FEEL LIKE TAKING A TRIP?
An examination into the relationship between personality and intention to travel
through the use of travel vlogs and the role that communication can play in this.
Master Thesis
MSc. in Business Administration – Marketing Track University of Amsterdam
Author: Stephanie van Eerd Student ID: 11422262
Submission Date: 25 January 2018, final version Supervisor: Prof. dr. Ed Peelen
Statement of originality
This document is written by Student Stephanie van Eerd who declares to take full
responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no
sources other than those mentioned in the text and its references have been used in
creating it.
The Faculty of Economics and Business is responsible solely for the supervision of
completion of the work, not for the contents.
Table of Contents
Abstract ... 5
Introduction ... 6
Literature Review ... 9
User Generated Content and Travel 2.0 ... 9
Vlogging ... 11
Personality as a stable measure for analyzing consumers ... 12
Effective communication ... 14
Hypotheses formulation ... 16
Method ... 22
Design ... 22
Participants and Procedure ... 22
Measures ... 23
Results ... 26
Regression Analyses ... 28
Nonverbal communication and verbal communication as moderators ... 31
PROCESS Model for Moderators ... 34
Discussion ... 40
Implications ... 44
Limitations and Directions for Future Research ... 45
References ... 47
Appendices ... 55
Appendix A: Distributed survey ... 55
Appendix B: Hierarchical Regression Model for Travel Intention ... 61
Appendix C: Object Points MCA ... 62
Index of Tables and Figures Tables
1 Descriptive Statistics, Reliability and test-retest Reliability 2 Pearson’s Correlation Matrix
3 Simple Linear Regression: Standardized Regression Coefficients with Confidence Intervals to estimate the effects of Extraversion, Emotional Stability, Openness to Experience, Agreeableness and Conscientiousness on Intention to Travel
4 Hierarchical Multiple Regression: Standardized Regression Coefficients with
Confidence Intervals to estimate the effects of Age, Gender, Nationality, Openness to Experience, Extraversion, Agreeableness, Conscientiousness and Emotional Stability on Intention to Travel
5 Transformed Correlation Matrix Dimension 1 6 Transformed Correlation Matrix Dimension 2 7 Multiple Correspondence Analysis Output
8 PROCESS: Unstandardized OLS Regression Coefficients with Confidence Intervals to estimate Nonverbal and Verbal Communication as Moderators within Extraversion and Age as a Control Variable
9 PROCESS: Unstandardized OLS Regression Coefficients with Confidence Intervals to estimate Nonverbal and Verbal Communication as Moderators within
Conscientiousness and Age as a Control Variable 10 Reporting Hypothesis Outcomes
Figures
1 Conceptual Framework
2 Output Squared Correlation Ratios
3 PROCESS Model 2
4 Extraversion PROCESS 5 Emotional Stability PROCESS 6 Openness to Experience PROCESS 7 Agreeableness PROCESS
Abstract
In a society that is now more technologically advanced than ever before, the boundaries between consumers continue to diminish as the rise of User Generated Content (UGC) nowadays enables consumers and businesses to share truly everything. As a result, this type of content has started to shape the decisions that consumers make in their lives, and has particularly begun to further develop the travel industry. A new and relatively unexplored phenomenon within both UGC and the travel industry that has experienced a rapid rise in popularity refers to the notion of (travel) vlogs, which consumers are starting to consult more and more to make their travel decisions. However, despite of the above, is there a way to ensure the effectiveness of these vlogs? How do we know what consumers consider to be important aspects of the vlog and can we actually predict how consumers will respond to the vlog itself?
This paper examines the effectiveness of travel vlogs in the perspective of the viewer and uses personality as a measure to determine the intention to travel based on a presented vignette study, applied to sample of 342 participants. Furthermore, verbal and nonverbal communication choices are explored as potential moderators within this relationship. Results indicate that personality, based on the Big Five, is not as strong of a predictor for future decision-making as initially expected. More specifically, the presented travel vlog showed not to be effective in terms of convincing any personality to travel to the destination. However, the introduction of verbal and nonverbal communication does seem to increase the overall intention to travel, and thus shows potential for further exploration. Moreover, particularly the extraversion trait seems to appreciate the use nonverbal communication, whereas the trait of conscientiousness does not respond favorably to verbal communication. This paper aims to contribute to the limited research
regarding the effectiveness of vlogging within the travel industry, to add to both the theoretical knowledge as well as the managerial implications in this relatively new field.
Introduction
The evolution of social media has become a popular topic of debate (Elliott, 2016; Akehurst, 2008; Hernández-Méndez, Muñoz-Leiva & Sánchez-Fernández, 2012; O’Reilly, 2005) with the Internet becoming part of everyday lives (Correa, Hinsley & De Zúñiga, 2009). The ability for online users to co-create, maintain and update social media content has started to revolutionize society in the sense that social media has started to dominate and even replace traditional ways of communication and has become a major driver in the way we behave (Fotis, Buhalis & Rossides, 2012). Within recent years, the rise of User Generated Content (UGC) now enables consumers to create and share their thoughts and experiences online (Elliott, 2016; O’Reilly, 2005; Kaplan & Haenlein, 2010), which has in turn diminished any former boundaries between these consumers (Hanna, Rohm & Crittenden, 2011), leading them to increasingly consult the web for any form of daily advice (Xiang & Gretzel, 2008; Cox, Burgess, Sellitto & Buultjens, 2009). With these technological developments occurring at such a rapid pace, research is yet to catch up to comprehending why and how consumers respond to this.
Industry wise, particularly the travel industry has greatly become affected by UGC (Yoo & Gretzel, 2011; Del Chiappa, 2011; Cox et al., 2009; Xiang & Gretzel, 2008) as consumers find it very difficult to estimate the quality of their trip and therefore seek the opinion of others (Park & Nicolau, 2014; Cox et al., 2009). A recent type of UGC that has gained a significant amount of popularity in a short amount of time is known as vlogging, in which a vlogger (also known as a content creator) shares opinions and experiences with a viewer through a virtual space
(Frobenius, 2014).Vlogging has become the most expressive and remote way of communication between consumers to date (Gao, Tian & Huang, 2010; Aran, Biel & Gatica-Perez, 2014) and assists consumers (viewers) in accurately estimating the quality of experiences (Park & Nicolau, 2014; Cox et al., 2009). With an industry that is so competitive (Hassan, 2000) and with the rise of a new phenomenon that creates an effective and credible way to influence an immense amount of consumers (Nusair, Bilgihan, & Okumus, 2012), the effectiveness of travel vlogs will become increasingly important to examine, as they will influence consumers in their intention to travel to destinations (Crowel, Gribben & Loo, 2014).
This study will therefore focus on comprehending the increasingly powerful role of the consumer in the unexplored phenomenon of travel vlogs. A popular theory that is often used to identify and describe personalities is known as the Big Five personality traits theory (Gosling, Rentfrow & Swann, 2003). As this theory is also known for its success in analyzing the social media engagement and actions of consumers, (Correa et al., 2009; Hughes, Rowe, Batey & Lee, 2012; Ryan & Xenos, 2011; Seidman, 2012), this theory will act as the foundation to make predictions about each viewer based on their personality. Secondly, the way vlogs are communicated will also be examined, as there is a noticeable debate with regards to what type of communication is most effective and whether this is nonverbal (Biel, Tsiminaki, Dines & Gatica-Perez, 2013; Biel & Gatica-Gatica-Perez, 2010; Sarkar, Bhatia, Agarwal & Li, 2014) or verbal communication (Frobenius, 2014; Sanchez-Cortes, Kumano, Otsuka & Gatica-Perez, 2015; Biel & Gatica-Perez, 2010; Hsiao & Lan, 2013). Authors recognize the importance of communication for the success of vloggers (Biel & Gartica Perez, 2010; Sarkar et al., 2014; Frobenius, 2014; Gievska & Koroveshovski, 2014; Sanchez-Cortes et al., 2015; Biel & Gatica-Perez, 2010), but previous studies have yet to specifically compare the effectiveness of verbal and nonverbal
communication to another. In this case, verbal communication will be measured through items developed by Chen, Dwyer and Firth (2015) that their sample considers to be important when they share, recommend and consider travel destinations. Nonverbal communication will be measured through facial expressions that were used in online conversational videos by Biel, Teijeiro-Mosquera and Gatica-Perez (2012).
Hence, the overall aim of this study is to determine what the relationship is between each
personality and their intention to travel to the destination based on the travel vlog and whether the type of communication moderates this relationship. This study will provide managerial
contributions for both the content creators (vloggers) as well as for the travel industry. Firstly, it will be the first to examine the (travel) vlog from the perspective of the viewer and will discuss the importance of personality in this respect, so that the vlogger can better tailor and design their travel vlogs. This will automatically contribute to the knowledge and research within the travel industry, as the importance of travel vlogs will continue to increase to promote destinations (Crowel et al., 2014) and thus successful partnerships with vloggers will become essential. Secondly, it will also be the first to analyze differences in the effectiveness of verbal and nonverbal communication within this context for vloggers to further personalize their content and to understand the results of doing so. Lastly, it adds to the theoretical knowledge of whether personality can be considered as a stable measure to make travel intention predictions and whether the introduction of communication increases travel intention in the travel vlog context.
The method of investigation will consist of a correlational quantitative approach to discover what personality each participant has and to establish how eager he or she is towards intention to travel based on a presented vignette study. As a next step, participants receive an explanation about the two types of communication and are then asked to select two
communication choices that they feel would be most effective in persuading their travel intention. After this, participants are asked how effective they find their communication selection in their intention to travel.
The following paper will initiate with a literature review in which UGC, Travel 2.0 and vlogging are elaborated upon. The literature review will then introduce the major theories that will be incorporated into this research, which include the Big Five Personality traits theory and the use of verbal and nonverbal analyses. As a next step, the method will be explained, followed by the actual results of this study. Finally, the discussion will reveal the significance of the findings and highlight implications as well as limitations and future research.
Literature Review User Generated Content and Travel 2.0
Within the rapid social media developments, a concept known as UGC in which users publish and enable peer-to-peer interactions and experiences (Elliott, 2016; O’Reilly, 2005; Kaplan & Haenlein, 2010) has recently become very popular due to its massive reach potential (Hernández-Méndez et al., 2012; Rosenbloom, 2004), its affordability and simplistic form of communication (Pan, MacLaurin and Crotts, 2007). With every industry or any type of consultation available within UGC nowadays, particularly the travel and the hospitality industry appear to be consulted often as peers find it difficult to estimate the perceived expected quality of their stay or experience (Park & Nicolau, 2014; Cox et al., 2009) and therefore turn to the web for advice (Nusair et al., 2012; Cox et al., 2009).
Today’s technological developments has given rise to Travel 2.0, which involves a fairly new set of tools to evaluate travel ideas and destinations through UGC tools such as social
networks, interactive websites and blogs (Hernández-Méndez et al., 2012). A study conducted by Yoo and Gretzel (2011) revealed that over half of the online travelers consult the web for planning their travel trips and that the majority of their sample trusts this information. More recent, users have become heavily dependent on Travel 2.0 and use it to generate travel ideas before, throughout and after the travel trip (Del Chiappa, 2011; Cox et al., 2009; Xiang & Gretzel, 2008). In addition to this, Jani, Jang and Hwang (2014) found that 93.6% of their entire sample that consults the Internet, uses it specifically for destination information, confirming Travel 2.0 has become indispensable. As users are easily able to search for specific information, they are becoming more and more able to accurately search for relevant sources regarding the potential destination (Hernández-Méndez et al., 2012).
Within this search, particularly travel blogs have received a great amount of attention and research (Akehurst, 2008; Wang, Beatty & Foxx, 2004; Hernández-Méndez et al., 2012; Wang, 2012; Lin & Huang, 2006; Wenger, 2008; Schmallegger & Carson, 2008). These blogs contain an individual’s written thoughts about travel stories and destination experiences, usually with frequent updates and in chronological order (Akehurst, 2008). The major advantage of using such sources is the ability to see or hear about how someone else finds the travel and destination experience, which has led to the surge in the consumer’s trust for consulting this type of source (Dickinger, 2011; Akehurst, 2008; Fakharyan, Reza, & Elyasi, 2012; Senecal & Nantel, 2004; Hernández-Méndez et al., 2012). Whereas some authors argue that blogs have increasingly gained the reputation of becoming more credible and popular than traditional ways of communication (Akehurst, 2008; Fotis et al., 2012), other authors contend that offline word of mouth (WOM) remains more valuable in travel planning than any other ways of communication
(Hernández-Méndez et al., 2012; Mack, Blose & Pan; 2008, Cox et al., 2009) as social media may not produce reliable content.
Vlogging
A relatively new phenomenon that actually works on integrating the traditional WOM into a new form of blogging to make the entire experience more credible and reliable refers to the notion of vlogging (Elliott, 2016; Foster, 2014; Gao et al., 2010; Wen, Yonghong, Tiejun & Qiang; 2010; Haider, Cerrato, Luz & Campbell, 2016). A vlog refers to a video created by a content creator in which he or she shares opinions and experiences first hand in a video type of format, making it much more expressive than former ways of communication (Gao et al., 2010; Aran et al., 2014). The content creator, also known as the vlogger, shares a virtual space with his or her audience and communicates in a one-directional way to them (Frobenius, 2014). Vlogging has experienced a massive increase and development online, with millions of communicators, particularly those on YouTube (Burgess & Green, 2009) actively involved on a daily basis (Nusair et al., 2012). In 2014, YouTube had over one million content creators on an international scale with numbers still on the rise (Sanchez-Cortes et al., 2015). As a result, major travel players recognize the importance of collaborations with vloggers to promote their experiences and destinations (Fritsch, 2016).
This new phenomenon further builds upon the technological advancements of UGC and appeals to the broad young audience that is constantly active on the Internet today (Gao et al., 2010; Nusair et al., 2012). Once anyone in the audience decides to actively become part of the channel or community, they develop emotional ties (Koh & Kim, 2004) and a relationship based on trust with these channels and communities (Casaló, Flavián, Guinalíu, 2011). As a result, vlogging gets its prosperous reputation from the fact that even though the majority of vlogging
interaction is occurring between strangers (Zapatero, Brandle & San-Roman, 2013), the connection that the audience experiences has resulted in vlogs becoming a major source of consultation for them (Gibson, 2016). This is why it plays into traditional WOM to a greater extent than blogging does, as the audience feels more acquainted to the person telling the story. With regards to the rise of this concept within the travel industry, there has been an exponential increase in viewers consulting travel vlogs for experiences and advice (Crowel et al., 2014).
Personality as a stable measure for analyzing consumers
So what do we know about these viewers? With the audience becoming increasingly more powerful and important in today’s online community, the interest in the reasoning and thoughts behind their choices has also arisen (Xiang & Gretzel, 2008). Several research papers have been written in terms of consumers and their responses to Travel 2.0. Casaló, Flavián, Guinalíu and Ekinci (2015) for example researched how feelings such as perceived risk and uncertainty generate a preference for positive reviews whereas Yoo & Gretzel (2011) demonstrate how differences in characteristics such as age, gender, income level and culture influence opinions about social media. However, there is a large area of future research left for what is perhaps regarded as the most stable measure of someone’s behavior over time, which is the notion of personality (Decrop, 2006; Woszcynski, Roth & Segars, 2002). Personality can be defined as “the coherent pattern of affect, behavior, cognition and desire over time and space, which are used to characterize a unique individual” (Alam & Riccardi, 2014, p. 1). Studies recognize the importance of personality as a measure as it includes dispositions, strategies and patterns of an individual’s life-long behavior (Costa & McCrae, 1988; Hogan, Hogan & Roberts, 1996) and due to its reliability across cultures (Jani et al., 2014).
Furthermore, the recognition of personality as a major determinant for travel decisions has also received significant attention from scholars to date (Nickerson & Ellis, 1991; Madrigal, 1995; Roehl & Fesenmaier, 1992; Griffith & Albanese, 1996; Amichai-Hamburger & Vinitzky, 2010; Jani et al., 2014; Decrop, 2006, Yoo & Gretzel, 2011) and with the Internet (Jani et al., 2014) and particularly vlogging (Crowel et al., 2014) becoming a major source for Travel 2.0, there is a need to better understand the personality of the online consumer in the Travel 2.0 context today (Jani et al., 2014; Ferweda, Schedl & Tkalcic, 2015; Fesenmaier, Xiang, Pan & Law, 2010; Beldona, Morrison & O’Leary, 2005; Cox et al., 2009).
A popular, reliable and stable theory for recognizing and categorizing personality refers to the Big Five personality traits theory (Gretzel, Mitsche, Hwang & Fesenmaier, 2004). This hierarchical personality traits model divides participants into five potential personality categories, which are: extraversion, neuroticism, openness to experience, agreeableness and conscientiousness (Gosling et al., 2003). Each of these categories is bipolar (e.g. extraversion vs. introversion) and is accompanied by specific traits (John & Strivastava, 1999). Extraversion refers to someone’s degree of sociability, neuroticism is about the amount of anxiety and emotional stability they have, openness reflects curiosity and intellectual interests, agreeableness regards sympathy and being helpful and lastly, conscientiousness is about being organized and having discipline (Bai, Zhu & Cheng, 2012). This theory has been used to better understand consumers and their engagement in the Internet as well as in social media (Correa et al., 2009; Hughes et al., 2012; Ryan & Xenos, 2011; Seidman, 2012) but studies so far are limited and have only focused on identifying either how each type of consumer actually behaves on UGC sites (Nusair et al., 2012; Correa et al., 2009) or how vlogger personalities influence their vlogging behavior (Biel & Gatica-Perez, 2012; Biel et al., 2012; Aran et al., 2014). Considering
that the literature above stressed the rise of Travel 2.0, revealed that vlogging has become the new ‘go to’ to seek for travel advice and determined that the personality of consumers can be used to predict future behavior, the further exploration of the personality of consumers within this context could generate valuable insights for the future of the travel vlog’s relevance.
Effective communication
Another new area that has been gaining grounds refers to analyzing the effectiveness of the way the vlogs are actually communicated (Biel & Gartica Perez, 2010; Biel et al., 2013; Sarkar et al., 2014; Frobenius, 2014; Gievska & Koroveshovski, 2014; Sanchez-Cortes et al., 2015; Gatica-Perez, Vinciarelli & Odobez, 2014).
Numerous studies find that nonverbal communication has the greatest potential for evaluating the effectiveness of the vlogs (Biel et al., 2013; Biel & Gatica-Perez, 2010; Sarkar et al., 2014), as it’s known for its strength to analyze different ways of communication by identifying and categorizing communication attributes (Ambady 1992; Pentland, 2008). Recent studies brought this traditional analysis into a modern light by applying this analysis specifically to vlogs, with findings that support the importance of successfully using nonverbal communication in vlogs as valuable, unconscious information can be found (Biel & Gatica-Perez, 2010; Biel et al., 2013). Within the vlogging literature, facial expressions as well as inferring moods of the vlogger have been examined (Biel et al., 2012; Gatica-Perez et al., 2012; Biel & Gatica-Perez, 2012; Aran et al., 2014; Sanchez-Cortes, Biel, Kumano, Yamato, Otsuka & Gatica-Perez, 2013; Sarkar et al., 2014) with a specific focus on automatic cues extraction either to analyze what cues are used (i.e. surprise, smile, anger) or to predict the vlogger’s personality based on these cues. It has therefore been established that facial expressions are effective
manners for a vlogger to communicate to its audience, yet the effectiveness of these facial expressions on the viewer itself and within the travel industry have not been examined.
Using verbal communication through vlogging on the other hand is also an appreciated medium that should be considered as vloggers can use speech to connect to the audience (Frobenius, 2014; Sanchez-Cortes et al., 2015; Biel & Gatica-Perez, 2010). Hsiao and Lan (2013) for example find that blogs that are written in a storytelling format (thus, similar to how a vlog is presented) enhances the connection between the audience and the one telling the story which in turn leads to an increase in attitudes (to travel in this case). It also enables vloggers to respond directly to comments or questions of the audience, which in turn strengthens the connection between the two even more (Frobenius, 2014). To further specify verbal communication within this context, one area for research entails examining how the vlogger describes his or her experiences as this is in line with the type of information that consumers look for (Hernández-Méndez et al., 2012) and because this is what vlogs are mostly about (Frobenius, 2014). Chen et al., (2015) incorporate a similar notion in their framework and established several items that tourists use to analyze tourism destinations, which include identity, dependence, attachment, memory and expectation, and thus this is of relevance for this research. But which communication type is best? Should the focus be on nonverbal or verbal communication? Madzlan, Reverdy, Bonin, Cerrato & Campbell (2015) find that their sample responds best to blogs that use audio and visual content, leaving the possibility of either verbal or nonverbal communication as well as the combination of the two as the most effective way of persuading the audience. Secondly, numerous studies find that a vlogger is most persuasive when he or she uses the right words and expressions (Werner, 2012; Hsiao & Lan, 2013; Madzlan et al., 2015), again leaving room for both types to be effective. As it has been established that
personalities can have different thinking styles (Zhang, 2002) and behaviors (Yoo & Gretzel, 2011), both types of communication may influence their responses.
Hypotheses formulation
Extraversion – People that score high on extroversion are typically very social and
outgoing with a large social network (Acar & Polonsky, 2007) that they actively maintain as they have an interest in others (Yoo & Gretzel, 2011). Internet wise, the majority of authors agree that this group spends less time online than others, which is potentially due to their active participation in social activities (Landers & Lounsbury, 2006; Kayis, Satici, Yilmaz, Simsek, Ceyhan & Bakioglu, 2016). This may result less consultation for travel information online. They do however use a combination of portal websites, tourism organizations and blogs when they consider travel plans (Jani et al., 2014), meaning they are open to a variety of sources. As this group generally seeks excitement and is willing to travel (Li & Tsai, 2013), the following hypothesis is formed.
H1: The higher the participant’s score on extraversion, the higher the intention is to travel to the destination after watching the travel vlog.
This group also tends to be full of confidence, is ready to take on challenges (Jani, 2014) and particularly values communication in which social contexts are shown (Ashton, Lee & Paunonen, 2002; Jani, 2014; Wrzus & Mehl, 2015). Communication wise, authors stress the potential to persuade the extravert group with excitement (Hirsh, Kang & Bodenhausen, 2012), which can be through both social conversations (Yoo & Gretzel, 2011; Wrzus & Mehl, 2015) as well as by the use of nonverbal communication such as facial expressions (Wrzus & Mehl, 2015; Riggio & Riggio, 2002).
H6A: The type of communication moderates the relationship between extraversion and intention to travel to the destination, so that the relationship is stronger for higher levels of nonverbal communication.
H7A: The type of communication moderates the relationship between extraversion and intention to travel to the destination, so that the relationship is stronger for higher levels of verbal communication.
Neuroticism - A high score in neuroticism means people are rather pessimistic, emotionally
unstable, self-conscious and insecure (Kahle, Matsuura & Stinson, 2005; Zhang, 2002; Yoo & Gretzel, 2011; Tan & Tang, 2013). While some authors argue that this group is active in the online community and searches for online travel information more than others with a particular preference for travel blogs (Jani et al., 2014; Guadagno, Okdie & Eno, 2008), another study shows a negative relationship between neuroticism and online presence and motivation (Yoo & Gretzel, 2011). Furthermore, a study by Zhang (2002) pointed out that neuroticism, more than any other personality, has a significant amount of variance in the way they think, meaning people with this personality vary more than others. It is difficult to estimate the way neurotic people respond, as on the one hand they often see and evaluate events in a negative light (Tan & Tang, 2013; Hamburger & Ben-Artzi, 2000) but on the other hand they feel a sense of comfort in the online community (Jani, 2014; Hamburger & Ben-Artzi, 2000; Landers & Lounsbury, 2006). Even though the neuroticism trait is considered as the dominant trait that is researched within the Big Five, emotional stability (it’s opposite), will be tested in this research as this trait resembles the other personalities in terms of the (positive) formulations. This approach is in line with numerous, similar studies (Mohamed, Hussein, Zamzuri & Haghshenas, 2014; Digman, 1990; Musek, 2007). People with a high score on emotional stability (i.e. a low score on neuroticism)
are less likely to be influenced by online information as they are less sensitive to this (Tan & Tang, 2013). As this group also does not see the value in social media (Correa et al., 2009; Amichai-Hamburger & Vinitzky, 2010) and because this group has a preference for official websites and search engines (Jani et al., 2014), the following assumption is made.
H2: A high participant’s score on emotional stability will not lead to a higher intention to travel to the destination after watching the travel vlog.
The next expectation is that the communication type will not increase the emotionally stable’s person intention to travel to the destination. This is expected because these people are generally stable, self-assured (MacIntyre, Babin & Clement, 1999), and not very sensitive to online communication (Tan & Tang, 2013).
H6B: Nonverbal communication does not moderate the relationship between emotional stability and intention to travel to the destination.
H7B: Verbal communication does not moderate the relationship between emotional stability and intention to travel to the destination.
Openness to Experiences – This group is generally considered to be imaginative, curious and
enjoys sharing experiences with their family and friends (Tan & Tang, 2013). These people are the most active in terms of online communities (Yoo & Gretzel, 2011; Tuten & Bosnjak, 2001), find interactive story telling a successful way of communication (Tan & Tang, 2013) and are actually most likely to be bloggers themselves (Gaudagno et al., 2008). Studies show that this group is active in online travel searches as well as (travel) blogs for advice (Guadagno et al., 2008; Jani et al., 2014). Thus, this group is expected to be willing to travel to the destination and to enjoy the travel vlog.
H3: The higher the participant’s score on openness to experience, the higher the intention is to travel to the destination after watching the travel vlog.
In addition to the above, this group enjoys enriching their knowledge about things to do in general (Jani, 2014; Tan & Tang, 2013; Kahle et al., 2005; Jani et al., 2014) and looks for communication that is about sensation seeking, excitement (Aluja, García López, & Garcia, 2003) and that stimulates them intellectually (Hirsh et al., 2012). Moreover, other studies recognize this trait as being open to new approaches (Ross, Orr, Sisic, Arseneault, Simmering & Orr, 2009; Amichai-Hamburger & Vinitzky, 2010), also in the light of communication (Butt & Phillips, 2008). As a result, the following hypotheses are expected.
H6C: The type of communication moderates the relationship between openness to experience and intention to travel to the destination, so that the relationship is stronger for higher levels of nonverbal communication.
H7C: The type of communication moderates the relationship between openness to experience and intention to travel to the destination, so that the relationship is stronger for higher levels of verbal communication.
Agreeableness – People with this trait are easy-going, accommodating (Tan & Tang, 2013;
Seidman, 2012) and helpful (Zhang, 2002). This group generally enjoys being part of the online community (Yoo & Gretzel, 2011) in which members are willing to be persuaded (Tan & Tang, 2013). In terms of choosing an information source, they actually prefer official organizations and websites for travel information instead of travel blogs (Jani et al., 2014). Regardless of this group potentially not choosing a travel blog as a source in the first place, they have a desire to be in line with the rest (Jani, 2014), meaning they are likely to follow the latest trends (vlogging in this case) for persuasion. As a result, it is expected that the travel intention will increase.
H4: The higher the participant’s score on agreeableness, the higher the intention is to travel to the destination after watching the travel vlog.
The agreeableness trait is least understood in the light of how and why people respond in certain ways (Tobin, Graziano, Vanman & Tassinary, 2000), meaning there is limited information regarding the effectiveness of communication types. However, a study by Berry and Hansen (2000) reveals that within interactions, people that score high on agreeableness find nonverbal components that include gesture, body language and facial expressions very important within communication. Furthermore, having this trait leads finding interactions with others more enjoyable as well as positive (Egges, Kshirsagar & Magnenat-Thalmann, 2004). As a result, it is expected that the person will feel empathy (Anaza, 2014) for the vlogger sharing their experience, and therefore verbal communication is also expected to increase intention to travel.
H6D: The type of communication moderates the relationship between agreeableness and intention to travel to destination, so that the relationship is stronger for higher levels of nonverbal communication.
H7D: The type of communication moderates the relationship between agreeableness and intention to travel to destination, so that the relationship is stronger for higher levels of verbal communication.
Conscientiousness – Characteristics that accompany this trait include being careful, disciplined,
determined and honest (Chiu, Hsieh, Kao & Lee, 2007; Jani, 2014) with a great deal of
perseverance (Shrapnel & Davie, 2001). These people thoroughly think before they act and want to get as much information as possible to justify their final decisions (Tan & Tang, 2013), meaning they do actively engage online (Yoo & Gretzel, 2011). There are several studies that highlight the essence of portal sites for their travel information and behavior (Jani et al., 2014;
Tan & Tang, 2013; Jani, 2014). As this group will be critical to the vlog, it is expected that watching the vlog itself will not be enough to persuade the person to travel to the destination.
H5: A high participant’s score on conscientiousness will not lead to a higher intention to travel to the destination after watching the travel vlog.
Communication wise, as this group looks for specific and informative information to justify decisions (Tang & Tang, 2013) such as information about activities or settings (Marbach, Lages & Nunan, 2016), it is expected that only verbal communication will have the potential to increase their intention to travel to the destination.
H6E: Nonverbal communication does not moderate the relationship between conscientiousness and intention to travel to the destination.
H7E: The type of communication moderates the relationship between conscientiousness and intention to travel to destination, so that the relationship is stronger for higher levels of verbal communication.
Method Design
This quantitative study was set up through a cross-sectional survey design to best generalize the findings within a specific time frame. It aimed to discover the effectiveness of (travel vlogs) by studying the relationship between each personality type and their intention to travel to a destination based on a presented vignette study and looked at whether the type of communication moderated this relationship.
A correlational / observational research design was used to examine the correlation between the specific variables for this study. The survey was generated through Qualtrics in which participants were asked to participate online.
Participants and Procedure
The population for this sample referred to ‘the millennial’ as millennials have become immensely active in the vlogging society (Arnold, 2017) and because they are starting to shape the entire travel industry (Christoff, 2017). These participants were reached via e-mail, Facebook, Linkedin but also through general forums for the appropriate target group, meaning a non-probability convenience sampling technique was used.
A pre-test was conducted amongst 25 participants to clarify whether the presented vignette was realistic and if participants were able to imagine the type of communication presented, which both appeared to be the case. Secondly, the participants were asked what personality traits a vlogger should have when he or she is presented to further build the vignette study and because there tends to be a pattern in preferred vlogger personalities (Biel, Aran & Gatica-Perez, 2011). The participants had a clear preference for a vlogger with an extravert and agreeable personality that was open to experiences. After establishing this, a pilot study was
launched in which 10 participants were asked to rate the overall quality of the survey, to dig further into the way communication types were presented and to decide which country to use as the destination. Participants agreed with the images that represented the nonverbal components and confirmed that they could imagine a vlogger saying the verbal statements. After presenting several potential destinations, all participants agreed that Costa Rica was most favorable to visit in their minds.
Measures
Participants will have answered according to the seven-point Likert-type scale in which they can respond from 1 = “strongly disagree” to 7 = “strongly agree” unless mentioned below. The following measures were adopted:
Personality: personality traits were measured using the adapted Ten-Item Personality
Inventory (TIPI) from Gosling, Rentfrow and Swann (2003) in which they analyze the Big Five-personality dimensions. These include “I see myself as: extroverted, enthusiastic”, “I see myself as: dependable, self-disciplined” and “I see myself as: reserved, quiet” for example. The authors use two (opposing) broad statements per construct (hence, 10 statements for 5 constructs).
Therefore, several items were first recoded, as they were counter-indicative. After this, reliability analyses were conducted. It is important to note that the authors stress that it is nearly impossible to get high alpha scores with this scale, as it is intended to measure a broad construct and aims to ensure criterion as well as content validity (Gosling, n.d.). For this reason, low scores were expected, which proved to be the case with extraversion (α = .72), emotional stability (α = .64), openness to experience (α = .32), agreeableness (α = .19) and conscientiousness (α = .57). In an effort to potentially increase the reliability of this scale, numerous papers suggest conducting a test-retest analysis to validate the TIPI scale’s consistency (Gosling et al., 2003; Hofmans,
Kuppens & Allik, 2008; Romero, Villar, Gómez-Fraguela & López-Romero, 2012). The first step in the test-retest analysis consists of asking a group of participants to rate themselves on the 10-item TIPI question (i.e. the first time the survey is taken). This process is then repeated for the same group of participants after roughly six weeks to ensure answers are as truthful as possible (Hofmans et al., 2008). The final data is then analyzed by calculating the intra class correlation coefficient, which produces alpha scores based on the consistency between the first answer(s) of the participants and the second answer (s). For this particular study, participants were asked whether they would be willing to contribute to this study further by providing their email address. There were 83 participants that gave this information and these participants were sent the TIPI question again roughly 1.5 months after filling it out for the first time. Overall, 48 participants responded and answered the TIPI questions again. The intra class correlation coefficients were then calculated for these 48 participants by comparing the first time they answered to the second time they answered (this was possible as they provided their email addresses). As a result, extraversion (α = .87), openness to experience (α = .72), and
conscientiousness (α = .82) were quite consistent, agreeableness was somewhat consistent (α = .68) and emotional stability was the same (α = .64). Although such a small proportion of the sample may not generalize the entire sample, it does indicate that the internal consistency within TIPI is somewhat present.
Intention to travel to the destination: This was measured by asking participants to rate
three statements on the 7 point Likert-type scale (Jalilvand, Samiei, Dini & Manzari, 2012). This includes “I predict I will visit country X in the future”, “In the future, I would rather visit country X than any other”. This scale proved to be reliable with α = .77. After asking participants to select the type of communication (see below), this question was asked again to check whether
intention would increase with α = .88. The country used for this specific study referred to Costa Rica, as this country came out most favorable in terms of destinations to visit in the pre-test.
Type of communication: The communication types were divided into nonverbal
and verbal communication. Nonverbal communication was shown by the common facial expressions used in online conversational video by Biel et al., (2012). These expressions include: smile, joy, surprise, fear and anger. Verbal communication was presented through a framework of travel destination consideration components from Chen et al., (2015). These include “I identify strongly with this destination” (i.e. identify), “I prefer this destination over others for the activities that I enjoy” (i.e. activities), “My experiences at this destination are unforgettable” (i.e. experiences), “I feel connected to the destination due to my experiences” (i.e. connection) and “I have a strong sense of belonging to the destination and its settings and facilities” (i.e. settings and facilities).
Participants were asked to make a selection of two verbal and two nonverbal communication types that they believed would be most effective in increasing their overall intention to travel. For this reason, this study not only generated insights into the verbal and nonverbal selections, but it also measured the weight of each selection with regards to the change in the travel intention based on the introduction of communication. To further operationalize this, multiple correspondence analysis (MCA) was performed to convert the nominal scale into a ratio scale, to ensure distances between choices became meaningful. This also enabled the generation of the transformed reliability scales which were α = .76 for nonverbal communication and α = .73 for verbal communication.
Control variables: Factors such as age, nationality and particularly gender have an
& Morrison, 2007; Shashaani, 1997; Riggio & Riggio, 2002; Jönsson & Devonish, 2008; Tan & Tang, 2013). Hence, these were included as control variables. Gender was measured by asking respondents whether they were male (1) or female (2) and participants were asked about their age and nationality through open-ended self-report questions. Additionally, as this framework regards the exploration of a popular concept in a relatively new phenomenon, participants were asked whether they consulted the Internet for travel plans and whether they were familiar with the concept of vlogging through a yes (1) and no (2) question. If participants answered no (2) to the vlogging question, an explanation of the notion was provided.
Table 1
Descriptive Statistics, Reliability and test-retest Reliability
Measure Items α M SD Test-retest
Extraversion 2 .72 5.07 1.30 .87 Emotional Stability 2 .64 5.14 1.17 .64 Openness to Experience 2 .32 5.5 .91 .72 Agreeableness 2 .19 4.63 .92 .68 Conscientiousness 2 .57 5.35 1.13 .82 Intention to travel 1 3 .77 4.68 1.06 Intention to travel 2 3 .88 5.49 .84 Nonverbal communication 5 .76 .01 1.83 Verbal communication 5 .73 .02 1.57 Results
There were 472 respondents that participated in the final survey. Out of these respondents, 121 respondents answered less than half of the survey and did not answer any DV question(s); therefore, they were removed from the sample. The 4 participants that never consulted the Internet for travel plans were also removed, as this was a set requirement to answer the survey
accordingly. The vlogging definition was provided to 11% of the sample. Frequency wise, 78.4% of the sample was female and 21.6% was male. Furthermore, 75.2% of the sample was between 18 and 35 years old, indicating that the aim to target millennials had been quite successful.
As a next step, the data was checked for normal distribution and both Kolmogorov-Smirnov and Shapiro-Wilk rejected the normal distribution hypothesis. The data was then analyzed visually through histograms as well as Q-Q plots in which a clear pattern was observed for all variables with the exception of several outliers. These outliers were accepted or rejected by using the 3x multiplier method from Hoaglin and Iglewicz (1987). The 6 outliers that fell outside of the 3x range were removed within the conscientiousness trait and within dimension 1.
A correlation matrix was compiled for all IV’s, the DV and the control variables to determine the strength and meaning of relationships between all variables. As can be seen in the Pearson’s correlations matrix (Table 2), several items are significantly correlated (** and *). For example, age is significantly and negatively correlated to intention to travel to the destination. In other words, the older a participant is of age, the less likely their intention is to travel baesd on the presented vlog. Secondly, the extraversion and openness to experience traits are significantly and positively correlated to intention to travel. This means that participants that score high on both of these traits are likely to find the vlog effective, and are therefore more inclined to travel to the destination, which is in line with the literature review findings. Moreover, the trait of agreeableness is significantly and positively correlated with the control variables of gender and age. Thus, as the majority of this sample is female (2), females are likely to score higher on agreeableness than men. In terms of agreeableness and age, it can be observed that the older a participant gets, the higher their agreeableness trait becomes. Lastly, to name some correlations between traits, the agreeableness and conscientiousness traits are positively and strongly
correlated to the traits of emotional stability and openness to experiences, whereas the openness to experience trait is positively and strongly correlated to the extraversion and emotional stability trait. This means that personalities also correlate with one another in the sense that a participant that is agreeable or conscientious is most likely to also be emotionally stable and open to experience. A participant that is open to experience is also likely to be an extravert and emotionally stable.
Table 2
Pearson’s Correlation Matrix
** Correlation is significant at the 0.01 level * Correlation is significant at the 0.05 level
Regression Analyses
The direct and isolated relationships between the IV’s and the DV were tested through single regression analyses and can be seen in Table 3. The results demonstrate that extraversion is significantly related to intention to travel F(1, 340) = 6.48 with p < .05 and R2 = .02, meaning this trait predicts 2% of the variance in this particular DV. The small positive correlation indicates that someone will be more likely to travel if they are extroverts, which is in line with H1.
Variables 1 2 3 4 5 6 7 8 9 1. Gender - 2. Age .15** - 3. Nationality -.02 -.08 - 4. ExtraTOT .02 -.05 .10 (.72) 2(.87) 5. EmotTOT -.05 .09 .00 .06 (.64) 2(.64) 6. OpenTOT .12* .02 .03 .30** .19** (.32) 2(.72) 7. AgreeTOT .22** .18* .03 .03 .15** .12* (.19) 2(.68) 8. ConscTOT .09 -.03 -.01 .04 .13* .15** .09 (.57) 2(.82) 9. TITOT -.04 -.16** .07 .14* .00 .14* .00 .04 (.77)
Secondly, openness to experience also appears to be significantly related to intention to travel F(1, 340) = 6.12 with p < .05 and R2 = .02, indicating that this trait also predicts 2% of the variance in this particular DV. This finding is in line with H3 as someone that is open to
experience correlates slightly (and positively) with intention to travel. Overall, both extraversion and openness to experience only predict a small amount (4%) of variance in the DV.
Table 3
Standardized Regression Coefficients with Confidence Intervals to estimate the effects of Extraversion, Emotional Stability, Openness to Experience, Agreeableness and
Conscientiousness on Intention to Travel
Coeff. T 95% CI Extraversion .14* 2.6 .03, .20 Emotional Stability .00 .04 -.09, .20 Openness to Experience .14* 2.5 .03, .28 Agreeableness .00 .08 -.12, .13 Conscientiousness .03 .63 -.07, .13
* Correlation is significant at the 0.05 level
As a next step, a hierarchical multiple regression analysis was conducted to include the control variables and to see what would happen if independent variables were added (Table 4). The first model that contained the control variables of age, gender and nationality proved to be statistically significant F(3, 339) = 3.51 with p < .05 and R2 = .03, meaning the control variables only accounted for a small degree of variance in the DV. When looking at the relative importance of each CV, only age proved to be significant with p < .05 and a slight negative correlation as shown in Table 2. In step 2 of the multiple regression analysis, the independent variables were added in an order based on literature assumptions and statistical significance of the previously conducted analysis. The model proved to be statistically significant again F(5, 334) = 2.56 with p < .05 and R2 = .06, indicating that the IV’s account for 6% of variance in the
DV and that all variables together account for 9% of variance in the DV. This means that the majority of the variance in the model (90%) is accounted for by other factors and that the choice of control variables and personality types are not strong predictors. Additionally, when looking at the relative importance of each IV, none of them prove to be statistically significant, which is contrary to the significant results of extraversion and openness to experience in the single regression analyses and thus H1 and H3 are rejected based on this analysis. It was expected that emotional stability and conscientiousness would not lead to a greater travel intention, meaning both analyses above show that H2 and H5 are accepted. Agreeableness on the other hand shows no significant effect in both cases, therefore H4 is rejected.
Table 4
Standardized Regression Coefficients with Confidence Intervals to estimate the effects of Age, Gender, Nationality, Openness to Experience, Extraversion, Agreeableness, Conscientiousness and Emotional Stability on Intention to Travel
Hierarchical Model Step 1 Coeff T 95% CI Age -.16* -2.90 -.02, -.00 Gender -.01 -.17 -.30, .25 Nationality .06 1.07 -.01, .04 Step 2 Age -.16* -2.85 -.02, -.00 Gender -.03 -.59 -.36, .20 Nationality .04 0.82 -.02, .04 Openness to Experience .11 1.96 -.00, .26 Extraversion .09 1.60 -.02, .16 Agreeableness .03 .45 -.10, .16 Conscientiousness .02 .32 -.09, .11 Emotional Stability -.02 -.32 -.11, .08
Nonverbal communication and verbal communication as moderators
The next process involved assessing the effectiveness of nonverbal and verbal communication as moderators between personality type and travel intention. As mentioned in the measures section, participants were asked to select two nonverbal and two verbal communication choices that they felt would be most effective for a vlogger to use. The nonverbal communication choices included: smile, joy, surprise, fear and anger whereas the verbal communication options were: I identify strongly with Costa Rica, I prefer Costa Rica over others for the activities that I enjoy, My experiences in Costa Rica are unforgettable, I feel connected to Costa Rica due to my experiences and I have a strong sense of belonging to Costa Rica and its settings and facilities. This data was represented in a nominal scale with each participant having four chosen variables in total. MCA is generally used to identify how individuals with similar profiles or traits answer to questions and to ultimately determine associations between the chosen answers in surveys (Kassambara, 2017). Additionally, this method enables researchers to convert the nominal scales into ratio scales so the variables can be used for further analyses. The transformed correlation outputs are displayed in Table 5 and Table 6 and represent Dimension 1 and Dimension 2. To name some examples within Dimension 1, there appears to be a significant positive correlation with entertainment and identify when experience is important, meaning that participants who value experience will have been likely to also choose entertainment or identify as a verbal communication choice. Participants that chose connection will have been very likely to choose entertainment and unlikely to value experience as this has a slight negative correlation. To provide another example, participants that chose surprise will have been extremely likely to choose smile and somewhat likely to choose joy as nonverbal communication. All in all, the majority of the correlations occur on the verbal communication side.
Table 5
** Correlation is significant at the 0.01 level * Correlation is significant at the 0.05 level
Table 6
** Correlation is significant at the 0.01 level * Correlation is significant at the 0.05 level
Transformed Correlation Matrix Dimension 1, Overall Cronbach’s Alpha: 0.76
Variables 1 2 3 4 5 6 7 8 9 10 1. Identify - 2. Entertainment -.15** - 3. Experience .26** .17** - 4. Connection .09 .54** -.14* - 5. Settings -.12* -.17* .30** .23** - 6. Smile .09 -.04 .09 -.03 -.04 - 7. Joy -.08 .08 .13* .07 -.01 -.16** - 8. Surprise .04 .09 .08 -.02 -.00 .75** .34** - 9. Fear -.03 -.05 .09 .07 -.05 .00 .06 -.07 - 10. Anger .02 .06 .03 .08 .03 -.08 .02 .04 .00 -
Transformed Correlation Matrix Dimension 2, Overall Cronbach’s Alpha: .73
Variables 1 2 3 4 5 6 7 8 9 10 1. Identify - 2. Entertainment .15** - 3. Experience -.26** .17** - 4. Connection -.09 .54** -.14* - 5. Settings .12* -.17* .30** .23** - 6. Smile .09 .04 -.09 .03 .04 - 7. Joy .08 .08 .13* .07 -.01 .16** - 8. Surprise .04 -.09 -.08 .02 .00 .75** .34** - 9. Fear .03 -.05 .09 .07 -.05 -.00 .06 .07 - 10. Anger -.02 .06 .03 .08 .03 -.08 .02 -.04 .00 -
The data was then analyzed to a further extent based on Inertia, object points (Appendix B) and discrimination measures (Husson, 2016). The overall MCA output (Table 7) demonstrates that the Inertia for Dimension 1 is .18, which means that Dimension 1 represents 18% of the deviation from independence, which is somewhat low. Dimension 2 represents an additional 16% and therefore Dimension 1 and 2 together represent 34% of the deviation from independence. Generally, more dimensions should be added to increase the overall Inertia (Husson, 2016) but as the goal of this analysis was to turn nonverbal communication and verbal communication moderators into two separate ratio scales, the same dimensions were kept. Secondly, the addition of dimensions also significantly reduced the Cronbach’s Alpha score below the .70 threshold. Lastly, an additional look at the dataset also revealed that the dimensions had clear differences between high and low and thus the separation and transformation had been successful.
Table 7
Multiple Correspondence Analysis Output
Dimension Cronbach’s Alpha Total (Eigenvalue) Inertia % Of Variance 1 .76 3.64 .18 18.20 2 .73 3.24 .16 16.20
The object points graph confirmed that there was nothing unusual about the data and thus the interpretation of the axes began to determine which dimension referred to nonverbal communication and which one represented verbal communication by displaying the squared correlation ratios. On the X axis, particularly smile and surprise demonstrate that Dimension 1 is nonverbal communication, whereas Connection and Entertainment on the Y axis reveal that Dimension 2 is verbal analysis. Furthermore, it can be seen that participants who chose smile
were likely to have chosen surprise and that participants who chose connection would have been likely to choose entertainment for example, which is in line with the correlation tables for both dimensions.
Figure 2. Output Squared Correlation Ratios
PROCESS Model for Moderators
After turning the moderators into ratio scales and establishing which moderator was which, PROCESS was used to test the entire model (Hayes, 2012). As two moderators (nonverbal and verbal communication) were tested on several relationships between IV’s (personalities) and the DV, model 2 was used with travel intention as the DV (this refers to the second time the travel intention question was asked based on the chosen communication types).
As this analysis was intended to measure the same DV that is asked a second time based on the introduction of the moderators, all personalities were included to analyze whether the moderators would lead to significant results. The regression analyses demonstrated that age appeared to be the only significant control variable for personalities and travel intention, therefore only age was included as a CV. As can be seen in Table 8, the moderation effect is taking place for nonverbal communication within the extraversion trait with a slight positive correlation and p < .05. This means that the relationship between extraversion and intention to travel is moderated by nonverbal communication and increases by .11 units as extraversion increases by 1 unit and thus H6A is accepted. The overall model also appears to be significant F(6, 335) = 2.06 with p < .05 and R2 = .05, meaning that 5% of the total variance of intention to travel is explained by this
model. Based on this information, H7A is rejected, as verbal communication does not appear to increase an extraverts travel intention.
Table 8
Unstandardized OLS Regression Coefficients with Confidence Intervals to estimate Nonverbal and Verbal Communication as Moderators within Extraversion and Age as a Control Variable
Extraversion Coeff SE T 95%-CI
Extra (X) .08 .05 1.62 -.01, .17 Nonverbal (W) -.04 .05 -.88 -.13, .05 Verbal (Z) .01 .05 .20 -.08, .10 Age -.01 .00 -.19 -.02, .00 X*W .11* .04 2.29 -.02, .00 X*Z .03 .05 .63 -.08, .10
Within the emotional stability trait, only the control variable age is a significant predictor of intention to travel with p < .05, this means H6B and H7Bare accepted as it was expected that both types of communication would not act as moderators. Interestingly, only the CV age is significant within openness to experience and within agreeableness, and as a result H6C, H7C,
H6D and H7D are rejected, as the moderation effect does not take place. Finally, even though there was no original relationship between conscientiousness and intention to travel, the
moderation effect does occur for verbal communication (Table 9). A slight negative correlation can be observed between conscientious individuals and verbal communication with p < .001, thus verbal communication moderates the relationship between conscientiousness and intention to travel and decreases by .13 as someone becomes more conscientious. This is against
expectations of H7E as it was expected that no effect would take place. Rather, it seems as if verbal communication makes this group even more skeptical and critical towards the information they are reading. The overall model is also significant F(6, 335) = 2.81 with p < .05 and R2 = .05 and so similarly to extraversion, this model explains 5% of the total variance in intention to travel. Age is also a significant predictor with p < .05. Furthermore, there is no effect taking place for nonverbal communication, which is in line with H6E, as it was expected that the nonverbal expressions would not be enough to persuade this personality group. Figures 4-8 display the statistical diagrams for the PROCESS outputs, which include each IV, the DV, the moderators and the CV. The hypotheses and their final outcomes can be found in Table 10.
Table 9
Unstandardized OLS Regression Coefficients with Confidence Intervals to estimate Nonverbal and Verbal Communication as Moderators within Conscientiousness and Age as a Control Variable
Conscientiousness Coeff SE T 95%-CI
Consc (X) .05 .05 1.17 -.04, .14 Nonverbal (W) -.04 .05 -.81 -.13, .05 Verbal (Z) -.02 .05 -.36 -.11, .07 Age -.01* .00 -2.22 -.02, .00 X*W .00 .04 -.11 -.09, .08 X*Z -.13* .04 -3.10 -.22, -.05
MODEL 2 PROCESS outputs
Figure 4. Extraversion
Figure 5. Emotional Stability
Figure 7. Agreeableness
Figure 8. Conscientiousness
Final change in travel intention
As a final step in the results, the overall difference in travel intention was measured using repeated-measures. Sphericity was met as only two variables were compared against each other (change in DV). Accordingly, both Greenhouse-Geisser and Huynh-Feldt were analyzed and proved that the within-subject effects were significant with F = 280.50 and p < .001. Secondly, there is a noticeable difference in the first DV mean = 4.67 and the second DV mean = 5.48. To conclude, the introduction of moderators did have an overall effect on the increase in travel intention, which intensifies the importance of examining communication within travel vlogs.
Table 10
Reporting Hypothesis Outcomes
Hypothesis Statement Outcome
H1 The higher the participant’s score on extraversion, the higher the intention is to travel to the destination after watching the travel vlog.
Rejected H2 A high participant’s score on emotional stability will not lead to a higher intention to
travel to the destination after watching the travel vlog.
Accepted H3 The higher the participant’s score on openness to experience, the higher the intention
is to travel to the destination after watching the travel vlog.
Rejected H4 The higher the participant’s score on agreeableness, the higher the intention is to
travel to the destination after watching the travel vlog.
Rejected H5 A high participant’s score on conscientiousness will not lead to a higher intention to
travel to the destination after watching the travel vlog.
Accepted H6A The type of communication moderates the relationship between extraversion and
intention to travel to the destination, so that the relationship is stronger for higher levels of nonverbal communication.
Accepted
H7A The type of communication moderates the relationship between extraversion and intention to travel to the destination, so that the relationship is stronger for higher levels of verbal communication.
Rejected
H6B Nonverbal communication does not moderate the relationship between emotional stability and intention to travel to the destination.
Accepted H7B Verbal communication does not moderate the relationship between emotional
stability and intention to travel to the destination.
Accepted H6C The type of communication moderates the relationship between openness to
experience and intention to travel to the destination, so that the relationship is stronger for higher levels of nonverbal communication.
Rejected
H7C The type of communication moderates the relationship between openness to experience and intention to travel to the destination, so that the relationship is stronger for higher levels of verbal communication.
Rejected
H6D The type of communication moderates the relationship between agreeableness and intention to travel to the destination, so that the relationship is stronger for higher levels of nonverbal communication.
Rejected
H7D The type of communication moderates the relationship between agreeableness and intention to travel to the destination, so that the relationship is stronger for higher levels of verbal communication.
Rejected
H6E Nonverbal communication does not moderate the relationship between conscientiousness and intention to travel to the destination.
Accepted H7E The type of communication moderates the relationship between conscientiousness
and intention to travel to the destination, so that the relationship is stronger for higher levels of verbal communication.
Discussion
The notion of travel vlogs is on the rise more than ever before (Crowel et al., 2014) and the findings of this study reveal several important insights in this regard. The overall aim was to explore the effectiveness of vlogs from the viewer’s perspective and to examine whether or how this influenced their intention to travel based on their personality (extraversion, emotional stability, openness to experience, agreeableness and conscientiousness). Moreover, verbal and nonverbal communication types were studied as moderators to see whether these influenced the relationship between personality and intention to travel. As can be seen in the regression analyses and Figures 4-8, there were no significant relationships between each of the personality traits (IV’s) and intention to travel (DV). This surprisingly contradicts numerous studies that consider personality as a major determinant in travel decisions (Nickerson & Ellis, 1991; Madrigal, 1995; Roehl & Fesenmaier, 1992; Griffith & Albanese, 1996; Amichai-Hamburger & Vinitzky, 2010; Jani et al., 2014; Decrop, 2006, Yoo & Gretzel, 2011). Regarding the finding that a high score on extraversion does not lead to intention to travel, one explanation may be that extroverts do not feel the need to look for confirmation online (Landers & Lounsbury, 2006; Kayis et al., 2016) and would rather use their existing offline network. Secondly, the reason for the insignificant relationship between openness to experience and intention to travel may be because this group misses intellectual information (Hirsh et al, 2012) in the vignette study and does not find it exciting enough (Aluja, et al., 2003). For those in the agreeableness group, the fact that they prefer tourist organizations and websites instead of travel blogs (Jani et al., 2014) may have led to the insignificant relationship of intention to travel based on a presented vlog, as the information provided is not similar enough to the information of tourist organizations.
