ad believability in comparative advertising

Ad believability in comparative advertising

“Believability in comparative advertising and the moderating influence of

perceived product risk and brand preference for the comparative brand”

Floris Hendrik Wubs

June 2012


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Master Thesis: Marketing Management


“Believability in comparative advertising and the moderating influence of

perceived product risk and brand preference for the comparative brand”

June 2012

Floris Hendrik Wubs

Kerklaan 2

9717 HE Groningen

[email protected]

Phone: 0622637554

Student: 1551086

University of Groningen, Marketing

MscBA Marketing management

Supervisor: Dr. K.J. Alsem


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Management summary

This study investigates advertising believability within a comparative advertising format. To consumers,

ad believability is generally perceived to be lower in comparative ads than in noncomparative ads.

Research suggests that ad believability in comparative advertising is essential in persuading customers,

and improving brand attitudes and purchase intentions. This study investigates how ad believability can

be improved, and what the effects are. Also, perceived product risk, and a brand preference for the

comparison brand are included as moderators in the predictive model for brand attitudes and purchase

intentions.

After selecting two product categories (toothpaste as low risk product and tablets as high risk product)

in a pretest, that are suitable for this study, an online survey accompanied with an ad is used to gain

respondents data. As is demonstrated in literature, ad believability is of major importance in

comparative advertising. Especially the influence on brand attitudes is considerable. The influence of ad

believability on the dependent variables is also contingent to perceived product risk. Under conditions

of high perceived product risk, the influence of ad believability is significantly stronger, and under

conditions of low perceived product risk, the influence of ad believability is weaker. Subsequently, a

significant moderating influence of a brand preference for the comparison brand is not established.

Future research can investigate the possibility for this moderator and other possible moderators.

The main conclusion of this study is that within comparative advertising, ad believability is of decisive

influence for advertising effectiveness. Firms utilizing this advertising format should consider this, and

take the influence of perceived product risk into account. As a result, advertising effectiveness can be

significantly improved.


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Preface

Writing the thesis to finish the study is the ultimate challenge for a student. For me, it has been a

grateful period, in which I felt freedom to investigate a topic of choice on the one hand, and a pressure

to deliver an attractive thesis on the other hand.

This gives me the opportunity to thank my supervisor, dr. K.J. Alsem, who has supported me in writing

my thesis, triggered my creativity in designing the study, and critically assessed my documents. The

feedback I received was always presented in a helpful, open-minded manner, which I have experienced

as a pleasant support style.

Also, I want to thank family and friends for support, enthusiasm and interest for the progress of my

thesis. Special thanks for the friends and co-students, with whom I spend long hours, days, weeks at the

library. By writing our theses simultaneously, we kept each other motivated and inspired, and we could

always count on each others help when the writing process slowed down.

Finally, I want to thank all the respondents who cooperated by filling out the online survey. The thesis

could not have been completed by the amount of time you spend.


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Table of contents

1. Introduction…………………………………………………………………………………………………. 7

2. Theoretical Framework..……………………………………………………………………………… 10

2.1 Explanation of comparative advertising 10

2.2 Processing mode in comparative advertisements 12

2.3 Believability in comparative advertising 13

2.4 Fostering advertising believability 17

2.5 The dependent variables influenced by believability 20

2.6 Moderating effect of perceived product risk 21

2.7 Moderating effect of brand preference for comparison brand 23

2.8 Literature summary and conceptual model 24

3. Methodology………………………………………………………………………………………………. 27

3.1 Research question and hypotheses 27

3.2 Pretest determining product categories 28

3.3 Research design of main study 30

3.4 Measurement 34

3.5 Manipulation checks 39

3.6 Sample and construct descriptive statistics 40

4. Results………………………………………………………………………………………………………… 42

4.1 Main descriptive statistics 42

4.2 Results of main hypothesis 44

4.3 Results concerning moderating effects 45

4.4 The influence of brand preference on ad believability 48

4.5 Manipulation check 49

5. Conclusions and recommendations……………………………………………………………… 50

5.1 Discussion of results 50

5.2 Conclusions 52

5.3 Managerial implications 54

5.4 Limitations and future research 56

6. Bibliography……………………………………………………………………………………………….. 58

7. Apendices…………………………………………………………………………………………………… 62


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Overview of tables and figures

List of tables

Table 1: Relative effects of comparative advertising versus noncomparative advertising 14

Table 2: Contingency model of message sidedness and competitiveness of claims 16

Table 3: Pretest results 30

Table 4: Overview of manipulation across the four groups 31

Table 5: Elements manipulating believability 32

Table 6: Origins of the used questions in the questionnaire 35

Table 7: Basic linear regression of brand attitude 44

Table 8: Basic linear regression model of purchase intentions 45

Table 9: Linear regression model including moderating effects 46

Table 10: Linear regression model of purchase intentions including moderators 47

Table 11: Revised linear regression model of purchase intentions 48

Table 12: Summary of hypotheses of this study 54

List of figures

Figure 1: Conceptual model 26

Figure 2: Depiction of the four ads used in the surveys 33

Figure 3: Distribution of gender among the four groups 40

Figure 4: Distribution of age 40

Figure 5: Distribution of age among the four groups 40

Figure 6: means of perceived risk of tablet and toothpaste groups 42

Figure 7: means of ad believability, brand attitudes and purchase intentions 43

Figure 8: Means of constructs of four groups 43

Figure 9: Ad believability means of respondents preferring comparison brand or not comparison brand 49


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1. Introduction

Companies often use advertisements to create brand awareness and to inform people about the quality

of the product advertised (Dröge, 1989). Traditionally, only the advertised brand is shown and

supported with one-sided messages. However, the last decades, advertising formats have become very

diverse for different products and brands. Comparative advertising is a form of advertisement that has

become increasingly attractive for companies. Wilkie and Farris (1975) defined comparative

advertisement as: “comparative advertising compares two or more brands of the same product or

service class and makes a comparison in terms of one or more product service attributes”. Distinctive to

this type of advertising is that it includes the brand name or product of a competitor in the

advertisement. The increase of popularity for this form of advertising is exemplified in the United States,

where the share of comparative advertisements was negligible before 1970, but twenty years later, the

share of comparative advertisements had grown to 40% (Muehling, Stoltman, and Grossbart, 1990). A

recent content analysis of television ads (Pechman and Stewart, 1990) found that approximately 80% of

the advertisements contained comparative claims. However, 75% of the comparative advertisements

contained indirect advertising claims (not mentioning the brand name of a competitor), and 25% of the

comparative advertisements contained direct comparative claims (mentioning the brand name of a

competitor in the ad). So it is evident that comparative advertising has become increasingly popular, but

a distinction must be made between direct and indirect comparative advertising, explicitly mentioning

competitors in the comparative claims, or not. This study focuses on direct comparative advertising,

which is explained in the following chapter.

More countries are making the legislation around comparative advertising more flexible, offering new

chances for companies. For example, in Germany comparative advertisement has recently been

permitted, creating opportunities for certain companies in a large market (Schwaiger, Rennhak, Taylor,

and Cannon, 2007). The European Union is reconciling laws of the individual states, including legislation

around media and advertising. Comparative advertising is permitted in the Netherlands, under some

conditions, though the use is more common in the United States. Further relaxation of the legal system

of the European Union makes research of comparative advertisement even more relevant.

Proponents of CA (comparative advertising) state that, in comparison with NA (noncomparative

advertising), this type of advertising has a greater impact on increasing attention and awareness,

improving attitudes toward the brand and increasing purchase intention (Grewal and Kavanoor, 1997),


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even though other studies show negative results (Dröge and Darmon, 1987; Swinyard, 1981). In these

studies however, differences in success are mainly imputed to cultural differences. Although CA is often

successfully used to position a product in a market, literature is inconclusive about the actual

effectiveness of CA. For instance, Rogers and Williams (1989) investigated 104 studies on CA, and found

that 17 studies concluded CA to be more effective than noncomparative advertising, 30 studies

concluded CA not to be more effective than noncomparative advertising, and 57 studies had neutral

results. Because literature is very inconclusive about its effectiveness, it is required to pinpoint

situations when CA is advantageous. The various results found in studies on CA indicate varying

effectiveness due to different variables. Variables that have been found to influence the effectiveness of

CA are: differences in cultures (Schwaiger, Rennhak, Taylor, and Cannon, 2007; Grewal and Kavanoor,

1997; Donthu, 1998), different product types (Putrevu and Lord, 1994), product category involvement

(Schwaiger et al, 2007), preexisting brand knowledge (Dröge, 1989), product experience (Schwaiger et

al, 2007), degree of comparing directly (Miniard, Barone, Rose, and Manning, 2006), comparative

intensity (Donthu, 1992), psychographic variables (Dutta-Bergman, 2006), and other variables.

More interestingly, Grewal and Kavanoor (1997) developed a hierarchical model that indicates what

cognitive, affective and conative variables (on the basis of Lavidge and Steiner’s advertising objectives,

1961) generally are more positively influenced, in comparison with noncomparative advertising. This

hierarchical model provides an excellent overview of strengths and weaknesses of CA versus NA.

Furthermore, comparative ads are generally expected to be processed centrally (Cacioppo and

Schumann, 1983), which changes attitudes that are relatively more enduring and predictive of

(purchasing) behavior. Causing such effective results due to advertising is the goal of many marketing

departments. Grewal and Kavanoor concluded that CA offers great opportunities to advertisers that

carefully manage the variables that influence the results, to increase brand attitudes and purchasing

intentions (and therefore, most likely, purchasing behavior too). Even though the model was presented

as a hierarchical model, the authors stated that relationships between the numerous variables might

very well be more complicated, and that (dependent) variables are likely to interact. A notable cognitive

variable that can influence the overall effects of the advertisement, is the (perceived) believability of the

ad. Grewal and Kavanoor concluded that on average, believability of CA is lower than the believability of

NA (noncomparative advertising). Because believability of an ad is essential for persuading consumers

(Swinyard, 1981), the variable has to be investigated closely. If advertising believability positively affects


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attitude toward the brand and purchase intentions, CA can become a better tool for advertisers. This is

the issue that is investigated in this study.

CA has been intensively studied (especially in the United States) since the seventies of the previous

century, and this has led to many insights. Also, believability of advertisements is a well-investigated

topic. Numerous studies identified that believability has a different effect in CA than in NA. This study,

however, emphasizes exclusively on the influence of believability in comparative advertising on

attitudinal and conative effects (based on Lavidge and Steiner’ advertising objectives of 1961), and

investigates the moderating impact of product risk and brand preference for the comparison brand.

Separately, product risk and ad believability are two well-researched topics, but the moderating

influence of product risk on the effectiveness of ad believability in the setting of comparative

advertising, is unique. Moreover, brand preference for the comparison brand is a topic that has not

been investigated in relation with effectiveness of believability in comparative advertising. Hence, the

moderating influence of this variable is also unique in literature, at this time. In conclusion, identifying

the mutual relations of the variables in this study can shed an interesting light upon the current

knowledge of the topics ‘comparative advertising’ and ‘ad believability’. Furthermore, this study

specifically investigates direct comparison advertising, where in most studies no distinction is made

between direct and indirect comparative advertising. The results can aid companies in designing

comparative advertisements more optimally, according to their advertising objectives. The research

question for this study is:

What is the influence of the believability of comparative advertising on consumers’ attitudes toward the

promoted brand and purchase intentions, and what is the influence of perceived product risk and a brand

preference for the comparative brand on this relation?

The structure of this study is as follows: the next chapter gives an extensive overview of current

research on comparative advertising, believability, product risk, brand preference and their relations.

The footing on answering the research question is based on previous research and theories. Chapter

three summarizes the hypotheses, and describes the research methods in answering the research

question. Chapter four describes the results that are obtained from the surveys. Finally, chapter five

discusses the results, and draws conclusions with respect to the research question. Limitations to this

study and directions for future research are included.


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2. Theoretical Framework

In most studies on comparative advertising, effects are investigated in comparison with noncomparative

advertisement. The emphasis is on differences, advantages and disadvantages of CA (comparative

advertising), with respect to NA (noncomparative advertising). This study focuses on effects of

believability in CA, and its influence on attitudes and behavior. So, relations of believability on classical

advertising objectives (attitude toward the brand, purchase intentions) are studied, within comparative

advertising. Firstly, literature on CA is discussed. Subsequently, literature on believability and its relation

with other variables are discussed.

2.1 Explanation of comparative advertising

2.1.1 Definition of comparative advertising

Due to the increased popularity of comparative advertisement, a large number of studies investigated

the effects of CA. Because CA is mainly investigated in comparison to traditional, noncomparative

advertising (NA), it is often defined in a way that distinguishes it from traditional advertising. McDougall

defined CA in 1978 as “any advertisement that compares, implicitly or explicitly, two or more products

and states or implies that information has been obtained, or a test has been conducted on a

comparative basis, or that states or implies a particular market standing in relation to other similar

products, whether the other products are named or not”. In this early definition on CA, no distinction is

made between explicitly naming the competitor in the ad (direct comparative), or implicitly comparing

to competitors (indirect comparative). However these days, companies always claim to be better at

certain aspects then competition in advertisements. So to some extend, it is inherent in advertising that

the advertiser states that their brand is better (than competition). The interesting aspect of comparative

advertisement emanates from naming competitors (direct comparative) creating a reference brand or

product, involving more complex information processing strategies for consumers. Because by naming

competitors, it activates people to process the ad in a different way, involving both attitudes about the

comparison brand as well as the sponsoring (Dröge, 1989). Priester, Godek, Nayakankuppum and Park

(2004) also confirm that the complex information processing due to explicit brand comparison, can lead

to strong attitudes toward the sponsoring brand. And naming a high-share brand can attract attention

to the entire ad, which can contribute to an increase in purchase intentions (Pechmann, and Stewart,

1991).

The comparison brand is the brand that is explicitly mentioned in the ad, and is used as a reference

brand, to indicate relative differences and similarities. The comparison brand is often the brand leader.


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The sponsoring brand is the brand being advertised in the ad. The sponsoring brand is trying to fill a gap

between how consumers currently think about the brand, and how the brand is in reference to

competitive brands. This brand is often normally seen as an inferior brand, but due to the ad, the brand

should seem to be equal or superior to the comparison brand. For example, a chocolate manufacturer X

claims its chocolate is at least as tasty as the chocolate of Milka (well-known chocolate manufacturer),

but much cheaper. Milka is the comparison brand, manufacturer X is the sponsoring brand, and the

comparison (as tasty, but cheaper) should persuade consumers that consuming manufacturer X’s

chocolate is a wiser choice.

For this research, the definition of Miniard, Barone, Rose and Manning (2006) is used. It is based on the

well-accepted definition of Wilkie and Farris (1975). Willie and Farris defined CA as: “comparative

advertising compares two or more brands of the same product or service class and makes a comparison

in terms of one or more product or service attributes”. Miniard et al, distinguishing explicit and implicit

comparative advertisements, define direct (explicit) advertising as follows: “[when] specific competitors

are identified explicitly as a reference point for interpreting claims about the advertised brand’s merits”

(2006). This is the specific type of advertising that is investigated in this study. Due to this type of

advertising, most people will think about how the sponsored brand compares to the comparison brand

(Miniard et al, 2006). It allows a brand to engage the consumer to reconsider the current attitudes they

have for the typical brand. This triggers people to process the advertisement more intensively, according

to Petty, Cacioppo and Schumann (1983), this type of advertising is most likely being processed centrally

(Priester, Godek, Nayakankuppum and Park, 2004), which is explained later on.

2.1.2 Application of comparative advertising

CA is generally employed by brands that are new in a market (no market share), or brands possessing a

small market share, and literature also suggests that this type of advertising is mainly effective for such

brands (Dens and De Pelsmacker, 2010; Barigozzi et al, 2009). The brand that possesses a large market

share, is a familiar brand to consumers, inducing greater feelings of relevance toward the ad. These

feelings of relevance prompt increased elaboration; increasing the chances of the ad being processed

centrally (Priester et al, 2004; Petty and Cacioppo, 1983). Moreover, brands can benefit from the halo

effect of being associated with the brand that the sponsored brand is compared to (Pechmann and

Rathneshwar, 1991). Zhang, Moore and Moore (2011) state that a consumer’ involvement with a

product can influence his information processing strategy. For example, higher priced, infrequently

purchased items generally evoke more centrally based information processing (in comparison with


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convenience goods), because it is more important for consumers to purchase the best suited product,

leading to a higher consumers’ involvement.

2.2 Processing mode in comparative advertisements

2.2.1 Elaboration likelihood model explained

Forming of attitudes by consumers due to advertising is highly dependent on the consumer’ information

processing mode. Petty and Cacioppo (1983) developed a contingency model, the elaboration likelihood

model, which illustrates how processing mode contributes to forming and changing attitudes. The

elaboration continuum ranges from low elaboration (little thoughts and processing) to high elaboration

(high thoughts and processing). The likelihood of elaborating to a certain degree in the continuum

generally indicates the route to persuasion. The central route to persuasion “views attitude change as

resulting from a person’s diligent consideration of information that s/he feels is central to the true

merits of a particular attitudinal position” (Petty and Cacioppo, 1983). Attitudes are thus based on

thorough considerations of a person, and are postulated to be relatively enduring and predictive of

behavior. Peripheral route to attitude change occurs “because the attitude issue or object is associated

with positive or negative cues, or because the person makes a simple inference about the merits of the

advocated position based on various simple cues in the persuasion context”. The attitude formations

and changes are postulated to be relatively temporary and not predictive of behavior (Petty and

Cacioppo, 1983). Elements in advertisements that are processed centrally should be designed differently

than certain elements in traditional advertisement. An element that is very important for people to

determine the motivation to intensely process ads is involvement. High involvement often leads to high

elaboration, thus are ads most effective with the central route to persuasion.

2.2.2 Elaboration likelihood model and comparative advertising

The theory of central and peripheral processing (Petty and Cacioppo, 1986) establishes that central

processing is “a person’s careful and thoughtful consideration of the true merits of the information

presented in support of an advocacy”. Comparative advertisements and products carrying more risk are

examples of factors increasing involvement, hence increasing the chance of ads being processed

through the central route to persuasion (Dröge, 1989). Dröge argues that comparative advertisements

are generally processed centrally, because of a variety of reasons. First of all, CA encourages rational

evaluation of brands due to the comparison (which evokes central processing). Subsequently, by

comparing a relatively unknown brand tot known brands, comparison shopping is encouraged, which

motivates information search strategies that are processed centrally. Also, higher content involvement


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is expected with CA, that triggers issue-relevant elaboration, which provokes central processing. Finally,

central processing depends on the presence and activation of preexisting knowledge structures, and by

directly using existing information about familiar brands, consumers are motivated to elaborate the

presented information with their current knowledge (Droge, 1989).

2.3 Believability in comparative advertising

2.3.1 Hierarchy of comparative advertising effects

In the model of the hierarchy of comparative advertising effects of Grewal and Kavanoor (1997) , a clear

overview is given on the effects of the advertising format (comparative or noncomparative), its effects

(cognitive, affective and conative; Lavidge and Steiner, 1961), and the moderators of the relationship

between the advertising format and the main effects. Grewal and Kavanoor state that the model is not

complete, and that more complicated relations between variables can exist and should be investigated.

The model gives an excellent general view of factors involved in advertising format and its effects.

Moreover, it is concluded that CA can be advantageous with respect to noncomparative advertising in

many situations, and that this form of advertising can be optimized. Grewal and Kavanoor summarize

the following advantages. In comparison with noncomparative advertising, on average, CA generates

more attention, and brand and message awareness is higher. CA also evokes more elaborate processing,

and CA tends to be more informative to consumers.

Furthermore, in comparison with noncomparative advertising, CA generally creates more favorable

brand attitudes. These results do differ strongly in current literature, and depend on circumstances in

which CA is applied. Finally, CA has a more positive impact on fostering purchase intentions and actual

purchase behavior. Grewal and Kavanoor conclude that on average, 22% more purchases are made due

to CA in comparison with noncomparative advertising (1997). The differences between the advertising

formats can be seen in table 1 below. It must be noted that the variables displayed in the table below

are positive or negative, in comparison with noncomparative advertising. So for instance, attitude

toward an advertisement is not by definition influenced negative in comparative advertising, but is rated

lower than in noncomparative advertising.


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Advertising function positive Negative

Attention

Awareness

Processing

Cognitive effects

Informativeness

Believability

Affective effects Attitude toward brand Attitude toward ad

Purchase intention Conative effects

Purchase behavior

Table 1: Relative effects of comparative advertising versus noncomparative advertising

2.3.2 Contingencies to comparative advertising

As is mentioned before, the effectiveness of CA in comparison with NA strongly depends on

circumstances in which it is applied. Apart from the in table 1 mentioned advantages and disadvantages

of CA on cognitive, affective and conative effects, results of CA can be based on more causes. Research

has described that the sponsoring brand and the comparison brand can be confused, characteristics of

the comparison brand can be transferred to the sponsoring brand (Dröge and Darmon, 1987), or CA can

be a useful tool to distinguish a brand from the comparison brand. Moreover, CA challenges current

beliefs of consumers, which can lead to counterarguing. This is more likely to happen to customers who

prefer the brand that is being compared (they are feeling attacked, loyalty enables defensive arguing).

So in contingency terms, since the comparison brand is often the market leader, the question rises to

what extend the ad should be comparing (how hostile can it be), and is it wise to apply this marketing

tool in a market with a dominant market leader? On the other hand, Dröge and Darmon (1987) argue

that brand attitudes toward market leaders are often more favorable, and through CA, these attitudes

can be transferred. So the exact influence of comparing with a market leader is not determined, and

needs to be investigated more thoroughly.

Attention is also mentioned in literature as a positive characteristic of CA in comparison to NA, because

of the novelty of such an ad, and the way it stands out to other ads. However, since this form of

advertising has become much more popular, the attention advantage is likely to diminish.

2.3.3 Definition of believability in advertising

Believability of ads is an important element to persuade people. In comparison with noncomparative

advertising, this advertising effect is associated negatively with CA. In traditional, noncomparative

advertising, believability in advertising is not critical in creating favorable attitudes and fostering


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purchase behavior (Swinyard, 1981). In traditional advertising, favorable attitudes and purchase

intentions are more dependent upon attitudes that are formed toward the ad, and peripheral cues in

the ad (elaboration likelihood model). CA is based on explicit comparisons of product or brand

characteristics, and therefore, must be believed to be effective. In literature, advertising believability is

described as how consumers perceive the believability of the source of an ad and the truthfulness of the

message (Grewal and Kavanoor, 1997; Settle and Golden, 1974). These two elements are inseparable,

and therefore believability, as a construct, is measured as one concept (Golden, 1977). A construct, like

ad believability or involvement, is an abstract variable that is hard difficult to visualize, and is used for

research and theory-building purposes. On the other hand, amount of sales is an objective, easily

measured variable (Cooper and Schindler, 2006).

If a comparative advertisement is believed, it is a very informative way of communication for the

consumer. However, less believable ads are dealing with counter arguing with the message arguments,

statements about the curiosity of the claims, derogating the source of the message and other positive or

negative statements about the message (Swinyard, 1981). Consequently, this leads to the formation of

less favorable attitudes. The most damaging to believability of the ad is counter arguing, according to

Wright (1973). And, based on the attribution theory, Swinyard argues that this can best be solved by

utilizing two-sided messages (1981). This way, the ad keeps being advantageous by providing high level

of information, but with good ad credibility.

Attribution theory is used as a framework for predicting consumer behavior. Attribution theory

describes how consumers think about communication of advertisers, and states that these consumers’

thoughts are an important determinant in accepting or rejecting the advertising message. Consumers

decide why an advertiser wants to deliver a message and whether or not the message is true (Gotlieb

and Sarel, 1991). Comparative advertising messages can be seen as attempts of advertisers to sell

products and create brand liking. This means that consumers discount the believability of the ad

(Gotlieb and Sarel, 1991; Chow and Luk, 2006) Eagley, Wood, and Chaiken (1978) identify two types of

bias that advertisers have, according to consumers’ perception; knowledge bias and reporting bias.

Knowledge bias hold that the advertisers’ claim is incorrect, because the advertiser’ knowledge about

the advertised issue is not complete. The reporting bias holds that the advertiser deliberately depicts an

advertising claim incorrect (in favor of the advertised brand). Attribution theory can be used to help

advertisers remove the bias consumers perceive in advertisements.

Subsequently, following Swinyard’ arguments of ad believability, CA delivers more information to

consumers about the relative characteristics of their brand in comparison with other brands. Swinyard


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depicts the enhancement of believability and the differences of CA and NA in a contingency model

(1981), as can be seen in table 2 below.

One-sided claims Two-sided claims

Comparative claims Rich in relative price information

Low credibility

Therefore, relatively ineffective

Rich in relative price information

Moderate credibility

Therefore, very effective

Noncomparative claims No relative price information

Moderate credibility

Therefore, moderately effective

No relative price information

Moderate credibility or better

Therefore, only moderately effective

Table 2: Contingency model of message sidedness and competitiveness of claims

Swinyard investigates differences of CA and NA on the basis of message sidedness, but the underlying

construct is advertising believability. As believability increases in noncomparative claims, ads are still

moderately effective because it lacks in informativeness to consumers. Believable comparative ads can

be very effective, due to the comparison in reference to competitors, where low believable comparative

ads can prove to be very ineffective.

2.3.4 Believability in comparative advertising and noncomparative advertising

In earlier models of comparative advertising (Wilkie and Farris, 1975), comparative ads were presumed

to provoke more believability than NA. However, further research concluded that noncomparative ads

are on average more believable than comparative ads. Grewal and Kavanoor explain that the

believability is lower, because the claims in comparative ads challenge consumers’ prior beliefs (1997).

Gotlieb and Sarel (1991) also argue that lack of believability is the major shortcoming of successful

comparative advertising. However, if this shortcoming in the model can be offset, CA becomes an even

more effective way of advertising. Thus, investigating how believability can be improved, and what the

influence of believability is on brand attitudes and purchase intention is, is important for improving the

knowledge about optimizing comparative ads.

Subsequently, research has shown that consumers generally form fewer favorable attitudinal responses

toward the advertisement than noncomparative ads (Gorn and Weinberg, 1984; Swinyard, 1981;

Putreva and Lord, 1994). Attitude toward the ad is a consumer’s feelings and overall attitude toward the

ad (Grewal and Kavanoor, 1997). Consumers form less favorable attitudes toward the ad because

comparative ads are more aggressive, intense, and perceived to be less honest, and considered to be an

attack on other brands (Grewal and Kavanoor, 1997).

In advertising literature, it is argued that consumers’ attitudes toward the ad positively influence

attitudes toward the sponsored brand (Mackenzie, Lutz, and Belch, 1986). However, Droge (1989) found


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that this relationship does not necessarily hold for comparative ads. It is mentioned earlier that

consumers are generally forming more positive attitudes toward the brand in comparative ads than in

noncomparative ads. Droge and Darmon (1987) explain that positive attitudes that are associated with

the comparison brand (often market leader) are transferred to the sponsoring brand. Also, because

comparative ads are clearer and differentiate the brand on certain characteristics, consumers form

more positive attitudes toward the brand than consumers do in noncomparative ads (Grewal and

Kavanoor, 1997).So the forming of attitudes toward the ad cannot predict the forming of attitudes

toward the sponsoring brand. In NA it is important to create an ad that enhances attitudes toward the

ad, because it is then expected that brand attitudes and purchase intentions improve. In CA, attitudes

toward the ad are very often negative, but brand attitudes are not directly influenced. So in short, a

comparative ad can be annoying or less entertaining than a noncomparative ad, but due to the richness

in information, it can be more persuasive in enhancing brand attitudes, and creating purchase

intentions. For this reason, this study focuses on brand attitudes, and not on attitudes toward the

advertisement. Forming of brand attitudes is considered the main dependent variable that should

increase by improved ad believability. Purchase intentions, which result from positive brand attitudes,

are also investigated and expected to be subject to the positive influence of ad believability. It is

plausible that attitudes toward the ad can still be of influence in this theoretical model, but in the scope

of this study, it is not incorporated. Not including attitudes toward the advertisement in studies of

comparative advertising is in line with earlier research (Grewal and Kavanoor, 1997).

2.4 Fostering advertising believability

The effects of low believability of an ad are that people derogate the source of the message of the ad,

people counter argue with the message claims, make statements about the curiosity of the claims, or

make other negative statements about the message. These effects are likely to influence consumer’s

attitudes about the brand, and their purchase intentions (because the persuasiveness is negated by its

lacking credibility). Since the believability is at stake in CA, increasing it should prove to be a fruitful

tactic.

2.4.1 Message-sidedness in comparative advertising

Chow and Luk elaborate on believability in CA in their article (2006), on the basis of the comparative

advertisement intensity theory of Donthu (1992). The theory of comparative advertising intensity holds

that the believability of comparative ads depends on the intensity of the comparisons. CAI (comparative

advertising intensity) is a rating of the intensity of comparative television ads, but it can also be used for


18

print ads. A CAI of 0 means that the ad is noncomparative. The intensity rises 1 level, (1) when the

advertisement explicitly names the comparison brand, or in other literature defined as direct

comparative advertisement (Miniard et al, 2006). The intensity raises 1 level, (2) when the ad makes

specific comparisons on the basis of product attributes (not general claims of superiority, as is common

in traditional advertising). Furthermore, the CAI increases (3) when the ad utilizes one-sides messages

(not two-sided messages, illustrating both positive and negative differences between brands). Finally,

the CAI increases (4) if it spends more than 50% of the time comparing the brands (this only holds for

television ads).

The CAI theory confirms that CA can perform better than noncomparative advertising on certain

dimensions, or perform worse when the comparisons made in the ad are too intense, measured on the

CAI scale. However, the theory also contains several elements that have already been discussed in

literature. In the definition of CA, it is captured that this research only employs direct comparative

advertisements (thus according to CAI theory, level +1 for comparative ad intensity). Since television ads

are not used in this study, that level becomes overdue. So, one-sided or two-sided, and specific or

generic comparison will determine the CAI. The previous research determined that CA are most

effective just one or two levels beneath the most intensive ads (Donthu, 1992) and that double-sided

messages are most important in increasing the believability, especially with high cognitive elaboration

(Chow and Luk, 2006). So in an ad where high cognitive elaboration is expected, using the most intense

comparative advertisement except employing two-sided messages instead of one-sided messages, will

lead to optimal results, as is confirmed by other studies.

According to research of Barrio-Garcia and Luque-Martinez (2003), when the CAI is higher, the ads tend

to be more informative, but the believability tends to decrease. Because Donthu (1992) and Chow and

Luk (2006) conclude that a very high level of CAI decrease positive attitudes toward the ad, ads should

be designed to have a moderate to high comparative intensity. Moreover, arguing on the basis of the

attribution theory, utilizing two-sided messages will lead to the consumer’ believe the advertiser is

informing the consumer, instead of selling a product (Iyer, 1988). Attributing the intentions of the

advertiser as informing, increases the believability of the ad. This concludes that two-sided messages

should be utilized to attain better ad believability.

Etgar and Goodwin (1982) argued in their research that by mildly attacking yourself in an ad (two-sided

message), negative counter arguments can be reduced and invalidated. In this study it is concluded that

two-sided messages in comparative advertising increased favorability of attitudes toward the brand.


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2.4.2 Establishing credible sources

Gotlieb and Sarel argue in their study that ad believability is a critical factor in forming favorable brand

attitudes (1991). Based on the attribution theory, source credibility (the second element in increasing

believability according to Grewal and Kavanoor, 1997) must be high for consumers in comparative

advertising (Golden, 1979).

Gotlieb and Sarel suggest that perceived expertise and trustworthiness are the underlying dimensions of

source credibility (1991). Perceived expertise is whether a consumer thinks the source is a

knowledgeable person (source as advertiser, endorser, or research agency). Trustworthiness is whether

the consumer thinks the source’s opinions are unbiased. For example, the message of an average

consumer may be trustworthy (he is objectively telling the truth), but the expertness can be very low.

The trustworthiness of a researcher of the advertising company may be perceived as an expert, but his

trustworthiness is low (because he can be biased in telling the truth). So establishing credible sources,

by using expert and trustworthy sources (for instance a research agency with well-known credentials, or

using objective measurements), can increase the believability of the ad. Eagley, Wood, and Chaiken

suggest that information from highly credible sources is perceived as providing a more accurate

perception of reality (1978).

2.4.3 Substantiating the claim

Golden (1979) investigated the influence of substantiating a comparative advertising claim, with

independent test results, on believability. The results of the study are not unequivocal, but they suggest

that believability increases, if the claims in an advertisement are supported by independent test results,

rather than being unsupported by test results. It seems acceptable that substantiating claims take away

counter arguing, and bolster the believability. Grewal et al (1997) also suggest that this is a factor that

determines believability of an advertisement. Therefore, in an effort to increase ad believability,

advertising claims are substantiated.

2.4.4 Attending to the message content

Edell and Stalin (1983), and Iyer (1988) argue that attending to the content of the message, by

comparing information with factual information instead of evaluative information, contributes to the

believability of an ad. Factual information, compared to evaluative information, is objective in nature,

and therefore elicits fewer counterarguments (Edell and Staelin, 1983). Evaluative information, or

subjective information, can be questioned by consumers because of its nature.

The comparisons made in comparative advertising are normally based on factual information, and


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previously described characteristics of CA (activating information searching strategies) suggest that this

is better suited. But in this study, all comparisons are drawn upon factual information. So the

contribution of this effort is not incorporated in the study design. Grewal and Kavanoor (1997)

investigate the use of both factual and evaluative information, but the results are not conclusive.

2.5 The dependent variables influenced by believability

The variables investigated in this study that are influenced by increased believability in comparative

advertisements are (1) attitude toward the brand, and (2) purchase intention, based on Grewal and

Kavanoor (1997). The main point of interest is brand attitude, because this is formed as a direct result of

advertisements, and is directly applicable in the model. Purchase intentions, as predictor of purchasing

behavior, are also influenced by prior formed brand attitudes, and can be less predictable upon the

identified independent variables. However, first the influence of ad believability and the moderators on

purchase intentions is investigated in the same model as brand attitudes.

2.5.1 Effect of believability on attitude toward the brand

Creating favorable brand attitudes is a purpose of many advertisements. If the believability of an ad is

higher, counter arguing and negative statements are less likely being formed. Fostering believability in a

comparative advertisement is based on creating less negative thoughts, diminishing counter arguing,

and the ads tend to be less aggressive. Consumers form less source derogating thoughts, and trust the

message of the ad more. When this is accomplished, consumers are open to the information in the ad,

which is relatively persuasive. As a result, the probability of forming positive attitudes toward the

sponsoring brand is increased. Hence, it is expected that with an ad with high believability, brand

attitudes for the sponsoring brand will increase as well.

2.5.2 Effect of believability on purchase intentions

Purchase intention is an often used predictor of actual purchasing behavior. Increasing purchase

intentions due to advertisements will be the goal for many advertisers, earning back ad investments and

gaining profit. Purchase intentions depend on several factors as is explained in the hierarchical model of

Grewal and Kavanoor (1997), but the direct relationship of ad believability and conative effects

(purchase intentions) is merely being suggested. As is stated earlier, a main advantage of CA is that its

informativeness for consumers dramatically increases, offering better possibilities for them to decide

what brand or product to purchase. The persuasiveness of an ad strongly depends upon the believability

of the claims being made, and the credibility of the sources. An assumable condition of actual purchase


21

behavior or purchase intentions, is whether the persuasive information that is being presented, is

actually believable or not. It is very likely that persuasive information that is totally unbelievable, is

being discarded, counter argued, and no purchasing intentions are being made as a result of it.

However, persuasive ad claims that are perceived to be believable, will increase the probability of

consumers forming purchase intentions. Hence, it is expected that high advertisement believability will

lead to increased purchase intentions. However, brand intentions are an important antecedent of

purchase intentions (Grewal and Kavanoor, 1997), and therefore, purchase intentions can be hard to

predict, solely based on ad believability and moderators.

2.6 Moderating effect of perceived product risk

2.6.1 Definition of product risk

It is established that in comparative advertising, believability can potentially influence the forming of

attitudes and purchasing behavior. The importance of believability can differ across different products.

In this study, it is suggested that the risk of a product can intensify the relation of believability and the

dependent variables (attitude toward the brand, and purchase intention). Product risk is a subject that

has been investigated in marketing literature for decades. It is the risk that a consumer perceives for a

product, concerning financial, performance, physical, psychological, social and time risk (Roselius, 1971).

These six risk types are rarely investigated in one study, and the majority of products contain a few risks

at most (Korgaonkar and Karson, 2007). Of these risks, financial, performance and psychosocial risks are

identified as most important risks in influencing consumers. Numerous studies base implications of risk

on the contingency between (psycho)social risk on the one hand and economic risk on the other hand

(Prasad, 1975). The scope of this study would be too broad if all types of risks are included, so it is based

on products that contain financial and/or performance risk. Delvecchio (2005) defines financial risk as

“the economic outlays that may be lost if a product does not perform adequately”. Performance risk is

defined as “Losses associated with the purchase of a product are often the result of the product’s failure

to meet consumers’ performance expectations”. These risks are strongly linked. Products that are

expensive (financially risky), are disappointing if the performance of the product is bad. And uncertainty

of the performance of cheap products are regarded a waste of financial means if the performance is not

meeting expectations. For this study, product risk is defined as the financial and or performance risk that

consumers perceive in a product, in the buying process.


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2.6.2 Moderating effect of product risk on attitude formation and purchase behavior

When consumers perceive a product to comprise high risk, they are more careful in their considerations

in buying a product or not. Also, an ad promoting a high risk product, is being judged more critically,

because it is more important for customers to prevent them from making wrong decisions. In other

words, the consumer is more involved with the ad, and judges the ad more critically and centrally (Petty

& Cacioppo, 1983). The consumer is less influenced by peripheral cues, but on the other hand he is more

critically assessing the arguments and truthfulness of the ad. A low risk product involves little risks to the

consumer, so the result of bad choices is diminished, which leads to less ad involvement. In this case,

the consumer is more sensitive to peripheral cues than the quality of arguments or believability of the

ad (Petty & Cacioppo, 1983).

In an effort to convince consumers of a lower product risk (so to diminish the perceived risk for a

consumer), advertising can be an effective method. Endorsers are often being used to lower the

perceived risk. It is generally acclaimed that different types of risks need different types of endorsers.

Friedman and Friedman (1979) argue that perceived psychosocial risks are best reduced by celebrity

endorsers, and that financial, performance (and physical risks) should be reduced by using expert

endorsers. Expert endorsers draw heavily on the underlying dimension source credibility. So, the goal of

using expert endorsers is to increase the believability, when normally, the financial and performance risk

to consumers is high. This conclusion suggests that products that contain great financial and

performance risks to consumers, reducing the perceived risk is optimally attained by boosting the

believability of advertising. Thus a high ad believability, that reduces consumers’ distrust and perceived

risk, leads to increased liking and formation of favorable attitudes. On the other hand, when financial

and performance risk is high, but the ad believability is low (so the advertiser apparently does not make

an effort in lowering the perceived risk for consumers), consumers will most likely distrust the product,

and not form favorable attitudes.

This line of reasoning is very acceptable when it is construed in examples of products that are

advertised. For example, a (financially and performance) high risk television, that is advertised as being a

better bargain in terms of price and performance without substantiating the claim (low ad believability),

is unlikely to convince consumers of its superior value. And because of the high risks of the product, it is

unlikely that consumers will consequently form favorable attitudes. On the other hand, if the

advertisement takes high effort in substantiating the believability of the ad, to reduce perceived risks, it

is likely that consumers’ beliefs and attitudes are influenced positively.

For a product that contains little financial and performance risk (for example an everyday convenience


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good in a supermarket), high ad believability is presumably not significantly influencing consumers’

attitudes and beliefs toward the brand. If the product is already perceived to contain little risk, it is not

likely to be important to substantiate advertisement claims and foster believability.

2.7 Moderating effect of brand preference for comparison brand

2.7.1 Advertising believability and brand preference for comparison brand

Grewal and Kavanoor explain that the believability is lower, because the claims in comparative ads

challenge consumers’ prior beliefs (1997). This especially affects users of the brand that is being

compared (Swinyard, 1981). Comparative ads normally compare a brand to the market leader with the

largest share of consumers. If these ads are less believable than noncomparative ads, and especially for

consumers who prefer the compared brand, then this is an important shortcoming to CA. A large

proportion of the consumers that are reached (consumers of the market leader), might be addressed in

a negative way. So, consumers who prefer the comparison brand are expected to resent a comparative

ad stronger. This relation is expected in literature, but has not been tested (Grewal and Kavanoor, 1997;

Swinyard, 1981).

In general, believability is lower for CA, but this does not necessarily have to infer that CA is less

effective than NA. However, the assumption that believability for consumers with a brand preference

for the comparison brand, often the market leader, is lower than consumers without a preference for

the comparison brand, might have severe implications. For example, if a small brand utilizes

comparative advertising, and compares itself with the market leader that has a market share of 80%,

80% of the consumers might resent the advertising claims beforehand, because it is not believable

enough. In this example, the advertiser can already lose interest of a large group of potential customers,

if the ad believability appears to be low. For this particular group of customers, it might be more

essential to focus on enhancing the believability of the ad. In conclusion, believability is expected to be

lower for consumers who prefer the comparison brand, due to counterarguing (Swinyard, 1981). Also

brand attitudes and purchase intentions are expected to be lower for this group of consumers,

compared to people not preferring the comparison brand, because of brand loyalty to and brand

knowledge of the comparison brand. Two interesting questions that should be answered are (1) are

there differences between people preferring the comparison brand and people not preferring the

comparison brand, concerning the believability of the ad, and (2) after measuring the ad believability for

individual consumers, what are the differences in brand attitudes and purchase intentions for

consumers who prefer the comparison brand and consumers who do not prefer the comparison brand.


24

A conclusion to these questions might be that a balance is needed in the relative market size of the

comparison brand; a too large or too small market share may negatively affect advertising effects.

Swinyard (1981) describes that consumers counterargue with advertising claims, especially if they feel

that ‘their’ brand is being attacked, and if the ad seems hostile. Counterarguements can best be reduced

by employing two-sided messages or substantiating advertising claims. So for the group of customers

where heavy counterarguing is expected (consumers who prefer the comparison brand), the effect of

enhancing ad credibility might be stronger. Furthermore, even though it is established that brand

preference influences several processes induced by the ad, this study seeks if there is still a significant

difference in brand attitudes and purchase intentions for consumers who prefer the comparison brand

and consumers who do not prefer the comparison brand, given the perceived ad believability. It is

expected that brand attitudes and purchase intentions are lower for people who prefer the comparison

brand. Moreover, these consumers are stiffer in changing their existing views about their brand, and the

advertised brand, due to brand loyalty and product knowledge. Therefore, even if ad believability is high

for these consumers, the influence on the formation of favorable brand attitudes and purchase

intentions is expected to be smaller, than for consumers not preferring the comparison brand. So in

short, the effects of ad believability are greater for people not preferring the comparison brand, than for

people preferring the comparison brand.

This means that many relations have to be measured, because it can be important in determining

whether it is always sensible to compare a product with the market leader. Positive effects (more

attention, more elaboration) may be offset, when believability of the ad is low, if a considerable large

proportion of the consumers resents the ad. Identifying these relations might increase the knowledge of

how and when to target the market leader in comparative advertising.

2.8 Literature summary and conceptual model

2.8.1 Literature summary

In this literature review it is described that comparative advertising can have several advantages

compared to noncomparative advertising. Because comparative advertisements are generally processed

centrally, more intense brand attitudes are being formed, and consumer behavior is more predictable.

This is a goal for many advertisers, and therefore it is important to investigate optimal conditions for this

type of advertising.

Apart from the several advantages CA can offer, the main disadvantage is that these ads are perceived

to be less believable. This can discount the advantage of superior persuasiveness, when the ad has a


25

very low believability. Increasing ad believability should result in less source derogation thoughts of

consumers, less counter arguing, and the forming of less negative thoughts. Consequently, it can be

measured whether believability has a direct influence on affective and conative consumer responses. It

is expected that brand attitudes are more positive when believability is greater. Also, purchase

intentions are expected to increase with a higher believability. Product risk (specifically financial and

performance risk) is expected to moderate these relationships. Under condition of high perceived

product risk, the influence of believability is extra important in forming favorable attitudes and forming

purchase intentions. Under condition of low perceived product risk, believability is less important in

forming favorable attitudes and purchase intentions. Furthermore, brand preference is identified as a

variable that can influence the relationship of ad believability and the dependent variables. Consumers

who prefer the brand that is used as a comparison are expected to be more critical and rejecting.

Believability is more important for this group of consumers, where it is expected that ads with low

believability have increased negative ratings. The difference in brand attitudes and purchase intentions

is expected to be smaller for people preferring the comparison brand or not preferring the comparison

brand, with high ad believability.

2.8.2 Conceptual model explained

Believability in comparative advertising is the independent variable in this study, and is depicted in the

blue box in figure 1. Believability positively influences the dependent variables (H1) attitude toward the

sponsoring brand and purchase intentions (yellow boxes). Furthermore, perceived (financial and

performance) risk increases the importance of believability in comparative ads. This variable strengthens

the relationship of believability on attitudes toward the brand and purchase intentions (H2). Moreover,

a brand preference for the comparison brand is incorporated in the model. It is expected that brand

preference for the comparison brand strengthens the relation of ad believability and the dependent

variables (H3). Brand preference is also expected to have a strong negative direct influence on the ad

believability variable (H4). The intensity of this relation is important, especially if this is a large group

with very low ad believability. Ad believability is influenced by utilizing two-sided messages, credible

sources and substantiation of the ad claim (high believable ad), as is depicted in the purple framework.

This is checked in the results for confirmation purposes only; the construct ad believability (blue box) is

the variable utilized in the statistical models.


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Figure 1: Conceptual model

Believability in CA

Attitude toward brand

Purchase intentions

Effects of advertising believability in comparative advertisement

Perceived

product risk

H1

H2

H3 H4

Credible sources

Substantiating claim

Message sidedness

Preference for

comparison brand


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3. Methodology

In the methodology part, the causal method to test the hypotheses is described and the methods for

calculating the results are explained. First, the hypotheses accompanied with the research question are

described.

3.1 Research question and hypotheses

This study is designed to give an answer to the research question, formulated in the introduction:

What is the influence of the believability of comparative advertising on consumers’ attitudes toward the

promoted brand and purchase intentions, and what is the influence of perceived product risk and a brand

preference for the comparative brand on this relation?

Research on believability in CA is essential in improving this advertising format. Based on literature,

believability is associated positively with attitude toward the brand and purchase intentions. These two

dependent variables do not form part of the same model in this research. Therefore, the hypotheses are

measured for both DV’s (resulting in double hypotheses for H1, H2 and H3). All hypotheses used are

explanatory hypotheses, which means that the existence of or a change in one variable (IV) causes or

leads to a change in the other variable (DV) (Cooper and Schindler, 2006). The hypotheses concerning

believability and DV’s are:

Hypothesis 1a: Believability in CA positively influences attitude toward the brand.

Hypothesis 1b: Believability in CA positively influences purchase intentions.

The main effects of believability are expected, but moderating variables deliver interesting additions to

current knowledge on believability in CA. A moderating variable affects the direction and/or strength of

the relation between independent and dependent variables. In this study, it is proposed that perceived

product risk strengthens the relationship of advertising believability and the dependent variables. On

the basis of earlier research, it is expected that the believability of ads is a more important factor for the

dependent variables, when product risk is high. On the other hand, when product risk is low,

believability is expected to be of less crucial importance. The following hypotheses are formulated:

Hypothesis 2a: The influence of believability on attitude toward the brand is strengthened by perceived

product risk.


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Hypothesis 2b: The influence of believability on purchase intentions is strengthened by perceived product

risk.

Another moderator in this study is brand preference of consumers. In the current literature, the

influence of brand preference on the relationship of believability and the dependent variables has not

been determined. It is expected that believability is more important for consumers who do not prefer

the comparison brand, for forming favorable brand attitudes and subsequently purchase intentions. The

following hypotheses describe the relationships:

Hypothesis 3a: The influence of believability on attitude toward the brand is stronger for consumers who

do not prefer the comparison brand, and weaker for consumers who prefer the comparison brand.

Hypothesis 3b: The influence of believability purchase intentions is stronger for consumers who do not

prefer the comparison brand, and weaker for consumers who prefer the comparison brand.

As was described, it is likely that ad believability is generally lower for consumers who prefer the brand

that is being compared. Because the comparison brand is often the market leader, it is of great

importance that behavior of this large group of consumers is investigated thoroughly. A strong negative

relation can prove to be an important finding in CA literature. The following hypothesis is formulated:

Hypothesis 4: Brand preference for the comparison brand has a negative influence on ad believability.

3.2 Pretest determining product categories

A pretest was held to ascertain if correct product categories were chosen. The products for the

advertisements (1) must be either low risk or high risk, and needs to be used by both genders (2), the

market leader brand of the product category must generally be preferred (measuring brand preference),

and some product category knowledge is required (brand awareness is measured by asking respondents

to name as many brands as possible in the category), (3) and must be interesting for the target group

(involvement level of approximately 3-4, on a 5 point Likert scale). In the pretest, ten respondents were

asked to rate two high risk and two low risk products. The entire pretest can be found in appendix D-1.

The questions measuring perceived product risk are based on Grewal et al (1994), DelVecchio and Smith

(2005) and Harmon and Coney (1982), as can be seen in appendix A-1. The questions measuring

involvement are based on Laroche and Nepomuceno, (2010). The products investigated are: Toothpaste

(low risk), shampoo (low risk), tablet computer (high risk) and cell phone (high risk). The expected

amount of financial and performance risk is based on research of Weinberger et al (1995), Korgaonkar


29

and Karson (2007). The expectations are that toothpaste and shampoo (as fast moving consumer goods)

generally pose little performance and financial risk to customers, in contrast to new technological

expensive products as tablets and cell phones. These products are suitable because the respondents in

the sample are expected to use such a product, consider buying it, or know friends who use the product.

For example, a product like cigarettes is less suitable, because a majority of the respondents does not

want to buy it. Other reasons for products to be less suitable are that the products are intended for a

certain gender or age.

A pretest deducted by 10 respondents can support the chosen product categories. Toothpaste and

shampoo have been selected as low risk products. Involvement is expected to be of average level

(everyone needs personal hygiene), and brand awareness is expected to be quite broad, due to

advertising.

Mobile phones and tablet computers have been selected as high risk products, because these products

pose potential financial and performance risks. People are expected to be involved, because they own a

product or might be interested in buying such a product. Brand awareness is also expected to be high,

due to heavy advertising in these product categories (this especially accounts mobile phones).

Product risk is assessed by four questions per product category, on a 5-point likert scale (1 means low

risk, 5 means high risk). As can be seen in table 3, the Cronbach’s alpha is four all products is

approximately 0,6-0,7, which means the constructs have been measured reasonable reliable. Cronbach’s

alpha for the 2 involvement questions is good, except for mobile phones (0,449), which is too low.

Toothpaste and shampoo are regarded as very low risk products (means of 1,63 and 1,78 respectively),

mobile phones are regarded as moderate risky (3,25) and tablet as highly risky (4,28). Furthermore, the

involvement for all products is of a moderate level (between 2,85-3,7), except for the involvement in

mobile phones (4,55) which is very high. Brand awareness is of an acceptable level, although

respondents mentioned the least tablet brands (2,7 on average), which is explained due to the fact that

this market has only few well-known brands. Moreover, in every product category, one product was

mentioned by most of the respondents, which is useful in selecting a comparison brand.

The results for mobile phones are disappointing; The Cronbach’s alpha for involvement is unexplainably

low, which means that other factors may be of influence for the respondents’ perceived risk; perceived

risk for mobile phones can be too complex for this product category to measure through these

questions. The involvement level is also extremely high, which explains the high number of mentioned

brands. The part of tablets shows much more useful figures and is therefore selected for this study.


30

Currently, there are not many owners of tablets in the Netherlands, but the market is growing rapidly,

and competition is high. The figures for toothpaste and shampoo are very similar. However, toothpaste

is selected for two reasons: (1) toothpaste is the same for both genders, where shampoos often focus

on men or women, and (2) toothpaste is more suitable for advertising on product characteristics, as is

exemplified by the well-known ad of Oral-B (see appendix C-5).

Product Risk

Involvement Brand awareness

Cronbach α Mean

Cronbach α Mean # brands Most mentioned brand

Toothpaste 0,591 1,63

0,816 3,70 4,8 8 out of 10 (Oral-B)

Shampoo 0,604 1,78

0,845 3,20 4,3 9 out of 10 (Andrelon)

Mobile Phone 0,621 3,25

0,449 4,55 6 10 out of 10 (Apple)

Tablet 0,701 4,28

0,850 2,85 2,7 10 out of 10 (Apple)

Table 3: Pretest results

3.3 Research design of main study

3.3.1 Research format

The hypotheses formulated in paragraph 3.1 are tested in a 2x2 between participants factorial design.

This means that 2 (high believability and low believability) x 2 (high product risk and low product risk)

advertisements are used. The high believability ads contain two-sided messages, substantiate the claim,

and utilize credible sources. The low believability ads contain one-sided messages, do not substantiate

the claim and do not utilize credible sources. In the survey, this is an independent variable. Its effect on

the construct ‘ad believability’ is mainly used to determine the positive/negative influence the variable

has on ad believability. The statistical models however, are based on how respondents rate the

construct ad believability. And the dependent variables (brand attitude and purchase intentions) are

explained by respondents’ ad believability ratings.

The other independent variable in the survey, product risk, is manipulated by using two different

products, divided over the participants’ groups. On the basis of the results of the pretest, toothpaste is

chosen as the low risk product and tablets are chosen as the high risk product category.

3.3.2 Data collection

For a full-factorial design, 4 groups of randomly assigned respondents have been used. 186 Participants

were approached to fill in a questionnaire on the internet. This group of respondents is a sample of the

population, which in this study are all potential customers in the Netherlands. The participants were

automatically randomly assigned by thesistools.com, after clicking on a link that led to the survey. In

conclusion, because all circumstances were equal for all respondents, significant differences in results


31

are caused by manipulations in the four versions of the ads. And since differences in the ads are

minimized, except for the deliberate manipulations, the variances of the results are directly attributed

to the preselected IV’s. The division of groups and independent variables of the survey can be seen in

table 4 below.

High product risk Low product risk

High believability Group 1 Group 3

Low believability Group 2 Group 4

Table 4: Overview of manipulation across the four groups

The sample used is primarily based on students of the University of Groningen and Hanze University

Groningen. The use of students for this type of study is very common. Students of Groningen are

relatively easy to reach, their product category knowledge is of a fair level, they are generally interested,

are familiar with this type of research, and are easily accessible through social media, university group

mailings and other channels. Sudman justifies the use of students from an efficient use of limited

resources point-of-view (1976). However, because students are a homogenous group in society, the

external generality of the study might be reduced.

The data of 15 of the 186 respondents that filled out the survey have been deleted from the sample for

various reasons:

- Respondents did not finish the survey, leaving several questions unanswered.

- Age of the respondent does not fit the sample (for example, age -5).

- Respondents filled out the survey choosing exclusively extreme answers (1 or 5 on the Likert scale, 24

times). These respondents obviously did not answer the questions truthfully, and have been deleted.

The constructs, perceived risk, ad believability and others, are measured by averaging the means of the

respondents’ answers on 3 or 4 questions. In several cases, respondents skipped one of the questions,

but did fill out all of the other questions in the survey. In these cases, that typical construct is measured

by averaging the other two or three questions. For example, in case a respondent agrees (4), agrees (4)

and is neutral (3) about statements measuring 1 construct, but has left the fourth question blank, this

issue is solved by averaging the three responses (3,67) . This solution, and the fact that the survey was

very short (3 minutes), has led to a usable sample of 171 respondents out of 186, which is relatively

high.


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3.3.3 Stimuli: the advertisements

The four ads that were used can be seen in appendix C. The ads contain several elements, as can be

seen in table 5 and appendix A-2. There are two versions of an ad with the low risk product toothpaste,

and two versions of an ad with the high risk product tablet. The two versions of the same product are

identical, but differ on some elements, listed in table 5. Differences of variance between the two

versions can be attributed to these elements. So within the product category, the ads are very similar.

But also the ads of the other different product categories are very similar. The layout, use of colors and

effects, amount of arguments, use of a main claim, use of an endorser, depiction of the price and brand

name, subtext, and emphasis on believability or not is executed in the same manner, so differences are

minimalized on purpose.

Small elements are different (but similar) to fit the product (background color corresponds with brand

color, expert endorser is dentist or technology salesman, claim substantiation by ‘care organization’ or

‘technology forum’, and other small differences), as can be seen in table 5.

High believability (Group 1 & 3) Low believability (Group 2 & 4)

Claim substantiation & source

credibility (2.4.2, 2.4.3)

1 main claim, substantiated

& with credible source

1 main claim

Claim substantiation (2.4.3) 2 ad arguments, substantiated 2 advertising arguments

Message sidedness (2.4.1) 1 negative arguments 0 negative arguments

Source credibility (2.4.2) Trustworthy and expert endorser None expert endorser

Table 5: Elements manipulating believability

Below in figure 2, the believable tablet ad, used for group 1, is compared to the other three ads, and

important manipulations have been circled in red. As can be seen in the top right ad, the circled items

have been replaced or removed from the ad. The text on the bottom of the ad is a short summary of the

arguments. The toothpaste ads are very similar, and the manipulations have been carried out in the

same way.

The endorser of the tablets in the high believable ad is an electronics sales person, recognizable for a

white shirt and neat tie. In the low believable ad, the endorser has an uncommon suit for its product

category, the suit is loosely fashioned, and he does not wear a tie. Also, the facial appearance of the

person is less neat. The endorser of the high believable toothpaste ad is a dentist (wearing white coat,

neat tie and carrying experiment data, is chosen as a credible source for the advertisement. The low

believable ad is endorsed by a businessman, wearing a loosely fashioned suit, and cannot be associated


33

to be a credible source for toothpaste affairs. In the survey, respondents are asked to rate the

believability of the endorsers, to affirm whether or not they have been chosen appropriately.

Figure 2: Depiction of the four ads used in the surveys

3.5 Procedure

On the internet, the respondents filled out a survey that is completely depicted in the appendix

(appendix D-2). The questions of the group 1 (version of the believable tablet ad) are included; the other

versions are the same, with a different ad, and tablet questions have been replaced by toothpaste

questions.

The respondents were shortly introduced to the cause (graduation research) and the goal of the

questionnaire (rating a product, on the basis of a printed advertisement). After filling in demographic

information (question 1 & 2), respondents indicated their brand preference of either toothpaste or

tablets (depending on what version of the questionnaire they have received) and indicated how risky

the product (category) is to them. Brand preference was chosen out of 6 (tablet) or 7 (toothpaste) listed

alternatives, and an option to choose ‘different’. These questions have all been completed without

viewing the ad, so brand preference and perceived product risk is predetermined and not influenced by

the ad. The sponsoring brand (Parodontax or Samsung) and the comparison brand (Oral-B or Apple)

have been placed in the middle of the list (place 3 and 5 respectively). This prevents the data to be


34

biased strongly, because respondents mainly choose the first or last brand on the list, the primacy and

recency effect (Cooper and Schindler, 2006).

After these questions, the respondents opened the next page, and saw either a believable or

unbelievable advertisement, for either toothpaste of Parodontax or a tablet of Samsung, depending on

the group that the respondent is randomly assigned to. After this, respondents were asked if they have

seen the advertising before (question 5), and indicated how involved they are with the product

(question 6). The fifth question is asked to increase the realism of the ad, the sixth question is asked to

measure the degree of involvement in the product category. Subsequently, the last six questions were

asked about the sponsoring brand, concerning the following:

- Attitude toward the brand

- Purchase intentions

- Ad believability

- Argument credibility

- Endorser credibility

These constructs are measured by three or four statements, or by bipolar adjectives, on a Likert scale of

1 – 5. The Likert scale is a frequently used summated rating scale, that consists of statements that

express a favorable or unfavorable attitude toward the object of interest (Cooper and Schindler, 2006).

The questions used to measure these constructs can be seen in appendix D-2. As can be seen, the

questionnaire used was relatively very short, which diminished the chance that respondents were

confronted with fatigue, disinterest or time pressure. This contributes to the reliability of the results.

The questions about argument credibility and endorser credibility are not incorporated in the

conceptual model (figure 1). These constructs are measured to check the manipulations (endorser

credibility and argument credibility should differ due to the made manipulations).

3.4 Measurement

3.4.1 Measurement of constructs

The constructs used in the statistical models are intangible, and measured with several questions, which

is a common practice in social and business studies. It is important that the construct validity and

reliability is high. Construct validity is whether you are measuring the ‘right’ construct with the

appropriate questions, and construct reliability is whether the measurement is consistent to other

respondents and for other questions (Cooper & Schindler, 2006). Research must be based on solid

measured constructs, if a researcher intends to draw conclusions on the data. The questions asked in


35

the survey have all been based on previous research, and are well-accepted questions for assessing

people’ attitudes for these particular constructs. In table 6 can be seen on what research the questions

are based.

Construct Questions derived from article

Perceived risk Grewal et al, 1994;

DelVecchio and Smith, 2005;

Harmon and Coney, 1982

Involvement Laroche et al, 2010

Brand attitude Zhang, 1996

Miniard et al, 1993

Purchase intentions Miniard et al, 1993

Believability Okazaki et al, 2010

Argument believability Okazaki et al, 2010

Endorser believability Okazaki et al, 2010

Counterarguments Harmon and Coney, 1982

Table 6: Origins of the used questions in the questionnaire

Furthermore, the statistical test reliability analysis assesses the internal consistency of several questions

that form one construct. The statistical test checks whether the response of several questions

correlates, and gives a measure of internal consistency with a Cronbach’s Alpha. The Cronbach’s alpha is

widely used in social sciences, business and other disciplines, to measure if the construct (e.g. perceived

risk) is measured using the appropriate questions (Devellis, 1991). The Cronbach’s alpha is an indicator

of the internal reliability, but not a hard measure that is used to reject certain items. Generally,

constructs are well measured with an alpha higher than 0,8, acceptable with an alpha higher than 0,6,

and doubtful with an alpha lower than 0,6. Conclusions in a study based on constructs with doubtful

Cronbach’s alpha’s are not well-grounded (Malhotra, 2010). In this study, Cronbach’s alpha of higher

than 0,8 is good, higher than 0,6 is accepted, and lower than 0,6 is questionable, an explanation should

be found for the low Cronbach’s alpha.

In the design of the advertisements, the variables ‘product risk’ and ‘believability’ are both

dichotomous, which means that there are only two values; 0 or 1 (Cooper and Schindler, 2006). Product

risk is incorporated in the ad designs, but the construct perceived product risk is used in the statistical

models. The dichotomous believability variable (designed to be high or low), is solely used for

hypothesis 6. The last dichotomous variable, brand preference for comparison brand or not (0 = no, 1 =

yes) is used in the statistical models. Due to the intangibility of constructs, it is harder to measure than


36

objective variables. In research, constructs are generally measured by several carefully selected

questions, drafted by respected researchers. In this study, the constructs are measured the same, based

on questions of previous researches. The constructs involvement, ad believability, attitude toward the

ad and purchase intentions, are measured on a 5 point Likert scale. In these questions, ‘5’ is coded as

the positive value, and ‘1’ is coded as the negative value. All constructs also contain a question that is

inversely coded (1 is the positive value and 5 is the negative value), to check for abnormalities. In

processing these constructs, the negative formulated questions are recoded to be similar as the positive

formulated questions. The values of the constructs are calculated by using the average of the responses

to the questions (Zhang, 1996). So for example, the value of a respondent for the construct perceived

risk is the average of his score on the three questions. In the statistical models, product risk and ad

believability are not the nominal variables by which the respondents are influenced (different products

for product risk, and high or low effort to achieve ad believability), but the interval variables, as outcome

of the questions on perceived product risk and ad believability. Because perceived product risk and ad

believability are subjective constructs, it is more useful to utilize the ratings of the respondents than the

arbitrary nominal division of the researcher. However, it will be checked whether the nominal variables

collide or agree with the interval variables. Interval scales have the power of nominal and ordinal data

(for instance, allowing the researcher to check for differences in chi-square), plus the additional strength

that it incorporates the concept of equality of interval (scaled distance between 1 and 2 equals the

distance between 2 and 3), which allows the researcher to execute statistically more power tests (like

comparing means, standard deviation, correlation, regression or analysis of variance). It is generally

accepted that researchers treat any attitude scale (like brand attitudes) as interval (Cooper and

Schindler, 2006).

Furthermore, an almost infinite number of extraneous variables exist, that might conceivably affect the

relations of IV’s and DV’s. Most of these variables have very little effect, or the impact occurs randomly.

For example, changes of peoples’ mood, or short-term changes in weather can have some effect, but

occur too randomly to take into account. If all possible variables are taken into account, behavior can be

predicted perfectly. However, for consumer behavior, this is impossible and unnecessary. The r square

of a regression model, which is explained later on, is an indication of the percentage of explained brand

attitude (as a percentage of explained variance of the DV in the statistical model, due to the IV’s).

3.4.2 Statistical tests

The chi-square statistic is used to assess the goodness-of-fit of the sample on certain variables


37

(Malhotra, 2010). In this study, the commonly used Pearson’s chi-square statistic is utilized.

It has been stated that companies are interested in predicted how consumers react to advertisements.

Predicting how dependent variables (like brand attitude, purchase behavior) are being influenced by

individual variables is important for explaining consumer behavior. However, consumer behavior is

complex, and variables can interact or be influenced by other (latent) variables. Integrating numerous

variables in a regression analysis enables a research to assess (a) whether a variable contributes to the

current variables in explaining a dependent variable, (b) the extent to which the variable contributes in

explaining a dependent variable, and (c) the extent to which the variance of the dependent variable is

explained by all the variables incorporated in the model (r-square value).

Also, in comparison with simpler tests like ANOVA and T-tests, a regression analysis is superior in that it

also explains whether a relation is positive or negative, and the Beta values can be used to assess the

individual relative contribution of the variables. The ANOVA and T-tests can be used to assess

differences between groups. ANOVA is used to test means of two or more groups, comparing the

variances. The null hypothesis means that means are equal; a significance of 5% or lower means this

hypothesis can be rejected. Significant relations between variables are marked with a *.

Moreover, interactions between variables can really improve the insight in consumer behavior. For

example, two individual variables significantly influence a dependent variable. However, incorporating

both variables into one model shows that only one of the variables is really responsible for changes In

the dependent variable, diminishing the influence of the other IV. An even more complex situation

arises when two IV’s influence a DV, but by combining the influence of the IV’s, the direction and/or

strength of the relation with the DV is altered. In statistics, this is called an interaction effect.

In this study, the main research question is to assess the influence of ad believability on (1) brand

attitude and (2) purchase intentions, considering perceived risk and brand preference. To statistically

identify the relations, the variables are investigated in a linear model explaining brand attitude, and a

model explaining purchase intentions. So two regressions are carried out, because a regression is limited

to 1 DV.

In the regression model, perceived risk, brand preference and ad believability are regarded as IV’s, and

the moderating effect of perceived risk and brand preference is incorporated by multiplying the

variables with ad believability. Perceived risk and brand preference are incorporated as IV’s, even

though their direct effects on the DV’s is not hypothesized and unimportant (Cox, 1984). Omitting the

main effects of these variables would produce nonsensical models (Nelder, 1977).


38

The results and models have been calculated with SPSS (Statistical package for the social sciences). In

the statistical models that are employed on the basis of the variables, one dependent variable (either

brand attitude or purchase intentions) can be predicted by numerous independent variables. Even

though the constructs product risk and brand preference are in the theoretical model considered as

moderators, in the statistical models they serve as independent variables. With these models, the

significance, the strength and the direction of the relation between IV’s (independent variables) and

DV’s (dependent variables) can be calculated. Relations are determined to be significant at a significance

level of 5%, thus the 0 hypothesis is tested to be untrue with a confidence level of 95% or more.

The relation of the DV and IV’s is represented as:

Y = b0 + b1X1 + b2X2 + b3X3

where

b0 = intercept

b1X1 = linear effect of X1 (believability)

b2X2 = linear effect of X2 (product risk)

b3X3 = linear effect of X3 (brand preference)

However, interesting in this study is the moderating influence of product risk and brand preference, on

the relation of believability and dependent variables. The variables change the form of the relation

between the IV and the DV. For example, the switch to commission from a salary compensation system

(IV) will lead to increased sales productivity (DV) per worker, especially among younger workers (MV)

(Cooper and Schindler, 2006). This is statistically known as an interaction effect (Hair, Black, Babin,

Anderson, and Tatham, 2006). The moderator effects employed in these models are bilinear

moderators, in which the slope of the relationship of one independent variable changes across values of

the moderator variable. The moderator effect is represented as a compound variable, formed by

multiplying the IV by the moderating variable. This can be represented in the statistical model as:

Y = b0 + b1X1 + b2X2 + b3X3 + b4X1X2 + b5X1X3

where

b4X1X2 = moderator effect of product risk on the influence of believability on the DV’s

b5X1X3 = moderator effect of brand preference for comparison brand on the influence

of believability on the DV’s


39

To take all the variables, relations and scales into account, the models used to calculate the results are

generalized linear models (GLM). To determine whether the moderator effects are significant, three

steps are followed: (1) DV is predicted with the IV’s, (2) DV is predicted with IV’s and moderated

relations, (3) significance of the change in deviance is checked. With a significant change in deviance, the

moderating effect is kept into the model, without a significance of change in deviance, the moderator

effect is dropped from the model. This process is repeated for both moderating effects, and for both DV

models.

3.5 Manipulation Checks

In the advertisements, product risk and emphasizing believability are manipulated across the four

random groups. Perceived product risk is expected to be high in groups 2 and 4, where perceived

product risk is expected to be low in groups 1 and 3, as can be seen in table 2. This is checked, by

assessing the average that respondents rated for these constructs. Significant differences are expected

between the ratings of product risk for the ‘high risk groups’ and the ‘low risk groups’. Apart from

significant differences between the high and low product risk groups, it is expected that the average

perceived risk for groups 2 and 4 is generally high, and the average perceived risk for groups 1 and 3 is

generally low.

In the ads of group 1 and 2, there is a strong emphasis on the believability of the ad, where in group 3

and 4, this emphasis is not strong. Even though this is not critical for the statistical models on ad

believability (which is expected to be a normal distribution), it is important to determine the correctness

of the literature this study is based on. So, it is checked if the ad believability is higher for ads where the

emphasis is on believability, in comparison with the ads without an emphasis on believability. This is

checked by comparing the averages on ad believability for the both groups (group 1 and 2 with the

emphasis on believability, in comparison with group 3 and 4 without an emphasis on believability). The

same applies to the variable product risk. The values of the respondents’ ratings are compared with

expectations.

Also, in the last question respondents had room to make statements about the ad they have seen. This

gave the respondents the opportunity to react positively or negatively toward the ad. The responses are

recoded, to list the amount of negative (counterarguing) responses to the advertising claims.


40

3.6 Sample and construct descriptive statistics

3.6.1 Sample description

Of the respondents, over 95% is aged between 20 and 30 years old. Furthermore, the sample consists of

96 males and 75 females. 4 respondents are younger than 20 and 3 people are older than 30; these

respondents are included in the sample. To check if the composition of groups concerning gender and

age is tolerable, a chi-square test is appropriate. The Pearsons Chi-square of 0,413 confirms that there

are no significant differences among the groups concerning gender. The average age is in all groups 24,

and is equally distributed over the 4 groups, as is confirmed by the Pearson Chi-square of 0,252. A Chi-

square smaller than 0,05 would indicate that the groups are not statistically random concerning age or

gender.

Figure 3: Distribution of gender among the four groups

Figure 4: Distribution of age Figure 5: Distribution of age among the four groups


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3.6.2 Testing the construct validity

Seven important constructs have been measured in the survey, based on three or four questions. As can

be seen in appendix A-3, all constructs are reliable of an acceptable Cronbach’s alpha level (0,6 or

higher), and, apart from perceived risk, the constructs are of a very reliable level (0,8 or higher). All

constructs have thus been measured using the proper questions, and are useful for interpretation.


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4. Results

In this part, the results of the surveys are spelled out. The methods of attaining the results have been

explained in the previous methodology. The results are shortly explained, but not discussed in detail. In

the conclusion chapter, the results are extensively discussed and linked to the literature and

hypotheses.

4.1 Main descriptive statistics

Primarily, it is important to check what the differences are between the four groups concerning product

risk and ad believability. It is expected that group 1 & 2 (tablet) score higher on product risk than group

3 & 4 (toothpaste). Furthermore, it is expected that group 1 & 3 (high believable ad design) score higher

on ad believability than group 2 & 4 (low believable design).

As can be seen in figure 6, the consumer’ perceived risk of

the tablet groups is considerably higher than of the

toothpaste groups. According to Levene’s test, the

variances differ significantly (sig = 0,039), and a two-tailed

independent t-test shows that the means differ significantly

as well (sig = 0,000).

Figure 6: means of perceived risk of tablet and toothpaste groups

Figure 7 shows the means of ad believability, brand attitudes and purchase intentions for the groups

with high believability design and low believability design. It is expected and desirable that the high

believability design provides higher scores on these three variables. Levene’s test of ad believability

shows that the variances of the high believable design groups (group 1 & 3) and low believable design

groups (group 2 & 4) do not differ significantly (sig = 0,989), but the independent sample T-test shows

that the differences in means (2,95 and 2,56) are significantly different (sig = 0,007). Subsequently,

Levene’s test shows that the variances of brand attitudes do not differ across the groups (sig = 0,328),

where the variances of purchase intentions do differ across the groups (sig = 0,006). More importantly,

the means of brand attitudes and purchase intentions do differ significantly (sig = 0,001 and 0,002

respectively), in favor of the high believable design groups, as can also be seen in figure 7. An overview

of the means of all constructs can be found in appendix B-1.

Also, The variances of perceived risk and involvement are equal (sig = 0,759 and 0,109 respectively,

accepting h0), according to Levene’s test, as can be seen in table 17 below. A T-test comparing the


43

means of perceived risk and involvement shows that these means are not significantly different (sig =

0,445 and 0,514 respectively), which is expected.

Figure 7: means of ad believability, brand attitudes and purchase intentions

The means of the previous mentioned variables ad believability, brand attitudes and purchase intentions

can be seen for the four groups in figure 8 below. This figure confirms that the means of both high

believable groups, for both product groups are higher. Furthermore, it can be seen that ad believability

is fairly similar for tablets and toothpaste, but brand attitudes are more positive for tablets, and

purchase intentions are more positive for toothpaste (figure 8, appendix B-1).

Figure 8: Means of constructs of four groups

Figure 8 indicates that the results of toothpaste and tablets are not entirely similar. A sharpened glance

on the results shows that ad believability does not significantly differ (sig = 0,197) when only the tablet

groups are taken into account, as can be seen in appendix B-2. Brand attitudes are significantly higher

for the high believable group (sig = 0,009), but purchase intentions do not differ significantly (sig =

0,067).

Concerning the toothpaste groups (group 3 & 4), differences in means are more apparent. Ad

believability is significantly higher for the high believable group (sig = 0,016), but brand attitudes and

purchase intentions are also significantly higher for this group (sig = 0,023 and 0,013 respectively), as


44

can be seen in appendix B-3. An overview of the means of all measured constructs of the four groups,

can be seen in appendix B-11

4.2 Results of main hypothesis

The first and central hypothesis concerns the influence of ad believability on brand attitude and

purchase intentions (H1, conceptual model figure 1). Brand attitude, as main dependent variable in this

study, is first described. A t-test can indicate a relation between the IV and DV. However, a regression

analysis also provides the slope of the relation and whether it is positive or negative. The results of the

linear regression model of brand attitude can be seen in table 7.

R square of the model (0,403) means that 40,3% of the variance in the model of brand attitudes is

explained by ad believability. Furthermore, the associated ANOVA confirms that the variance of the IV’s

significantly explain the variance of brand attitude (sig = 0,000, appendix B-4). Very interesting results

can be seen in table 7 below. It displays that brand attitude is significantly influenced by ad believability

(sig = 0,000), with a positive beta of 0,642. This beta implies that a change of 1 of ad believability, is

expected to change brand attitude with 0,642. Hence, an increase of ad believability will increase brand

attitude.

Hypothesis 1a is accepted

Unstandardized

Beta

Standardized

Beta

Significance

(Constant) 1,277 0,000

Ad Believability 0,642 0,635 0,000*

Table 7: Basic linear regression of brand attitude

Next, the results of the linear regression model of purchase intentions are described. R square of the

model (0,140) means that 14,0% of the variance in the model of purchase intentions is explained by ad

believability, as can be seen in appendix B-4. The influence of ad believability on purchase intentions is

marginal, compared to the influence of ad believability on brand attitudes. The associated ANOVA

confirms that the variance of the IV significantly explains the variance of purchase intentions (sig =

0,000). The beta of 0,381, with a significance of 0,000, shows that ad believability has a positive

influence on purchase intentions (table 8). The beta implies that a change of 1 of ad believability, is

expected to change purchase intentions with 0,374. Hence, an increase of ad believability will increase

purchase intentions.


45

Unstandardized

Beta

Standardized

Beta

Significance

(Constant) 1,320 0,000


Table 8: Basic linear regression model of purchase intentions

Hypothesis 1b is accepted

Both hypothesis 1a as hypothesis 1b are significantly accepted, and therefore, the main relation in the

conceptual model (expected positive influence of ad believability in comparative advertising on brand

attitudes and purchase intentions) is determined.

4.3 Results concerning moderating effects

4.3.1 Perceived product risk and brand preference for comparison brand modeled

Incorporating the moderating effects into the model provides insight in how the influence of ad

believability on both brand attitudes as purchase intentions, is altered by perceived risk and brand

preference for the comparison brand.

In the model of brand attitudes has an R square of 0,449, which implies that 44,9% of the variance is

explained by the IVs and the two interactions of ad believability with the moderators. Also of interest, is

that the adjusted R square has increased from 0,399 to 0,432 (appendix B-4 and B-5). Since adding

variables can always randomly explain some variance, the adjusted R square indicates whether adding a

variable is useful in explaining the DV or not, thus giving a measure of the improvement of the model.

The adjusted R square confirms that adding the moderating relations increase the power of the

regression model (by 3,3%). The significance value of the ANOVA of 0,000 (appendix B-5) implies that

the IV and moderators significantly explain the variance of brand attitude.

Looking at the individual influence of the variables, as can be seen in table 8, some interesting figures

can be seen. The influence of ad believability on brand attitudes is significant and positive (sig = 0,012),

with a beta of 0,621 and standardized beta of 0,614. The IV perceived risk has a significant negative

relation with brand attitude (beta of -0,372, significance of 0,023), and respondents preferring the

comparison brand tend to have lower brand attitudes, indicated by the positive relation (beta of 0,461

and standardized beta of 0,234), however, this relation is not significant (sig = 0,183). In this model, the

dichotomous variable brand preference is coded as 0 = comparison brand, 1 = not comparison brand.

Concerning the moderators, both effects seem to strengthen the influence of ad believability (with

respective betas of 0,150 and 0,218, and standardized betas of 0,555 and 0,417 respectively). The


46

moderator effect of perceived risk has a significance value of 0,007, which means that the influence of

ad believability is strengthened by perceived risk. Under conditions of high perceived risk, the influence

of ad believability on brand attitudes is stronger, and under conditions of low perceived risk, the

influence of ad believability on brand attitudes is weaker.

The significance value for the moderator effect of brand preference for the comparison brand on ad

believability-brand attitudes is not significant (sig = 0,069). A relation seems to exist, but by this data, it

cannot be supported. It is possible that the effect of perceived product risk-ad believability is so strong,

that the moderator comparison brand preference-ad believability is overshadowed to some extent. The

results can be seen in table 9 below.

Unstandardized

Beta

Standardized

Beta

Significance

(Constant) 1,481 0,000


Perceived risk -0,372 -0,372 0,023*

Brand preference 0,461 0,234 0,183

Mod risk/believability 0,150 0,555 0,007*

Mod brand/believability -0,218 -0,492 0,069

Table 9: Linear regression model including moderating effects

Hypothesis 2a is accepted.

Hypothesis 3a is not accepted, due to a significance value of 0,069. However, a relation is indicated by

these figures.

In table 10 below, the linear regression model of purchase intentions with the inclusion of the

moderators can be seen. The r square of the model is 0,148, which is very disappointing, meaning that

approximately 85% of the variance must be attributed to other variables than those included. The

adjusted r square of 0,122 is actually lower than the adjusted r square of the model that solely

measured the influence of ad believability on purchase intentions. So the minor improvement of the r

square (0,148 in comparison with 0,140) must be attributed to increased insights based on random

influence of variables (appendix B-5). The ANOVA significance value (sig = 0,000) does determine that

the variance of purchase intentions are significantly being explained by this model. In table 10 below can

be seen that no variable or moderator is significantly influencing purchase intentions. Therefore, the

betas and standardized betas have little predicting value. This leads to the conclusion that purchase

intentions are influence by different, more important variables.


47

Unstandardized

Beta

Standardized

Beta

Significance

(Constant) 1,478 0,098

Ad Believability 0,301 0,295 0,329

Perceived risk -0,153 -0,152 0,452


Mod risk/believability 0,039 0,142 0,577

Mod brand/believability -0,017 -0,039 0,908

Table 10: Linear regression model of purchase intentions including moderators

Hypothesis 2b is rejected

Hypothesis 3b is rejected

Altogether, inferences concerning hypothesis 2 and hypothesis 3 can be made. The influence of ad

believability on brand attitudes is significantly strengthened by perceived product risk (sig = 0,007), but

the same does not account for purchase intentions (sig = 0,577).

In conclusion, hypothesis 2 is partially accepted

Moreover, the influence of ad believability on brand attitudes is not significantly moderated by

comparison brand preference (sig = 0,069), and the moderating effect on purchase intentions is also not

significantly determined (sig = 0,908).

In conclusion, hypothesis 3 is rejected

4.3.2 Alternative model explaining purchase intentions

As stated, the explanatory value of the model for purchase intentions is very low. Literature suggested

that other variables, including involvement and brand attitudes, are essential for creating purchase

intentions. To get insight in the variables that can be used in explaining purchase intentions, a regression

including all variables that have been measured (perceived risk, brand preference for the comparison

brand with 2 groups , ad believability, and the addition of involvement) is calculated. The results can be

seen in appendix B-5 and appendix B-6. The R Square of the model is 0,174, and the adjusted R square is

0,154 with ANOVA significance of 0,000 (appendix B-6). This is an improvement of the old model, but

the model can still become more predictive when brand attitudes are included.

Brand attitude is considered to be a dependent variable in this study, but the exclusion of it can be a

cause of the poor value of the current models. Also, brand attitudes are generally confirmed to be a


48

major predictor of purchase intentions (Grewal and Kavanoor, 1997). When brand attitudes is included

as an independent variable, the R square of the model is 0,287, meaning that 28,7% of the variance of

purchase intentions is explained by the variables used. This is significantly better than the 14,8% of the

hypothesized model, meaning that purchase intentions can be better explained and predicted using this

model. Also when taking explaining random variance into account with the adjusted R square, the model

is still improved from 13,5% to 26,6% (appendix B-4 and appendix B-6).

A closer look at the variables, as can be seen in appendix B-7, shows that the variable ‘perceived risk’ is

not useful for explaining purchase intentions (sig = 0,894, with a beta of -0,009). Ad believability explains

14% of the variance of purchase intentions in a one-on-one relationship, however, in this extensive

model, the influence is not significant (sig = 0,276). Its influence is possibly overlapping with other

variables like brand attitude, which leads to multicollinearity. The adjusted r square (0,270) is optimal

when ad believability, brand preference for the comparison brand, involvement and brand attitudes are

included. Dropping ad believability and/or comparison brand preference causes the adjusted r square to

diminish. The adjusted, optimal linear regression model can be seen in table 11. Brand attitudes are the

best predictor of purchase intentions (standardized beta of 0,442, significance of 0,000), involvement is

also an important predictor (standardized beta of 0,228, significance of 0,001), where ad believability

and brand preference for the comparison brand are not significant and have low standardized betas

(0,095 and 0,075 respectively). In conclusion, this model is superior and significantly predicting purchase

intentions, but the model lacks considerable power compared to the model predicting brand attitudes.

Unstandardized

Beta

Standardized

Beta

Significance

(Constant) -0,198 0,590



Involvement 0,217 0,228 0,001*

Brand attitudes 0,446 0,442 0,000*

Table 11: Revised linear regression model of purchase intentions

4.4 The influence of brand preference on ad believability

Respondents who do not prefer the comparison brand (not the Apple Ipad, or Oral-B toothpaste), 101

respondents, generally rate the ad believability 2,88 on a 5-point Likert scale (see figure 9 and appendix

B-8). Respondents who prefer the comparison brand, 70 respondents, generally rate the ad believability

2,59. An independent T-test reveals that the variances are equal, according to Levene’s test for equality of


49

variances. With equal variances, the T-test reveals that an influence of comparative brand preference on

ad believability cannot be supported significantly (sig = 0,051, which is just above the 0,05 margin).

Figure 9: Ad believability means of respondents preferring comparison brand or not comparison brand

Hypothesis 4 is rejected

4.5 Manipulation check

In this part, it is checked to what extend the manipulations in the ads had the desired effect on the

respondents’ response. Apart from perceived product risk, ads were created to be contain high or low

ad believability, based on literature recommendations. In the survey (appendix D-2), respondents were

asked to rate the credibility of the endorser, and the credibility of the arguments that were presented in

the ad. Presenting expert and trustworthy endorsers is an example of establishing credible sources

(chapter 2.4.2), and argument credibility can increase by utilizing two-sided messages (chapter 2.4.1)

and substantiating advertising claims (chapter 2.4.3). The endorser should be more credible for groups 1

& 3 (see table 4), and argument credibility should be higher, in comparison with groups 2 & 4.

As can be seen in appendix B-9, both models of endorser credibility and argument credibility have

significant ANOVA values (0,000 and 0,000), with respective r square values of 0,148 and 0,767, which

determines that argument credibility is far more important than endorser credibility in predicting ad

believability. The model that incorporates both variables has an r square of 0,767 (equal to the r square

of argument quality alone), but the adjusted r square is slightly lower than the model that solely

incorporates argument credibility. The values of the variables show that both variables have a positive

relation with ad believability (appendix B-10), with significant values (0,000 and 0,000). The beta of

argument credibility (beta = 0,834) is again considerably higher than the beta of endorser credibility

(beta = 0,386). When both variables are incorporated in one model, the variable endorser credibility

becomes negative (beta = -0,17) and not significant (sig = 0,781). This demonstrates that argument

believability is definitely the best predictor of ad believability, out of these two measured constructs.


50

5. Conclusions and recommendations

In this final chapter, the results are being discussed and placed in perspective with the associated

literature. Subsequently, implications of the most important findings are explained. Finally limitations

this study was confined to are summed up, and directions for future research, improving comprehension

on this subject, are given.

5.1 Discussion of results

This study was mainly designed to provide a clear overview of the influence of ad believability on the

formation of brand attitudes, incorporating moderating influence of perceived product risk and brand

preference, in comparative advertising. Furthermore, relations of the same variables have been

investigated with respect to purchase intentions.

First of all, the results of the pretest and actual experimental survey differed considerably concerning

perceived risk ratings. The average rating of product risk in the pretest for toothpaste was 1,63, and in

the survey the average rating was 1,98. The average rating of product risk in the pretest for tablets was

4,28, and in the survey the average rating was 2,97. Hence, the pretest showed more extreme results.

This can be explained by the fact that respondents compared four products in the pretest (both risky

and not risky products), where in the survey the respondents had to rate one product, without any

knowledge of other products. So in the pretest, a within respondents test provided the results, where in

the survey a between respondents test provided the results. Also, the sample of the pretest (10

respondents) was small, so the reliability of such results is lower. However, the results are usable

enough to interpret differences between more risky and less risky products. It can be concluded that the

respondents agreed that toothpaste is a low risk product, and tablets are high(er) risk product).

As was expected, ad believability is of significant importance in creating favorable brand attitudes. The

regression model showed that an increase of ad believability of 1%, resulted in an increase of 0,64% in

brand attitudes. This confirms Swinyard’ model, that higher believability is of major influence on brand

attitudes in comparative advertising. Purchase intentions were modeled equally, and the linear

regression model showed that ad believability is also of considerable influence on purchase intentions in

comparative advertising. An increase in ad believability of 1% results in an increase of 0,38% in purchase

intentions. The influence is much weaker than the influence on brand attitudes, but this can be

explained. The formation of brand attitudes occurs earlier in the buying process than creating purchase


51

intentions. Also, favorable brand attitudes generally are a requisite in forming purchase intentions, but

one does not need purchase intentions to form favorable brand attitudes.

An integral model incorporating numerous variables and interaction effects, better assesses causality in

a model however. An integral model covering both moderating effects showed that perceived risk has a

positive influence on the relation between ad believability and brand attitudes, and brand preference

for the comparison brand has a negative influence on the relation between ad believability and brand

attitudes, as was suggested in literature. However, the moderating influence of brand preference for

the comparison brand is not significant, and therefore, the influence cannot be ascertained. Perceived

product risk does significantly moderate the relation between ad believability and brand attitudes.

Especially when consumers perceive a product to be risky, ad believability is necessary to create

favorable brand attitudes. This corresponds with literature, that consumers judging risky situations or

products can be effectively reassured by believable cues.

Concerning purchase intentions, no significant influence of the moderators was found. The moderator

perceived risk has a small positive beta, and the moderator comparison brand preference has a small

negative beta, but both without sufficient significant values. Upon these figures, it can be concluded

that purchase intentions are not best explained by incorporating these specific variables.

Theory found that involvement and brand attitudes are better predictors of purchase intentions, and a

revised model confirmed the theory. Brand attitudes proved to be the best predictor of purchase

intentions, improving purchase intentions by 0,42% for every percentage of brand attitude

improvement. Involvement is the second best predictor of purchase intentions, and its effect is

significantly supported. Other variables (ad believability, perceived risk, brand preference for the

comparison brand) have no significant influence in this model. An important conclusion is that

purchase intentions are more difficult to model than brand attitudes, especially on the basis of an

advertisement. Also, as is described in current literature, other factors play an important role.

Involvement in a product (category) is a requisite for people to consider purchasing a product. Most

importantly, chances of purchasing a product greatly improve when people favor a brand. The results in

this study confirm that brand attitudes are the most important, confirm that involvement is a requisite

in purchase intentions, and indicate that ad believability is of added value, but not a decisive variable.

The value of ad believability is better represented in creating favorable brand attitudes, than for

explaining purchase intentions.


52

Furthermore, in this study it is not confirmed that people who prefer the brand that is used as a

comparison brand, perceive the ad to be less believable. There are strong indications that there is a

negative relation; this study shows a significance value of 0,051, which is slightly too high to confirm the

hypothesis. It is important information, because very often, the brand of the market leader is used as a

comparison ad. It seems disadvantageous if a large group of consumers perceive the ad to be less

believable, due to their brand preference. It is unlikely that firms intend to advertise a product that is

disliked by the major group of consumers, by comparing its product to the leading brand. In conclusion,

there are strong indications for a direct relation, but further research is necessary.

Subsequently, the factors that are mentioned in literature to be most important for increasing ad

believability (message sidedness, source credibility and claim substantiation), and used as manipulations

to influence ad believability, did significantly increase the ad believability. The ad believability was not

excessively low or high in any group, but this is explained because the differences between all the ads

were marginal. In designing a genuine ad, that is looked at by real customers in normal situations, ad

believability is likely to vary more. An ad that is designed professionally, and placed in the real context

(for example a magazine), and not interpreted in a survey, with a student as its source, is in all likelihood

interpreted in a different manner. Ad believability may be even more important in such an

advertisement, because its believability is less in doubt.

It must also be mentioned that the differences in ad believability for the tablet ads are not significantly

different. The endorser believability manipulation check does show significant differences, but the

argument believability manipulation check does not, as well as the ad believability. This implies that the

ads have not been designed in such a way, the arguing differences particularly, that the ‘high believable

ad’ produces significantly higher ad believability. Also, a larger sample might have delivered evidence for

significant ad believability improvements in these groups. The results of the toothpaste ads concerning

ad believability do differ significantly, so the arguing is presumably better designed. Overall, the results

of the high believable groups differ significantly of the low believable groups (2,95 on the 5-point Likert

scale versus 2,56). So view all the results, the manipulations have been successful, especially for the

toothpaste ads.

5.2 Conclusions

Based upon the results of this study, it can be concluded that in comparative advertisements, ad

believability is a major influence of brand attitudes and purchase intentions, as was hypothesized by

research of for example Grewal and Kavanoorm and Swinyard. Subsequently, this study determines the


53

moderating influence of perceived product risk on the relation of ad believability and brand attitudes

and purchase intentions. Previous research generally focused on differences between comparative

advertising and noncomparative advertising, but in specific comparative advertising literature, this

effect has not been incorporated. The validation of this relation is therefore an important addition to

current literature on comparative advertising.

Also, this study provided indications of a moderating influence of brand preference for the comparison

brand, on the relation of ad believability and brand attitudes and purchase intentions, in comparative

advertising. Although the influence was not significantly supported by the data of this study, indications

for a negative relation are present in this study.

Furthermore, the negative influence of brand preference for the comparison brand on ad believability

has not been established in this study, but strong indications exist.

Subsequently, as is suggested by the models of involvement of Petty and Cacioppo, comparative

advertising is potentially more effective than noncomparative advertising. The main advantages are that

attitudes that are being formed are more enduring and that purchasing behavior is more predictive.

Effects of adequately designed advertising campaigns are thus lasting longer, and the marketing division

can better predict results, which is making the advertising campaign more accountable. Also, this study

has a limited design, with limited resources, but the results for improving advertising effectiveness are

substantial. That should be evidence to large firms that such research can be used to optimize

advertising campaigns, and it should encourage more research to increase understanding of consumer

behavior.

Finally, taking the conclusions in consideration, the proposed research question can be answered. The

influence of believability in comparative ads on brand attitudes and purchase intentions is considerable.

Perceived (financial or performance) product risk is an important variable to incorporate in the

predicting models. To consumers, high risk products require an advertisement that is designed with a

high believable message, in order to create favorable brand attitudes and purchase intentions. Low risk

products also benefit from ad believability, but it is far less important for persuading consumers. In this

study, it is not established that brand preference for the comparison brand has a negative influence on

the formation of favorable brand attitudes and purchase intentions. However, this might be explained

because this study used a relative small sample in comparison with the target group, to draw definite

conclusions. Also, purchase intentions are less influenced by ads than brand attitudes. As current

literature describes, attitudes toward the ad are primarily influenced, subsequently, brand attitudes are


54

formed (though this process is different than for noncomparative, traditional advertising), and after

brand attitudes, purchase intentions are formed. So although the influence on purchase intentions are

smaller than for brand attitudes, and although brand preference for the comparison brand has not

been proven to be of major importance in the model, these are factors to take into account, and are

likely to influence advertising success.

An overview of the hypotheses that have been accepted or rejected can be seen in table 12 below. It is

important to mention that rejecting a hypothesis in this study, does not mean that this is evidence that

no relation exists. On the contrary, relations are conceivable, but not determined in this study.

Hypothesis 1

Believability in CA positively influences brand attitudes / purchase intentions

Accepted

Hypothesis 2

The influence of believability on brand attitude / purchase intentions is

strengthened by perceived product risk

Partially accepted

Hypothesis 3

The influence of believability on brand attitudes / purchase intentions is

stronger for consumers who do not prefer the comparison brand, and

weaker for consumers who prefer the comparison brand

Rejected

Hypothesis 4

Brand preference for the comparison brand has a negative influence on ad

believability

Rejected

Table 12: Summary of hypotheses of this study

5.3 Managerial implications

Academic research can be used for firms in making strategic and tactical choices concerning their

brand(s) in the market. It provides models and theories that can be applied, to improve the results of,

for example, marketing campaigns. This study is designed to enhance the current understanding of

comparative advertising, and ad believability in comparative advertising in particular. There is an

abundance of literature investigating advantages and disadvantages of comparative advertising versus

noncomparative advertising. This research mainly focusses on aspects of implementation of

comparative advertising, and is most useful for firms that have decided to utilize this form of

advertising.

Certain recommendations of previous research can be incorporated in the implications of this study.

Comparative advertising is not suitable for any firm or purpose. It must be aligned with the goals of a

firm. Considering Lavidge and Steiner’s advertising objectives, comparative advertising has negative

effects on attitudes toward the advertisement, people generally dislike this type of advertising.

Literature shows that brand attitudes, on the contrary, are generally more positive for comparative

advertising than for noncomparative advertising. This study showed that given comparative advertising,


55

ad believability is of major importance to positively influence brand attitudes. So a company that utilizes

this type of advertising, and aims at improving brand attitudes, should consider the ad believability, and

sources to improve the ad believability (like message sidedness, source credibility, claim substantiation,

intensity of the ads). This study found that two-sided messages, credible sources, and substantiated

claims result in more believable advertisements to consumers, than ads that contain one-sided

messages, have less credible sources, and that do not substantiate advertising claims. Furthermore,

investigating whether or not the product of a firm is considered to be risky in this context is very

important. Especially products that are perceived to bear (financial and performance) risks, benefit from

increased ad believability. This relation has not been established in current literature on comparative

advertising, but is very important to firms that develop ads. Assessing their own products, how risky the

products are perceived by the target group, can significantly increase the advertising effectiveness.

Considering the amount of resources that are put into an advertising campaign, and the effects a

successful campaign has to a firm, improvements in brand attitudes and purchase intentions of several

percentages, based on recommendations of research, can make an immense difference.

Moreover, a firm should consider what group of consumers they want to target with the comparative

ad. In this study it is indicated that in general, people with a brand preference for the brand that is used

as a comparison, dislike the ad and also perceive the believability of the ad to be more negative, than

people who do not prefer the comparison brand. If the group of consumers who prefers the comparison

brand is substantial, it may not always be wise to use this type of advertising, or to use that specific

brand as comparison. At this point, the conclusions are still indicative, but are important for firms to

consider whether or not to use comparative ads, and in what way the ads should be designed. In the

market for tablets in the Netherlands for example, Apple is the market leader with over 90% of market

share; utilizing comparative ads with the intention to increase one’s market share (at the cost of the

market leader), might not be fruitful if this group of consumers dislikes the ads and questions the

believability of the ad and arguments.

Purchase intentions are, in accordance with current literature, mainly explained by brand attitudes.

Brand attitudes are not a direct factor that can be manipulated by a firm, so when this advertising

objective is formulated, a firm should realize its complexity. Purchase intentions depend on the

involvement of a person, and also for a minor part to ad believability. When increasing purchase

intentions is the main advertising goal, a firm should focus on improving brand attitudes, encouraging

involvement in the product and product category, and design an ad with an adequate level of

believability (which is especially important for creating favorable brand attitudes).


56

In designing an ad that incorporates high believability, advertisers should prevent the ad from becoming

too hostile and aggressive. Preferably, the comparative ad should contain two-sided messages, inhibit

high source credibility and claims ought to be substantiated. This diminishes the hostility of the ad, and

the message is perceived to be more objectively truthful and supported by other trustworthy

authorities. When the comparative ad is designed correct with high believability, it should be superior in

creating favorable brand attitudes and encouraging purchase intentions.

5.4 Limitations and future research

This study contains several limitations that the study was confined to, and directions for further

research to enhance understanding of comparative advertising are given.

First of all, the ads that were designed for this study are not genuine, real-used ads, which diminishes

the reality of the subject for participants of the study. Ads by Samsung or Parodontax would be designed

more professionally, and product information would be displayed in a different manner. In reality, it

cannot be expected that consumers peruse an ad as intense as the respondents did for this research.

However, because all four ads were designed similar, differences in results could still be interpreted as

differences due to manipulations. So for research purposes, the design was appropriate, but actual

results of professional and authentically designed ads will be different.

Moreover, because two product categories were investigated, to incorporate differences in product risk,

the ads were designed very similarly, except from minor differences in color, product display, endorser

and arguments used. However, it is not clear whether both product categories are equally suitable for

the particular style of advertising that was utilized. Toothpaste ads regularly use the particular format,

but for tablets (or advances electronic products), this format is less standard. It may be that toothpaste

is better suitable for this type of advertising. This might have had an influence on the results of the

study, and actual implementations of firms should consider it. It is mentionable that the results of the

toothpaste ads were more convincing, and differences between the ads within this product category

differed more. However, it cannot be ascertained this was caused by better suitability in this product

category. In conclusion, it is conceivable that the conclusions drawn in this study are better applicable to

certain product categories than for other product categories. And other contingencies to the advertising

effectiveness of a comparative ad, based on ad believability, are conceivable and should be identified.

Also, future research must determine the exact influence of brand preference. This study was not

conclusive on the influence, although the results indicate that it plays a role in advertising effectiveness.

Subsequent to determining its influence, research should focus on mapping what position the


57

comparison brand can have in the market. For example, recommendations upon the market share of the

comparison brand (whether it should be very dominant or not) can aid companies in their decisions of

implementing this type of advertising.

Subsequently, in this study two product categories were tested, and data of 171 respondents have been

used. All inferences have thus been based on a small amount of product categories with a limited

sample. The sample almost exclusively consisted of students in the region of the city of Groningen. Such

a sample gives an indication of what the entire population looks like, but is too small to formulate

conclusive statements about the Dutch population concerning these issues. The reliability of the study

can be improved when the design is tested over more product categories, with different samples.

Another limitation is that in this study perceived product risk was defined as financial and/or

performance risk. The scope of this study would be too broad if all types of risks are included. However,

in literature, several other types of perceived risks have been identified and can influence judgment of a

respondent. Future research could identify how the model performs when different types of risks are

incorporated. Hence, the conclusions and implications of this study are limited to products inhibiting

financial and/or performance risks.

Furthermore, purchase intentions were explained by the same model as brand attitudes. Current

literature already indicates that purchase intentions are more complex, and the results of this study

confirm that the hypothesized model is not appropriate. Incorporating brand attitudes and involvement

of participants improved the model, but it can still be improved. Also, attitude toward the

advertisement is important in noncomparative advertising, but is not included in this study. Literature

on comparative advertising is inconclusive about the exact role of attitudes toward the ad, but further

research should increasing understanding.

Finally, the causality of the variables in the model is not tested. Respondents rated the believability,

brand attitudes and purchase intentions after being exposed to the ads. This study assumes that brand

attitudes are based on ad believability. However, it is also possible that higher brand attitudes lead to

higher perceived believability of the ad. Respondents might prefer the advertised brand, the type of

advertising, or other aspects, and subsequently also consider its believability to be higher. This aspect of

causality was not prevented in this study.


58

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7. Appendices Appendix A: Tables and figures in chapters 1 – 3

Construct Questions derived from article

Perceived risk Grewal et al, 1994;

DelVecchio and Smith, 2005;

Harmon and Coney, 1982

Involvement Laroche et al, 2010

Appendix A-1 : Origins of used questions in the pretest

Layout of text and pictorials

Visual effects used around product and arguments

Use of logos of other organizations

Use of checkmarks

Explicit question, comparing both products

Including product price

Brand name and logo of sponsoring brand

Brand name of comparison brand

Depiction of product advertised*

Endorser for product*

Subtext in ad*

* Slightly different, to fit product

Appendix A-2: Elements in all advertisements

# Questions Cronbach’s Alpha

Perceived Risk 3 0,671

Involvement 3 0,803

Endorser believability 3 0,904

Argument believability 4 0,844

Ad believability 4 0,869

Brand attitudes 4 0,908

Purchase Intentions 3 0,899

Appendix A-3: Cronbach’s alpha of reliability analysis


63

APPENDIX B: Tables of chapter 4

High believability (group 1 & 3)

Low believability (group 2 & 4)

Levene’s Test for equality of variances

T-test

Perceived Risk 2,38 2,50 0,759 0,445

Involvement 3,21 3,31 0,109 0,514

Argument believ. 3,02 2,68 0,509 0,019*

Endorser credibility 3,04 2,16 0,288 0,000*

Ad Believability 2,95 2,56 0,989 0,007*

Brand Attitudes 3,29 2,79 0,328 0,001*

Purchase Intentions 2,60 2,13 0,006* 0,002* Appendix B-1: Means of constructs for high believable and low believable groups

Group 1 Mean Group 2 Mean Levene’s Test for

equality of variances

T-test for equality

of means

Perceived Risk 2,87 3,07 0,131 0,335

Involvement 2,58 2,95 0,690 0,114

Argument believ. 2,99 2,68 0,361 0,177


Ad Believability 2,80 2,52 0,075 0,197

Brand Attitudes 3,48 2,85 0,269 0,009*

Purchase Intentions 2,47 2,06 0,028 0,067

Appendix B-2: Independent T-test of means of tablet products

Group 3 Mean Group 4 Mean Levene’s Test for

equality of variances

T-test for equality

of means

Perceived Risk 1,99 1,98 0,089 0,952

Involvement 3,73 3,64 0,938 0,614

Argument believ. 3,05 2,69 0,939 0,052


Ad Believability 3,08 2,60 0,051 0,016*

Brand Attitudes 3,14 2,73 0,724 0,023*

Purchase Intentions 2,70 2,20 0,044 0,013*

Appendix B-3: Independent T-test of means of toothpaste products


64

Brand attitudes

basic model

Purchase intentions

basic model

R Square 0,403 0,140

Adjusted R Square 0,399 0,135

ANOVA significance 0,000 0,000

Appendix B-4: main statistics of basic regression models of brand attitudes and purchase intentions

Brand attitudes

+ moderators

Purchase intentions

+ Moderators

R Square 0,449 0,148

Adjusted R Square 0,432 0,122

ANOVA significance 0,000 0,000

Appendix B-5: R square and ANOVA values of complete model of brand attitudes and purchase intentionsw

Basic model

+ involvement

Basic model + inv.

+ brand attitude

Model + inv. +

br. attitude - risk

R Square 0,174 0,287 0,287

Adjusted R Square 0,154 0,266 0,270

ANOVA significance 0,000 0,000 0,000

Appendix B-6: R square and ANOVA values of alternative purchase intentions model

Unstandardized

Beta

Standardized

Beta

Significance

(Constant) -0,164 0,718


Perceived risk -0,009 -0,009 0,894


Involvement 0,215 0,225 0,001*

Brand attitudes 0,446 0,442 0,000*

Appendix B-7: Alternative linear regression on purchase intentions, containing possible IV’s.

Ad believ. mean Levene’s test Means t-test

Respondents do not prefer comparison brand

2,88

Respondents prefer comparison brand

2,59

0,376

0,051*

Appendix B-8: Ad believability statistics for brand preference groups


65

Endorser cr. Argument cr. Both variables

R Square 0,148 0,767 0,767

Adjusted R Square 0,137 0,764 0,761

ANOVA significance 0,000 0,000 0,000

Appendix B-9: Linear regression statistics of endorser and argument credibility on ad believability

Unstandardized

Beta

Significance

(Constant) 1,747 0,000

Endorser cr. 0,386 0,000*

(Constant) 0,298 0,063

Argument cr. 0,834 0,000*

(Constant)

Endorser cr. 0,841 0,000*

Argument cr. -0,17 0,781

Appendix B-10: Betas and significance values of three regression models

Group 1 Group 2 Group 3 Group 4

Perceived Risk 2,87 3,07 1,99 1,98

Involvement 2,58 2,95 3,72 3,64

Argument believability 2,99 2,68 3,05 2,69

Endorser credibility 2,84 1,89 3,20 2,41

Ad Believability 2,80 2,52 3,08 2,60

Brand Attitudes 3,48 2,85 3,14 2,73

Purchase Intentions 2,47 2,06 2,70 2,20

Appendix B-11: Means of the measured constructs for all groups


66

Appendix C: Images used in the surveys

Appendix C-1


67

Appendix C-2

Appendix C-3

Appendix C-4


68

Appendix C-5


69

Appendix D: Pretest and survey

Vragenlijst

Ik ben een: Man / Vrouw

Leeftijd: ……………….

Vraag 1:

Naar welk merk Tandpasta gaat je voorkeur uit?

Vraag 2:

Welke merken tandpasta kun je opnoemen?

Vraag 3:

Als ik tandpasta koop ……….

Niet mee Neutraal Helemaal


70

eens mee eens

Maak ik me zorgen over de financiële consequenties van de

aankoop. 1 2 3 4 5

Ben ik bang dat het kan tegenvallen 1 2 3 4 5 Zou dit het geld niet waard kunnen zijn 1 2 3 4 5

Vraag 4:

Het product tandpasta is ………

Niet mee

eens Neutraal Helemaal

mee eens

Belangrijk voor mij 1 2 3 4 5 Niet waardevol voor mij 1 2 3 4 5

Vraag 5:

Naar welk merk tablet (kruising tussen laptop met touchscreen en pda) gaat je voorkeur uit?


71

Vraag 6:

Welke merken tablets kun je opnoemen?

Vraag 7:

Als ik een tablet koop ……….

Niet mee


mee eens


aankoop. 1 2 3 4 5


Vraag 8:

Een tablet is ………

Niet mee


mee eens


Vraag 9:

Naar welk merk mobiele telefoon gaat je voorkeur uit?

Vraag 10:


72

Welke merken van mobiele telefoons kun je opnoemen?


73

Vraag 11:

Als ik een mobiele telefoon koop ……….

Niet mee


mee eens

Maak ik me zorgen over de financiële consequenties van

mijn keuze. 1 2 3 4 5


Vraag 12:

Een mobiele telefoon is ………

Niet mee


mee eens


Vraag 13:

Naar welk merk shampoo gaat je voorkeur uit?

Vraag 14:

Welke merken van shampoo kun je opnoemen?

Vraag 15:


74

Als ik shampoo koop ……….

Niet mee


mee eens


aankoop. 1 2 3 4 5



75

Vraag 16:

Shampoo is ………

Niet mee


mee eens


Vraag 17:

Hoe riskant vind jij ……..

Niet riskant Neutraal Erg

riskant

Het kopen van tandpasta 1 2 3 4 5 Het kopen van een tablet 1 2 3 4 5 Het kopen van een mobiele telefoon 1 2 3 4 5 Het kopen van shampoo 1 2 3 4 5

Appendix D-1

Enquête tablets

Hallo,

Bedankt dat je de moeite neemt om mij te helpen bij mijn afstudeeronderzoek voor de Rijksuniversiteit Groningen.

In het onderzoek word je gevraagd het merk in een advertentie te beoordelen.

De enquete bestaat uit 12 vragen en duurt ongeveer 3 minuten. Neem alsjeblieft even de tijd om de vragen zo eerlijk mogelijk

in te vullen.

Alvast bedankt!

Start


76

Pagina: 2

Enquête tablets

1.

Geslacht

-- maak uw keuze --

2.

Leeftijd

3.

Naar welk van de onderstaande merken tablets (platte kleine computer met aanraakscherm) gaat je voorkeur uit?

Asus

Motorola

Samsung

Apple

Blackberry

LG

Ander

4.

Geef aan in hoeverre je het eens bent met de volgende drie stellingen.

Mee oneens Mee eens


77

Gezien de kosten, is het kopen van een tablet een riskante

keuze

Ik ben voorzichtig bij het aanschaffen van een tablet,

omdat er veel aan kan mankeren

Er zitten geen risico’s aan het aanschaffen van een tablet

Submit

Pagina: 3

Bekijk de onderstaande advertentie goed. De laatste 8 vragen gaan over deze advertentie.

* Zorg dat je een goed beeld hebt gevormd over de beweringen en producten in de advertentie!


78

5.

Heb je deze advertentie al eens gezien?

-- maak uw keuze --

6.

Een tablet is voor mij

Mee oneens Mee eens

Belangrijk

Betekenisvol

Waardeloos


79

7.

Wat is je gevoel over het merk Samsung, dat je zojuist in de advertentie hebt gezien?

Slecht

Goed

Niet leuk

Leuk

Onprettig

Prettig

Positief

Negatief

8.

Geef aan hoe waarschijnlijk het is dat je een tablet van Samsung zou aanschaffen.

Onwaarschijnlijk

Waarschijnlijk

Onmogelijk

Goed mogelijk

Grote kans

Kleine kans

9.

Geef aan in hoeverre je de advertentie geloofwaardig vindt.

Niet overtuigend

Overtuigend

Niet acceptabel

Acceptabel

Niet geloofwaardig

Geloofwaardig

Waar

Onwaar

10.

Geef aan hoe betrouwbaar je de beweringen van de advertentie vindt.


80

Niet betrouwbaar

Betrouwbaar

Niet acceptabel

Acceptabel

Niet geloofwaardig

Geloofwaardig

Waar

Onwaar

11.

Geef aan hoe betrouwbaar je de persoon vindt, die het product in de advertentie aanprijst.

Betrouwbaar

Niet betrouwbaar

Niet acceptabel

Acceptabel

Niet geloofwaardig

Geloofwaardig

12.

Heb je nog opmerkingen over de advertentie?

Einde

Pagina: 4

Dat was het einde van de enquete. Bedankt voor de medewerking!

De advertentie die gebruikt was berust niet op waarheid, en is slechts ontworpen voor onderzoeksdoeleinden.

Voor vragen of opmerkingen kun je mailen naar:

[email protected]

Appendix D-2

ad believability in comparative advertising

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