Influencer marketing: the more followers, the better? The effect of macro - versus micro-influencers on the influencers' perceived credibility, while considering the role of brand fit in this relationship

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Influencer marketing: the more followers, the better?

The effect of macro - versus micro-influencers on the influencers' perceived

credibility, while considering the role of brand fit in this relationship.

Master thesis Persuasive Communication

University of Amsterdam

Student: Demi Buijs

Supervisor: Dr. Ivana Busljeta Banks Student number: 11068272

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Abstract

Advertisers try to find new and more effective ways of advertising due to the advertising clutter and its negative consequences (Kadić-Maglajlić, Arslanagić-Kalajdžić, Micevski,

Michaelidou, & Nemkova, 2017). Because consumers spend more time on social media nowadays (Childers, Lemon & Hoy, 2019), it is unavoidable marketers find their new ways of advertising online. Social media influencers are considered to be the most effective and cost-efficient marketing trend nowadays (Harrison 2017; Patel 2016; Talaverna 2015) and, therefore, more brands use social media influencers to promote their products (de Veirman, Cauberghe & Hudders, 2017). However, a distinction between micro-influencers (less than 100.000 followers) and macro-influencers (100.000 followers or more) can be made (Fuller, Gross, Zullo &

Valentine, 2019). Earlier research has found micro-influencers are characterized by credibility (Alassani & Göretz, 2019) due to their higher personal engagement compared to

macro-influencers (Fuller et al., 2019; Lim et al., 2017). This higher credibility generally leads to lower resistance to the message, and is, therefore, more effective than traditional advertising tactics (de Veirman et al., 2017). To build on existing literature, this research will examine the influence of the type of influencer on perceived credibility in which brand fit will be considered as a

moderator in this relationship. It is expected that micro-influencers will have a higher perceived credibility compared to macro-influencers, and this effect will be stronger when the brand fit is stronger. Results showed no hypotheses could be accepted. Discussion and limitations will be discussed hereafter.

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Introduction

Nowadays, you see commercials literally everywhere around you. This is also known as the advertising clutter (Kadić-Maglajlić, Arslanagić-Kalajdžić, Micevski, Michaelidou, & Nemkova, 2017). This advertising clutter can be seen as annoying and could cause a negative attitude towards advertising (Rauwers et al., 2017). This negative attitude is a result of the activation of the advertising scheme (Dahlén and Edenius, 2007). Such a scheme can be defined as a mental network that helps interpreting of information and automatically reacts to this information. Advertisements that activate the advertising scheme can cause a reduction of the attention and memory of the advertisement, counterarguments, a reduction of the believability and a less positive attitude towards the advertisement. This all happens when a person identifies an advertisement as an advertisement. (Dahlén and Edenius, 2007). Advertisers, therefore, try to find new and more effective ways of advertising. Because consumers spend more time on social media nowadays (Childers, Lemon & Hoy, 2019), it is unavoidable marketers find their new ways of advertising online.

Recent studies show U.S. adults spend approximately 2.15 hours per day on social

platforms, which makes up 33% of all online activity (Childers, Lemon & Hoy, 2019). According to Alassani and Göretz (2019), social media is a revolution in media development. Some of the biggest social media platforms are Facebook, Twitter, YouTube and Instagram, of which

Instagram has gained acknowledgement and popularity due to its visual content and obtains high levels of user engagement. This means the majority of users check the platform on a daily basis (Duggan & Smith, 2013). The social platform Instagram, thus, offers a valuable opportunity for companies to market their products and services, for example through influencers. A specific part of online advertising is social media influencers, who make it possible to advertise without it being directly recognized as advertisement (Alassani & Göretz, 2019). This is because their advertisements are often seamlessly woven into daily narratives (de Veirman et al., 2017).

These social media influencers are considered to be the most effective and cost-efficient marketing trend nowadays (Harrison, 2017). This is why more brands use social media

influencers to promote their products (de Veirman, Cauberghe & Hudders, 2017). De Veirman et al. (2017) describes social media influencers as people who have built a sizeable social network of people following them. Social media influencers are likely to be interpreted as highly credible electronic Word of Mouth (eWOM) rather than paid advertising, as their advertisements are often

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seamlessly woven into the daily narratives influencers post on their Instagram accounts (de Veirman et al., 2017). This higher credibility generally leads to lower resistance to the message, and is, therefore, more effective than traditional advertising tactics (de Veirman et al., 2017).

The size of this social network can differ between types of influencers. Micro-influencers have a smaller number of followers compared to macro-influencers, who typically have 100.000 followers or more (Fuller, Gross, Zullo & Valentine, 2019). Although the number of followers of micro-influencers is smaller compared to macro-influencers, these followers will generally have a level of personal engagement beyond that of a macro-influencer (Fuller et al., 2019). This higher personal engagement will eventually lead to a higher perceived credibility (McCroskey & Teven, 1999).Because fees paid to these macro-influencers can range from thousands of dollars to hundreds of thousands of dollars for a promotional campaign (Fuller et al., 2019), the question is, whether investing in macro-influencers will be more effective than investing in micro-influencers with lower costs and a higher perceived credibility, and, thus, a lower resistance to the message (de Veirman et al., 2017). Earlier research has already found micro-influencers are characterized by credibility (Alassani & Göretz, 2019) due to their higher personal engagement compared to macro-influencers (Fuller et al., 2019; Lim et al., 2017). This research will, however, investigate this relationship again to confirm or disconfirm the already existing findings.

To build on existing literature, this research will examine whether the effect of the type of influencer on perceived credibility will be moderated by brand fit. By doing so, this research will fill this gap of knowledge. Nowadays, there are thousands of different influencers available on Instagram who all have different interests and other characteristics (Swant, 2016). It is important to look at the fit between influencer and brand (Breves, Liebers, Abt & Kunze, 2019). Influencer-brand fit, namely, has a positive influence on the image of the influencer and on the effectiveness of advertising, according to Breves et al. (2019). On the other hand, influencers endorsing

incongruous brands risk damaging their perceived credibility (Breves et al., 2019).

The final research question will be: What is the influence of type of influencer (micro-influencer vs. macro-(micro-influencer) on the (micro-influencers' perceived credibility? And is this relationship

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Theoretical background

Influencer marketing

Companies increasingly turn to social media influencers, also known as

'micro-celebrities', in addition to using 'traditional' celebrities to add value to a brand (Schouten, Janssen & Verspaget, 2019). These 'micro-celebrities' could be, for example, vloggers or 'instafamous' personalities (Schouten, Janssen & Verspaget, 2019). Social media influencers are considered to be the most effective and cost-efficient marketing trend nowadays (Harrison, 2017).

Approximately 80% of online marketers claimed social media influencers are potential endorsers who boost their online businesses to higher levels, according to Media Kix marketing (Forbes, 2017). This is why advertisers are investing large budgets on influencer endorsements (Schouten, Janssen & Verspaget, 2019). Influencer marketing emphasizes the use of influencers to

communicate a brand’s message to reach the target audience (Lim, Cheah & Wong, 2017). Social media influencers are used to publicize product information and latest promotions to online followers on social media (Lim et al., 2017). These influencers, thus, typically engage with their followers by regularly updating them with the latest product information (Liu et al. 2012). They have built a sizeable social network of people following them (De Veirman et al., 2017) and represent a new type of independent third party endorser who shape audience attitudes through the use of social media (Freberg, Graham, McGaughey & Freberg, 2011). The size of their social network can differ between types of influencers. Influencers with less than 100.000 followers are known as micro-influencers, whereas macro-influencers typically have 100.000 followers or more (Fuller, Gross, Zullo & Valentine, 2019). Fees paid to these macro-influencers can range from thousands of dollars to hundreds of thousands of dollars for a promotional campaign (Fuller et al., 2019). However, followers of micro-influencers generally have a level of personal

engagement beyond that of a macro-influencer (Fuller et al., 2019).

Perceived credibility

It is clear now that social media influencers are likely to be interpreted as highly credible eWOM rather than paid advertising (de Veirman et al., 2017). This higher credibility generally leads to lower resistance to the message and is, as a result, more effective than traditional

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that showed social media influencers' messages are often perceived as more reliable and compelling to consumers. In these polls, consumers reported to be more likely to follow their favorite influencers' recommendations (Lim, Radzol, Cheah & Wong, 2017). According to Lim et al. (2017), due to social media influencers' amiability in building rapport with consumers, they are regarded as more credible, trustworthy and knowledgeable. This is especially the case for businesses that target the younger generations (Lim et al., 2017).

The difference between micro- and macro-influencers affects, as mentioned before, the perceived credibility of the influencer (Fuller et al., 2019; McCroskey & Teven, 1999). A micro-influencer has, generally, a higher personal engagement compared to a macro-micro-influencer (Fuller et al., 2019), which leads to a higher perceived credibility (McCroskey & Teven, 1999). Micro-influencers are characterized by credibility, relevance, and great social media engagement, which mean they interact often with their followers (Alassani & Göretz, 2019). Having fewer followers as a micro-influencer, thus, has its advantages. Although they have a lower reach compared to macro-influencers, fewer followers allow them to create a more intimate and personal community (Quarter, 2011). This translates to a higher rate of engagement with followers and a higher level of influential power over them, according to Quarter (2011). Followers of micro-influencers, therefore, generally have a level of personal engagement beyond that of a macro-influencer (Fuller et al., 2019). This micro-influencers' higher level of personal engagement translates into a higher perceived credibility, as Lim et al. (2017) found due to an influencers' amiability in building rapport with consumers, he or she is regarded as more credible, trustworthy, having more good will and knowledgeable.

Perceived source credibility can be defined as 'judgments made by a perceiver concerning the believability of a communicator' (Spence, Lachlan, Westerman, & Spates, 2013). According to McCroskey and Teven (1999), influencer credibility should be measured using three separate dimensions: competence, goodwill, and trustworthiness. Competence can be defined as the cognitive (e.g. knowledge and skills), affective (e.g. attitudes and values), behavioural and motivational (e.g. motives) characteristics or dispositions of a person, which enable him or her to

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It is expected that micro-influencers should be perceived as having more competence, goodwill and trustworthiness (Lim et al. (2017). Therefore,this research will build on existing literature about the influence of macro- versus micro-influencers on the influencers' perceived competence, goodwill and trustworthiness. By doing so, results will confirm or disconfirm the already existing findings. The dependent variable 'perceived credibility' will, thus, be split into three different dependent variables: 'competence', 'goodwill' and 'trustworthiness'. Finally, we predict that:

H1: Micro-influencers will be perceived to have more competence compared to macro-influencers.

H2: Micro-influencers will be perceived to have more goodwill compared to macro-influencers.

H3: Micro-influencers will be perceived to have more trustworthiness compared to macro-influencers.

Brand fit

Brand-influencer congruency implies that relevant characteristics of the influencer are consistent with relevant attributes of the brand (Misra & Beatty, 1990). A strong influencer-brand fit increases consumers' brand attitudes, behavioural intentions and the perceived credibility of the influencer (Breves et al., 2019). On the other hand, influencers endorsing incongruous brands decline their perceived credibility (Breves et al., 2019). This has also been confirmed by Kamins and Gupta (1994), who found that the more noticeable this congruency is, the more the consumer will accept the endorser’s influence, which will lead to greater advertising effectiveness and greater credibility (Kamins & Gupta, 1994). An influencer advertising a congruent brand leads thus to higher advertisement effectiveness, including higher perceived credibility, relative to an influencer advertising a less congruent brand-endorser image (Kamins & Gupta, 1994). This is because an absence of such a connection, namely, may lead consumers to distrust the influencer due to the belief that the influencer has been paid to promote the brand (Erdogan, 1999). On the other hand, influencers advertising a congruent brand, this perceived bias will be reduced (Erdogan, 1999).

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Because we measure credibility with the three constructs 'competent', 'goodwill' and 'trustworthiness', and we expect micro-influencers to be perceived as being more competent, having more goodwill, and being more trustworthy (Lim et al., 2017), we expect advertising a more congruent brand will strengthen this relationship. We, therefore, predict that:

H4: Micro-influencers will be perceived to have more competence compared to macro-influencers and this effect will be stronger when the brand fit is stronger.

H5: Micro-influencers will be perceived to have more goodwill compared to macro-influencers and this effect will be stronger when the brand fit is stronger.

H6: Micro-influencers will be perceived to have more trustworthiness compared to macro-influencers and this effect will be stronger when the brand fit is stronger.

Figure 1 shows the conceptual model including the independent variable, the dependent variables, the moderator, and the six hypotheses.

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Method

This paper investigated the influence of macro- versus micro-influencers on competence, goodwill and trustworthiness. Besides, brand fit was considered as a moderator. This is

investigated with an online experiment to take casualization into account. An experiment makes it possible to manipulate the independent variable and to measure the dependent variable (Boeije, 't Hart & Hox, 2009).

Sample & design

The questionnaire was placed on social media and filled in through the social network of the investigator. This makes the study a convenience sample (N = 100) in order to find as many participants as possible in the short amount of time available. Participants were eighteen years and older to be ethically approved and they had to fill in the whole questionnaire. They were randomly allocated to one of the two conditions, the macro-influencer condition or the micro-influencer condition.

The experiment is a 2 (type of influencer: micro versus macro) by 2 (brand fit: stronger vs. weaker) factorial between-subjects design about the influence of macro- versus micro-influencers on competence, goodwill and trustworthiness, with brand fit as a moderator.

Procedure

The questionnaire started as soon as the participant read the introduction of the

experiment and approved with the informed consent. The participants were randomly allocated to one of the two conditions. First, participants had to look at a picture from the assigned condition followed by a few questions to measure competence, goodwill, trustworthiness and brand fit. Before these questions appeared, the participants were kindly requested to pay attention to the brand of the clothes the influencer is wearing and the influencer itself. Hereafter, some questions appeared about their demographics, followed by a manipulation check. At the end the participants were thanked for participating in this research. See Appendix 1 for an overview of the

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Stimulus material

The stimulus material consists of a picture of an Instagram account of a Dutch macro-influencer named 'Rianne Meijer' including an Instagram post of her and her boyfriend. An Instagram account of a real influencer is chosen to keep the stimulus material as original as possible. Besides, Rianne Meijer posts a lot of pictures together with her boyfriend. This means her content is not only attractive for girls and bias because of gender differences will be limited. Participants assigned at the micro-influencer condition who were familiar with Rianne Meijer, were deleted. These participants could namely treat the stimulus material as a macro-influencer condition instead.

As mentioned earlier, the independent variable consists of two different conditions. The stimulus material consists of a picture of an Instagram account, including a post, of a micro-influencer in one condition and a picture of an Instagram account, including a post, of a macro-influencer in the other. However, only the number of followers was manipulated. The number of followers, namely, determines the fact whether the influencer is a macro-influencer or a micro-influencer. Influencers with less than 100.000 followers are known as micro-influencers, whereas macro-influencers typically have 100.000 followers or more (Fuller, Gross, Zullo & Valentine, 2019). However, macro-influencers are mostly more popular and better known than micro-influencers (Boerman, 2020). Having more followers also ensures a higher reach. This all makes it plausible macro-influencers will get more likes and comments compared to micro-influencers. Therefore, the number of likes and comments were manipulated too. The other characteristics of the picture stayed the same to keep the stimulus material as original as possible. Finally, brand fit was not manipulated, but measured afterwards. See Figure 2 (A: micro-influencer condition, B: macro-influencer condition) for an example of the stimuli.

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Figure 2: A) micro-influencer condition.

Figure 2: B) macro-influencer condition.

Measuring instruments

This experiment measured the three dependent variables competence, goodwill and

trustworthiness. Each dependent variable was measured using a 6-item, 7-point semantic

differential scale (McCroskey & Teven, 1999). See Figure 3. A factor analysis using principal axis factoring with oblimin rotation showed that the 18 items, that measure competence, goodwill

and trustworthiness, are three factors. The analysis namely showed three Eigenvalues higher than

1: (EVcompetence = 5,43, R2 = 0,30), (EVgoodwill = 3,70, R2 = 0,21), (EVtrustworthiness = 1,94, R2 =

0,11), a KMO of 0,76 and all of the items scored higher than 0,45. This means the items form three valid scales. The reliability analyses showed a Cronbach's Alpha higher than 0,7 for all of the three scales, namely competence: (α = 0,71; Mean = 3,91; SD = 0,37), goodwill: (α = 0,73; Mean = 4,16; SD = 0,09) and trustworthiness: (α = 0,75; Mean = 4,22; SD = 0,38). The different items that measure competence, goodwill and trustworthiness, thus, form three valid and reliable scales. Scales are created calculating the mean of the items that measure competence, goodwill

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and trustworthiness.

Competent Goodwill Trustworthiness

1 7 1 7 1 7

Intelligent Unintelligent Cares about me

Doesn't care about me

Honest Dishonest

Untrained Trained Has my interest at heart Doesn't have my interest at heart Untrustworthy Trustworthy

Inexpert Expert Self-centered Not-self centered

Honorable Dishonorable

Informed Uninformed Concerned with me

Unconcerned with me

Moral Immoral

Incompetent Competent Insensitive Sensitive Unethical Ethical

Bright Stupid Not

understanding

Understanding Phoney Genuine

Figure 3: Influencer credibility measurement (McCroskey & Teven, 1999).

Brand fit was measured asking participants whether they think the combination of the

brand and influencer does not belong with/belongs with, does not go together/goes together, does not fit together/fits together on a 7-point semantic differential scale (Till & Busler, 2000). A factor analysis using principal axis factoring with oblimin rotation showed that the three items, that measure brand fit, are one factor. The analysis namely showed only one Eigenvalue higher than 1: (EVbrand fit = 2,68, R2 = 0,89), a KMO of 0,73 and all of the items scored higher than 0,45.

This means the items form a valid scale. The reliability analysis showed a Cronbach's Alpha higher than 0,7 (α = 0,94; Mean = 15,30; SD = 4,60). The different items that measure brand fit, thus, form a valid and reliable scale. The scale is created calculating the mean of the items that measure brand fit.

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micro-influencer condition answered 'less than 100.000' and participants in the macro-influencer condition answered '100.00 followers or more', the manipulation went successfully. Last but not least, participants were asked whether they were familiar with the influencer. Participants in the micro-condition that were familiar with the influencer were deleted and not taken into further analytics.

Results

The sample consists of 100 participants in total and no participants were excluded from the data set. Almost all of the participants were female (86%) between 18 and 50 years old (84%). Only 14% was male and a small percentage of the participants were older than 50 (16%). Participants younger than 18 years old were not allowed to participate in this research in order to be ethically approvable.

A manipulation check is done at the end of the survey to see if participants perceived the micro- and macro-influencer condition as intended by the researcher and, thus, whether

participants in the micro-influencer condition understood they saw a post of a micro-influencer and visa versa. A regression model shows a significant relationship between the experimental conditions and memory of the number of followers, b* = 0,25, t = 2,53, p < 0,001, 95% CI [0,05, 0,44]. This means all of the participants perceived their assigned condition as intended by the researcher.

The first three hypotheses are tested conducting three single regression analyses. After this, three multiple regression analysis are conducted to test H4, H5, and H6. The first single regression analysis is conducted to test the direct relationship between type of influencer (micro versus macro) and competence. This regression model shows type of influencer (micro versus macro) predicts only 1,2% of the variance in competence (R2 = 0,01) and there is no significant relationship between type of influencer (micro versus macro) and competence, b* = 0,11, t = 1,07, p = 0,287, 95% CI [-0,15, 0,50]. Therefore, H1 is rejected.

The second single regression analysis is conducted to test the direct relationship between

type of influencer (micro versus macro) and goodwill. This regression model shows type of influencer (micro versus macro) predicts only 4,3% of the variance in goodwill (R2 = 0,04) and there is no significant relationship between type of influencer (micro versus macro) and goodwill,

b* = 0,21, t = 2,10, p = 0,038, 95% CI [0,03, 0,93]. Therefore, H2 is rejected.

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type of influencer (micro versus macro) and trustworthiness. This regression model shows type of influencer (micro versus macro) predicts 0% of the variance in trustworthiness (R2 = 0,00) and there is no significant relationship between type of influencer (micro versus macro) and

trustworthiness, b* = 0,01, t = 0,12, p = 0,907, 95% CI [-0,31, 0,35]. See table 1 for a clear

overview of the results of the three single regression analyses. Therefore, H3 is rejected.

Variables B* P

Type of influencer and competence

0,11 0,287

Type of influencer and goodwill

0,21 0,038

Type of influencer and trustworthiness

0,01 0,907

Table 1: an overview of the results of the three single regression analyses.

Hereafter, three multiple regression analyses are conducted to test H3, H4 and H5. The multiple regression analyses consist of the independent variables type of influencer (micro versus macro), brand fit and the interaction variable (type of influencer * brand fit) and the dependent variables competence, goodwill and trustworthiness.

The first multiple regression analysis with the independent variables type of influencer (micro versus macro), brand fit and the interaction variable (type of influencer * brand fit) and the dependent variable competence shows type of influencer (micro versus macro), brand fit and the interaction variable (type of influencer * brand fit) predict only 3,3% of the variance in

competence (R2 = 0,03) and there is no significant relationship is found between type of

influencer (micro versus macro) and competence, b* = 0,06, t = 0,17, p = 0,862, 95% CI [-1,08,

1.29], between brand fit and competence, b* = -0,15, t = -1,23, p = 0,222, 95% CI [-0,21, 0,05] and between the interaction variable (type of influencer * brand fit) and the dependent variable

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interaction variable (type of influencer * brand fit) predict only 7,2% of the variance in goodwill (R2 = 0,07) and there is no significant relationship is found between type of influencer (micro versus macro) and goodwill, b* = -0,18, t = -0,50, p = 0,619, 95% CI [-2,05, 1.23], between

brand fit and good will, b* = 0,04, t = 0,36, p = 0,721, 95% CI [-0,15, 0,22] and between the

interaction variable (type of influencer * brand fit) and the dependent variable goodwill b* = 0,41, t = 1,16, p = 0,250, 95% CI [-0,13, 0,49]. Therefore, H5 is rejected.

The third and last multiple regression analysis with the independent variables type of

influencer (micro versus macro), brand fit and the interaction variable (type of influencer * brand fit) and the dependent variable trustworthiness shows type of influencer (micro versus macro), brand fit and the interaction variable (type of influencer * brand fit) predict only 1,7% of the

variance in trustworthiness (R2 = 0,02) and there is no significant relationship is found between

type of influencer (micro versus macro) and trustworthiness, b* = -0,08, t = -0,23, p = 0,820, 95%

CI 1,32, 1.05], between brand fit and trustworthiness, b* = 0,105, t = 0,84, p = 0,404, 95% CI [--0,08, 0,187] and between the interaction variable (type of influencer * brand fit) and the

dependent variable trustworthiness b* = 0,11, t = 0,30, p = 0,763, 95% CI [-0,19, 0,26]. Therefore, H6 is rejected. A clear overview of these results is shown in table 2.

Variables B* P Independent variables - type of influencer - brand fit - interaction variable Dependent variable - competence 0,06 0,862 Independent variables - type of influencer - brand fit - interaction variable Dependent variable - goodwill -0,18 0,619 Independent variables - type of influencer - brand fit - interaction variable Dependent variable - trustworthiness -0,08 0,820

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Table 2: an overview of the results of the three multiple regression analyses.

Conclusion & Discussion

The results of this study clearly do not support the hypotheses based on the literature. According to the literature, micro-influencers will have more competence compared to macro-influencers (Lim et al., 2017; McCroskey and Teven, 1999). Also, micro-macro-influencers will have more goodwill (H2) and trustworthiness (H3) compared to macro-influencers (Lim et al., 2017; McCroskey & Teven, 1999). Besides, this effect should be stronger when brand fit is stronger (Breves et al., 2019). This study, however, shows no differences in consumers' perceptions of credibility between macro-influencers and micro-influencers.

The fact that the stimuli consists of an influencer wearing H&M clothes, and H&M has lost their immense popularity and positive image last years (De Groot, 2019), could have affected the results of the study. A negative brand image, namely, has a negative impact on perceived credibility of the brand, which could influence the perceived credibility of the influencer (Wang & Yang, 2010). This could be a first explanation of the contradictory findings compared to other studies. The results, thus, might have been affected by respondent's attitudes and prior

experiences with the brand (Saunders, Lewis & Thornhill, 2007). This could have been prevented by creating a fictitious brand. However, the picture would be less authentic when doing so.

Limitations

This research has its limitations. The first limitation is the fact that the external validity is possibly lower due to its sample. Participants were found through the social media of the

researcher, which makes it a convenience sample. This means participants were mostly close friends or family and not completely randomly selected. The generalizability of the results could be affected because of this (Boeije, ’t Hart & Hox, 2009). Participants, for instance, were mostly female (86%) and between 18 and 50 years old (84%). Only 14% was male and a small

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might be less generalizable (Boeije, ’t Hart & Hox, 2009). A realistic situation is not comparable to a controlled environment, in which most of the factors that could influence the results are left out. A field experiment with a less controlled environment is advised to do in future research.

Besides, the experiment was a cross-sectional study, which means the data collected only involved a one-shot exposure to the stimuli (Johannessen, Tufte & Christoffersen, 2010). The

research, therefore, couldn’t examine whether attitudes would change because of multiple exposures to the ad. The respondents were directly asked about perceived credibility and brand fit, after exposure to the stimuli and thus had a limited time to process and elaborate over what they just saw. This could affect the results (Hosein, 2012). Future research could do a

longitudinal study to see whether results would be different.

The study focuses only on the clothing industry including a specific brand, and is, therefore, not generalizable to other industries and brands. Future research should consider comparing the effect of micro- and macro-influencer marketing on different industries and brands.

Finally, we didn't asked participants about their familiarity with Instagram. Future research should investigate whether familiarity with Instagram could change participants' attitudes towards a brand and an influencer. Moreover, focussing on different social media platforms would be interesting to see what type of differences exist between the different social media platforms, and how the choice of platform could affect the perceived credibility of the influencer.

Implications

However, this research adds interesting knowledge into the existing field of influencer marketing. It, namely, shows that, contrary to the finding of previous research, micro-influencers might not being perceived as having more competence, goodwill, and trustworthiness compared to macro-influencers. Besides, a stronger brand fit doesn't make this effect powerful. It is

therefore important for future research to look into this further and try to provide a consensus on the topic, as advertisers invest large budgets on influencer endorsements (Schouten, Janssen & Verspaget, 2019). Companies should know if it is effective to invest large amounts of money into macro-influencers.

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effective too according to existing literature, although not confirmed in this research. Companies should stay up to date about this research field and think twice before investing. The more followers, the better? Time will tell!

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Appendix 1: Questionnaire online experiment

Start of Block: Introduction experiment

Q1 Dear participant,

Hereby I invite you to participate in an online experiment that is carried out under the responsibility of College of Communication, a part of the University of Amsterdam. This research, in which I ask your cooperation, is titled: 'Influencer marketing'. In the online survey you will see an image of a post of an influencer. I ask you to pay attention to this image. After seeing this image, a few questions will appear. To participate in this research, you have to be eighteen years or older. The goal of this research is to obtain more knowledge about the influence of influencer marketing. It will take around 5 minutes. I want to ask you to participate in this research at a place without disturbing elements. This ensures you are able to pay full attention to the survey. Because this research is carried out under the responsibility of the University of Amsterdam, you will be guaranteed that:

1) You will stay anonymous.

2). You can stop with this research at any time. You can also cancel your approval to use your data, at least within seven days.

3) By participating in this research, no risks or inconveniences will follow, no deliberate deception takes place and you will not be confronted with explicit offensive material.

4) You are able to have insights into the research report within five months after the research including the results.

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If you want more information about this research and this invitation to participate, please contact the research manager, Demi Buijs, via email (demibuijs95@gmail.com). If you have any

questions or complaints about your participation in this research, please contact the Ethics

Committee of Communication sciences: Commissie Ethiek, Universiteit van Amsterdam, Postbus 15793, 1001 NG Amsterdam; 020‐525 3752; ascor‐secr‐fmg@uva.nl.

Hopefully you are well informed and I thank you in advance for your contribution to this research that will be much appreciated.

Kind regards,

Demi Buijs.

End of Block: Introduction experiment

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Q2 I hereby declare to be informed clearly about the method of this research, as described in the introduction. I agree to participate in this research and keep my rights to cancel this agreement at any time without mentioning why. If my results will be used in scientific publications, or

somewhere else in public, this will be done anonymously. My personal data will not be shown to a third party without my agreement. If I want to have more information, now or in the future, I can contact Demi Buijs, demibuijs95@gmail.com. If I have any questions or complaints about my participation in this research, I can contact the Ethics Committee of Communication sciences: Commissie Ethiek, Universiteit van Amsterdam, Postbus 15793, 1001 NG Amsterdam; 020‐525 3752; ascor‐secr‐fmg@uva.nl.

By signing this document, you understand all of the information above and you approve participating in this research.

o

I understand the information above and I approve participating in this research. (1)

End of Block: Informed Consent

Start of Block: Description of the course of research

Q3 Imagine you are scrolling through your timeline on Instagram and you see this post of an influencer wearing a sweater from H&M. Observe this photo carefully. After, there will be a few questions about this photo.

End of Block: Description of the course of research

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Q4

Q5

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Q6 Think about the photo you just saw. What did you think about the influencer? Answer the following statements on a scale from 1 to 7.

I think the influencer is:

1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) Intelligent

o

o

o

o

o

o

o

Unintelligent Untrained

o

o

o

o

o

o

o

Trained Inexpert

o

o

o

o

o

o

o

Expert Informed

o

o

o

o

o

o

o

Uninformed Incompetent

o

o

o

o

o

o

o

Competent Bright

o

o

o

o

o

o

o

Stupid

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Q7 I think the influencer (is): 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) Cares about me

o

o

o

o

o

o

o

Doesn't care about me Has my interest at heart

o

o

o

o

o

o

o

Doesn't have my interest at heart Self-centered

o

o

o

o

o

o

o

Not self-centered

Concerned with me

o

o

o

o

o

o

o

Unconcerned with me Not understanding

o

o

o

o

o

o

o

Understanding Insensitive

o

o

o

o

o

o

o

Sensitive

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Q8 I think the influencer is: 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) Honest

o

o

o

o

o

o

o

Dishonest Untrustworthy

o

o

o

o

o

o

o

Trustworthy Honorable

o

o

o

o

o

o

o

Dishonorable Moral

o

o

o

o

o

o

o

Immoral Unethical

o

o

o

o

o

o

o

Ethical Phoney

o

o

o

o

o

o

o

Genuine

End of Block: Perceived credibility

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Q9 Think about the photo you just saw. What did you think about the brand? Answer the following questions on a scale from 1 to 7.

I think the combination of the brand and the influencer:

1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) Does not belong with

o

o

o

o

o

o

o

Belongs with Does not go together

o

o

o

o

o

o

o

Goes together Does not fit together

o

o

o

o

o

o

o

Fits together

End of Block: Brand fit

Start of Block: Demographic variables

Q10 What is your gender?

o

Female (1)

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Q11 What is your age?

o

< 18 (1)

o

18 - 50 (2)

o

50 + (3)

End of Block: Demographic variables

Start of Block: Manipulation check

Q12 How many followers did the influencer have on the picture?

o

Less than 100.000 (1)

o

100.000 followers or more (2)

End of Block: Manipulation check

Start of Block: Other questions

Q13 Are you familiar with the influencer?

o

Yes (1)

o

No (2)

End of Block: Other questions

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Q14 I would like to thank you for your participation. Please click on 'submit' to finish this survey.

With kind regards,

Demi Buijs

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