Does message appeal matter on Instagram?

Does message appeal matter on Instagram?

A research on the relationship between message appeal

and attitude toward brand.

By Liliya Nos-Mentink

Does message appeal matter on Instagram?

A research on the relationship between message appeal and attitude toward

brand.

By Liliya Nos-Mentink (s4135733)

University of Groningen, Faculty of Economics and Business,

M.Sc. Marketing

Master Thesis

11 January 2021

l.nos-mentink@student.rug.nl

+31 6 13 09 07 02

Abstract

Preface

Table of contents

2.2 Literature Review and Hypotheses 11

2.2.1 Rational versus emotional Message Appeals 11

2.2.2 Attitude toward Message 12

2.2.3 Attitude toward Influencer 12

3. Methodology 14 3.1.Research design 14 3.2. Data collection 16 3.3. Construct measurement 16 3.3.1 Measurement scales 16 3.3.2 Factor Analysis 18 3.3.3 Reliability analysis 19 3.3.4 Manipulation check 20 3.5. Method of Analysis 20 4. Results 23 4.1 Hypothesis testing 23

5. Conclusion 29

5.1. Discussion 29

5.2. Managerial Implications 31

5.3. Limitation of study 31

1.Introduction

As reported by Business Insider, the influencer marketing industry is constantly growing and was expected to be worth up to 15 billion $ by 2020. While across channels the form of this type of advertising may vary, however, usually it is done in implicit mode (“I use this product”) (McCracken, 1989). This can take the form of a product review on social media that is aimed to sway brand preferences, gain brand awareness, affect buying decisions or get loyalty within a certain target group (ANA, 2018). As of 2020, over 3.6 billion people use social media, and this number is likely to increase to a whopping 4.41 billion by 2025 (Clement, 2020). Consequently, social media platforms have grown coverage that is so large that it has the power to challenge TV advertising’s reach of 1.6 billion households (IMARC, 2020). Additionally, one of the reasons why companies are in favor of influencer marketing is the high dependency of consumers on influencers’ recommendations. According to the Digital Marketing Institute, not only do 49% of consumers seek advice from influencers, but around 40% had purchased after being exposed to the message on one of the social media platforms (Digital Marketing Institute, 2019).

comfortable and more relatable environment upon which the users can engage with the influencers more easily than in other platforms (Estay, 2020).

The success that influencers have had in appealing to the constructs can make the message being passed more effective, as has been explained in persuasion theories. Two appeal perspectives are used to explain the type of messages given by influencers: informational and emotional. These two types of messages are described by Venkatraman et al., (1990) as factual and evaluative orientation respectively, and are the formats through which influencers communicate and endorse company products to their audiences. In informational message appeal, influencers describe the products that they recommend in a logical and verifiable yet unbiased way (Grigaliunaite & Pileliene, 2016), thus showing that their perspective on the products in question are not influenced by any subjective opinion. Therefore, the customers’ trust is enhanced by ensuring that the message is objective, and this appeals to people who are genuinely interested in scrutinizing and combining pieces of information concerning the products (Venkatraman et al., 1990). In contrast, a message with emotional appeal focuses on subjectivity (Kim et al., 2020) and the personal feeling of influencer. In this case, the process of thinking about the product does not matter but instead, what is of importance is the outcome of said process.

Considering how the messages spread through these appeals, it is useful to understand what constructs it can possibly affect. For instance, brand attitude as a positive or negative predisposition toward a brand is a popular measurement in marketing due to the relatively stable and enduring nature of this indicator and well-developed theoretical models and scales related to it (Madhavaram & Appan, 2010). While considering brand attitude as an indicator that influences consumers' choices, it is vital to understand the factors that distinguish brand attitude. In this case, looking into the role of influencers' messages in convincing their audiences of the benefits of their endorsed products.

audience is more likely to accept the message arguments when they are coming from a trustworthy versus a non-trustworthy message source (Wilson & Daniel, 1993; Yalch & Elmore-Yalch, 1984). If the message appeal triggers a positive attitude and effect towards the influencer and, ultimately the brand, it could be argued that the attitude towards the brand is therefore determined by the influencer's attitude, and that their attitude is determined by the audience’s attitude towards the message. The purpose of this study is to determine if influencers’ message appeal on Instagram is a powerful construct that can determine brand attitude through attitude toward message and attitude toward influencer. This thesis adds to the existing knowledge on the online marketing communication by empirically testing message appeal on brand attitude.

2. Theoretical Framework

2.1 Conceptual Model

To understand the impact of message appeal on customer’s attitudes toward the brand, a conceptual model is presented herein (Figure 2.1).

Figure 2.1

2.2 Literature Review and Hypotheses

2.2.1 Rational versus emotional Message Appeals

Persuasion Theories study the qualities of the message that recipients are exposed to as one of the main factors that influence Attitude toward Message. Any passed-to-consumer message can be one of two types based on appeal: emotional-based or rational (Fennis & Stroebe, 2016). The message that is rational based informs the potential consumer about benefits and makes persuasive arguments; in contrast, emotional one is based more on information about how the influencer feels (Venkatraman et al., 1990). Considering the number of products and information that consumers are presented with on a daily basis, there is evidence that nowadays consumers are often more dependent on simple heuristics that help to eliminate the number or alternatives (De Veirman M. et al., 2017; Iyengar & Lepper, 2000; Payne, 1982; Payne, Bettman, & Johnson, 1988; Timmermans, 1993; Wright, 1975). This type of processing information is mainly used while dealing with emotional based appeal information.

On the other hand, persuasion theories consider messages with information appeal as more persuasive than emotional ones, forming more favorable brand attitudes on the basis of factual information (Holbrook, 1978). Furthermore, information appeal assumes the presentation of factual product information and benefits for consumers that play an important role in consumer attitudes (Kim & Lennon, 2000; Mitchell & Boustani, 1994). Considering this, it is expected that informational Message Appeal leads to a more favourable Attitude toward Message:

H1: Rational Message Appeal has a positive impact on Attitude toward Message.

H6: Rational Message Appeal has a positive indirect effect on Attitude toward Brand through favourable Attitude toward Message and Attitude toward Influencer.

Moreover, the message appeal affects the attitude toward source and consumer attitude toward brand indirectly (Kim and Lee, 2012).

2.2.2 Attitude toward Message

To consider the Instagram setting, a post about branded products is seen as advertisement and Attitude toward Message as a proneness to positive or negative response on an influencer's message. The researchers studied the Attitude toward Message as one of the causal determinants of Brand Attitude (Thomas & Johnson, 2019; Chen, Fay, & Wang, 2011; Madhavaram & Appan, 2010; Brown & Stayman, 1992; Derbaix, 1995; Muehling, 1987; Phelps & Hoy, 1996). Moreover, this is proved by the Affect Transfer Hypothesis that links Attitude toward the advertising Message and Brand Attitude (De Veirman et al., 2018; Gardner M, 1985). Other studies posit that Attitude toward Message has a mediating influence on Brand Attitude (Mitchell & Olson, 1981; Shimp, 1981).

Attitude toward Message sways not only the Attitude toward the Brand being offered (Moore et al., 1994; Lutz, 1985; MacKenzie & Lutz, 1985; Mitchell & Olson, 1981), but also the individual's attitude toward the message source, which is an Attitude toward Influencer (Moore et al., 1994; Smith & Hunt, 1978). In other words, Attitude toward Influencer is the construct that can diminish the persuasive impact of Message appeal and Attitude toward Message on the Brand Attitude (Mowen & Brown, 1981).

H2: Attitude toward Message has a direct effect on the Attitude toward Influencer.

H5: Attitude toward Influencer mediates relationships between Attitude toward Message and Attitude toward Brand.

2.2.3 Attitude toward Influencer

al., 2000; Bhatt et al., 2013; Atkin & Block, 1983; Fishbein & Ajzen, 1975; Goldberg & Hartwick 1990; Mitchell & Olson, 1981):

3. Methodology

In this chapter, the research design and data collection are discussed; the construct measurements together with the results of factor and reliability analyses are explained; the results of manipulation check are examined and the method is presented.

3.1. Research design

The research was based on a between-subjects experimental design with two conditions: one where the influencer presents rational benefits (Figure 3.1) about the product and another where she expressed her emotions about product consumption (Figure 3.2).

Figure 3.2 Emotional condition

To make the advertising message more realistic, a famous US lifestyle blogger, one of the top influencers recognized by Forbes (Forbes, 2017), is chosen and a real brand name that she had advertised on her account. The style of language is very close to her own as all the phrases for the stimuli are a mix of her own two posts. The size of both posts and the picture in both conditions is the same. The brand of drink is also real and was advertised in her account.

3.2. Data collection

The research was conducted in the form of an online experiment on the platform Qualtrics. All the questions were structured types (Malhotra, 2010) with a set of response alternatives that were predominantly scale-type, but which also asked dichotomous and multiple choice questions. The pre-test (twenty-two respondents) was conducted to perform a manipulation check and identify potential problems and misunderstandings.

Data from the survey is used to test the hypotheses previously defined. The experimental stimuli were 2 versions of the advertising messages, one with an informational appeal, another with an emotional one. Convenience and judgmental types of sampling were used to select the respondents by distributing links in Facebook groups and through a personal network. Additionally, to get more respondents, a snowball sampling technique was used by asking respondents to distribute the link through their network (Malhotra, 2010). After getting the information about the influencer, participants were randomly exposed to one of the promotion posts and after asked to answer the questions that were meant to test the variables chosen.

The sample size contained 85 full answers, the 24 incomplete answers were deleted and not processed. The age of the respondents varied: the minimum age was 18 while the maximum was 45. This gave a mean age of 28 years with (58 people) 61% of the total being aged between 22 and 33. 81% of the participants had an Instagram account .

3.3. Construct measurement

3.3.1 Measurement scales

The constructs are measured by using scales from the existing theories.

For the Attitude toward Influencer a 7-point semantic differential scale proposed by Moore (Moore et al., 1994) was used: unbelievable/believable, untrustful/trustful, biased/unbiased, insincere/sincere.

To evaluate the dependent variable – Attitude toward Brand the 7-item scales measuring five criteria proposed by Spears& Singh, (2004) was used: unappealing/appealing, bad/good, unpleasant/pleasant, unfavorable/favorable, unlikable/ likable.

Table 3.1. summarizes the findings of factor and reliability analyses per construct, performed in sections 3.3.2 and 3.3.3

Constructs Items Factor

loadings Cronbach's Alpha

Attitude toward the message unpleasant/pleasant 0,864 0,885 unlikable/likable 0,853 boring/interesting 0,852 tasteless/tastefull 0,799 artless/artfull 0,751 bad/good 0,699

Attitude toward the brand unappealing/appealing 0,936 0,958 bad/good 0,935 unpleasant/pleasant 0,932 unfavorable/favorable 0,919 unlikable/likable 0,905

* item was deleted during factor analysis (see section 3.3.2)

3.3.2 Factor Analysis

In the experiment there were three constructs that included different numbers of questions, measured on a 1-7-scale: Attitude Toward Message, attitude toward influencer and attitude toward brand. To analyze the relationships between these three variables, the items had to be formed into factors (Kerby, 1979) in order to have a minimal amount of components providing maximum information (Stewart, 1981). To test how well measured items represent the constructs, Factor Analysis was done for 3 types of items: those that are related to the Attitude toward Message, Attitude toward Influencer and Attitude toward Brand.

with the results obtained on factor loadings, Question 2_3 (biased/unbiased) was excluded from further analyses. The CPA analysis showed that the minimum number of factors that count for the maximum variance are four. There were four factors with eigenvalues larger than 1.0 and the Cumulative Eigen Value of them was equal 79,805%. This is considered to be high, since the factors should account for at least 60% of variance (Malhotra, 2010).

Taking into consideration the results of analysis performed, the three factors as means of items can be calculated.

3.3.3 Reliability analysis

To assess the reliability of a summated scale, a Cronbach’s Alpha is calculated and considered (Malhotra, 2010). Considering that internal consistency can be assumed for the factors with Cronbach's Alpha ≥ 0,6, all three factors are reliable: Attitude toward Message 0,885, Attitude toward Influencer 0,890 and Attitude toward the brand 0,95. Comparing the Cronbach’s Alpha of every item when deleted to the Cronbach’s Alpha of the factor showed that there were no items once deleted would improve reliability or internal consistency of the factor, since every Chronbach’s Alpha if deleted was less than Chronbach’s Alpha of the factor. After that, the factors were calculated as means of items.

To test if the variables are correlated, the Person’s coefficients were calculated at two tailed 0,01 level significance (Table 3.5). The test revealed significant correlations between all the variables. Table 3.5

Variable Mean SD Attitude toward _Message Attitude toward _Influencer Attitude toward _Brand

Attitude toward Message

Attitude toward Influencer 3,447 1,430 ,657* 1 Attitude toward Brand 3,664 1,306 ,758* ,669* 1 * p-value < ,01 (2-tailed)

3.3.4 Manipulation check

To determine if respondents are interpreting message appeal correctly, a pretesting survey was organized (Reynolds, Diamantopoulos, and Schlegelmilch, 1993). The main goal was to check that the manipulations are perceived as intended. 22 respondents were exposed to one of the two conditions: 10 to rational and 12 to emotional. The manipulation check question was: “to what extent do you think this post is emotional/informative (7- absolutely emotional, 1- is totally informative”). The results were analyzed with a two-tailed t-test that showed a significant difference (p= 0,001) between rational appeal (M=2,30; S.D.=0,823) and emotional appeal (M=4,58; S.D.=1,676) .

The manipulation for the main data replicated the result of the Pre-test and showed significance (p=0,000) with the results on rational appeal (M=2,09; S.D.=0,793) and the emotional appeal M=4,18; S.D.=1,647). Even though the results of the Manipulation Check were significant between groups both if equal variance is assumed and when it is not, considering mediation it appears to be that emotional appeal wasn’t evaluated very high by respondents on the emotional.

3.5. Method of Analysis

mediation effect of Attitude toward Message and Attitude toward Influencer, dropping into the relationship between independent and dependent variables, Hayes macros #6 was used (H6).

Regression models MA - Message Appeal

(coded as 1 for Rational and 2 for Emotional)

AM – Attitude toward Message AI – Attitude toward Influencer AB – Attitude toward Brand ε – Error H1: AM = β0 +β1MA +ε H2: AI = β0 +β1AM +ε H3: AB = β0 +β1AI +ε H4: 1. AI= β0+β1MA +ε 2. AM = β0 +β1MA +ε 3. AI= β0 +β1AM +ε 4. AI= β0 +β1MA+ β2AM+ε

H6: 1. AB= β0+β1MA +ε

2. AM= β0+β1MA +ε

3. AI= β0+β1MA +ε

4. Results

4.1 Hypothesis testing

Based on the central limit theorem for the sample size of more than 20 observations (Tian & Wilcox, 2011), it can be assumed that the sample mean has a normal distribution. Therefore, only parametric tests are used to test hypotheses.

4.1.1 The direct effect (H1, H2 & H3)

The conceptual model hypothesizes 3 direct effects: between Message Appeal on Attitude toward the Message (H1), of an Attitude toward Message on Attitude toward Influencer (H2), of an Attitude toward Influencer on Attitude toward Brand (H3). For each of these conditions a linear regression was performed. The summary of the results of the H1, H2 and H3 are presented in Table 4.1.

Table 4.1.

Hypotheses H1 H2 H3

F-value 2,932 63,161 67,138 * p-value < ,05 ** p-value < ,1

H1 stated that Rational Message Appeal has a positive impact on Attitude toward Message. The linear regression with the independent variable Message Appeal (rational= 1; emotional= 2) on the dependent variable Attitude toward Message, considering 0,05 level of significance, was non-significant, p=0,091, R2 _{= 0,034. Message Appeal accounted for a non-significant 3.4% of the} variance in Attitude toward Message, β= -0,425, t= -1,712, p=0,091, thus the null hypothesis was not rejected. However, considering the 0,1 level of significance and 90% confidence interval, the model showed significance (90%CI [-0,837; -0,012]), the marginal significance can be assumed. The negative unstandardized beta shows that the rational message appeal is more favorable.

As of H2 Attitude toward Message has a direct effect on the Attitude toward Influencer. The predictive value of the model is 43 % (R2 _{= 0,432). Based on the data β= 0,813, t= 7,947, p=0,000} the model is significant. Additionally, the results show that that the higher the Attitude toward Message the better Attitude toward Influencer. Hypothesis 2 is confirmed.

The analysis showed the support of H3, stating that the positive Attitude toward Influencer has a positive effect on Attitude toward Brand. The linear regression was significant, p=0,000, R2 = 0,447 and Attitude toward Influencer can be accounted as a predictor of Brand Attitude (β= 0,612, t= 8,194, p=0,000). Therefore, Hypothesis 3 is confirmed.

4.1.2 The indirect effect (H4, H5 & H6)

Since Hypotheses H4, H5, H6 assume an indirect effect between variables, a bootstrapping mediation analysis (Hayes’ Process) was performed; the summary of results obtained in SPSS is presented per hypothesis. To visualize the outcome, Baron and Kenny path diagrams, depicting causal chains (Baron & Kenny, 1986), are presented.

four conditions proposed by Baron & Kenny (1986). Only the second criterion is met, showing significance (Figure 4.1).

Figure 4.1

of β and level significance p on the four conditions. However, the mediation is partial, since both path c and c’ are significant. This means that the Attitude toward Message partially affects Attitude toward Brand through Attitude toward Influencer.

Figure 4.2

The results are confirmed with bootstrap analysis: total effect (SE= 0,0809; t= 10,6031; p= 0,0000, 95% CI [0,6973; 1,0192]; direct effect (SE= 0,1014;t= 6,2680; p= 0,0000; 95% CI [0,4338; 0,8371]) and indirect effect (95%CI [0,0596; 0,4684]) are all significant. Moreover, the predictive value of the model is rather high, with R2 _{= 0,6262, F= 0,6528. Thus, hypothesis H5 is confirmed.}

Figure 4.3

Table 4.2

Hayes Model 6 B SE t p

D DV Attitude toward Message

R2 = 0,0341 F= 2,9322 p= 0,0906

Message Appeal -0,4245 0,2479 -1,7124 0,096

DV Attitude toward Influencer R2 = 0,4322 F= 31,2121 p= 0,000

DV Attitude toward Brand R2 = 0,6264 F = 45,2758 p = 0,000 Message Appeal 0,0358 0,1797 0,1992 0,8426 Attitude toward Message 0,6381 0,1029 6,2029 0 Attitude toward Influencer 0,2744 0,0825 3,3264 0,0013

DV Attitude toward Brand (Indirect effect) R2 = 0,0168 F = 1,4195 p = 0,2369

5. Conclusion

In this chapter, the results of the analysis are discussed, the managerial implications are presented, and limitations of analysis are defined.

5.1. Discussion

The aim of this study was to prove that Message Appeal indirectly affects Attitude toward Brand. Consequently, it was expected that the message with a rational-based appeal in contrast to an emotional one would get a more favorable attitude toward the brand. This indirect effect was expected to be mediated by Attitude toward Message and Attitude toward Influencer, as the source of a message. The results of the hypotheses are summarized in Table 5.1.

Hypotheses Results

H1: Rational Message Appeal has a positive impact on Attitude toward

Message. Rejected

H2: Attitude toward Message has a direct effect on the Attitude toward

Influencer. Confirmed

H3: Positive Attitude toward Influencer has a positive effect on Attitude

toward Brand. Confirmed

H4: Rational Message Appeal has a positive indirect effect on Attitude

toward Influencer. Rejected

H5: Attitude toward Influencer mediates relationships between Attitude

toward Message and Attitude toward Brand. Confirmed

H6: Rational Message Appeal has a positive indirect effect on Attitude toward

Even though there was a significant difference in perception of the two conditions, the evidence shows that a message with an emotional based appeal wasn’t seen as persuasive by participants based on emotions. As one of the fundamentals of experimental design is to intentionally manipulate the independent variable and examine the changes in a dependent variable (Miller, 1984), improving the quality of stimuli might lead to finding significant effects on attitudinal variables. In the case of this experiment, there appears to be scope for improvement by enhancing the emotional appeal. One of the ways to do this is by attempting to trigger feelings of joy, love, humor, pride etc. (Teichert et al., 2017). Practically, it might be that making the same advertising message more humorous would increase the difference between the groups, leading to higher scores on emotions and resulting in a significant effect on attitude constructs.

Additionally, during the experiment, twenty-four respondents, accounting for 22% of the total number of participants, failed to complete the survey, thereby rendering this data invalid. One of the ways to improve the willingness of respondents to finish the poll is to ask the questions using the third-person technique, formulating them as if they referred to other people (Malhotra, 2010). This might help in obtaining a higher degree of accuracy in the results and a greater number of answers.

Even though there is a large body of research that has shown the effect of Message Appeal on Attitude toward Brand (Golden & Johnson, 1983; Coulson, 1989; Holbrook & O'Shaughnessy, 1984), no significant effect was found in this study. In addition to the flaws in the design discussed above, it’s possible that the low predictive value of the model and its insignificant effect is explained by the underweight sample size and increasing the sample size might therefore improve the accuracy of the model.

Considering the factors predicting Attitude toward Influence, it is noteworthy that no direct or indirect effects of message appeal on the perception of trustworthiness/ credibility of influencers were discovered, even though such relationships exist in the literature. This might be because of the imperfections in the designed stimuli that decreased the power of Message Appeal as a predictor. However, a mediating attitudinal effect of Influencer on formation of Brand attitude while evaluating the message was ascertained. Additionally, in accordance with the match-up hypothesis formulated by Till&Busler (1998) the attitude toward the endorser determines the extent of an advertisement perception.

5.2. Managerial Implications

This study provides valuable insights and guidance for marketing managers. First of all, focusing on getting a better attitude toward the advertising message can result in an improvement of the brand attitude. Since there is evidence that Attitude toward Message has a significant effect on Attitude toward Brand, constructing a message that is believable, likeable, interesting and tasteful in campaigns is more likely to get a desirable outcome and sway consumer’s opinion about a brand. The effect of Attitude toward Influencer on the Attitude toward Brand proves the importance of selecting the source of message methodically. Brand managers should be particularly careful while choosing influencers to represent the brands. For instance, one of the most important criteria for selecting an Influencer is how trustworthy they are seen as by the followers and target audience of the brand. If the goal of the campaign is to enhance brand attitude among a certain group of people, they should ensure that the blogger is trustworthy, sincere and appealing and develop in collaboration consistent and persuasive communication.

5.3. Limitation of study

Model suggests to include the need of cognition and involvement with the product in the model (Petty & Cacioppo, 1986). Johnson and Scileppi (1969) found that greater attitude change resulted from the message source in low ego-involvement conditions than in high ego-involvement conditions. The source was more influential in the low involvement condition than in the high involvement condition (Wilson & Sherell, 1993). Future research might include one of these additional variables in the model to improve it.

The effect of Attitude toward Influencer was studied based on trustworthiness/credibility criteria. Several researchers broaden the measurement of this construct by adding measurements of perceived expertise (Ohanian, 1990; Dholakia & Sternthal, 1977; Pornpitakpan, 2004) and attractiveness (Evans & Clark, 2012; Erdem & Swait, 2004; Joseph, 1982) of the Influencer as indicative sources of credibility. The impact of attractiveness on attitude toward source is explained by scholars as a desire to identify oneself with attractive people (Carison & Donavan, 2008), meaning that people perceive information coming from attractive sources as more valid (Clark & Evans, 2014).

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