Does a Video Blog Positively Influence Consumers’ Travel Decision Planning?

1. Introduction

According to the statistics of UNWTO in 2017, the number of international tourist arrivals had been grow about 7% to 1,323 million (World Tourism Organization, 2018). On the rapidly growing tourism sectors especially in Asia and Pacific, the digital revolution has strongly developed at the forefront in changing traditional travel systems. The Internet has fundamentally shifted a new form of travel-related communication that consumers can exchange or create travel information as quickly as possible (Buhalis and Law, 2008). The growing availability of internet access further lead to the creation of social networking sites such as Facebook or YouTube. Web 2.0 is a term that end users can utilize as a platform which content are created in a collaborative interaction instead of the era of Web 1.0 (Kaplan and Haenlein, 2010). With the advent of Web 2.0 technologies, customers expect to generate more value and service actively for determining their own travel experiences. In terms, users not only can gain information they need, but also publish their own content to others online (Ridings et al., 2002).

Increasingly, travellers tend to rely on reviews commented on virtual communities to plan their journeys rather than only following content from official websites (Buhalis and Law, 2008; Litvin et al, 2008). The creation of UGC are nowadays fundamentally observed identifiable which straightforward states in high-degree richness information is transmitted (Kaplan and Haenlein, 2010). According to Arsal et al. (2008), user-generated content related to travel sources can help travellers obtain useful information to determine what choices or tours are suitable for them. In addition, it significantly influences on travel decision planning when booking hotels online (Ye et al., 2011). Online consumer reviews are considered more trustworthy than provided by companies, which third-party websites are more preferably regarded as a belief or expectation (Park et al., 2007; Senecal and Nantel, 2004). Recently, people are already involved in UGC sites actively as part of travel decision planning before or during the trip. Individuals can express their personal thinking, opinions and reactions efficiently in virtual communities despite what it might relatively be positive or negative viewpoints (Dellarocas, 2003). Owing to the peer-to-peer communication formed by consumers with similar interests, those reviews or opinions are more likely to be accepted and believed as decision planning on travel purpose (Smith et al., 2007). This shows that UGC helps facilitate information sharing and has a profound effect on travel decision planning.

A video blog, shortened to vlog, which is a record of individual’s thoughts, opinions or experiences filmed that upload often on video sharing communities and websites (Raby et al., 2018). Alongside the spread of Web 2.0 applications, the most well-known of UGC websites especially YouTube incredibly takes lead to the most popular online social activity, which online participants daily view nearly 100 million videos (Latham et al.,2008). Vlogs have been described as user-generated content or videos, a form of online publishing that allow people to view and comment on (Gao et al., 2010). As Bruce (1996) indicated, videos can facilitate the emotional expressions when viewing that this new technology can transform the boundaries by changing communication to foster intimacy (Milliken et al, 2008). The tourism industry has been now dominated by social media comprised of text, images and videos via social networking sites, review sites, blogs and even video blogs, which build on technological foundation of Web 2.0 that stimulate travel discussions and change travellers’ behaviour with regards to information search and travel planning (Kaplan and Haenlein, 2010; Xiang and Gretzel, 2010). Prior work conducted by Ayeh et al. (2013a),Ayeh et al. (2013b),Fotis et al. (2012)andChen et al. (2014), for instance, show that user-generated content are reliable and useful for consumers to make decision and plan for journey. More tourism researches have demonstrated that Travel recommendations on UGC can potentially influence the travel decision over accommodations, restaurants and destinations as well as UGC enables consumers to reduce perception of risk on identifying worse products or service with the improving of decision planning (Gretzel and Yoo, 2008; Dickinger, 2011; Filieri and McLeay, 2014; Fotis et al., 2012). Other study have illustrated that travel blog narratives play an important role on driving consumers’ enjoyment on travel that could be key for identifying factors (Magnini et al., 2011).

In a recent study from YouGov (2018), over half of Americans tend to watch vlogs on platforms like YouTube or Facebook and millennials take lead to 72% compared to people ages 55 and over. As for a wide variety of genres in vlogs, educational vlogs are the most popular type for watching and more than half also watch travel-related vlogs. Specially, they are more likely to search for a product online by watching vlogs, which vlogs can be one of methods for facilitating some purchase decisions. Researches on vlogs that significantly have an impact on consumers’ purchasing behaviour in recent years, especially on beauty and luxury brand products (Kim et al., 2011; Loiacono et al., 2007; Lee andWatkins, 2016;Munnukka et al, 2019).As for a survey conducted by Gretzel and Yoo (2008), it showed that almost 80% of travellers prefer collecting information from other consumers during planning trips for pleasure. On the other hand, it could help generate value-added experiences and aggregated pieces of information to users in travel decision-planning process (Neuhofer et al., 2013).

Nevertheless, notwithstanding the growing popularity of social media, research findings suggest that have started to questioned the reliability of UGC, criticising not as more valuable to trust on due to the fake glowing reviews posted by managers or staff (Cox et al., 2009; Bray and Schetzina, 2006; Smith et al., 2007). Despite the importance of video blogs, little is known about the specific relevance of vlogs characteristics on Taiwanese consumers’ behaviour related to travel purpose. Consequently, this study presents an investigation of user-generated content, focusing on video blogs which cognitive factors affecting travel consumers attitude to use for the purpose of travel planning.

This study addresses the challenge by answering the following question:

RQ. Does a video blog positively influence consumers’ travel decision planning?

The rest of the paper is structured as follows. First, we provide a review of previous studies pertaining to the relevant variables considered in this work. Then formulating several hypotheses and explain data collection and measure validation processes. While the study demonstrates the reliability and validity of model to the context of vlogs usage for travel planning. It goes further to verify the significant roles of distinctive factors such as their perception of trustworthiness, usefulness, novelty and enjoyment as well as linking to behavioural intention and demographic factors towards it. The final session gives the conclusion with some remarks through result analysis.

2. Literature review

The emergence of Web 2.0 has revolutionised the Internet in a significant way by making interaction and collaboration with users. It provides benefits for second generation based on online communities and services. In the other hands, customer value has been created by the way of searching, gathering, sharing and communicating with in the form of integration towards Web 2.0 (Sigala, 2011). On a different level, consumers transform Web into user-driven information to easily evaluate travel alternatives, no longer dominated by travel providers (O’Connor, 2008). As a result, the potential impact of Travel 2.0 worldwide on travel users can be dedicated to shape travellers’ preference and planning process.

2.1 The impact of user-generated content in tourism

The growing importance of user-generated content (UGC), it refers to media content that produced in a virtual community by users not marketers, which includes texts in forums, digital videos on Facebook, blogs or video blogs on YouTube and podcasting (Van Dijck, 2009). As the distribution of Web 2.0 is adopted for user-generated platforms, every user can be more accessible to publish own content or comment on people’s posts. In terms, Fernando (2007) indicated that UGC is different from traditional media since it is created by consumers rather than marketers. In an online context, UCG has effectively helped travellers engage in a virtual community that enables them to understand more completely towards others’ travelling experience (Wang and Fesenmaier, 2004; Ye et al., 2011). Moreover, online travel reviews are significantly regarded as critical information towards determining hotel bookings, which makes user-generated content increasingly be adopted for travel planning (Litvin et al, 2008; Sigala et al, 2001). In the tourism domain, online content produced by users on social media platforms can be mainly affected from the perception of changing towards travel destinations during decision-making process (Marhiori andCantoni, 2015). With the rapid growth of user-generated content online, it was also claimed that information provided by travel agency websites is less influenced to consumers’ planning process compared to those from relevant travellers (Gretzel et al., 2007).

However, it is not necessary to be all positive influence for consumers in planning journey via UGC. Cox et al. (2009) investigated that UGC is not considered the most trustworthy for consumers. While people tend to accept the information provided by tourism websites, which is more well-structured and useful to enhance incorporation of business-to-consumer strategies. Furthermore, if user-generated content is negative created by releasing frustration or anger, the impact would not be as strong as positive UGC to change consumers’ mind (Wetzer et al., 2007). The power of UGC is sometimes criticised as fake content based on travel operators who might pretend consumers to make comments online (Bray and Schetzina, 2006). It can easily be concerned about how users enable using UGC for decision planning process as the content is no longer objective and independent.

Among the vast array of information sources on the Web, UGC has increasingly played an important role in tourist decision making and continuingly changes forms of tourism-related information for decision (Blackshaw and Nazzaro, 2006; Litvin et al, 2008). During the Web 2.0 era in travel planning, increasing number of users are significantly affected by UGC especially on social media platforms due to the function that makes users more accessible to gain information from travellers’ sharing content (Fotis et al, 2012). From consumers’ perspective in travel decision, they expect to obtain information which is enjoyable or sincere as user-generated content, instead of too perfectly posed photos or much more commercial texts, consumers usually take qualitative reviews and feedback as superior from prior experiences to take action selecting travel attractions or hotels (O’Connor, 2008).

2.2 Trustworthiness

As trust is studied in different disciplines such as marketing and psychology or transactive relationship between sellers and buyers (Ganesan and Hess, 1997). Within state conceptualization of trust, it has been understood as the willingness to take risks in a relationship (Deutsch, 1960). Mayer et al. (1995) further defined trust as the willingness to be vulnerable to actions of another party that will behave while other perform based on the expectation in order to control others. Referred to the framework provided by Mayer et al. (1995), belief-based as perceived trustworthiness can affect the degree of trust which encompass three dimensions: ability, benevolence and integrity. Marketing research has focused on belief-based conceptualization of trust regarded as perceived trustworthiness, which perform confidence of credibility and benevolence towards a particular objective (Gefen et al., 2003; Doney and Cannon, 1997).

According to Hovland et al. (1953), trustworthiness is the degree of communicator’s proposition to what extent to he or she considers most reliable. As the internet becomes more persuasive, trustworthiness of information is particularly complex and increasingly too reluctant to be harmful due to high accessibility of digital information (Fritch & Cromwell, 2001; Park et al., 2002). Trust is particularly key for quality and expertise as information, which enables people to engage in communication and maintain a network to make them seek for advice in form of high perception of reliability (Tseng and Fogg, 1999). In the existing literature, trustworthiness can affect the attitude in the context of persuasibility of communication which messages created from individual’s rather then non-opinionated production can be highly trustworthy (Ohanian, 1990). In the context of this study, this is taken to mean prospective travellers’ attitudes and intentions to watch vlogs for travel planning are influenced by their perception of its trustworthiness for this purpose.

2.3 Usefulness

In the view of understanding the antecedents of travellers’ intention to watch vlogs for travel planning, thetechnology acceptance model (TAM) is regarded as the important role of consumer using behaviour towards Internet technology products in explaining customers’ acceptance and adoption of new technology applications (Davis et al., 1989). This model has been validated in variety of studies with which researchers finding it is appropriate for explaining individual’s behaviour and intention of adopting in new technology (Adams et al., 1992; Straub et al., 1997). According to Davis et al. (1989), perceived usefulness is defined as the degree of which individual believe that using this system can help improve job performance. Nonetheless, TAM model of studies has been criticised for lack of task focus when applying as well as task-technology fit can be more constructed and useful than TAM alone (Dishawand Strong, 1999; Goodhue and Thompson, 1995). As for the TAM model adapted from the Theory of Reasoned Action (TRA), it is assumed that an individual’s perception of usefulness can affect his/her attitude and behavioural intention towards the use of that system (Davis et al., 1989; Ajzen and Fishbein, 1980; Workman, 2014;Persico et al., 2014; Casaló et al., 2011; Huh et al., 2009). In the content of this study, perceived usefulness is taken to be one of components which influenced for travel purpose of planning by watching vlogs.

2.4 Novelty 

The term of novelty is associated with emotion which highly affect or stimulate reactions (Clark and Fiske, 2014). As previous stated, novelty is consistent with positive orientation of characteristics of during adoption of a technology (Fichman and Kemerer, 1993). Innovativeness is the term of seeking new or unique products or service which may be related to the brand or an individual behaviour. More specifically, perceived novelty can be defined as the degree to which subjective perception of a user expresses new and unusual to an existing technology (Wells et al., 2010). In terms, it reflects the view of a technology as fresh and interesting compared to the original of use. Consequently, perceived novelty can be one of a variable about how individuals adopt a new technology or information systems such as the rising of video blogs. Flavell (1977) noted that novelty seeking seems to represent an inherent attribute for information. Complementary for its functions, consumers tend to seek information about new products and pertain to consumption situations to enhance his/her performance (Hirschman, 1980). Further, Lee and Crompton (1992) proposed that novelty in tourism to what the extent to perception of objects such as landmarks, environment or people. Within a traveller’s blog, the information which can be perceived to be identifiably different from existing one (Chen et al., 2014).Perception of novelty therefore can be the important character in exploring the tourist decision planning (Jang and Feng, 2007; Chen et al., 2014).

2.5 Enjoyment

The term of novelty is associated with emotion which highly affect or stimulate reactions (Clark and Fiske, 2014). As previous stated, novelty is consistent with positive orientation of characteristics of during adoption of a technology (Fichman and Kemerer, 1993). Innovativeness is the term of seeking new or unique products or service which may be related to the brand or an individual behaviour. More specifically, perceived novelty can be defined as the degree to which subjective perception of a user expresses new and unusual to an existing technology (Wells et al., 2010). In terms, it reflects the view of a technology as fresh and interesting compared to the original of use. Consequently, perceived novelty can be one of a variable about how individuals adopt a new technology or information systems such as the rising of video blogs. Flavell (1977) noted that novelty seeking seems to represent an inherent attribute for information. Complementary for its functions, consumers tend to seek information about new products and pertain to consumption situations to enhance his/her performance (Hirschman, 1980). Further, Lee and Crompton (1992) proposed that novelty in tourism to what the extent to perception of objects such as landmarks, environment or people. Within a traveller’s blog, the information which can be perceived to be identifiably different from existing one (Chen et al., 2014).Perception of novelty therefore can be the important character in exploring the tourist decision planning (Jang and Feng, 2007; Chen et al., 2014).

2.6 Attitude and Behavioural intention

Based on Fishbein and Ajzen (1977), attitude is kind of learning method to respond with a particular object in a positive or negative pattern. As Davis et al. (1989) defined, TAM model include attitude towards the use of technology. In the framework of this scholar’s research, attitude is defined as the degree of evaluation that influence individuals’ beliefs to take action using specific system for work (Davis et al., 1989). Triandis (1979) also mentioned that attitude can be an individual’s positive or negative behaviour forming towards innovation adaption. In terms, customer attitude is comprised of one’s perception about the given object in behavioural intention to make decision (Polatoglu and Ekin, 2001). Among a research from Ajzen and Fishbein (2000), it was indicated that attitude can be formed through different stage of value which motivates to be in favour of or not. Traditionally, behavioural intention is referred to an individual’s likelihood of predicting actual behaviour in decision making (Ajzen and Fishbein, 1980). Further, it is regarded as attitude-behaviour relationship is possibly mediated by intention, whereas Bentler and Speckart (1981) criticised there is no influence if intention has been controlled. With established by Davis et al. (1989), behavioural intention is relatively predicted to a positive attitude, not only in the use of social media or other technology systems (Litvin et al, 2008; Casaló et al., 2011; Huh et al., 2009)but also leading to strong intention to shop online (Limayem et al., 2000). 

2.7 The impact of Video Blogs

Due to Web 2.0 era, different structure of information can be quickly spread worldwide. Specially, blogs are the common trend that offer new forms of interactivity and co-creation, which consumers tend to build up information of trust from blogs and even be more willing to purchase (Munnukka et al, 2019).  Nowadays, video blogs (vlogs) are typically considered as user-generated content that users have authority to publish their own content within different forms of video rather than only texts mostly on YouTube platform, which visualization for vlogs are more appealed to viewers compared to traditional blogs (Van Dijck, 2009; Zhang et al, 2009). The use of vlogs are established in the more direct and interactive space for providers to express their opinions and engage with their subscribers, this form of content creation can educate and entertain with others by sharing opinions . In terms, Parboteeah (2005) showed viewers can certain extent to be satisfied with hedonic needs via watching vlogs. Moreover, majority of consumers are more likely to be controlled if watching vlogs before purchasing, which perceptions can be easily differentiated from luxury brands (Lee and Watkins, 2016).

Basically, marketer-generated information usually includes commercial elements that are uploaded from official accounts of brands, whereas user-generated content such as vlogs can be strongly influenced on purchasing intention because of high perceived-credibility from vloggers as fellow ordinary consumers (Moran et al, 2014). In addition to the trustworthiness of vlogs, creativity are also considered as key element for willingness to view. Crompton (1979) defined that novelty of content plays an important role in travel decision making, which influenced the perceived to be new or creative for viewers. It is easily attracted for viewers due to the novel content and quality of videos, which creative vlogs can be impressed from people and take advantage of positive responses within purchasing whatever consumers are desire to (Till and Baack, 2005). With several genres of vlogs such as beauty, lifestyle, fashion, food and even travel, it can bring viewers inspiration of thoughts and make them live up to expectation, capturing a new way of creating content and making engaging with audiences. Distinct from other online communication channels, vlogs are constituted of video content that leads to higher perception of interestingness and enjoyment within more interactive combination for viewers (Frobenius, 2011).

Unlike previous studies, it is revealed that when vlogs are exposed to advertising disclosure can increase young adolescents’ negative attitude towards watching sponsored vlogs (De Jans et al., 2018). As for Rahmi et al. (2016), there is no significant effect of beauty vlogs on consumers’ purchase intention, in terms that consumer perceptions of trustworthiness does not mediate the vlogs towards purchase intention on beauty products. Additionally, vloggers who express their personality trait can negatively influence consumer buying-intention if they are rated lower (. Pornpitakpan (2004) also mentioned that consumers belonged to collectivistic cultural orientation are more likely to trust information provided by traditional celebrities rather than vlogs as digital celebrities.

Recent studies have investigated the role of user-generated content or consumer-generated media in information search for travel planning process (Litvin et al, 2008; Fotis et al, 2012; Cox et al., 2009), the effect of e-WOM on hotel bookings or travel decision (Ye et al., 2011; Gretzel and Yoo, 2008), the impact of travel blogs on destination making (Pan et al., 2007; Akehurst, 2009)and how vlogs influence purchase intention (Munnukka et al, 2019; Lee and Watkins, 2016; Till and Baack, 2005). However, the determinants of vlogs usage for the travel planning purpose have rarely been explored. Therefore, this study will focus on the unexplored area regarding to different aspects of vlogs content for viewers’ perception and understand how these can be influenced to attitude for watching vlogs and behavioural intention.

3. Conceptual model and hypotheses

Many variables related to consumers’ perception of technology acceptance have been identified in previous literature. The framework for this research is formed with TAM model, intrinsic motivation theory, trustworthiness and novelty. It operationalises how these motives of perception affect individuals’ acceptance of vlogs. Based on the previous concepts and description, a conceptual model was generated and present in Figure 1. More detailed assumptions related to association toward each variable will be put forward below.

Trustworthiness is considered to be the fundamental predictor of consumers’ acceptance of a message in user-generated content (Hovland et al., 1953; McGinnies and Ward, 1980). On the whole, it has shown that travellers can have higher perception of trustworthiness within UGC related to travel sources and be beneficial from its impact (Yoo et al., 2009). Research in the travel and tourism has provided evidence that UGC is equally or more important with respect to official providers, which greatly influenced as more authentic feelings of what consumers had experienced and even more desire to establish the trustworthiness than traditional marketing communications (Inversini et al., 2009; Litvin et al, 2008). Consumers increasingly rely on the Internet to obtain information and advice, which negative online messages are perceived more credible towards attitude on credence goods on the contrary to experience goods (Pan and Chiou, 2011). It can be easily manipulated with more accessibility of information that perception of trustworthiness is seek for to facilitate in the process of decision-making or planning. When it comes to key findings from previous studies, the credibility of travellers’ reviews based on their experiences are more trustworthy and reliable for users on travel-oriented website such as TripAdvisor, showing that trustworthiness is an important predictor towards attitude and intention for travel purpose of seeking advice (Gretzel, 2007; Casaló et al., 2011; Ayeh et al., 2013a; Ayeh et al., 2013b). On the basis of perceived level of influence such as trustworthiness towards travel destination choices, previous research revealed that over half percentages of respondents could high-possibly make changes from existing plans due to user-generated content found in third parties instead of official tourism websites (Fotis et al, 2012). In existing literatures, trust has been recognised as a character that affect consumers’ purchasing behaviour as well as strongly direct the tourist decision planning (Akehurst, 2009; Gretzel and Yoo, 2008; Ayeh et al., 2013a; Casaló et al., 2011). In view of this, the following hypothesis is proposed.

H1: Perceived trustworthiness positively influences attitude towards watching vlogs for travel planning.

Several researches showed strong support for the impact of perceived usefulness on attitude and intention (Casaló et al., 2011; Huh et al., 2009; Ayeh et al., 2013a; Porter and Donthu, 2006; Yang and Yoo, 2004). An individual’s attitude towards use of the technology can be positively influenced when being more useful (Porter and Donthu, 2006). Moon and Kim (2001) also explained that perceived usefulness is key for determining the attitude on the use of World-wide-web. In tourism, Casaló et al. (2011) and Huh et al. (2009)found thatperceived usefulness strongly form a positive attitude toward relying on advice in online travel communities and use of information system. Ayeh et al (2013a)also confirmed that perceived usefulness can affect consumers’ attitude and behavioural intention to use consumer-generated media for travel planning. Furthermore, perception of usability can be more favourable to improve attitude on use of travel 2.0 websites such as TripAdvisor or Facebook (Muñoz-Leiva et al., 2012). In the context of adoption of UGC for travel planning, perceived usefulness relates to the individual’s perception that will make decision more effectively. Hence, Chung et al. (2015) posited that perceived usefulness is a key determinant of use of UGC on social media for travel information acquisition. As for understanding the great development of presence of online travel communities, Agag and El-Masry (2016) demonstrated that consumers can be potentially facilitated attitude towards participating in travel communities due to greater perception of usability on advances of technology. In previous studies, it has not explicitly been explored the role of perceived usefulness as a antecedent of watching vlogs for travel planning. It is therefore expected that consumers’ perception of usability on information via vlogs will have a positive effect on their attitude towards watching vlogs for travel planning.

H2: Perceived usefulness positively influences attitude towards watching vlogs for travel planning.

Apart from TAM model of perceptions mentioned above, perceived novelty is a up-and-coming antecedent for technology acceptance or travel intention. As Herlocker et al. (2004) pointed out that the concept of novelty has been recently expanded to positive recommendations for users. It is also claimed by Vargas and Castells (2011)that novelty is suitable for online recommendation, which can be adapted for measuring whether vlogs are influential in this study. Perceived novelty represents a significant influence on perception of brand and attitude to use related products or service (Wells et al., 2010), which can be taken into account with the model to be mediated by attitude. Flight et al. (2011)emphasize on perception of innovation when evaluating a new product or adoption of technology on attitude towards an IT innovation. It also appears to be a key determinant of attitude (Bodur et al., 2000). The importance of novelty factor has been claimed that it can influence travellers feel highly distinctive with bloggers’ experiences when reading travel blogs before or during travelling (Chandralal et al., 2015). If the content of travel blogs maintain in a familiar level with no additionally new sources to keep attractive, they might feel bored and no pleasure to make trip planning (Jang and Feng, 2007). On this account, perceived novelty stands in an important factor to focus on in this researh. Besides, Lee and Crompton (1992)measured the construct of novelty can motivate pleasure seekers to plan for journey or travel. With respect to novelty, there is regularly creating new desire to change online environments for potential consumers, associated with intention to use the internet as a retailing platform (Ming-Sung Cheng et al., 2009). However, although video blogs become more popular in consumer behaviour or tourism, it is still uncleared about impact of video blogs on travel planning examined by perceived novelty. As a result, with the search for novelty being positioned as a perception of vlogs for travel planning, this research presents the following hypothesis.

H3: Perceived novelty positively influences attitude towards watching vlogs for travel planning.

A number of studies have shown that perceived enjoyment as an intrinsic motivation directly influences attitude toward using information technologies (Davis et al., 1992; Moon and Kim, 2001; Kim et al., 2007; Venkatesh et al., 2002; Lee et al., 2007). Moon and Kim (2001) demonstrated the importance of enjoyment in individual-level of technology acceptance, which is highly related to intention on use of world-wide web. According to Ayeh et al. (2013a), individual’s perceived hedonic benefits can positively influence intention to use social media for travel planning. Besides, it has shown that participating in online travel communities with fun can make travellers feel enjoyable for travel planning (Gretzel et al., 2007). Indeed, it also has been proved that enjoyment is an important predictor with use of social media for planning on travel purpose (Kang and Schuett, 2013). Based on gender differences, it was found that females are more likely to perceive hedonic value about travel review on sites in terms of reaching travel decision planning process compared to males (Gretzel and Yoo, 2008). As shown in the result of perceived enjoyment analysed from Ryu et al. (2009), the elderly can perceive more intrinsic value of benefits based on the user-generated videos, while potentially identifying this antecedent can be one of major to participate in vlogs in this case. From different perspectives, perceived enjoyment can be a key construct that shows continuity of usage of blogs can be affected by the value of blog use experience (Nysveen et al. 2005; Serenko et al. 2007; Shiau and Luo, 2013). When experiencing a blog or social media website, travellers inherently tend to be immersed in using as perceiving enjoyable from involving activities (Hsu and Lin, 2008). It has also been proposed perceived enjoyment as a determinant of behavioural intention (Venkatesh, 2000; Lee et al., 2005). This may lead to influential part of travellers’ planning process for shaping attitude towards vlogs. Therefore, the hypothesis below is proposed.

H4: Perceived enjoyment positively influences attitude towards watching vlogs for travel planning.

Based on Fishbein and Ajzen (1977), attitude is kind of learning method to respond with a particular object in a positive or negative manner. As related theory such as the theory of planned behaviour knows, attitude towards behaviour intention refers to the degree to which an individual behaves favourably or unfavourably on specific evaluation (Ajzen, 1991). In the framework of TAM constructs, it has a direct effect on attitude towards behavioural intention on using e-learning in university (Park, 2009). Similar to online environment, it supported a strong positive effect on attitude towards online purchasing to intention to purchase online (Vijayasarathy, 2004). In terms, BAYAZIT et al. (2017) also described that attitude towards word-of-mouth as interactive communication depending on different perception of vlogs can absolutely foster intention for online shopping. Surprisingly, there is still overthrown as no significant relationship between attitude and behavioural intention for choosing travel destination (Lam and Hsu, 2006).

When it comes to attitude towards vlogs to intention, consumers tend to have a long-term relationship within levels of perception about luxury brands that vlogs can increase the likelihood of behavioural intention to repurchase after attitude forming (Lee andWatkins, 2016). Which shows that customer attitude is gradually important for linking to behavioural intention. Based on the source credibility, content published by vloggers with brand-related information or experiences can relatively influence audience’s attitude towards brands (Munnukka et al, 2019). Within the last decade, attitude has adopted in majority of research for mediating a dependent variable. This mediator implies to watch vlogs for travel planning in this case. A study from Ayeh et al (2013a)got a result illustrating that attitude perfectly plays a critical role on mediation between partial perception of user-generated content via videos and behavioural intention to use for travel planning. Similarly in online travel communities, Casaló et al. (2011)also found that the attitude is strongly related to intention to follow advice from the community. This relationship has been empirically evident in consumer behaviour (Fishbein and Ajzen, 1977)and even documented in mainstream of positive link between attitude and use intention (Venkatesh, 2000; Muñoz-Leiva et al., 2012; Huh et al., 2009; tom Dieck et al., 2017; Shin and Kim, 2008)in recent years. In light of the above, we therefore hypothesize as follow. 

H5: attitude towards watching vlogs for travel planning positively influences behavioural intention to watch vlogs for travel planning.

4. Research methodology

4.1 Data collection

The online survey built on the web platform of Qualtrics, was employed to collect data from individuals who come from Taiwan watch vlogs to search for travel information and take trip planning. The survey composed of 6 single-choice questions about demographic characteristics and 6 questions that the respondents had to answer with seven-point Likert scale. Before heading to pages for answering questions, there is provided a travel video blog from one of Taiwanese YouTuber called壹加壹, decided to make sample for participants to understand how vlogs present travel information to the public.

The respondents for the study were selected from individuals in Taiwan who have been watching vlogs before in purpose of whether for entertaining, purchasing products such as cosmetic goods, travel decision planning and so on. This survey also collects a wide range of age groups and both genders of users to ensure what difference linked to these relationships. It was opened for sixteen days (3^rd July to 18^th July).

The travel consumers who participated to this study had experiences in the use of vlogs for travel planning (e.g. determining accommodations, attractions or restaurants), which was assessed in a specific way. The respondents were asked to select an option related to the habit of what online resources for travel planning as well as for frequent usage of vlogs per week and per time. Participants were given approximately 5 minutes to fill in the survey anonymously, and a total of 329 consumers responded. However, not all surveys were fully completed such as outliers or missing cases, 319 usable questionnaires were included in the analysis.

4.2 Measures

The measures were adapted to make them applicable to the study’s context. Trustworthiness was measured by a scale developed Ohanian, R. (1991) and recently used by Flanagin et al. (2000)in perception of internet information credibility research. Usefulness was measured through a scale developed by Davis et al. (1992)for the use of computers in the workspace with extrinsic and intrinsic motivation. The scale used to measure novelty towards watching vlogs was similar to which adopted in a study about destination revisit intention (Jang and Feng, 2007). Enjoyment was measured to use a scale derived from Davis et al. (1992) which is adapted same source as previous mentioned and used in Lee et al. (2005) related to acceptance of internet-based learning medium. When it comes to a mediator of attitude, it was measured by Moon and Kim (2001) for WWW usage. The ultimate aim was to measure behavioural intention to watch vlogs for travel planning through a scale utilized by Ayeh et al. (2013a) and Venkatesh et al. (2003)in CGM and technology acceptance studies. According to the method of scale, seven-point semantic differential scale was employed for the measurement of attitude. The items of remaining constructs were measured by using a seven-point Likert-type scale ranging from (1) strongly disagree to (7) strongly agree.

4.3 Sample profile

The demographic characteristics of the sample are presented in Table 2. The target population for the study was Taiwanese individuals who had experiences for watching travel vlogs on travel purpose. This sample was primarily composed of 37% of males and 63% of females. Respondents ranged from under 18 to 55 or older of age. With a majority of percentages were distributed across 18-24 (26.6%) and 45-54 (21.9%) age groups. In regards of employment status, 51.7% of the respondents were in primary; 21.9% of the respondents were in secondary and rest of percentages were in self-employed, out-of-work, homemakers, retired or other situation. The participants rarely had habits to watch vlogs relevant to travel information (44.8%) or 1-2 times on a week (38.2%). Finally, with regard to online methods of planning for trips, the majority of respondents (48.9%) adopted travel video blogs as their primary way compared to checking in travel review websites, online travel agency or viewing travel-related content on social media.

Table 2

Profile of respondents (n=319).

4.4 Data analysis

Before analysing association with each variable and hypotheses testing, reliability and validity of measurement items and scales are primary task to be tested. The data of this study was then analysed using statistical software SPSS (25.0).

For scale reliability and validity, internal consistency (Cronbach alpha and composite reliability (CR)), confirmation factor analysis (factor loadings) and convergent validity (average variance extracted (AVE)) were tested. Factor loadings are necessary to be calculated and then determine which items of each variable are desirable to adopt for. Alpha reliability coefficients were calculated for the identified factors. If Cronbach alphas values greater than 0.07 are the reference of whether obtaining good values or not (Cronbach, 1951). As similar as Cronbach alpha, CR is an indicator as being assessed to evaluate usable items in each variable. If CR values are higher than 0.6, these items are acceptable to use in following testing (Fornell and Larcker, 1981).

After completing measurement of reliability, confirmatory factor analysis is used to determine how well the hypothesized model fits to the data provided from survey, which reflects to the variations in response to observe potentially lower number of underlying variables. The overall model fit was measured using the normed chi-squared fit index (NFI)

References

Adams, D.A., Nelson, R.R., and Todd, P.A. 1992. Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication,î MIS Quarterly (16:2), pp. 227-247

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour.

Ajzen, I. and Fishbein, M. 2000. “Attitudes and the attitude-behaviour relations: Reasoned and automatic processes”. In European review of social psychology, Edited by: Stroebe, W. and Hewstone, M. 1–33. Chichester, , United Kingdom: Wiley.

Akehurst, G. (2009). User generated content: the use of blogs for tourism organizations and tourism consumers. Service Business 3( I): 51-61.

Arsal, I., Backman, S., & Baldwin, E. (2008). Influence of an online travel community on travel decisions. In Information and communication technologies in tourism 2008 (pp. 82-93). Springer, Vienna.

Ayeh, J. K., Au, N., & Law, R. (2013a). Predicting the intention to use consumer-generated media for travel planning. Tourism management, 35, 132-143.

Ayeh, J. K., Au, N., & Law, R. (2013b). “Do we believe in TripAdvisor?” Examining credibility perceptions and online travelers’ attitude toward using user-generated content. Journal of Travel Research, 52(4), 437-452.

Bentler, P. M., & Speckart, G. (1981). Attitudes `cause’ behaviors: a structural equation analysis. Journal of Personality and Social Psychology, 40(1), pp. 22-238.

Blackshaw, P., and Nazzaro, M. ( 2006). Consumer-generated Media (CGM) .Word-of-Mouth in The Age of the Web-fortified Consumer. New York: Nielsen Buzz Metrics.

Bruce, V. (1996). “The Role of the Face in Communication: Implications for Videophone Design.” Interacting with Computers, 8(2), 166-176.

Buhalis, D., & Law, R. (2008). Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research. Tourism management, 29(4), 609-623.

Casaló, L. V., Flavián, C., & Guinalíu, M. (2011). Understanding the intention to follow the advice obtained in an online travel community. Computers in Human Behavior, 27(2), 622-633.

Chen, Y. C., Shang, R. A., & Li, M. J. (2014). The effects of perceived relevance of travel blogs’ content on the behavioral intention to visit a tourist destination. Computers in Human Behavior, 30, 787-799.

Wetzer, I. M., Zeelenberg, M., & Pieters, R. (2007). Never eat in that restaurant, I did!: Exploring why people engage in negative word-of-mouth communication. Psychology and Marketing, 24, 661–680.

Bray, J., & Schetzina, C. (2006, Fall). Travel 2.0: Harnessing the power of user-generated content and tagging. Hospitality Upgrade, Fall, 28–29.

Clark, M. S., and Fiske, S. T. (Eds.). (2014). Affect and cognition: 17th annual Carnegie Mellon symposium on cognition. Psychology Press.

Crompton, J. L. (1979). Motivations for pleasure vacation. Annals of tourism research, 6(4), 408-424.

Deutsch M. 1960. Trust and suspicion. Journal of Conflict Resolution 2: 265–279.

Fichman, R. G., & Kemerer, C. F. (1993). Adoption of software engineering process innovations: The case of object orientation. Sloan Management Review, 34, 7–22.

Filieri, R., & McLeay, F. (2014). E-WOM and accommodation: An analysis of the factors that influence travelers’ adoption of information from online reviews. Journal of Travel Research, 53(1), 44-57.

Flavell, J. H. (1977). Cognitive development. London;Englewood Cliffs;: Prentice-Hall.

Fritch, J.W., & Cromwell, R.L. (2001).Evaluating Internet resources: Identity, affiliation, and cognitive authority in a networked world. Journal of the American Society for Information Science and Technology, 52(6), 499–507.

Frobenius, M. (2011). Beginning a monologue: The opening sequence of video blogs. Journal of Pragmatics, 43(3), 814–827.

Ganesan S, Hess R. 1997. Dimensions and levels of trust: implications for commitment to a relationship. Marketing Letters 8(4): 439–448

Gao, W, Tian, Y, Huang, T. (2010) Vlogging: a survey of videoblogging technology on the Web. ACM Computing Surveys 42(4): 1–57. 

Hirschman, E. C. (1980). Innovativeness, novelty seeking, and consumer creativity. Journal of consumer research, 7(3), 283-295.

Huh, H. J., Kim, T. T., & Law, R. (2009). A comparison of competing theoretical models for understanding acceptance behavior of information systems in upscale hotels. International Journal of Hospitality Management, 28(1), 121-134.

Jang, S. S., & Feng, R. (2007). Temporal destination revisit intention: The effects of novelty seeking and satisfaction. Tourism management, 28(2), 580-590.

Kim, H. W., Gupta, S., & Koh, J. (2011). Investigating the intention to purchase digital items in social networking communities: A customer value perspective. Information & Management, 48(6), 228-234.

O’Connor, P. (2008). User-generated content and travel: A case study on Tripadvisor. com. Information and communication technologies in tourism 2008, 47-58.

Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers’ perceived expertise, trustworthiness, and attractiveness. Journal of advertising, 19(3), 39-52.

Pan, L. Y., & Chiou, J. S. (2011). How much can you trust online information? Cues for perceived trustworthiness of consumer-generated online information. Journal of Interactive Marketing, 25(2), 67-74.

Pan, B., MacLaurin, T., & Crotts, J. C. (2007). Travel blogs and the implications for destination marketing. Journal of Travel Research, 46(1), 35-45.

Parboteeah, D.V. 2005. A Model of Online Impulse Buying: An Empirical Study, Doctoral Dissertation, Washington State University.

Park, H.W., Barnett, G.A., & Nam, I.‐Y.(2002). Hyperlink‐affiliation network structure of top web sites: Examining affiliates with hyperlink in Korea. Journal of the American Society for Information Science and Technology, 53(7), 592–601.

Persico, D., Manca, S., & Pozzi, F. (2014). Adapting the technology acceptance model to evaluate the innovative potential of e-learning systems. Computers in Human Behavior, 30, 614-622.

Pornpitakpan, C. (2004). The persuasiveness of source credibility: A critical review of five decades’ evidence. Journal of Applied Social Psychology, 34(2), 243-281.

Raby, R., Caron, C., Théwissen-LeBlanc, S., Prioletta, J., & Mitchell, C. (2018). Vlogging on YouTube: the online, political engagement of young Canadians advocating for social change. Journal of Youth Studies, 21(4), 495-512.

Rahmi, Y., Sekarasih, L., & Sjabadhyni, B. (2016). The influence of beauty vlog on perceived source credibility and purchase intention. Makara Hubs-Asia, 20(2), 13-23.

Ridings, C. M., Gefen, D., & Arinze, B. (2002). Some antecedents and effects of trust in virtual communities. The Journal of Strategic Information Systems, 11(3-4), 271-295.

Smith, D, Menon, S and Sivakumar, K (2007) Online peer and editorial recommendations, trust and choice in virtual markets. Journal of Interactive Marketing, 19 (3) pp 15-37.

Straub, D., Keil, M., and Brenner, W. ìTesting the Technology Acceptance Model Across Cultures: A Three Country Study,î Information & Management (33:1), 1997, pp. 1-11.

Till, B. D., & Baack, D. W. (2005). Recall and persuasion: does creative advertising matter?. Journal of Advertising, 34(3), 47-57.

Tseng, S., & Fogg, B.J. (1999). Credibility and computing technology. Communications of the ACM, 42(5), 39- 44.

Cox, C., Burgess, S., Sellitto, C., & Buultjens, J. (2009). The role of user-generated content in tourists’ travel planning behavior. Journal of Hospitality Marketing & Management, 18(8), 743-764.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), pp.319-339.

Dellarocas, C (2003) The digitization of word-of-mouth: Promise and challenges of online feedback mechanisms. Management Science, 49 (10), pp 1407-1424.

De Jans, S., Cauberghe, V., & Hudders, L. (2018). How an advertising disclosure alerts young adolescents to sponsored vlogs: The moderating role of a peer-based advertising literacy intervention through an informational vlog. Journal of Advertising, 47(4), 309-325.

Dickinger, A. (2011). The trustworthiness of online channels for experience-and goal-directed search tasks. Journal of Travel Research, 50(4), 378-391.

Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task–technology fit constructs. Information & management, 36(1), 9-21.

Doney PM, Cannon JP. 1997. An examination of the nature of trust in buyer-seller relationships. Journal of Marketing 61(1): 35–51.

Fotis, J. N., Buhalis, D., & Rossides, N. (2012). Social media use and impact during the holiday travel planning process (pp. 13-24). Springer-Verlag.

Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS quarterly, 213-236.

Gefen D, Rao VS, Tractinsky N. 2003. The Conceptualization of Trust, Risk and Their Relationship in Electronic Commerce: The Need for Clarifications

Gretzel, U, Hyan-Yoo, K and Purifoy, M (2007) Online Travel Review Study: The role and impact of online travel reviews. Laboratory for Intelligent Systems in Tourism, College Station.

Gretzel, U., & Yoo, K. H. (2008). Use and impact of online travel reviews. Information and communication technologies in tourism 2008, 35-46.

Hovland, C.I., Janis, I.L., & Kelley, H.H. (1953). Communication and persuasion. New Haven, CT, US: Yale University Press.

Latham, G. P., Borgogni, L., & Petitta, L. (2008). Goal setting and performance management in the public sector. International Public Management Journal, 11(4), 385-403.

Lee, T. H., & Crompton, J. (1992). Measuring novelty seeking in tourism. Annals of tourism research, 19(4), 732-751.

Lee, J. E., & Watkins, B. (2016). YouTube vloggers’ influence on consumer luxury brand perceptions and intentions. Journal of Business Research, 69(12), 5753-5760.

Limayem, M., Khalifa, M., & Frini, A. (2000). What makes consumers buy from Internet? A longitudinal study of online shopping. IEEE Transactions on systems, man, and Cybernetics-Part A: Systems and Humans, 30(4), 421-432.

Litvin, S. W., Goldsmith, R. E., & Pan, B. (2008). Electronic word-of-mouth in the hospitality and tourism management. Tourism Management. 29 (3). 458-468.

Loiacono, E. T., Watson, R. T., & Goodhue, D. L. (2007). WebQual: An instrument for consumer evaluation of web sites. International Journal of Electronic Commerce, 11(3), 51-87.

Magnini, Vincent P., John C. Crotts, and Anita Zehrer. (2011). “Understanding Customer Delight: An Application of Travel Blog Analysis.” Journal of Travel Research, 50 (5): 535-45.

Marchiori, E., & Cantoni, L. (2015). The role of prior experience in the perception of a tourism destination in user-generated content. Journal of Destination Marketing & Management, 4(3), 194-201.

Mayer RC, Davis JH, Schoorman FD. 1995. An integrative model of organizational trust. Academy of Management Review 20(3): 709–734.

Milliken, M., Gibson, K., O’Donnell, S., & Singer, J. (2008). User-generated online video and the Atlantic Canadian public sphere: A YouTube study.

Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38, 217–230

Moran, G., Muzellec, L., & Nolan, E. (2014). Consumer moments of truth in the digital context: How “search” and “e-word of mouth” can fuel consumer decision making. Journal of Advertising Research, 54(2), 200-204.

Munnukka, J., Maity, D., Reinikainen, H., & Luoma-aho, V. (2019). “Thanks for watching”. The effectiveness of YouTube vlogendorsements. Computers in Human Behavior, 93, 226-234.

Neuhofer, B., Buhalis, D., & Ladkin, A. (2013). High tech for high touch experiences: A case study from the hospitality industry. In Information and Communication Technologies in Tourism 2013 (pp. 290-301). Springer, Berlin, Heidelberg.

Kim, H. W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of mobile internet: an empirical investigation. Decision support systems, 43(1), 111-126.

Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business horizons, 53(1), 59-68.

Inversini, A., Cantoni, L., & Buhalis, D. (2009). Destinations’ information competition and web reputation. Information Technology & Tourism, 11(3), pp.221-234.

Senecal, S., & Nantel, J. (2004). The influence of online product recommendations on consumers’ online choices. Journal of retailing, 80(2), 159-169.

Sigala, M. (2011). eCRM 2.0 applications and trends: The use and perceptions of Greek tourism firms of social networks and intelligence. Computers in Human Behavior, 27(2), 655-661.

Sigala, M., Lockwood, A., & Jones, P. (2001). Strategic implementation and IT: gaining competitive advantage from the hotel reservations process. International Journal of Contemporary Hospitality Management, 13(7), 364-371.

tom Dieck, M. C., Jung, T. H., Kim, W. G., & Moon, Y. (2017). Hotel guests’ social media acceptance in luxury hotels. International Journal of Contemporary Hospitality Management, 29(1), 530-550.

Triandis HC (1979). Values, attitudes and interpersonal behaviour. Unpublished paper, University of Nebraska Press, Lincoln, NE.

Vallerand, R. J. (1997). Toward a hierarchical model of intrinsic and extrinsic motivation. In Advances in experimental social psychology (Vol. 29, pp. 271-360). Academic Press.

Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision sciences, 33(2), 297-316.

Van Dijck, J. (2009). Users like you? Theorizing agency in user-generated content. Media, culture & society, 31(1), 41-58.

Xiang, Z., & Gretzel, U. (2010). Role of social media in online travel information search. Tourism management, 31(2), 179-188.

Wang, Y., & Fesenmaier, D. R. (2004). Towards understanding members’ general participation in and active contribution to an online travel community. Tourism Management, 25, 709–722.

Wells, J. D., Campbell, D. E., Valacich, J. S., & Featherman, M. (2010). The effect of perceived novelty on the adoption of information technology innovations: a risk/reward perspective. Decision Sciences, 41(4), 813-843.

Workman, M. (2014). New media and the changing face of information technology use: The importance of task pursuit, social influence, and experience. Computers in Human Behavior, 31, 111-117.

World Tourism Organization (2018), UNWTO Tourism Highlights, 2018 Edition, UNWTO, Madrid

Ye, Q., Law, R., Gu, B., & Chen, W. (2011). The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings. Computers in Human behavior, 27(2), 634-639.

YouGov. (2018). Vlog watching is especially popular among minorities | YouGov. [Online]. [Accessed 20 Jul. 2019]. Available from: https://today.yougov.com/topics/technology/articles-reports/2018/12/12/vlog-watching-more-popular-among-minorities

Zhang, X., Xu, C., Cheng, J., Lu, H., and Ma, S. 2009. Effective Annotation and Search for Video Blogs with Integration of Context and Content Analysis. IEEE Transactions on Multimedia, 11(2), 272-285.