“Say yes to new adventures!” – or to what others say on Instagram
A study of how people are being influenced in their travel intentions
on Instagram by micro- and macro-influencers
Master’s Thesis
Graduate School of Communication
Master’s programme Communication Science
Corporate Communication Track
Author:
Pinar Tas
Student number:
10558381
Supervisor:
Dr. Suzanne de Bakker
Date of completion: June 26
th, 2020
2 Abstract
Both academics as well as marketing professionals have been investigating different
influencer marketing strategies on social media while simultaneously the travel industry has been growing exceptionally over the last years. In light of these trends, this thesis investigates the effects of micro-influencers’ and macro-influencers’ Instagram posts promoting travel destinations on followers’ attitudes towards the promoted destination and final travel intentions while considering the possible moderating roles of source credibility and para-social relationship and the potential mediating effect of attitude towards the destination. Contrary to expectations, results from two 2 x 2 experiments showed that micro-influencers have no stronger effect on followers’ attitudes towards the destination and final travel intentions than macro-influencers. In addition, the findings did not support a moderating effect of para-social relationship and source credibility or a mediating effect of attitude. Source credibility did, however, reveal to have a direct impact on travel intention while attitude showed to have an effect on travel intention. These findings suggest that influencers with a smaller follower base are as effective for online travel promotions as influencers with a larger follower base and that, disregarding the popularity of the influencer, other source characteristics such as credibility should be taken into account when developing influencer marketing strategies.
Keywords: influencer marketing, Instagram, micro-influencer, macro-influencer, para-social
3 Introduction
Sabbaticals, gap years and backpacking trips all over the world - more and more people are surrendering to grown-up gap years and are taking a break from their studies or careers to experience life elsewhere (Buckley, 2019; Shankman, 2019). According to the World Travel and Tourism Council, the travel industry was the second-fastest expanding industry in 2019 and is adding a peak of $8.8 trillion and 319 million jobs to the global wealth (Leposa, 2019). Simultaneously, social media also still keep growing tremendously with an approximate amount of 2.65 billion people utilizing social media on a global scale in 2018 and expected to increase to 3.1 billion by 2021 (Clement, 2019). The rise of social media has had a substantial effect on the travel industry enabling (potential) travellers to use these platforms to explore and obtain travel-related information, acquire travel products and
services and share their personal experiences in a convenient way (Xiang & Gretzel, 2010; Xu & Pratt, 2018). Next to this, social media have also created new opportunities to promote and increase awareness of previously unknown travel destinations (Hanan & Putit, 2014).
Previous research has shown that user-generated content (UGC), and consumer
reviews specifically, can influence travellers’ prepurchase judgements and purchase intentions (Mauri & Minazzi, 2013; Noone & McGuire, 2014). More specifically, positive reviews can impact consumer decision making positively, whereas negative reviews can impede purchase intentions (Bambauer-Sachse & Mangold, 2011; Sparks & Browning, 2011). In addition, Xu and Pratt (2018) found that social media influencers can have a significant influence on their followers’ intentions to visit their endorsed destinations. More specifically, studies looked into distinctions between the impacts of different types of influencers and found that
influencers with a smaller follower base lead to higher levels of followers’ product knowledge and feelings of uniqueness (e.g. De Veirman, Cauberghe, & Hudders, 2017; Kay, Mulcahy, & Parkinson, 2020). Finally, scholars concluded that both social media influencers and peers can
4 have a significant influence on their followers’ judgements on destinations and intentions to visit their recommended destinations (Currie, Wesley, & Sutherland, 2008; Shuqair & Cragg, 2017; Xu & Pratt, 2018).
Additionally, past studies have also looked into Instagram, specifically, as a platform to promote tourism destinations and concluded that the functions of Instagram provide multiple options to boost a tourist destination with user-generated content photography, geo-tagging and hashtags (Fatanti & Suyadnya, 2015). Others focussed specifically on UGC on Instagram and claim that positive UGC results in a positive destination image and may enhance awareness of the promoted destination (Shuqair & Cragg, 2017).
In conclusion, although many researchers have looked into the influence of different types of people on travel destination choices, the effects of different influencers in general and into travel marketing on Instagram, there is still a lacuna in past literature on the differences in impacts of different types of Instagram influencers in the travel industry specifically.
Contrary to the scarcity in literature on the influence of different types of social media influencers on travel decisions, current research on organizational use of Instagram does include studies on the effects of psychological processes and source characteristics on
Instagram users. Johnson and Kaye (2013) found a relation between source credibility and the social media content users select to view or ignore. In addition, research shows that
trustworthiness and perceived expertise have a significant impact on the attitude, behaviours and purchase intentions of users (Gunawan & Huarng, 2015; Ohanian, 1990). Other scholars have looked into psychological processes happening through social media and found a positive link between the use of social media and the establishment of para-social relationships (PSR) with influencers (Kim, Ko, & Kim, 2015). According to Hwang and Zhang (2018), the establishment of PSR between influencers and their followers has a positive influence on followers’ trust in the provided information, purchase intentions and
5 electronic word-of-mouth (eWOM) intentions.
Although various research has been conducted on the marketing effects of para-social relationships and source credibility online, they all looked into actual products or services whereas the promotion of a travel destination involves a completely different type of endorsement as it is not a specific service or product provided by one brand. As consumers use social media increasingly as a source of information for travelling (Xiang & Gretzel, 2010), it is not only important to know through who, but also how Instagram users are being persuaded into travel destinations.
The focus of this thesis is on different types of influencers of Instagram posts and their effect on followers’ travel destination decisions. Next to this, it investigates source credibility and PSR as moderators and attitude towards the destination as a mediator in this relationship. Based on this, the next research question is proposed: To what extent does the type of
influencer of an Instagram post influence followers’ travel destination attitudes and travel intentions and how is this process impacted by source credibility and para-social
relationships?
The aim of this thesis is to increase the understanding of the effects of different Instagram authors on people’s travel plans and the psychological dynamics and source characteristics which might influence this relationship. Comparing the effects of travel posts from micro- and macro-influencers will extend the literature on influencer marketing and the difference in influence on their followers as this is still highly debated (De Veirman et al., 2017; Kim & Xu, 2019). This is of scientific relevance as this thesis will try to solve conflicting findings on the effects of micro- and macro-influencers on their followers by proposing possible moderating factors such as PSR and source credibility which could explain the effectiveness in terms of marketing for one of the two. Thereby, this research also
6 credibility as these factors could be important in influencer marketing (Kay et al., 2020) As marketing executives are planning to spend more of their budgets on social media efforts (Busby et al., 2010), one of the challenges for the growing travel industry is to
establish an effective social media strategy. Therefore, more theoretical and empirical evidence is needed on which authors are more influential and which psychological processes and source characteristics play a role in order for businesses to develop the right social media strategies and effective relationships. The findings of this research are of social and practical relevance as travel marketers and businesses overall will benefit from understanding these processes as they will be more effective in their online promotion strategies for travel destinations by enhancing the popularity of travel destinations while, simultaneously, reducing their marketing costs. Finally, businesses can also profit from these findings when they are considering using influencers for their social media strategies overall.
Theoretical background Travel attitudes and intentions
As social media have an evident impact on travel decisions, it is crucial to know how this decision-making process works. According to the adapted travel decision-making model from Dwityas and Briandana (2017), there are three phases in the decision making process in travelling: the trip phase, during-trip phase and post-trip phase. For this research, the pre-trip phase is essential as this stage involves the need to go travelling, obtaining information and judgements on different destinations and, finally, the travel decision making (Dwityas & Briandana, 2017). The final decision, more specifically, involves purchasing the required products such as tickets or hotels. This pre-trip phase also includes the three more general mental stages of purchase decisions including becoming aware of the potential, becoming interested to learn more about the good or service and, finally, making a decision which
7 involves an observable action including a purchase (Bettman, 1979). This research
specifically focuses on the pre-trip stage and thereby the search for information and judgements and the intention to purchase tickets to a certain destination.
Tham, Croy and Mair (2013) complement this by referring to a destination choice as the process of choosing a destination from competing options and involves a thorough cognitive decision-making process. A destination choice is mainly dependent on the
destination image a person holds over a certain place. A destination image can be defined as the beliefs, ideas and impressions someone holds over a potential travel destination
(Crompton & Ankomah, 1993). Consequently, the more favourable a destination image gets, the more likely it is that the potential destination will be picked over others (Gartner, 1993). This, finally, leads to the decision and intention to visit a certain destination or not (Gartner, 1993).
Besides the final intention, consumer attitude is another important construct to focus on while developing marketing strategies (Solomon, Bamossy, Askegaard, & Hogg, 2006). According to Solomon et al. (2006), attitude compromises an overall and enduring judgement of people, goods, services or matters. People form attitudes about certain objects or ideas based on their beliefs about them (Ducoffe, 1996; Wolin, Korgaonkar, & Lund, 2002). More particularly, audiences can also establish an attitude towards an advertisement or post which refers to the tendency to respond favourably or unfavourably to a specific stimulus displayed to them (Solomon et al., 2006). This research specifically looks into consumer attitudes’ towards the travel destinations which are recommended in the Instagram posts and the final travel intentions.
Type of authors on Instagram
8 exhibit some combination of desirable attributes - whether personal attributes like credibility, expertise, or enthusiasm, or network attributes such as connectivity or centrality - that allows them to influence a disproportionately large number of others, possibly indirectly via a cascade of influence” (Bakshy, Hofman, Mason, & Watts, 2011, p. 65). Over the last years, the use of influencers for marketing purposes on social media has been discussed by an infinite amount of marketing professionals and scholars and has proven to be successful (Carter, 2019; De Veirman et al., 2017; Lou & Yuan, 2019; Mathew, 2018). As disbursements on social media influencer marketing are increasing exceptionally (Lou & Yuan, 2019), it is important to know what type of influencers work best.
One distinction being made is between micro-influencers and macro-influencers. The specific numbers of their followers are arguable as different sources state different sizes, but this thesis will view micro-influencers as Instagrammers with 1,000 - 100,000 followers and macro-influencers as people with more than 100,000 followers (Alassani & Göretz, 2019; Chue, 2018; Ismail, 2018). Although a lot of academic research has been conducted on
influencers in general, there is still a scarcity in academic literature on the differences between the types of influencers. Therefore, also insights of marketing professionals were used to recognize the distinctions.
More specifically, micro-influencers are known for their expertise in certain topics or niches and recognized for their credibility, high social media engagement and extensive interaction with their followers (Alassani & Göretz, 2019; Wessel, 2018). They are viewed more as ‘normal people’ and are also characterized by their cheaper prices and niche
audiences (Hatton, 2018). Macro-influencers, in turn, are signified by their higher amount of followers, lower engagement numbers and a high amount of posts (Alassani & Göretz, 2019). Besides, they have more fame, higher visibility, higher reach and are seen as trendsetters (Mediakix, n.d.). However, they do often come with a higher price too (Mediakix, n.d.).
9 Influencers and attitudes
According to Freberg, Graham, McGaughey and Freberg (2011), social media influencers influence and form their audiences’ attitudes by generating and posting their authentic content online. More specifically, followers are more likely to have a positive attitude towards a micro-influencer and their content as they mainly follow them because users like their lifestyle or content rather than because of knowing them from other media (Sammis, Lincoln, Pomponi, 2016). Additionally, Amos, Homes and Strutton (2008)found a positive relationship between attitude towards the source and attitude towards the endorsed brand. As micro-influencers are perceived more positively themselves, audiences will also have a more favourable attitude towards the brands or destinations they recommend. Besides, a lower amount of followers may cause the idea that the recommended product is more unique than when it would be endorsed by an influencer with a larger follower base (De Veirman et al., 2017). This increase in the perceived brand exclusivity, in turn, leads to higher brand attitudes. So, as the recommended goods, services, or travel destinations of micro-influencers will be perceived as more unique, it is likely that recommendations from micro-influencers will lead to more positive attitudes towards the promoted destination. Following from this discussion, the next hypothesis is posed: H1a: Travel destination recommendations from micro-influencers have more influence on followers’ attitude towards the destination than travel destination recommendations from macro-influencers.
Influencers and travel intentions
In addition to the existence of a relationship between the type of influencer and followers’ attitudes, scholars also looked into the effects of influencers on behavioural intentions (e.g. Chu & Kamal, 2011; Lim, Radzol, Cheah, & Wong, 2017). Firstly, followers
10 might feel that a product or service is less unique when it is endorsed by more highly followed accounts than by less followed social media users (De Veirman et al., 2017). As consumers acquire products, among others, to feel unique and differentiated from others (Mazodier & Merunka, 2014), it is likely that promotion by highly popular accounts will lead to fewer purchase intentions than those from less followed Instagram accounts.
Also, Kay et al. (2020) found that micro-influencers have a stronger influence on followers’ product knowledge than macro-influencers which, in turn, lead to more purchase intentions. Finally, audiences are likely to think that macro-influencers are trying to be more persuasive because of their popularity compared to a micro-influencer. When audiences recognize this intention, they will either ignore or resist the try (Kay et al., 2020).
In conclusion, because of the need for uniqueness, the persuasive intentions and product knowledge (De Veirman et al., 2017; Kay et al., 2020), recommendations from micro-influencers are likely to lead to more purchase intentions and thereby also to more travel intentions than recommendations from macro-influencers. Hence, the following hypothesis is proposed:
H1b: Travel destination recommendations from micro-influencers have more influence on followers’ travel intentions than travel destination recommendations from
macro-influencers.
The mediating effect of attitude
Besides the direct effect of the type of influencer on attitude and purchase intentions, past studies have also looked into the impact of one’s attitude on their behavioural intentions. Social media audiences with positive attitudes towards social media advertising tend to seek more information about the advertised brand, which finally leads to higher purchase intentions (Chu, Kamal, & Kim, 2013). Other scholars found that a positive attitude from users towards
11 a certain social media influencer affects audiences’ intentions to purchase the influencers’ promoted product or service (Lim et al., 2017). Lu, Chang and Chang (2014) also found a positive relation between users’ attitude towards a sponsored recommendation post and users’ purchase intention.
Finally, Nunes, Ferreira, de Freitas and Ramos (2018) claim that persuasive messages from online opinion influencers on social media lead to approval of the content of the
message, a positive attitude concerning the purchase of the recommended product or service and, in turn, enhancement in the purchase intention of the recommended service or good. In conclusion, a mediating effect of followers’ attitude towards the recommended destination is expected based on the results on the relationship between social media posts from influencers, followers’ attitudes and purchase intentions.
H1c: The relationship between the type of influencer and followers’ travel intention is mediated by followers’ attitude towards the destination.
Para-social relationship (PSR)
The concept of para-social relationship (PSR) describes the establishment of one-sided consumer relationships with media personas or celebrities (Labrecque, 2014; Rubin & Step, 2000). More specifically, PSR can be viewed as a hallucinatory relationship as audiences interact or engage with mediated personas like they are actually present and committed to this mutual relationship (Labrecque, 2014). Whereas para-social relationships specifically concern a long-lasting relationship that involves more than one interaction, para-social interactions include the understanding of a media personality as a confidant conversational companion that appears during the interaction itself (Dibble, Hartmann & Rosaen, 2016; Munnukka, Maity, Reinikainen, & Luoma-aho, 2019). PSR can lead to audiences perceiving these personas as real friends who they know and understand (Perse & Rubin, 1989; Stern,
12 Russell, & Russell, 2007). Additionally, audiences come to view these celebrities and
personas as trustworthy sources and follow advise from them as they would from actual friends (Rubin, Perse, & Powell, 1985). Finally, PSR increases when audiences perceive these personalities as more similar to themselves (Eyal & Rubin, 2003).
Just like audiences develop such relationships with celebrities through their visibility in traditional media, they also form relationships with vloggers through their frequent
exposure online (Lee & Watkins, 2016). With the increase of social media use overall, social media users now also form PSR with other users (Shin, 2016). The expansion in the reliance on the Internet enhances this process as it provides audiences with boundless access to media sources (Shin, 2016).
More specifically, the establishment and strength of PSR are dependent on interactivity and openness in communication (Labrecque, 2014). Whereas interactivity involves audiences’ perception of taking part in two-way communication, openness in
communication refers to self-disclosure from the mediated source (Labrecque, 2014; Perse & Rubin, 1989). Especially the time to respond and message personalisation are essential aspects for perceived interactivity (Song & Zinkhan, 2008). As social media influencers are known for sharing details of their everyday lives to their followers and interacting with them openly (Dhanesh & Duthler, 2019), it is likely that users view influencers as interactive and open and, therefore, will establish PSR with them more easily. Since followers perceive other social media users and digital celebrities as friends whom they trust, they also get influenced by their product evaluations (Hwang & Zhang, 2018).
The moderating role of para-social relationship
Audiences who engage in PSR identify themselves with the mediated personas they interact with (Dibble et al., 2016). Higher levels of PSR result in audiences coming to view
13 these personas as actual friends who they trust, understand and follow advice from (Perse & Rubin, 1989; Rubin et al., 1985). Forbes (2013) found that people base their purchases on recommendations from people they do not regard as opinion influencers but from connected friends instead. Based on this, it can be assumed when audiences perceive a higher level of PSR, recommendations from influencers are likely to exert a larger impact on followers’ travel intentions than when PSR is low, indicating a moderating effect of PSR.
Additionally, the strength of PSR partially relies on interactivity and openness in communication by the mediated source (Labrecque, 2014; Perse & Rubin, 1989). As micro-influencers are known for their interactivity by involving in dialogues with their followers in the comments, direct communication and personal interaction (Anderson, 2019; Hudson, 2019), it is likely for followers to develop PSR with them. This leads to the belief that because of the characteristics of micro-influencers and PSR, the effect of micro-influencers on
followers’ travel intentions will be stronger for higher PSR than for lower PSR. Based on these findings, the following moderator hypothesis is posed:
H2: Travel recommendations from micro-influencers will lead to higher travel
intentions than travel recommendations from macro-influencers, but this effect will be more pronounced for higher PSR than for lower PSR.
Source credibility
Source credibility refers to the extent of trustworthiness and expertise of a certain source (Hovland, Janis, & Kelley, 1953; Pornpitakpan, 2004). On the one hand,
trustworthiness refers to the amount to which viewers assume the claims made by a source to be valid, while expertise includes the degree to which a source is viewed to be competent to make accurate statements (Hovland et al., 1953). Ohanian (1990) expanded the construct of source credibility and defines it, in turn, as all the favourable traits of a communicator that
14 influence the audience’s approval of the message. Thereby, the scholar also added psychical attractiveness as an element of the concept as this has become a significant component with the growing use of celebrity endorsers for brands (Baker & Churchill, 1977; Caballero & Solomon, 1984; Ohanian, 1990).
Credibility focuses on the perceived quality of the communication by the receiver (Sokolova & Kefi, 2020). More importantly, source credibility also involves the degree to which the audience obtains information from this source for their perception of a specific good or service (Ohanian, 1990). Consequently, the perceived credibility of a source also affects the credibility of its disseminated communication, whether it is face-to-face or digital (Lowry, Wilson, & Haig, 2014).
The moderating effect of credibility
Relatability and credibility are two powerful source characteristics in terms of influence and persuasiveness (Djafarova & Rushworth, 2017; Horai, Naccari, & Fatoullah, 1974; Maddux & Rogers, 1980). Audiences are likely to disregard the claims made in a message from low-credibility sources (Eagly & Chaiken, 1975), whereas recommendations from high-credibility sources tend to have more impact on one’s recommendation adoptions, and thereby behavioural intentions (Luo, Luo, Schatzberg, & Sia, 2013). So, the effects of influencers’ recommendations on social media are likely to be stronger when audiences perceive the credibility of the source to be higher than when source credibility is lower, implying a moderating effect of source credibility.
Schouten, Janssen and Verspaget (2020) add to this that social media users feel that influencers are more trustworthy, more similar and easier to identify with than celebrities. According to them, consumers find influencers more credible because they perceive them to express true judgments without promotional goals (Evans, Phua, Lim, & Jun, 2017). As
15 bigger influencers are being perceived more and more as actual celebrities (Kim, 2012), viewers will perceive smaller influencers as more trustworthy, and thereby, more credible. Additionally, Gupta and Mahajan (2019) also found that Instagram users perceive micro-influencers, specifically, as relatable and trustworthy and thereby as more credible. This would mean that because of the features of micro-influencers and source credibility, the impact of micro-influencers’ recommendations on followers’ travel intentions will be stronger for higher source credibility than for lower source credibility. Based on this discussion, this study hypothesizes:
H3: Travel recommendations from micro-influencers will lead to higher travel
intentions than travel recommendations from macro-influencers, but this effect will be more pronounced for higher source credibility than for lower source credibility.
All hypotheses and relationships between the key variables are shown in the conceptual model (figure 1).
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Methods
Design
Two online survey experiments were conducted with a 2 (type of influencer: micro-influencer vs. macro-micro-influencer) x 2 (source credibility: low vs. high) and 2 (type of
influencer: micro-influencer vs. macro-influencer) x (para-social relationship: low vs. high) factorial between-subjects design with para-social relationship and source credibility as moderators. As the goal was to test PSR and source credibility as separate moderators, there was chosen to conduct two separate experiments in the design in order not to mix up source credibility and PSR and thereby the complete vignette design. A between-subjects design was chosen to avoid a possible carry-over effect as participants being exposed to numerous
conditions could impact responses in later conditions and cause bias (Greenwald, 1976). Dutch participants were randomly assigned to one of the eight conditions differing in source credibility, PSR and the type of influencer. Figure 2 and 3 provide the design diagrams of the eight conditions.
Source credibility
Type of influencer Low source credibility High source credibility
Micro-influencer Condition 1 (n = 41) Condition 2 (n = 40) Macro-influencer Condition 3 (n = 32) Condition 4 (n = 51)
17 Para-social relationship (PSR)
Type of influencer Low PSR High PSR
Micro-influencer Condition 5 (n = 39) Condition 6 (n = 34) Macro-influencer Condition 7 (n = 46) Condition 8 (n = 40)
Figure 3. Experiment B: experimental design including sample distribution (n = 159)
Stimulus material
The stimulus material presented in the experiment is the fictitious Instagram account of a travel couple named Isabelle and Danny (Instagram handle: @Alwaysonthemove) including their Instagram feed, three different Instagram posts with captions and two comments sections. A fictitious Instagram account was chosen to avoid any pre-existing judgements, established PSRs and perceived source credibility regarding existing influencers. Furthermore, a couple was chosen to avoid any gender bias and possible gender identification. The shown pictures were taken from various, real travel Instagram pages. Appendix A shows all the stimulus material and the eight conditions.
Type of influencer. As the research focuses on micro- and macro-influencers, the
number of followers for the micro-influencer condition was set at 2,212 whereas the number for the macro-influencer account was set at 2.7 million to have a clear distinction between the two categories. Besides the number of followers, every other visual aspect was exactly the same in terms of the number of followees, number of pictures, profile picture, bio and the pictures shown in the feed. The three Instagram posts shown for both conditions were also manipulated the same way with the caption and picture, except for the number of likes and number of comments as they were made higher for the macro-influencer condition and lower
18 for the micro-influencer condition. These numbers were manipulated based on real
influencers’ Instagram accounts.
Para-social relationship. According to Labrecque (2014), PSR can be established by a
source through interactivity and openness in communication. Therefore, the PSR conditions were made based on these two message cues. Openness in communication was created through the change in the caption of the Instagram post. Both conditions showed exactly the same images, format, caption length, amount of likes and comments as this guaranteed equivalence in terms of visual presentation. The only difference was found in the text where the low condition mentioned general information about the place, whereas the high condition included personal aspects such as personal memories or feelings from the couple.
Interactivity, in turn, was manipulated through the comment section of the Instagram posts. According to Song and Zinkhan (2008), the time to respond and message
personalization are crucial aspects of perceived interactivity. Therefore, in the high PSR condition, the responses of the account were personalized by replying to actual Instagram-followers directly within an hour after the comment was made. In the low PSR condition, the account only replied generically by addressing everyone at once after four days. All
comments were modelled from real-life comments found on Instagram travel accounts.
Source credibility. Source credibility was manipulated by describing the source, the
travel couple, in two ways. In the low source credibility condition, the couple was described as being known for their travel pictures in different countries, but also for little mistakes found in some of their travel pictures which made followers doubt whether they have been in the places they said they were or whether they made places prettier than how they looked in real-life. On the other hand, the couple was manipulated as highly credible by depicting them as an account known for their travel pictures in different countries, having visited more than fifty countries and therefore very experienced travellers who like to share their experiences.
19
Manipulation check
A manipulation check was conducted to find out whether the participants perceived the micro-influencer and macro-influencer conditions, the high vs. low para-social
relationship conditions and the high vs. low source credibility conditions as intended.
Appendix B provides an overview of the original and translated items of the multi-item scales. Type of influencer. Regarding micro- and macro-influencer, three items were used from De Veirman et al. (2017) to measure the perception of the number of followers and popularity of the influencers. The question asked were: “Isabelle and Danny from
Alwaysonthemove have a (1) very small versus (7) verge large number of followers”, “The number of followers from Isabelle and Danny from Alwaysonthemove are (1) much smaller versus (7) much larger than the average influencer’s number of followers” and, finally, “Do you think that Isabelle and Danny from Alwaysonthemove are (1) very unpopular to (7) very popular”. Responses to the last question were measured on a 7-point Likert scale instead of the original 5-point scale as it provides a more precise assessment of a participant’s evaluation (Finstad, 2010). An independent sample t-test was conducted to test whether participants perceived the micro-influencer and macro-influencer conditions as intended. The test showed a significant difference between the micro-influencer (M = 3.83, SD = 1.09) and macro-influencer (M = 5.50, SD = 1.02), t(321) = -14.19, p < .001.
Para-social relationship. The manipulation of PSR was assessed by using ten items
from the modified 10-item scale created by Rubin and Perse (1987) proven successful in measuring PSR with soap opera characters, other media characters and YouTubers (de Bérail, Guillon, & Bungener, 2019). The wording of the items was somewhat adapted to the
Instagram context and examples of the scale include “Isabelle & Danny from
Alwaysonthemove make me feel comfortable, as if I am with friends” and “I see Isabelle & Danny from Alwaysonthemove as natural, down-to-earth persons”. Responses were measured
20 on a 7-point Likert scale ranging from (1) “strongly disagree” to (7) “strongly agree” instead of the original 5-point scale as it provides a more accurate measurement of a participant’s judgment (Finstad, 2010). Another independent sample t-test was conducted to assess whether the low vs. high PSR conditions were perceived as intended and showed no significant
difference between the low PSR (M = 3.41, SD = 0.97) and high PSR conditions (M = 3.35, SD = 1.18), t(157) = 0.37, p = .710.
Source credibility. To check for the source credibility conditions, the well-established
7-point semantic differential pairs scale by Ohanian (1990) was used. To assess whether participants viewed the authors as credible, the five items to measure trustworthiness where used: undependable-dependable, dishonest-honest, unreliable-reliable, insincere-sincere, and untrustworthy-trustworthy. Because of semantic differences, undependable-dependable, untrustworthy-trustworthy and unreliable-reliable, could only be translated into one item in Dutch. This resulted in three items being used in the survey. A final independent sample t-test revealed a significant difference between the low source credibility condition (M = 3.56, SD = 1.13) and high source credibility condition (M = 4.51, SD = 1.41), t(162) = -4.79, p < .001. In conclusion, the manipulations for the type of influencer and source credibility were successful whereas the one for PSR was not.
Sample
All participants were recruited online through the use of non-probability sampling and, more specifically, convenience sampling, by spreading the online survey experiment via the researcher’s network on Whatsapp, Facebook, LinkedIn and Instagram. The requirements shown in the introduction text made clear that only Dutch participants above 18 years could participate in the research.
21 values. Finally, a sample size of 323 was used (N = 323) of which 75.9% was female and 23.8% was male. Participants were aged between 18 and 66 (M = 25.91, SD = 6.70) and 94.4% of all participants had an Instagram profile. In addition, 93.4% of respondents with Instagram accounts were daily users of Instagram of which 73.7% used Instagram less than two hours a day. Finally, 66.3% travelled internationally 1 or 2 times per year.
Procedure
After reading and approving the informed consent (Appendix C), participants were exposed to the first question checking for the inclusion criteria (Dutch nationality and above 18 years). Participants who fit both inclusion criteria were randomly assigned to one of the eight conditions and asked to look at and read the Instagram account, feed, posts and
comments section, carefully. A 15-second time-lock was used to make sure attention was paid closely to the stimuli. After the stimuli, based on the specific condition, was shown to the participant, a manipulation check followed regarding their perceptions of the popularity of the influencer, their evaluation of the source’s credibility or the level of PSR. After that, the participants were asked about their attitude towards the recommended destination and their final intention to visit the recommended destination. The questionnaire ended with
demographic questions. Finally, the participants were debriefed and thanked for participating (Appendix C).
Measurements
All the scales were translated from English into Dutch for the survey. Appendix B provides an overview of the original and translated items of the multi-item scales.
Dependent variables. Attitude towards the destination. Attitude towards the
22 scale. The items were extracted from the study from Jalilvand, Samiei, Dini and Manzari (2012) as these were specifically used to assess attitude towards a destination (bad-good, worthless-valuable, unpleasant-pleasant). A principal component factor analysis (PCA) with Varimax rotation was conducted and yielded one unidimensional scale with an eigenvalue above 1 (eigenvalue 2.66), which explained 88.53% of the variance. All items showed factor loadings above .90 and the scale showed good reliability (α = .94), (M = 5.32, SD = 1.17). Table 1, Appendix D, provides all the factor loadings.
Travel intention. The intention to travel to the promoted destination was measured by the three-item scale from Jalilvand et al. (2012) proven reliable in assessing travel intentions, namely “I predict I will visit .. in the future”, “I would visit .. rather than any other tourism destination” and “If everything goes as I think, I will plan to visit .. in the future”. They were all assessed on a 7-point Likert scale ranging from “strongly disagree” to “strongly agree”. A PCA indicated that the 3 items of the scale form one unidimensional scale with an eigenvalue above 1 (eigenvalue 2.25), which explained 74.99% of the variance. All items had factor loadings above .75 and the scale showed to be reliable (α = .83), (M = 3.81, SD = 1.36). Consider Table 2, Appendix D, for all the factor loadings.
Randomization check
Numerous Chi-square tests of independence revealed no significant differences in experiment 1 for gender, X²(3, N = 164) = 7.11, p = .069, nor for the covariates Instagram account, X²(3, N = 164) = 3.20, p = .362, use of Instagram X²(6, N = 156) = 8.40, p = .210, daily use of Instagram, X²(12, N = 147) = 8.97, p = .706, and amount of international travel, X²(12, N = 164) = 7.34, p = .834, between the four conditions. A one-way ANOVA also revealed no significant differences for age between the conditions, F(3, 160) = 0.41, p = .749. For experiment 2, several Chi-square tests of independence also showed no significant
23 differences for gender, X²(6, N = 159) = 4.76, p = .575, nor for the covariates Instagram account, X²(3, N = 159) = 2.68, p = .444, use of Instagram, X²(6, N = 149) = 12.41, p = .053, daily use of Instagram, X²(12, N = 138) = 9.79, p = .634, and amount of international travel X²(12, N = 159) = 7.18, p = .846. Finally, a one-way ANOVA also did not show any significant differences for age in experiment 2, F(3, 155) = .52, p = .672. Hence,
randomization for both experiments was successful and no control variables were subject to subsequent analyses.
Results
Hypothesis 1a predicted that travel destination recommendations from micro-influencers have more influence on followers’ attitudes than travel recommendations from macro-influencers. To test this, an independent sample t-test was conducted with the type of influence as independent variable and attitude towards the destination as dependent variable. It revealed no significant difference between the impact of the micro-influencer (M = 5.34, SD = 1.20) and macro-influencer (M = 5.31, SD = 1.16) on attitude, t(321) = 0.25, p = .806. To assess whether micro-influencers’ travel destination recommendations have a stronger impact on followers’ travel intentions than travel recommendations from macro-influencers, proposed in hypothesis 1b, another independent sample t-test with the type of influencer as independent variable and travel intention as dependent variable was it
conducted. It also showed no significant difference between the micro-influencer (M = 3.74, SD = 1.38) and macro-influencer (M = 3.87, SD = 1.34), t(321) = -0.88, p = .379. Therefore, hypothesis 1a and hypothesis 1b have to be rejected.
Hypothesis 1c proposed that the relationship between the type of influencer and travel intention would be mediated by attitude towards the destination and was tested using
24 The first model was insignificant, F(1, 321) = 0.06, p = .804, R² < .01. It revealed that the type of influencer has a negative and insignificant effect on attitude towards the destination, b = -0.03, SE = 0.13, t(321) = -0.25, p = .806. The second model revealed to be significant, F(2, 320) = 38.05, p < .001, and predicted 19% of the variance in travel intention (R² = .19). It showed a positive insignificant effect of the type of influencer on intention, b = 0.15, SE = 0.14, t(320) = 1.10, p = 0.274, and a positive significant effect of attitude towards the destination on travel intention, b = 0.50, SE = 0.06, t(320) = 8.67, p < .001. Finally, the indirect or mediation effect revealed to be insignificant, b = -0.02, SE = 0.07, 95% BCa CI [-0.15, 0.12]. Hence, hypothesis 1c has to be rejected (figure 4).
Figure 4. Mediation effect of attitude towards the destination.
Hypothesis 2 predicted that PSR would moderate the relationship between the type of influencer and followers’ travel intentions in such a way that the relationship between micro-influencers and followers’ travel intentions is stronger when PSR is higher. As the
manipulation check was unsuccessful, this hypothesis could not be tested properly. Despite this, a factorial ANOVA was still conducted to assess the main effects of the type of influencer and PSR on travel intention and the interaction effect between the two on travel intention. It revealed no significant main effect of the type of influencer, F(1, 155) = 0.94, p =
25 .333. The results also showed no significant main effect of PSR on travel intentions, F(1, 155) = 0.08, p = .776. Finally, the interaction effect also was insignificant, F(1, 155) = 0.00, p = .999. Thus, hypothesis 2 has to be rejected.
Finally, hypothesis 3 proposed that travel recommendations from micro-influencers would lead to higher travel intentions than travel recommendations from macro-influencers, but that this effect would be more pronounced for higher source credibility than for lower source credibility. A factorial ANOVA was conducted to measure the main effects of the type of influencer and source credibility on travel intention and the interaction effect between the two on travel intention. The main effect of the type of influencer showed to be insignificant, F(1, 160) < 0.01, p = .961. The main effect of source credibility, however, revealed to be significant, F(1, 160) = 5.76, p = .018. Finally, the interaction effect was not significant, F(1, 160) = 0.24, p = .622. Therefore, hypothesis 3 can not be accepted.
Conclusion and discussion
In light of the popularity of online influencer marketing and a tremendous increase in international travel, this research aimed to shed more light on the effects of types of
influencers, psychological aspects and source characteristics in the promotion process of travel destinations on Instagram. More specifically, it looked into the effects of micro- and macro-influencers on attitude towards the travel destination, travel intentions and the effects para-social relationships and source credibility potentially have on this relationship as moderators and attitude towards the destination as mediator.
This study showed that influencers with a relatively smaller amount of followers, named micro-influencers, do not have a stronger impact on followers’ attitude towards the destination and followers’ travel intentions with their travel destination recommendations on
26 Instagram than the recommendations from macro-influencers. This result refutes earlier studies that argue that recommendations or advertisements from less followed accounts lead to higher purchase intentions (De Veirman et al., 2017; Kay et al., 2020; Lim et al., 2017; Sammis et al., 2016). One of the elucidations for this could be that despite the expansion of travel-related information online, travellers continue to be persuaded to a greater degree by recommendations from friends or real-life contacts than by other Internet users such as online influencers overall (Hernández-Méndez, Muñoz-Leiva, & Sánchez-Fernández, 2015). As one of the reasons for the success for micro-influencers was predicted because of their extensive interaction with their followers (Alassani & Göretz, 2019; Wessel, 2018), WOM from real-life friends and acquaintances have proved to impact travellers’ behavioural intentions more than any other communication with internet users, whether they know them or not
(Hernández-Méndez et al., 2015).
Another interpretation of this result could be related to the complexity of travel decision making. Whereas certain products or services can be easy and cheap to acquire and decide upon, travel decisions include a great deal of budgetary and personal risks and
therefore potential travellers usually obtain information from numerous sources instead of just one (online) source to decrease these perceived uncertainties (Mäser & Weiermair, 1998). This would also explain why the impact of both types of influencers on followers’ attitude towards the destination was measured more positively than on the final intention to travel to the destination.
As there was no direct effect found from the type of influencer’s online travel
recommendations on followers’ travel intention, there was also no possibility for a mediating effect of followers’ attitude towards the destination in this relationship. Although this study showed no difference between micro- and macro-influencers in terms of their impacts, it did reveal a direct impact from people’s attitude towards a travel destination on one’s final travel
27 intention. This is in accordance with earlier studies that claim that one’s attitude eventually leads to higher behavioural intentions (e.g. Chu et al., 2013; Lim et al., 2017; Lu et al., 2014). Regarding the moderating influence of para-social relationships on the relationship between the type of influencer and travel intention, no clear conclusions can be drawn as the PSR manipulation may have failed to influence travel intention as it was intended. Besides, this research shows no moderating effect of PSR which contradicts existing findings that when PSR is more apparent, the impact of a social media influencer on one’s purchase
intentions will be stronger too (e.g. Chi, Yeh, & Yang, 2009; Hwang & Zhang, 2018; Malik et al., 2013). The fact that the manipulation for PSR did not show successful could be explained as PSR tends to develop over time (Eyal & Rubin, 2003). Instead, followers of the fictitious account Alwaysonthemove were only exposed to the influencers’ content once and therefore it could be harder to feel this deeper connection. This was also confirmed by Rubin et al. (1985) who claim that repeated measure to a certain media persona can evoke an
improvement in the feeling of a relationship and that followers only start to see this media persona as a trusted source of information when this relationship advances.
Interestingly, the role of PSR in this relationship is also arguable. Although this thesis looked into para-social relationships as a moderator which would strengthen the relationship between micro-influencers and final travel intention with higher perceived levels of PSR, it could also be a possible mediator. As micro-influencers are known for their excessive interactivity by engaging in dialogues and direct communication with their followers
(Anderson, 2019; Hudson, 2019), it can be assumed that the level of PSR will also be higher as it partly depends on interactivity (Labrecque, 2014). In turn, numerous studies have shown that para-social relationships with social media influencers significantly increase audiences’ purchase intentions (Hwang & Zhang, 2018; Kim et al., 2015; Lee & Watkins, 2016;
28 moderator to explain the relationship between micro-influencer and travel intentions.
Additionally, the role of source credibility was also taken into account in the relationship between the type of influencer and the intention to travel to a promoted
destination. Again, as there was no direct influence found from the type of influencer on the travel intention, there could also be no interaction effect of source credibility. Numerous earlier studies, however, argue for a stronger relationship between influencers’
recommendations on social media and followers’ behavioural intentions when the source is perceived as more credible (e.g. Eagly & Chaiken, 1975; Gunawan & Huarng, 2015; Luo et al., 2013; Mizerski, Golden, & Kernan, 1979). Despite this, a direct effect was found from source credibility on followers’ travel intentions. This confirms previous results that credible sources are more powerful regarding their influence on followers than low-credibility sources (e.g. Djafarova & Rushworth, 2017; Maddux & Rogers, 1980). According to Currie et al. (2008), consumers who encounter uncertainty, which is often the case in the elaborate process of travel decision making, seek credible sources that are able to guide them in their decisions. Finally, the role of source credibility in the relationship between micro-influencers and travel intention could also be debatable. As influencers with a larger follower base are
recognized more and more as celebrities who are less trustworthy and harder to identify with, influencers with a smaller follower base such as micro-influencers are perceived as more trustworthy (Evans et al., 2017; Kim, 2012; Schouten et al., 2020). As trustworthiness is one of the components of credibility, it is likely for micro-influencers to lead to more credibility. Finally, this positively affects people’s behaviours and purchase intentions and thereby one’s travel intentions (Gunawan & Huarng, 2015; Ohanian, 1990). In conclusion, the part of source credibility in this relationship could be looked at as both a moderator or mediator.
29
Implications
Theoretically, these results imply that there is no clear and proven medallist in terms of influencer type yet. It is, however, another extension on the literature on influencer marketing and shows that solely the number of followers, likes and comments do not influence followers in their travel intentions. Thereby, an extra dimension of influencer marketing and travel marketing has been explored. Besides, it confirms the importance of attitude as a predictor of behavioural intentions. Finally, the role of source credibility specifically has shown to be a relevant aspect when it comes to travel intentions.
For marketing executives in the travel sector these results imply that they should not bet their money on just one type of influencer yet. As both smaller and larger Instagram accounts in terms of followers have proven to be almost equal in their impacts on their followers’ attitudes towards their promoted travel destination and final travel intentions, marketing experts should use this information for their social media strategies. As micro-influencers are known to be cheaper and known for their niche audiences (Hatton, 2018), travel marketers and travel businesses overall should consider collaborating with the smaller players in the Instagram field instead of only focussing on the bigger ones. Thereby, they could work together with multiple micro-influencers for the price of one macro-influencer and thereby try out different collaborations while reducing their marketing costs instead of betting on one bigger and more expensive influencer.
Finally, travel businesses should pay close attention to source characteristics when seeking out the right influencer for their travel promotions. As Instagram users are more likely to be influenced in their behavioural intentions by credible sources, marketers should look extensively into the existing image, experience and background of the influencers they would like to collaborate with.
30
Limitations and future research
This research has several limitations that simultaneously offer opportunities for future research. Firstly, as the manipulation of PSR showed to be unsuccessful, no clear conclusions could be drawn about the possible interaction effect PSR might have on the relation between the type of influencer and the travel intention. As PSR tends to develop over time (Eyal & Rubin, 2003; Rubin et al., 1985), future research should investigate PSR with a real instead of a fictitious Instagram account which respondents are already familiar with. Another way to investigate the possible impact of PSR more closely would be with a longitudinal study where participants will be observed repeatedly on PSR over a longer period of time.
Also, both roles of source credibility and PSR have shown to be debatable in the relationship between micro-influencers, specifically, and audiences’ travel intentions (Evans et al., 2017; Gunawan & Huarng, 2015; Hudson, 2019; Lee & Watkins, 2016). As this thesis focused on them solely as moderators in this relationship, it would be interesting for future research to look into the effects of source credibility and PSR more deeply to see whether they act as moderators or mediators. This could result in more clarity around the potential success of micro-influencers and their impact on their followers' attitudes and intentions. Although this thesis looked separately into PSR and source credibility as constructs, earlier research also looked into possible relations between the two variables. More
specifically, Munnukka et al. (2019) found a positive effect of PSR on perceived source credibility. Additionally, Jin and Muqaddam (2019), argue for PSI as one of the components of credibility. More research is needed to investigate the correlations between these two constructs in relation to influencers’ recommendations and behavioural intentions.
Fourthly, although careful consideration was given to all the manipulations and stimuli to make them as real as possible, future studies should include more real data. They could integrate real travel influencers, their accounts, posts and captions in a field experiment
31 setting to see if the outcomes would be different.
Besides, this study did not make use of a pre-test due to its limited scope and time frame. Although the manipulation of PSR was duplicated and only adjusted to travel-related content from the study of Labrecque (2014), future studies should look more closely into the manipulation opportunities for PSR as it has proven to be an important construct in online marketing with its impact on viewers and followers (Chi et al., 2009; Hwang & Zhang, 2018; Malik et al., 2013).
Furthermore, this study only focussed on the differences between micro- and macro-influencers in terms of the number of followers, likes and comments, but did not look into the differences often discussed by marketing professionals such as distinctions in interaction with followers, type of contents and type of audience. As adding such differences all in one
experiment would be too difficult to control for, future studies should focus on other
differences between micro- and macro-influencers and which aspects could account for more or less success for either one of those influencers.
Finally, to gain a more comprehensive understanding of how travel influencers affect people’s attitudes and behavioural intentions, future research should investigate more possible mediators and moderators such as other source characteristics (e.g. source attractiveness) audience characteristics, prior knowledge or beliefs from the audience and the type of influence exercised by the influencer.
Conclusion
In a world where both international travels and social media keep expanding tremendously (Clement, 2019; Leposa, 2019), utilizing social media in an effective and successful way has become crucial for the travel industry and marketing professionals. While both recent studies and marketing professionals have been arguing for the success of
micro-32 influencers in influencer marketing (De Veirman et al., 2017; Kay et al., 2020; Wessel, 2018), the findings of this research do not confirm a higher impact on their followers’ travel
destination attitudes and travel intentions from micro-influencers compared to macro-influencers. In addition, this study does not show a mediating effect of attitude towards the destination on the relationship between the type of influencer and the final travel intention but does confirm a direct effect of attitude on the intention. Finally, it does not confirm a
moderating effect of both PSR and source credibility on this relation but does show the direct importance of source credibility on followers intentions. Therefore, travel marketing
executives should try collaborations with different types of influencers and always keep in mind the importance of consumer attitudes and source characteristics such as credibility when they decide to collaborate with influencers to accomplish a successful social media strategy.
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