makes three contributions from a theoretical perspective. First, it extends the U&G, TAM, and TPB to the context of content sharing by travel-related CGM users. It also examines the factors that influence users’ intention to create and share content on travel-related CGM from three perspectives: technical, social, and psychological, and how they influence it. The results again test the possibility and validity of combining the TAM, TPB, and U&G. The TAM and TPB can be used to understand the different factors that influence behavioral intention; however, they do not consider the impact of users’ voluntariness. Mohebbi et al. [19] argued that much of the background to supporting research related to these two theories is mandatory adoption. The U&G suggests that users actively choose to use a medium to satisfy their wants and requirements [17], which compensates for the limitations of the TAM and TPB. Next, previous studies have mostly examined the direct relationships between gratification-related factors and behavioral intention or actual behavior [21, 25], and few studies have examined the relationships between gratification-related factors and attitude. This study provides a solid theoretical basis for this hypothesis.

6.2 Implications for Practice

This study has several practical implications. Based on the data analysis, this study makes the following suggestions. First, according to the evaluation objects, different description dimensions can be shown in the input box for users to choose. For example, the evaluation of a restaurant can be set as the dimensions of service, taste, and hygiene. Suppose users choose a service dimension, the system automatically populates “Service:” and users can then directly write their views. It can provide some convenience when writing, as well as encourage users to provide more details. Second, it is significant to enable users to feel happy and express themselves through content sharing. Content posted by users can be judged by a human or machine to determine if it is worthy of recommendation. Thereafter, big data will filter out people who may be interested/have similar experiences based on historical browsing records, dwell time, liked and favorited content, etc., and recommend the content to them. This allows reviewers and other users to exchange views, share positive emotions, or release negative ones. Third, travel-related CGM can be associated with mainstream social media because subjective norms affect intention to share. This allows users to share the content they create with those around them and receive a more diverse range of opinions from relatives and friends. A few local Japanese travel-related CGM such as 4travel and UTRAVEL NOTE offer the service of sharing reviews via Twitter or Facebook, whereas on Tripadvisor, users can only share via email or links. Fourth, Liu et al. [39] demonstrated that reviewers with high-level badges posted more content, but the quality of the content was lower. This study found that rewards increase users’ positive attitudes toward content sharing. Therefore, it is advisable to collaborate with other booking platforms to offer better discounts to high-level reviewers who consistently provide high-quality content, than to merely high-level reviewers. Additionally, regular contests should be held to reward or offer extra points to the most valuable newly posted content and reviews. Travel-related CGM managers can also organize regular events, such as “Write a Review Day” [11]. Guidance on writing reviews can improve reviewers’ narrative skills and self-confidence, thereby encouraging them to produce more and higher-quality content. Through these methods, administrators can not only retain and motivate experienced users, but also attract novice users to share their travel experiences. This will increase user activity throughout the site, improving site sustainability.

6.3 Limitations

This study has a few limitations. First, separate studies have not been conducted on different websites. Each website has its own characteristics, and different services bring different experiences to users; therefore, separate investigations are required to obtain more focused conclusions. Furthermore, the Japanese market was used as the subject of this study; however, Tripadvisor [10] has revealed many differences in usage between users in Japan and other countries. The cultural context of each country may lead to different results. Therefore, further analyses in other countries are required to verify the generalizability of the results. Finally, there are many types of gratification within the U&G, but only six were selected for this study. Future studies should explore whether other types of gratification also influence users’ intention to share content.