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UNIVERSITEIT GENT

FACULTEIT POLITIEKE EN SOCIALE WETENSCHAPPEN

Wetenschappelijk artikel

TIM DE GEYTER

MASTERPROEF COMMUNICATIEWETENSCHAPPEN afstudeerrichting COMMUNICATIEMANAGEMENT

PROMOTOR: PROF. DR. VEROLINE CAUBERGHE

COMMISSARIS: DR. ERLINDE CORNELIS

COMMISSARIS: DR. KATARINA PANIC

ACADEMIEJAAR 2009 - 2010

THE EFFECTIVENESS OF HUMOROUS VERSUS RATIONAL APPEALS IN PRINT ADVERTISING FOR UTULITARIAN AND

HEDONIC PRODUCTS

aantal woorden: 9418

2

THE EFFECTIVENESS OF HUMOROUS VERSUS RATIONAL APPEALS IN PRINT ADVERTISING FOR UTILITARIAN AND HEDONIC

PRODUCTS

ABSTRACT (ENG)

Are there golden rules to be respected concerning the use of humor in advertising?

The omnipresence of humor in commercial messages contrasts sharply with the empirical

inconsistencies about its effects on persuasion and credibility. This study makes an attempt to

contribute to this debate and is based upon two classic conceptual frameworks; the ‘Elaboration

Likelihood Model’ (ELM) and the ‘Product Color Matrix’ (PCM).

A between subject factorial experiment among 263 respondents was designed to examine

whether humor is more appropriate for high or low involvement products and for utilitarian or hedonic

products. The results show that a rational appeal enhances the credibility of high involvement

products. Humorous appeals on the contrary have a positive effect on the credibility of low

involvement products. Nevertheless, there is no moderating role of product involvement or product

type on the effectiveness of humor in advertising. Although men rated the humorous ads significantly

higher on perceived humor, this higher likeability of the ads did however not turn out into increased

brand attitudes and purchase intention.

The mediating effect of ad attitudes supports the conceptualization that humor (positively)

influences brand attitudes through the attitude towards the ad. This implicates that a humorous

advertisement can cause a higher likeability of the ad and consequently evokes more favorable

feelings towards the brand.

KEYWORDS

Humor, advertising effectiveness, utilitarian, hedonic, involvement, PCM, Credibility, mediator,

moderator, ELM

3

SAMENVATTING (NED)

Zijn er gouden regels omtrent humor in reclame?

De alomtegenwoordigheid van humor in commerciële boodschappen staat in schril contrast met de

empirische inconsistentie over de effecten van humor op de geloofwaardigheid en overtuigingskracht

van reclame. Dit onderzoek poogt een bijdrage te leveren aan dit debat en is gebaseerd op twee

conceptuele schema’ s; het ‘Elaboration Likelihood Model’ (ELM) en de ‘Product Color Matrix’

(PCM).

Door middel van een between subject factorial design (tussen-persoondesign) werd bij 263

respondenten nagegaan of humor beter geschikt is voor hoge of lage betrokkenheidsproducten en voor

utilitaire of hedonistische producten. De resultaten tonen aan dat een rationele appeal de

geloofwaardigheid van hoge betrokkenheidsproducten verhoogt. Een humoristische appeal

daarentegen, heeft een positieve invloed op de geloofwaardigheid van lage betrokkenheidsproducten.

Er is echter geen modererend effect van betrokkenheid van het product of van product type (utilitair of

hedonistisch) van humor op reclame effectiviteit. Hoewel de mannelijke respondenten de advertenties

significant hoger scoorden op waargenomen humor dan de vrouwelijke respondenten, leidt dit niet tot

verhoogde merkattitudes en koopintentie.

Dit onderzoek bevestigt eveneens dat de invloed van humor op merkattitudes volledig

gemedieerd wordt door de attitudes ten opzichte van de advertentie. Dit impliceert dat een

humoristische reclame kan leiden tot een verhoogde aantrekkelijkheid van de advertentie en zal

bijgevolg positieve gevoelens ten opzichte van het merk oproepen.

4

INTRODUCTION

In the past few decades, numerous studies have been dedicated to the effects of humor in advertising.

Nevertheless, they seldom lead to univocal results. Academics generally agree that humor does attract

the attention, (Sternthal, Craig, 1973, p.17) but there is still discussion about the effectiveness of

humor on brand recall, brand attitude and purchase intention when used in advertisements. The lack of

empirical consistency contrasts sharply with the ubiquitous use of humor in advertising. Various

researchers inquired into the use of rational and emotional - or more specific- humorous advertising

appeals and found out that humor is present in 15 to 42 percent of US advertising messages

(Weinberger, Spotts and Parson, 1997; McCullough, 1992).

Together with the increasing use of humor in advertising, there is also a growing interest in the

academic research of the effectiveness of humorous appeals. Several researchers however did not

succeed in generalizing their results. Chattopadhy and Basu (1990) emphasized the need for a

paradigm shift; they feel that researchers should ask ‘when’ the use of humor is effective, rather than

wondering ‘whether’ humor in advertising leads to better results. It is important to take into account

different moderating variables such as prior brand evaluation (Chattopadhy and Basu, 1990), need for

cognition (Zhang, 1996; Geuens and De Pelsmacker, 2002) and also product type (Weinberger, Spotts,

Campbell and Parsons, 1995).

In the early days, there was hardly any belief in the persuasiveness of humor in advertising.

Advertisements were not designed to entertain, but to inform. This can be derived from quotes as

“people do not buy from clowns” (Claude Hopkins, 1923) and “Good copywriters have always resisted

the temptation to entertain” (David Ogilvy, 1963). This assumption, however, evolved into an

increasing belief and conviction that humor can be a convincing communication strategy as well. Even

David Ogilvy had to reconsider his vision; he had “reason to believe that...humor can now sell”

(1982). In addition, creative advertisers nowadays proudly present campaigns relying upon humor.

Those campaigns have not only won prestigious prices, but were able to display positive sales figures

as well. Few research has put emphasize on the credibility of humor in advertising. This research will

make an attempt to answer the question whether some products are more suited to be communicated in

a humorous manner and whether the credibility suffers when using comedy in commercial print

messages. Therefore, a classification matrix has been made, based on the Product Color Matrix

(Spotts, et al, 1997, p. 21). A minor adjustment on both theoretical classifications was made: the think

– feel dimension was replaced by a utilitarian – hedonic dimension, which basically are other terms to

define to level of functionalism and pleasure. The choice for print advertisements is quite obvious;

advertisements in magazines and newspapers are still manifold and account for 48% of the total

advertising expenditures (De Pelsmacker, Geuens and Van den Bergh, 2005). Moreover, it appeared to

be a useful medium to manipulate the ads. First, relevant literature will be discussed and hypotheses

will be developed. Second, the research and its results will be described. The last part of this article

consists of a discussion about the findings and suggestions for further research.

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THEORETICAL BACKGROUND

Influence of humor on attitudes and purchase intention The results on the effects of humor on brand attitude are unclear, because no univocal results have

been found. Sternthal and Craig (1973, p. 17) state that humor attracts more attention, but the

persuasiveness is not greater than that of serious appeals. This conclusion is being supported by

Brooker (1981, p. 39), who found little to no results on the effectiveness of humorous and rational

messages for the same object. From a marketing point of view, understanding the role of attitude

towards the ad (Aad) and attitude towards the brand (Ab) is important and has pragmatic implications

for marketers and other professionals engaged in advertising. Hence, it is meaningful to know what the

predictive and explanatory power of Aad is (Gardner, 1985, p.192).

Basically, there are two models that declare the relationship between Aad and Ab. According to

the Superiority of the pleasant – hypothesis, there is a positive linear relation between Aad and Ab. Via

a conditioning process, the positive feelings one has towards an ad (because of its pleasantness) will

be transferred to the advertised brand. The second theory is the law of the extremes – principle:

advertisements that evoke affective reactions are more effective than neutral advertisements. A very

positive Aad will turn in a positive Ab. However, a negative attitude towards an ad can also result into a

positive attitude towards the brand. That is, once the irritations caused by the ad are gone, only the

brand name remains (De Pelsmacker, Geuens and Van den Bergh, 2005, p.86).

Zang and Zinkhan (2006, p.115) suggest that humor, especially under a low involvement

condition, will presumably draw more attention to the ad and thus may serve as an influencer of Aad.

According to the Affect transfer process – proposition, Aad will for his part, have an influence on Ab

(Cf. figure 1). Consequently, attitudes are considered to be good predictors of behavior towards a

product, i.e. purchase intention (Mitchell and Olson, 1981, p. 318). Zang and Zinkhan (2006, p. 116)

recognized the moderating effect of influencers such as involvement and found out that Ab is mediated

by Aad when humor serves as a peripheral cue under a low involvement condition and such an effect

does not takes place under a high involvement condition.

Figure 1: The causal mediating role of Aad

Humor

PI

Ab

Aad

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The Elaboration Likelihood (Advertising) Model

Petty and Cacioppo (1986) developed the Elaboration Likelihood Model (ELM), a theory of how

people elaborate advertising messages. They came up with a two-route model, in which consumers

process advertisements either along a central or a peripheral route depending on their motivation

(characteristic of the audience) and their capacity (characteristic of the specific situation) to elaborate

the information at hand. People process information differently depending on their motivation, thus an

involvement- condition: people who are lowly involved, process information via a peripheral route,

rather than via a central route. In this low involvement condition, ‘executional’ cues like attractiveness

of the endorser or humor in the ad are much more important than argument strength (Vyncke, 2008,

p.25 – 26). Hansen (1997) modified this model, based on long-term information processing studies

and concentrated it even more on advertising (Cf. Figure 2).

Figure 2: The Elaboration Likelihood Advertising Model (Hansen, 2005)

According to Hansen, central information processing focuses especially on product and brand

relevant information. This can be measured by brand awareness and image, and eventually also by

purchase intention. Peripheral information processing concentrates more on how the message looks

and generates an attitude towards the ad (and not so much to the brand). Subsequently, the emotional

response and the formed attitude towards the ad result to the ad-liking and will influence brand

attitudes and purchase intention. Therefore, attitude towards the ad and ad liking can be seen as

important measurements related to peripheral information processing (Hansen, 2005, p. 1429).

7

Product involvement and product type

Product classifications

Probably the best known classification of products is the ‘Foot-Cone-Belding Matrix’ , or shorter the

FCB-Matrix by Vaughn (1980), later on adjusted by Rossiter and Percy (1991). They set up a state of

the art framework and gave clear understanding in how consumers evaluate products or brands. This

matrix consists of two dimensions: an involvement continuum and a think-feel aspect. Involvement

indicates the importance one attaches to a product or a purchase decision. The think-feel continuum

explains if the choice is either cognitive or affective. They state that consumer information processing,

and consequently also advertising decisions, can be categorized into four dimensions.

A variation of this matrix is the so called ‘Product Color Matrix’ (Cf. Figure 3) and is very

similar to the FCB Matrix. PCM can be seen as a useful tool for marketing practitioners and

advertising agencies. It offers the ability to analyze the consumer decision – making process and takes

into account the important product related effects on advertising (Spotts, Weinbergers and Parsons,

1997, p. 21). The colors white, red, blue and yellow are used as a metaphor to emphasize the meaning

of products and represent one of the four portions of the grid. White goods fulfil functional needs, are

expensive and require attentive comparison because of its high risk. Red goods satisfy a need for self-

expression and are mostly bought for its sensory gratification. Blue goods are routine purchases and

therefore require little information processing. Finally, yellow goods are also low involved routine

purchases, but they are bought to make us feel better (Cf. Figure 3).

Figure 3: The Product Color Matrix (PCM) and Prototype products

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Utilitarian and hedonic products: conceptualization and findings

In this research, the think-feel aspect is been replaced by respectively the terms utilitarian and

hedonic. Utilitarian goods can be described as instrumental and functional. Insurances, washing

products and personal computers fall in this category. The consumer will process information before

he moves on to purchase. Such a process can be goal oriented or problem solving. Hence, he will take

rational arguments into consideration. Hedonic goods on the other hand, are more experiential and

pleasure related (e.g. beer or travelling). The consumer experiences a certain feeling of enjoyment.

Utilitarian and hedonic products are not necessarily two end of a one-dimensional scale (Voss

et al, 2003). That is, different products can score high or low on both the utilitarian and hedonic

attributes. For example, a person who makes a trade-off between a pair of sneakers may take both

utilitarian (e.g. durability) and hedonic (e.g. design) features into consideration (Khan, Dhar and

Wertenbroch, 2004).

Previous research revealed interesting managerial insights relating the level of hedonism of

products. Dhar and Wertenbroch (2000, p.69) found out that marketers can charge a premium price for

products that are highly valued on the hedonic dimension. This is because hedonic products are

consumed for fun and pleasure, thus saving money might not be a concern. The choice between

utilitarian and hedonic products also seems to differ in on another important factor of product

acquisition, the trade-off between time (i.e. effort) and money. Consumers, for instance, show a

preference to pay in time (e.g. wait in line) to acquire hedonic products and in money to obtain

utilitarian product (Okaka, 2005).

Product type and humor When you pay attention to the bunch of advertisements for different product categories, it is

remarkable that for some product categories hardly ever humorous appeals are used e.g. products like

perfume, detergents and over the counter medicines.

Clearly, advertisers struggle with the question how to gain attention in the advertising clutter

on the one hand and pass on product information or a product image on the other hand. This raises the

question whether certain products or – in the broadest sense – certain product categories are more

suitable for humorous appeals than others.

Common sense says that humor is not the most effective advertising strategy under all

conditions. Various research studies prove that (1) the use and (2) the impact of humor for different

product categories varies. First of all, Weinberger and Campbell (1992) found a significant difference

in the use of humorous messages in radio commercials. For high involvement – feeling products,

hardly 10% of the commercials were humorous, whereas for low involvement – feeling products,

humor was used in almost 40% of the investigated commercials. Furthermore, according to this same

study, no humor appeared to be the best approach for high involvement – thinking products.

Weinberger, Spotts, Campbell and Parsons (1995, p.11) declare, on basis of their later research, that

9

low involvement – transformational goods are best suited to humor, because humor enhances attention

and aided brand recall, while on the other hand the high involvement transformational goods are least

suited. This can be explained by the flamboyance and especially the social risk that goes along with

these products (e.g. designer clothing or expensive perfume). Because these red products often have a

relationship with the personality of the buyer, making fun of these brands may be considered

threatening and offensive.

Wu, Crocker and Rogers (1989, p 653 – 663) inquired into (the main and interaction) effects

of humor, comparative strategy and product type. They made a number of ads for both athletic shoes

(high involvement product) and facial tissues (low involvement product). Humor in an ad for high

involvement products makes the ad look less impressive, gives the consumer the impression of

needing additional information and stimulates the recall of competing brands. In a low involvement

condition, humor reduces belief of the arguments, but reduces the recall of competing brands as well.

Nevertheless was only Aad significantly higher for the humorous version of the ad, regardless of the

product type.

Type of humor Cline and Kellaris (2007, p. 55 – 56) recognize the importance of humor relatedness to the product or

message. They argue that relatedness of humor plays a significant role and may be a good predictor of

ad successfulness. Weinberger and Gulas (1992, p.39) share this vision and define related humor as

having a link with the particular product. In addition, they indicate that related humor causes an

increased attention and comprehension of advertisements. In contrast, incidental (or unrelated) humor

could inhibit brand and claims recall, but enhances recall of the joke itself at the expense of the brand

(Cline and Kellaris, 2007, p.56).

There is no general accepted classification of humor types, but various researchers have based

themselves on the typology of Speck (1991). He introduced the ‘Humorous Message Taxonomy’

(HMT). This typology and classification focuses on both humor type and the relation of humor

elements towards the other message elements. Speck distinguishes three major levels of humor

relatedness in an ad: intentional relatedness, semantic relatedness and structural relatedness.

Intentional (or pragmatic) relatedness refers to dominance of either humor or arguments. Semantic

relatedness determines whether the humor is rather relevant or irrelevant for the product or service in

the ad. Structural (or syntactic) relatedness describes which syntactic role the humor fulfils within an

ad. Or in other words: is the humor meaningful to the message?

Speck makes also a distinction between five humor types. (1) Comic wit is a form of cognitive

humor, e.g. exaggeration. (2) Sentimental humor is aimed at provoking positive feelings and warmth.

(3) Satire holds both a cognitive element and an aggressive or derisive element. (4) Sentimental

comedy is a combination of comic wit and sentimental humor, thus proving cognitive and affective

pleasure. Finally, (5) Full comedy can be seen as sentimental comedy plus satire.

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Ad Credibility Leo Burnett (cited in Atkin et al, 2007, p. 169) once declared: “ The greatest thing to be achieved in

advertising … is believability” . This indicates clearly the importance of credibility in advertising.

Unfortunately, hardly any attention has been given to the effects of humor on ad credibility. A few

studies however did examine the effects of humor on source credibility (Eisend, 2009, p. 21). But the

results of these studies can only be described as mixed. Since there are four studies reporting an

enhancement of source credibility in a humor condition, three studies indicate a negative result and

five indicate a neutral or mixed result (Weinberger and Gulas, 2006, p. 117).

McKenzie and Lutz (1989, p. 51) define credibility as “ the extent to which the consumer

perceives claims made about the brand in the ad to be truthful and believable”. Cotte, Coulter et al

(2005, p. 362) support this definition and believe that ad credibility focuses on the advertisement itself

and the consumer’ s perception of the believability and trustworthiness of that advertisement.

Moreover, Cotte et al also believe that when consumers evaluate an ad on credibility, they will mainly

interpret the ad and not so much the source.

Demographic factors

Audience factors are another variable, researchers should bear in mind and include in their study.

Sternthal and Craig (1973, p.16) already indicated the importance of further research to individual

characteristics such as age and level of education. Madden and Weinberger (1984, p. 27) asked around

in advertising agencies whether certain consumers are more susceptible to humor in advertising. Those

advertising practitioners believe that using a humorous appeal is the most appropriate for a young,

well educated and male audience. On the other hand, they are convinced that humor is very difficult to

pass on to a less educated and older market segment. However, few empirical researches support this

assumption.

RESEARCH HYPOTHESES

The purpose of this article is to get better understanding of the role of humor in advertising, to

regenerate the discussion and to offer an addition to earlier studies in this field. Therefore, this study

will make an attempt to find out whether (1) the proposed causal path of the mediating role of Aad can

still be supported, (2) humor is more appropriate for certain products in the (adjusted) Product Color

Matrix, (3) if there are important consequences regarding the credibility of the advertisements, and (4)

to what extent socio-demographic characteristics have an influence on humor likeability and

persuasiveness. To offer an answer to these questions, following hypotheses have been developed:

11

Is the relation between humor and brand attitudes mediated by Aad?

To get a better understanding of how humor works en what its influence is on behavior, it is

interesting to know whether humor influences attitude towards the brand through attitude towards the

ad. Several researches found evidence that Ab indeed is a function of Aad (De Pelsmacker, Geuens and

Van den Bergh, 2005, p. 78). This means humor can have an influence on Ab both direct and indirect

via Aad. This is also the point of view of McKenzie, Lutz and Belch (1986), who see humor as an

antecedent of Aad. In addition, Hansen (2005, p.1430) beliefs that humor serves as a peripheral cue and

will generate attitudes towards the ad (rather than towards the brand). This leads to the following

hypothesis:

H1: There is a causal relation between humor and attitude towards the brand, with Aad as a

mediating variable.

Does the effectiveness of humor in advertising vary among product categories?

When having a look at the use and the beliefs of using humor for certain products, both practitioners

and academics generally agree that using humor for high involvement products holds quite some risks.

Weinberger and Campbell (1992) investigated a pool of 1660 radio commercials, which could clearly

be classified in the FCB Matrix. They came to the conclusion humor that humor is not very often used

for high involvement products (14.3 % for utilitarian and 10% for hedonic products).

The assumption is that both involvement and product type (utilitarian or hedonic products)

moderate the effectiveness of humor effectiveness in advertising. The reason is twofold: first, for low

involvement products, the consumers will elaborate the ad peripherally and pay more attention to

executional cues such as the humor in the ad (Petty and Cacioppo, 1983). Furthermore, it seems

plausible that for high involvement products, the consumer will also watch the ad under a high

involvement condition. The subjects than elaborate the information via a central route and thus pay

attention to the arguments in an attempt to seek reassurance in those arguments. Second, it has been

suggested that consumer attitudes are two-dimensional, because consumers purchase products or

services basically for two reasons: (1) for its affective or hedonic attributes or (2) for instrumental or

utilitarian reasons (Batra and Athola, 1990, p. 160).

Drolet and Aaker (2002, p. 59) found out that the effectiveness of cognitive versus affective

appeals depends on whether the appeal is congruent with the attitude object type. Drolet, Williams et

al (2007, p. 212-213) emphasize the importance of congruency and add to the discussion that

consumers generally prefer rational ads for utilitarian products and affective ads for hedonic products.

Based on these findings and the FCB Matrix, the suggestion is made that utilitarian products

require rational and informative messages. Hedonic products, conversely, are advertised more

effectively by using pleasure and humorous appeals.

12

H2a: Product involvement moderates the effect of humor. A humorous appeal will positively

influence ad and brand attitudes and purchase intention for low involvement products, whereas

for high involvement products humor will not.

H2b: Product type moderates the effect of humor. A humorous appeal will positively

influence ad and brand attitudes and purchase intention of hedonic products, whereas for

utilitarian products, it will not.

It is almost a general rule for advertising practitioners to avoid using humor when advertising a high

involvement – utilitarian product. Because of the (financially) important purchasing decision and the

complexity of the product (or service), consumers want to be well informed about the characteristics

and details of the product. Moreover, the humor in ads for this kind of products can become irrelevant

and can produce unfavorable results on the ad and consequently also on the brand (Zhang and

Zinkhan, 2006, p.114). Besides, not only Aad and Ab determine the persuasiveness of an ad. For this

product category, the credibility of the ad is considered to have a huge impact as well.

According to Geuens (1997) prudence is indeed called for when advertising a high

involvement product for which consumers reflect strongly before purchasing. Based on the ELM of

Petty and Cacioppo, there are sufficient reasons to assume that consumers process information of high

involvement – thinking products (e.g. insurances) via a central route, elaborating the content of the ad

in depth and paying attention to the argument strength. This raises the hypothesis that for this product

category a marketer should better use a rational appeal.

H2c: For high involvement – utilitarian products, a rational appeal enhances the effectiveness

of the ad.

The influence of humorous or rational appeals on ad credibility Sutherland and John (1982) already examined the effect of humor on recall and credibility for two

kinds of products in a radio advertisement. The subjects were exposed to a serious ad of one product

and a humorous ad of the other product and rated the ads on a few variables, including credibility.

They found out that the subjects rated the serious version of the ad significantly more credible than the

humorous ads. Furthermore, it seems plausible that high involvement products are elaborated via a

central route, therefore rational arguments will increase the credibility. Based on the ELM and the

results of Sutherland et al, this study postulates the following hypothesis:

H3: Product involvement moderates the effect on credibility. A rational appeal will positively

influence credibility for a high involvement product, whereas for a low involvement product it

will not have a positive effect.

13

Socio-demographic differences between the effectiveness of humorous appeals Madden and Weinberger (1982) and Lammers (1983) found out that humor scores higher for a male

audience than a female audience. De Pelsmacker and Geuens (1996), however, found no difference in

gender on recall, brand recognition, cognitive reactions, Aad, Ab and purchase intention for humorous

advertising messages. Moreover, Brooker (1981, p.39) found no evidence either for increasing

persuasiveness on well – educated individuals. Therefore, this research postulates the hypothesis that

there is a difference between males and females on humor appreciation. This will however have no

significant effect on the advertising effectiveness, measured by Aad, Ab and PI.

H4: Gender, age and education level have no significant effect on the effectiveness of humor

in print advertisements

RESEARCH METHOD

Design

An experiment was conducted to determine the moderating role of product type and involvement on

the effects of humor on attitude towards the ad, brand attitude, purchase intention and credibility. This

research uses a 2 (high or low involvement product) x 2 (utilitarian or hedonic product) x 2 (humorous

or rational ad) randomized between – subject factorial design and contains eight cells with ca. thirty

subjects in each of these conditions.

Stimuli

Thirteen fictitious ads, nine humorous and four rational, were made. All rational ads consist of a

picture of the product in the centre of the ad, a neutral brand name and three rational arguments. The

choice for the fictitious brand name ‘NOVA’ for all products was twofold. First, it provides the

opportunity to control the bias of prior brand attitude. Second, it excludes the bias when the likeability

of a particular brand name is higher than another.

The humorous advertisements developed for the study were created to be identical in terms of gender

(main character is a man), type of humor (satire, Cf. Speck, 1990) and message (advertised product

offers a solution for a negative situation). In this research, related humor was used in the ads (supra).

Procedure The study is made up of three major parts: a pre-test to make a product classification, a second pre test

to examine which of the developed ads were rated the funniest, and the initial study. The initial study

(n = 263) and the first pre-test (n= 40) have been conducted via an online survey. The second pre-test

(n = 15) was conducted by a face-to-face questionnaire. For the initial study, the subjects received

completely at random an internet link, referring to one of the eight questionnaires. The first page

contained brief instructions and information. The second page contained an advertisement, followed

14

by the measures. On the third page, the subjects were asked to fill in a few socio-demographic

questions. The last page was a thank you message.

Respondents The initial study was conducted with 266 subjects, who rated at random one of the eight

advertisements by means of an online survey. 263 valid responses were obtained. 45 % of the

respondents was male and 55 % was female. Of these 263 (mean = 30, median = 24 years old) valid

respondents was 14.3% younger than 21, 38.1 % was aged between 21 and 25, 16.6 % between 26 and

35, 11.7 % between 36 and 45 and 18.3% was older than 45. Only 1,5% holds a primary degree,

37,6% a secondary degree, 39,5 a college degree, 18,6 a university degree and 2,7% holds a post

university degree.

Measures Five dependent measures were used in this research: Attitude towards the ad (Aad), Attitude towards

the brand (Ab), Purchase intention (PI), Credibility and Product class Involvement.1

Four items (Cronbach’ s � = 0.952) on a seven point bipolar scale were used to measure Aad:

negative/positive, like it/dislike it, unfavourably/favourably, bad/good (Holbrook and Batra, 1987).

Ab measures the respondent’ s attitude towards the fictitious brand ‘NOVA’ and uses the same four

items as for the Aad –construct (Cronbach’ s ��= 0.929)

PI (Cronbach’ s � = 0.866) is a three-item, seven point Likert scale(‘It is very likely that I will buy

NOVA’ , ‘I will purchase NOVA the next time I need a product’ and ‘I will definitely try NOVA’ ) and

measures the degree to which a consumer intends to buy a brand in the (near) future (Putrevu, Sanjay

and Lord, 1994).

For the credibility construct, the following 4 items were measured on a 7 point bipolar scale:

‘the ad is not at all believable/highly believable’ , ‘not at all sincere/very sincere’ , ‘not at all

acceptable/ totally acceptable’ and ‘not at all credible/very credible’ . This is a slightly modified

version of the Gürhan – Canli and Maheswaran scale (2000).

In former research, it has sometimes been the case that answers were somewhat biased by the lack of

interest in certain product categories. Therefore, an additional scale has been added to take into

account the involvement with the four product classes. Again, a 4 item 7 point semantic differential

scale was used: ‘In general I have a strong interest in this product category’ , ‘This product category is

very important to me’ , ‘This product category matters a lot to me’ and ‘I get bored when other people

talk to me about this product category’ (Beatty and Talpade, 1994).

1 All these scales were found in: Bruner, G. (2001). Marketing scales handbook 3. A compilation of multi-item measures.

15

PRETESTS

Pre test 1 First, a classification of products has been made to set up a four dimension product matrix. Two

bipolar scales were used to determine if a number of products are either highly or lowly involved on

the one hand, and have a utilitarian or hedonic aspect on the other hand. To measure the degree of

involvement one has toward the product, the Personal Involvement Inventory (PII) of Zaichkowsky

(1994) was used.

The choice for this ten point semantic differential scale was twofold. First, it is a reduced and

revised version of the initial PII scale of Zaichkowsky (1985). Second, it can be seen as quite complete

as it takes into to account both the cognitive and affective elements of the involvement construct

(Cronbach’ s � = .914).

To measure the utilitarian-hedonic construct, the ten point bipolar scale of Voss, Spangenberg

and Grohman (2003) was used. The subjects scored twelve products on involvement and level of

hedonism. These twelve products (Cf. table 1) were expected to fit in the four quadrants of the PCM.

Table 1: 12 products for pre-test 1

HI - UT HI – UT/HED HI - HED LI – UT LI – HED

Insurances Car Perfume Paper tissues Beer

Toothpaste Mobile phone Detergent Soft drink

Printer Computer Chocolate bar

Factor analysis on the results pointed out that this scale holds two dimensions. Five items

measure the ‘utilitarian’ construct, the other five items measure the ‘hedonic’ construct. After a

consistency-check (Cronbach’ s � utilitarian = .948, hedonic = .944), new variables have been created.

The most surprising result was the high involvement with toothpaste (Cf. table 1). An analysis of the

survey results pointed out that this is probably due to the interpretation of the respondents, as they see

toothpaste as a sine qua non in daily life. Consistent with the literature, certain products scored almost

equally high on the utilitarian and hedonic constructs (HI-UT/HED). Examples are cars, mobile

phones and computers. The products with the most extreme values were picked out, one of every

quadrant. These products are: insurances, perfume, paper tissues and soft drink (lemonade). The next

step was to determine whether the products with the most extreme values differ significantly from

each other.

The subjects felt significantly higher involved to insurances and perfume than to paper tissues

and soft drinks (F = 23.754, df = 11, p < .01, required Scheffe groupings were different). The same

products were perceived as differentially utilitarian (F = 94.743, df = 11, p < .01) required Scheffe

16

groupings were different) and hedonic (F = 22.606, df = 11, p < .01, required Scheffe groupings were

different). Finally, a matrix has been created, as can be seen in figure 4.

Figure 4: Product Matrix

Subsequently, one rational and several humorous ads were created for each of the selected products (or

services): insurances, perfume, paper tissues and soft drinks.

Pre test 2

The nine humorous ads needed to be reduced to the four best advertisements. Therefore, fifteen

respondents rated each ad on amusingness, using the 5 items bipolar scale ‘Attitude towards the ad

(humor)’ (Cronbach’ s � = .924) (Zhang & Yong, 1996). For the products insurances, soft drinks and

paper tissues, one ad was clearly rated higher than the other, making the choice very obvious. The two

perfume ads, scored almost equally high, making it a lot more difficult to choose from2. The humorous

advertisement for insurances displays a workman fooling around with funny glasses in a sawmill (M =

2.12). The ad for perfume consists of a man in an ambulance with an enormous body odour,

whereupon the paramedics need to use the oxygen masks. Also a catchphrase was used: “ Better use

NOVA perfume next time?” (M = 2.60). The ad for paper tissues pictures a pigeon sitting on a pole and

watching down on a man who is about to walk by underneath it. This is accompanied by the phrase:

“ Thank God, there are still NOVA tissues.” (M = 2.32) The humorous ad for lemonade displays an

employee sleeping in a business meeting and having a face shaved in his hair, so it looks like he is

actually paying attention. A catchphrase was used as well: “ NOVA Drinks will get you through the

day” (M = 2.96). 2 A small additional study examined which of the two perfume ads should be picked. Ten subjects rated both ads by means of a7-point Likert scale ‘this ad made me laugh’ . Based on these results, the second perfume ad was chosen.

17

RESULTS

Manipulation check Two items were added to the survey to verify the effectiveness of the humor manipulation. ‘This

advertisement is funny’ and ‘This advertisement is amusing’ were measured with a 7 point Likert scale

and were used to capture the subject’ s perceptions of how humorous the ads are. Since the correlation

between those two items was high (r = 0.847, p < .001), the new variable ‘perceived humor’ has been

created. A T-test proved the manipulation to be successful; the humorous ads were rated significantly

higher on perceived humor than their rational counterparts (M humor = 4.40, M rational = 2.56, p < .01).

Mediator effect

Test of H1: There is a causal relation between humor and attitude towards the brand, with Aad

as a mediating variable.

The assumption is that humor has a positive influence on attitude towards the brand, through attitude

towards the ad. In order to recover such a potential mediating effect, the procedure of Baron and

Kenny (1986, p. 1177) has been followed and regression analyses were used.

Table 2: The mediating role of Aad.

Visual depiction Significant?

Step 1 There is a relationship between

humor and Ab.

Humor Ab

Yes (� = .323, p < .01)

Step 2 humor must have a significant

effect on the mediator (Aad)

Humor Aad

Yes (� = .682, p < .01)

Step 3 this mediator (Aad) must also have

a significant effect on Ab

Aad Ab

Yes (� = .483, p < .01)

Step 4

The previously relationship

between humor and Ab is no

longer significant once the

variance of Ab is partialled out

Humor, Aad Ab

No (� Aad = .460, p < .01;

� Humor = .03 < .323, p

> .05)

Because all of these steps can be established, there is a full mediating role of Aad. This result is

consistent with the hypothesis that Aad completely mediates the humor – brand attitudes relationship.

Therefore, H1 is supported. This means humor can be an important determinant in the persuasion of

18

consumers, as it has an effect on the affective reactions one has towards the ad. Aad, on his turn,

influences how someone feels towards the brand. When that person has positive feelings towards that

particular brand, the chances of that person actually buying those products increase.

Moderator effect First of all, the data were analyzed in a MANOVA (two – way ANOVA) procedure to reveal potential

interaction effects between the appeal, the product involvement and the utilitarian or hedonic aspect of

the product. This procedure included the four dependent variables: Aad, Ab, PI and Credibility. The

multivariate test revealed a significant main effect of appeal on credibility, a main effect of product

type on credibility and on purchase intention and a main effect of involvement on credibility.

Furthermore, the multivariate analysis of variance a shows a significant two – way interaction effect of

appeal and involvement on credibility (Cf. Table 3). No other effects were significant.

Table 3: The interactive effect of involvement, product type and appeal on advertising effectiveness

Source Univariate

df

Aad Ab PI Credibility

Appeal (A) 1 3.099 .205 .164 7.219*

Product type (P) 1 .799 1.243 7.369* 22.180**

Involvement (I) 1 4.137 .478 4.527 8.972*

A x P 1 4.907 .005 .697 5.256

A x I 1 4.501 .286 4.366 18.312**

P x I 1 .991 .375. .049 2.008

A x P x I 1 .298 .341 .224 4.302

* p < .05 ** p < .01

Test of H2a: Product involvement moderates the effect of humor. A humorous appeal will

positively influence ad and brand attitudes and purchase intention for low involvement

products, whereas for high involvement products humor will not.

H2a postulates that the effect of humor on advertising effectiveness is moderated by product

involvement. In case of low involvement, humor positively influences attitudes towards the ad,

attitudes towards the brand and purchase intention, whereas in case of high involvement, it does not

have a positive result on these variables. To check the eventual moderating role of involvement, some

ANOVAs were used, with Aad, Ab, and PI as dependent variables and appeal, product type and

involvement (high or low) as independent variables. As shown in Table 3, there is no significant result

of involvement on Aad, Ab and PI. Thus, H2a is not supported.

19

Test of H2b: Product type moderates the effect of humor. A humorous appeal will positively

influences ad and brand attitudes and purchase intention for hedonic products, whereas for

utilitarian products, it will not.

This hypothesis predicts that the effectiveness of humor is moderated by the product type. When

making promotion for a utilitarian product, a rational appeal is the best communication strategy.

Conversely, a humorous appeal is better suited when dealing with a hedonic product. To investigate

these propositions, again MANOVAs were run. No significant results have been found for Aad and Ab.

However, for PI a significant main effect has been found. The subjects have a higher intention in

buying a utilitarian product than a hedonic product. This can be explained by the fact that utilitarian

products are seen as indispensable products. Consumers do not buy those products for their

experiential function, but rather see them as basic products which cannot be forfeited (Dhar and

Wertenbroch, 2000, p. 61). These results do not support H2b.

Test of H2c: For high involvement – utilitarian products, a rational appeal enhances the

effectiveness of the ad.

H2c suggests that when making an ad for a high involvement – utilitarian product (e.g. insurances),

the use of a rational appeal is recommended. To test this hypothesis, independent sample T-tests were

used to determine whether there are differences in effectiveness and persuasiveness between the

humorous and the rational version of the insurance ad. No significant differences have been found for

Aad and Ab.. For PI no significant result has been found either. However, the difference between both

means (M humor = 3.500 vs. M Rational = 3.2396) is higher than those of the other ads leading almost in a

significant difference (p = .108). The results do not support H2c.

Test of H3: Product involvement moderates the effect on credibility. A rational appeal will

positively influences credibility for a high involvement product, whereas for a low involvement

product it will not have a positive effect.

To test this hypothesis, again some multivariate analyses of variance (MANOVAs) have been used

including successively appeal (humor or rational), involvement (high or low), product type (utilitarian

or hedonic) as fixed factors and credibility as the dependent variable. The results from these tests show

that there are significant main effects of appeal, involvement and product type on credibility.

Consistent with the expectations, the rational appeals appeared to be experienced as more credible than

the humorous appeals (M humor = 3.684, M Rational = 4.029, F = 4.623, p. = .033). Furthermore, the

advertisements of low involvement products were rated higher on credibility than those of high

involvement products (M high involvement = 3.664, M low involvement = 4.048, F = 5.746, p. = .017). The

third main effect is the higher perceived credibility for utilitarian products than for hedonic products

(M utilitarian = 4.158, M hedonic = 3.554, F = 14.205, p. = .000).

20

Figure 5: Interaction effect of Appeal and Involvement on Credibility

There is also an interaction effect of appeal and involvement on credibility (F = 11.728, p. = .001).

Further examination of the interaction effect revealed that using a humorous appeal for low

involvement products leads to a higher credibility than using a humorous appeal for high involvement

products (M high involvement = 3.217, M low involvement = 4.151, p < .01). On the other hand, the credibility

for high involvement products increased and for low involvement products decreased when a rational

appeal was used (M high involvement = 4.111, M low involvement = 3.946). There was no significant three-

way interaction between appeal, product type and involvement. It may however be interesting to have

a closer look at the difference in credibility between both humorous and rational ads for all product

categories. The rational ads for the products insurances (M insurance = 4.308, t = -2.324) and perfume

(M perfume = 3.914, t = -3.318), both high involvement products score significantly higher (p < .05) on

credibility than the humorous ads for the same products (M insurances = 3.442, M perfume = 2.992). For

lemonade, the low involvement – hedonic product, no significant effect was found (M humor = 3.4773,

M rational = 3.8676, t = -1.245, p. = .217). The analysis of the credibility of paper tissues delivered an

unexpected result. Here, the humorous ad scored significantly higher on credibility (M humor = 2.9706,

M rational = 3.9138, t = 3.318, p = .002). This is probably due to the fact that the subjects find (rational)

advertisements for this kind of products irritating and untrustworthy, which gave a negative influence

on the credibility score. The results support the notion that a rational appeal generates more credibility

for a high involvement product, whereas for a low involvement humor will generate more credibility.

Therefore, H3 is supported.

21

Socio-demographic differences

Test of H4: Gender, age and education level have no significant effect on the effectiveness of

humor in print advertisements.

The effect of gender on humor appreciation has been examined by selecting only the humorous ads

and running an independent T-test. The perceived humor variable seemed to be significant. The male

subjects rated the humorous ads a lot higher than the female respondents (M male = 4.8852, M female =

3.8417, t = 3.197, p < .01). This considerable difference in perceived humor did lead to an increased

attitude towards the ad (M male = 4.4153, M female = 3.7716, t = 2.134, p < .05), but did not have an

influence on attitude towards the brand or purchase intention. In order to verify whether age plays an

important part, a one – way ANOVA has been used, but no differences were found.

Finally, the influence of level of education was verified. To do so, again a one – way ANOVA

and Post Hoc Scheffe was used and found that people with a master degree differ from those with a

secondary school diploma and bachelor degree on purchase intention (F = 6.773, p < 0.01). Probably

this is because people with a higher degree usually are more skeptical towards advertising than those

with a lower degree. This disbelief and skepticism will than probably lead to a decreased purchase

intention. This assumption finds support when analyzing the credibility. Although there was no

significant result between people with a master degree and those with a lower level of education on

credibility, there clearly is a tendency. Masters probably hold, due to their skepticism, fewer beliefs in

the credibility of the advertisements. Therefore they will feel less inclined to purchase the advertised

products. In conclusion; men give more appreciation scores to humorous ads than women. This

however does not have repercussions on the effectiveness of the advertisements, measured by Aad, Ab,

purchase intention and credibility. Thus, H4 is supported.

DISCUSSION AND CONCLUSIONS

The goal of this study was twofold. The first objective was to get a better understanding in the way

humor in advertising works. Second, the interaction effects of product type (utilitarian versus

hedonic), appeal and product involvement were measured to determine whether the use of humor is

more effective for certain product categories.

Based on the suggestions that for low involvement products (i.e. Fast Moving Consumer

Goods), peripheral information processing is widespread and the most effective (Spotts, Weinbergers

and Parsons, 1997, p. 21), this study examined first the moderating effect of involvement on the

effectiveness of humorous appeals. Although almost all humorous ads scored higher on attitude

towards the ad than their rational counterparts, no moderating effect of involvement has been found on

advertising effectiveness measured by Ab and PI.

In addition, the PCM provides a foundation for suggesting that utilitarian products require a

rational and informative message, whereas hedonic products profit from sensory or pleasure related

22

messages (Cotte et al, 2007, p. 212-213). However, this study did not find any moderating effect of

product type on advertising effectiveness. The cause is a matter for conjecture, yet it is possible that

the humor in the perfume ad may be considered inappropriate for these (self-expression) products. The

purchase intention of utilitarian goods was significantly higher, but this is probably due to the

everyday use of these products (Dhar and Wertenbroch, 2000, p. 61).

The incremental contribution of this research is that it, unlike many others, included the effects

of humor and rational appeals on credibility. The results of the study indicate significantly higher

perceived ad credibility for the rational ads than for the humorous ads. In depth examination of the

results revealed that for low involvement product, a humorous appeal increased the credibility. On the

other hand, a rational appeal increased the credibility of high involvement products. These present

findings are in line with those of Sutherland (1982) and fully support H3. Hence, it may have practical

implications in terms of guidelines for advertisers and other professionals in the field of marketing.

The same results can add to our knowledge that rational appeals for low involvement – utilitarian

products result in a decreased credibility. One reasonable explanation is that rational appeals for this

product category causes a reduced likeability of the ad and evokes feelings of irritation.

Consistent with the results of Madden and Weinberger (1982) and Lammers (1983), this study

shows that men rate the humorous ads significantly higher on perceived humor. This higher likeability

of the ads did however not lead to different brand attitudes and intentional behavior. In consistency

with the literature (Geuens and De Pelsmacker, 1996; Brooker, 1981), the conclusion can be made that

age does not play a significant role in humor appreciation and effectiveness. The level of education

does not have an effect on humor appreciation either. However, education does effects purchase

intentions. It appeared that highly educated consumers (master degree) have less intentions in buying

the products shown in the ads. A feasible explanation for this can be the higher skepticism towards

advertisements of well educated consumers.

Finally, this study also made an attempt to make a theoretical contribution by examining the mediating

effect of ‘Attitude towards the ad’ . Consonant with previous research (De Pelsmacker, Geuens and

Van den Bergh, 2005, p. 78; McKenzie, Lutz and Belch, 1986; Hansen, 2005, p.1430), the results

provide evidence that humor has an indirect influence on brand attitudes through Aad.

These results can offer valuable insights and can be used as a guideline in how to

communicate for different product categories. The existing distinctions between high or low

involvement and more or less information processing seem useful. Especially regarding the perceived

credibility, rational or humorous appeals are more appropriate for one product category than the other.

23

LIMITATIONS AND SUGGESTIONS FOR FURTHER RESEARCH

There are several limitations with the present investigation, each offering an opportunity for further

research. First, the study solely used print advertisements. It could be interesting to investigate

whether the present results also apply on other media. Because of the increasing importance of online

advertisements, it would be particularly useful to examine if the same effects will be obtained for

electronic media (Zhang and Zinkhan, 2006, p. 124).

Second, only one product was used to represent each of the four quadrants. It is recommended

to examine the effects of humor on different products within the quadrants of the PCM. Third, with the

use of insurances to represent the high involvement – utilitarian quadrant, a service was used, whereas

for the other quadrants, a product (lemonade, tissues and perfume) was used. It would be an

incremental contribution to examine whether there are differences between products and services

when using humorous or rational appeals.

Finally, in order to keep the humorous advertisements more or less identical, the same

message was used, i.e. the products in the ads offer a solution for a negative situation. Literature,

however suggests that utilitarian products are bought because of a negative motivation (to solve

problems), whereas hedonic products are bought because of a positive motivation (self gratification).

Hence, the negative situations in the humorous ads might have biased the results for those product

types. Therefore, further research concerning the effects of positive or negative motivations for

utilitarian and hedonic products is recommended.

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1��

Appendix

�

Appendix 1: Online survey Pre test 1 – product classification ................................................................ 2

Appendix 2: Face to face survey Pre test 2 – Perceived humour ............................................................ 2

Appendix 3: Initial online survey ............................................................................................................ 3

Appendix 4: Advertisements ................................................................................................................... 7

Appendix 5: Pre test 1 ............................................................................................................................. 8

Factor analysis ..................................................................................................................................... 8

ANOVA and Multiple Comparisons test (Scheffe) ............................................................................. 9

Appendix 6: Pre test 2 – Mean scores humor scale ............................................................................... 22

Appendix 7: Outputs Reliability Analyses ............................................................................................ 22

Scale Involvement ............................................................................................................................. 22

Scale Hedonism ................................................................................................................................. 23

Scale Utilitarianism ........................................................................................................................... 24

Scale Perceived humour .................................................................................................................... 24

Scale Attitude towards the ad ............................................................................................................ 25

Scale Attitude towards the brand ....................................................................................................... 26

Scale Purchase intention .................................................................................................................... 26

Scale Credibility ................................................................................................................................ 27

Appendix 8: Output Manipulation check .............................................................................................. 28

Correlation ......................................................................................................................................... 28

T-test .................................................................................................................................................. 28

Appendix 9: Mediator - effect ............................................................................................................... 29

Step 1 ................................................................................................................................................. 29

Step 2 ................................................................................................................................................. 29

Step 3 ................................................................................................................................................. 30

Step 4 ................................................................................................................................................. 30

Appendix 10: Moderating effects (MANOVA) .................................................................................... 31

Appendix 11: Credibility per product.................................................................................................... 39

Output 12: Socio-demographic differences ........................................................................................... 42

Gender: T-tests .................................................................................................................................. 42

Level of education: ANOVA............................................................................................................. 45

Age categories: ANOVA ................................................................................................................... 50

2��

Appendix 1: Online survey Pre test 1 – product classification 12 products:

• Insurance • Soft drink • Perfume • Car

• Printer • Chocolate bar • Beer • Mobile phone

• Paper tissues • Computer • Detergent • Toothpaste

Onbelangrijk Belangrijk Irrelevant Relevant Zegt mij niets Zegt mij veel Waardeloos Waardevol Oninteressant Interessant Niet opwindend Opwindend Onaantrekkelijk Aantrekkelijk Alledaags Fascinerend Onnodig Nodig Niet bij betrokken Erbij betrokken Niet efficiënt Efficiënt Niet probleemoplossend Probleemoplossend Niet functioneel Functioneel Overbodig Noodzakelijk Onpraktisch Praktisch Niet leuk Leuk Saai Opwindend Niet vermakelijk Vermakelijk Niet spannend Spannend Niet prettig Prettig Appendix 2: Face to face survey Pre test 2 – Perceived humour Ik vind deze advertentie... -4 -3 -2 -1 0 +1 +2 +3 +4 Niet humoristisch Humoristisch Niet grappig Grappig Niet speels Speels Niet leuk Leuk Niet saai Saai Niet vervelend Vervelend �

3��

Appendix 3: Initial online survey

�

De effectiviteit van humoristische vs rationele appeals in print advertenties voor utilitaire en hedonistische producten.

In het kader van mijn masterproef voer ik een onderzoek naar de effectiviteit van reclame voor verschillende producten. U kunt me hierbij helpen door het invullen van een vragenlijst. Deze vraagt ongeveer 5 minuten van uw tijd. Gelieve de advertentie die u zal te zien krijgen aandachtig te bekijken en vervolgens de vragenlijst te vervolledigen. Er zijn hierbij geen juiste of foute antwoorden. Uw antwoorden zullen op een volstrekt anonieme manier behandeld worden. Alvast bedankt voor uw medewerking! Tim De Geyter Master Communicatiewetenschappen – Universiteit Gent �

4��

Gelieve deze advertentie aandachtig te bekijken en op elke vraag te antwoorden. Deze enquête is volledig anoniem en er bestaan geen foute antwoorden. �

Hieronder ziet u telkens een aantal tegenstellingen. Het is de bedoeling dat u voor elke tegenstelling aanduidt welke term (links of rechts) volgens u het meest van toepassing is op deze advertentie. Is volgens u de linkse term het meest van toepassing, dan duidt u het bolletje aan de linkerkant aan. Vindt u daarentegen de term aan de rechterkant het meest van toepassing, dan duidt u het bolletje het meest rechts aan. Indien u vindt dat beide termen evenveel van toepassing zijn, dan duidt u de optie in het midden aan.

Wat is uw houding t.o.v. deze advertentie?

Negatief Positief

Ik hou er niet van Ik hou er van

Niet wenselijk Wenselijk

Slecht Goed

Hoe geloofwaardig acht u deze advertentie?

Helemaal niet betrouwbaar Zeer betrouwbaar

Helemaal niet oprecht Zeer oprecht

Helemaal niet aanvaardbaar Zeer aanvaardbaar

Helemaal niet geloofwaardig

Zeer geloofwaardig

�����������

5��

Wat is uw mening over deze advertentie? Indien u vindt dat de uitspraak niet bij het merk NOVA past, dan duidt u de meest linkse kolom aan. Als u neutraal staat ten opzichte van de uitspraak, dan duidt u de middelste kolom aan. Als u de uitspraak zeer sterk van toepassing vindt op het merk NOVA, dan duidt u de meest rechtse kolom aan.

Helemaal

niet akkoord

Niet akkoord Neutraal Eerder

akkoord Akkoord Helemaal akkoord

Ik vind deze advertentie grappig

Ik vind deze advertentie leuk

We zijn ook geïnteresseerd in uw houding ten opzichte van het merk 'NOVA'

Het merk NOVA is een slecht merk Het merk NOVA is

een goed merk

Ik hou niet van het merk NOVA Ik hou van het merk

NOVA

Het merk NOVA is niet wenselijk Het merk NOVA is

wenselijk

Ik sta negatief t.o.v. het merk NOVA

Ik sta positief t.o.v. het merk NOVA

Veronderstel dat de aankoop van dit product voor u financieel haalbaar is. Hoe waarschijnlijk is het dat u het merk NOVA zou aankopen?

Helemaal

niet akkoord

Niet akkoord Neutraal Eerder

akkoord Akkoord Helemaal akkoord

Het lijkt met een goed idee om het merk NOVA te kopen

Het is heel waarschijnlijk dat ik het merk NOVA koop bij de volgende aankoop van (productcategorie)

Het is mogelijk dat ik het merk NOVA ooit zal kopen

6��

Hoe staat u tegenover parfum in het algemeen?

Helemaal

niet akkoord

Niet akkoord Neutraal Eerder

akkoord Akkoord Helemaal akkoord

In het algemeen heb ik een grote interesse in deze productcategorie

Deze productcategorie is zeer belangrijk voor mij

Deze productcategorie betekent veel voor mij

Ik geraak verveeld wanneer anderen tegen mij praten over deze productcategorie

Wat verwacht u in een advertentie voor dit product?

Helemaal

niet akkoord

Niet akkoord Neutraal Eerder

akkoord Akkoord Helemaal akkoord

In een advertentie voor (product) ga ik vooral op zoek naar informatie

In een advertentie voor (product) is informatie minder belangrijk en wil ik vooral vermaakt worden

Tot slot nog een aantal algemene vragen (deze worden eveneens anoniem verwerkt) Wat is uw geslacht?

o Man o Vrouw Wat is uw geboortejaar? 19.. Wat is uw hoogst behaalde diploma?

o Lager onderwijs o Middelbaar onderwijs o Hoger onderwijs van het korte type (bachelor / graduaat) o Hoger onderwijs van het lange type (master / licentiaat) o Post universitair

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Appendix 4: Advertisements

1 2

3

4

5

6

7 8

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Appendix 5: Pre test 1

Factor analysis

Communalities

Initial Extraction

HEDEffectief 1,000 ,857

HEDProbleemopl 1,000 ,868

HEDFunctioneel 1,000 ,881

HEDNoodzakelijk 1,000 ,760

HEDPraktisch 1,000 ,810

HEDLeuk 1,000 ,807

HEDOpwindend 1,000 ,838

HEDVermakelijk 1,000 ,858

HEDSpannend 1,000 ,803

HEDPrettig 1,000 ,790

Extraction Method: Principal Component Analysis.

Total Variance Explained

Comp

onent

Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 4,593 45,931 45,931 4,593 45,931 45,931 4,150 41,504 41,504

2 3,677 36,774 82,705 3,677 36,774 82,705 4,120 41,201 82,705

3 ,349 3,487 86,192

4 ,314 3,136 89,328

5 ,230 2,298 91,626

6 ,208 2,077 93,702

7 ,190 1,902 95,605

8 ,173 1,729 97,334

9 ,148 1,482 98,816

10 ,118 1,184 100,000

Extraction Method: Principal Component

Analysis.

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Rotated Component Matrixa

Component

1 2

HEDFunctioneel ,939 ,006

HEDProbleemopl ,931 -,008

HEDEffectief ,912 ,160

HEDPraktisch ,890 ,134

HEDNoodzakelijk ,871 -,029

HEDVermakelijk ,012 ,926

HEDOpwindend -,008 ,915

HEDLeuk ,091 ,894

HEDSpannend ,068 ,893

HEDPrettig ,083 ,885

Extraction Method: Principal Component

Analysis.

Rotation Method: Varimax with Kaiser

Normalization.

a. Rotation converged in 3 iterations. �

ANOVA and Multiple Comparisons test (Scheffe)

ANOVA

Sum of Squares df Mean Square F Sig.

Involvement Between Groups 368,378 11 33,489 23,754 ,000

Within Groups 648,513 460 1,410

Total 1016,892 471

Hedonic Between Groups 470,659 11 42,787 22,606 ,000

Within Groups 863,086 456 1,893

Total 1333,745 467

Utilitarian Between Groups 1124,688 11 102,244 94,743 ,000

Within Groups 494,263 458 1,079

Total 1618,951 469

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Multiple Comparisons

Scheffe

Dependent

Variable (I) Producten (J) Producten

Mean

Difference (I-J) Std. Error Sig.

95% Confidence Interval

Lower Bound Upper Bound

Involvement insurance soft drink 1,33686* ,26720 ,010 ,1448 2,5289

perfume -,20814 ,26720 1,000 -1,4002 ,9839

detergent ,71436 ,26720 ,786 -,4777 1,9064

mobile phone -,58064 ,26720 ,943 -1,7727 ,6114

toothpaste -,42051 ,26888 ,996 -1,6201 ,7791

beer 1,77436* ,26720 ,000 ,5823 2,9664

computer -1,00459 ,27065 ,250 -2,2121 ,2029

car -,93064 ,26720 ,357 -2,1227 ,2614

chocolate bar ,82436 ,27065 ,597 -,3831 2,0318

paper tissues 1,17949 ,26888 ,060 -,0201 2,3791

printer ,02308 ,26888 1,000 -1,1765 1,2227

soft drink insurance -1,33686* ,26720 ,010 -2,5289 -,1448

perfume -1,54500* ,26550 ,001 -2,7295 -,3605

detergent -,62250 ,26550 ,904 -1,8070 ,5620

mobile phone -1,91750* ,26550 ,000 -3,1020 -,7330

toothpaste -1,75737* ,26720 ,000 -2,9494 -,5653

beer ,43750 ,26550 ,994 -,7470 1,6220

computer -2,34145* ,26897 ,000 -3,5414 -1,1415

car -2,26750* ,26550 ,000 -3,4520 -1,0830

chocolate bar -,51250 ,26897 ,979 -1,7125 ,6875

paper tissues -,15737 ,26720 1,000 -1,3494 1,0347

printer -1,31378* ,26720 ,014 -2,5059 -,1217

perfume insurance ,20814 ,26720 1,000 -,9839 1,4002

soft drink 1,54500* ,26550 ,001 ,3605 2,7295

detergent ,92250 ,26550 ,361 -,2620 2,1070

mobile phone -,37250 ,26550 ,999 -1,5570 ,8120

toothpaste -,21237 ,26720 1,000 -1,4044 ,9797

11��

beer 1,98250* ,26550 ,000 ,7980 3,1670

computer -,79645 ,26897 ,643 -1,9964 ,4035

car -,72250 ,26550 ,764 -1,9070 ,4620

chocolate bar 1,03250 ,26897 ,199 -,1675 2,2325

paper tissues 1,38763* ,26720 ,006 ,1956 2,5797

printer ,23122 ,26720 1,000 -,9609 1,4233

detergent insurance -,71436 ,26720 ,786 -1,9064 ,4777

soft drink ,62250 ,26550 ,904 -,5620 1,8070

perfume -,92250 ,26550 ,361 -2,1070 ,2620

mobile phone -1,29500* ,26550 ,015 -2,4795 -,1105

toothpaste -1,13487 ,26720 ,085 -2,3269 ,0572

beer 1,06000 ,26550 ,148 -,1245 2,2445

computer -1,71895* ,26897 ,000 -2,9189 -,5190

car -1,64500* ,26550 ,000 -2,8295 -,4605

chocolate bar ,11000 ,26897 1,000 -1,0900 1,3100

paper tissues ,46513 ,26720 ,990 -,7269 1,6572

printer -,69128 ,26720 ,822 -1,8834 ,5008

mobile phone insurance ,58064 ,26720 ,943 -,6114 1,7727

soft drink 1,91750* ,26550 ,000 ,7330 3,1020

perfume ,37250 ,26550 ,999 -,8120 1,5570

detergent 1,29500* ,26550 ,015 ,1105 2,4795

toothpaste ,16013 ,26720 1,000 -1,0319 1,3522

beer 2,35500* ,26550 ,000 1,1705 3,5395

computer -,42395 ,26897 ,996 -1,6239 ,7760

car -,35000 ,26550 ,999 -1,5345 ,8345

chocolate bar 1,40500* ,26897 ,005 ,2050 2,6050

paper tissues 1,76013* ,26720 ,000 ,5681 2,9522

printer ,60372 ,26720 ,925 -,5884 1,7958

toothpaste insurance ,42051 ,26888 ,996 -,7791 1,6201

soft drink 1,75737* ,26720 ,000 ,5653 2,9494

perfume ,21237 ,26720 1,000 -,9797 1,4044

detergent 1,13487 ,26720 ,085 -,0572 2,3269

mobile phone -,16013 ,26720 1,000 -1,3522 1,0319

12��

beer 2,19487* ,26720 ,000 1,0028 3,3869

computer -,58408 ,27065 ,946 -1,7915 ,6234

car -,51013 ,26720 ,979 -1,7022 ,6819

chocolate bar 1,24487* ,27065 ,035 ,0374 2,4523

paper tissues 1,60000* ,26888 ,000 ,4004 2,7996

printer ,44359 ,26888 ,994 -,7560 1,6432

beer insurance -1,77436* ,26720 ,000 -2,9664 -,5823

soft drink -,43750 ,26550 ,994 -1,6220 ,7470

perfume -1,98250* ,26550 ,000 -3,1670 -,7980

detergent -1,06000 ,26550 ,148 -2,2445 ,1245

mobile phone -2,35500* ,26550 ,000 -3,5395 -1,1705

toothpaste -2,19487* ,26720 ,000 -3,3869 -1,0028

computer -2,77895* ,26897 ,000 -3,9789 -1,5790

car -2,70500* ,26550 ,000 -3,8895 -1,5205

chocolate bar -,95000 ,26897 ,332 -2,1500 ,2500

paper tissues -,59487 ,26720 ,932 -1,7869 ,5972

printer -1,75128* ,26720 ,000 -2,9434 -,5592

computer insurance 1,00459 ,27065 ,250 -,2029 2,2121

soft drink 2,34145* ,26897 ,000 1,1415 3,5414

perfume ,79645 ,26897 ,643 -,4035 1,9964

detergent 1,71895* ,26897 ,000 ,5190 2,9189

mobile phone ,42395 ,26897 ,996 -,7760 1,6239

toothpaste ,58408 ,27065 ,946 -,6234 1,7915

beer 2,77895* ,26897 ,000 1,5790 3,9789

car ,07395 ,26897 1,000 -1,1260 1,2739

chocolate bar 1,82895* ,27240 ,000 ,6137 3,0442

paper tissues 2,18408* ,27065 ,000 ,9766 3,3915

printer 1,02767 ,27065 ,215 -,1798 2,2351

car insurance ,93064 ,26720 ,357 -,2614 2,1227

soft drink 2,26750* ,26550 ,000 1,0830 3,4520

perfume ,72250 ,26550 ,764 -,4620 1,9070

detergent 1,64500* ,26550 ,000 ,4605 2,8295

mobile phone ,35000 ,26550 ,999 -,8345 1,5345

13��

toothpaste ,51013 ,26720 ,979 -,6819 1,7022

beer 2,70500* ,26550 ,000 1,5205 3,8895

computer -,07395 ,26897 1,000 -1,2739 1,1260

chocolate bar 1,75500* ,26897 ,000 ,5550 2,9550

paper tissues 2,11013* ,26720 ,000 ,9181 3,3022

printer ,95372 ,26720 ,314 -,2384 2,1458

chocolate bar insurance -,82436 ,27065 ,597 -2,0318 ,3831

soft drink ,51250 ,26897 ,979 -,6875 1,7125

perfume -1,03250 ,26897 ,199 -2,2325 ,1675

detergent -,11000 ,26897 1,000 -1,3100 1,0900

mobile phone -1,40500* ,26897 ,005 -2,6050 -,2050

toothpaste -1,24487* ,27065 ,035 -2,4523 -,0374

beer ,95000 ,26897 ,332 -,2500 2,1500

computer -1,82895* ,27240 ,000 -3,0442 -,6137

car -1,75500* ,26897 ,000 -2,9550 -,5550

paper tissues ,35513 ,27065 ,999 -,8523 1,5626

printer -,80128 ,27065 ,643 -2,0087 ,4062

paper tissues insurance -1,17949 ,26888 ,060 -2,3791 ,0201

soft drink ,15737 ,26720 1,000 -1,0347 1,3494

perfume -1,38763* ,26720 ,006 -2,5797 -,1956

detergent -,46513 ,26720 ,990 -1,6572 ,7269

mobile phone -1,76013* ,26720 ,000 -2,9522 -,5681

toothpaste -1,60000* ,26888 ,000 -2,7996 -,4004

beer ,59487 ,26720 ,932 -,5972 1,7869

computer -2,18408* ,27065 ,000 -3,3915 -,9766

car -2,11013* ,26720 ,000 -3,3022 -,9181

chocolate bar -,35513 ,27065 ,999 -1,5626 ,8523

printer -1,15641 ,26888 ,075 -2,3560 ,0432

printer insurance -,02308 ,26888 1,000 -1,2227 1,1765

soft drink 1,31378* ,26720 ,014 ,1217 2,5059

perfume -,23122 ,26720 1,000 -1,4233 ,9609

detergent ,69128 ,26720 ,822 -,5008 1,8834

mobile phone -,60372 ,26720 ,925 -1,7958 ,5884

14��

toothpaste -,44359 ,26888 ,994 -1,6432 ,7560

beer 1,75128* ,26720 ,000 ,5592 2,9434

computer -1,02767 ,27065 ,215 -2,2351 ,1798

car -,95372 ,26720 ,314 -2,1458 ,2384

chocolate bar ,80128 ,27065 ,643 -,4062 2,0087

paper tissues 1,15641 ,26888 ,075 -,0432 2,3560

Hedonic insurance soft drink -2,00500* ,30763 ,000 -3,3775 -,6325

perfume -3,01500* ,30763 ,000 -4,3875 -1,6425

detergent -,78179 ,30960 ,846 -2,1631 ,5995

mobile phone -2,80000* ,30763 ,000 -4,1725 -1,4275

toothpaste -1,46676* ,31380 ,028 -2,8668 -,0667

beer -1,83432* ,31380 ,000 -3,2344 -,4342

computer -3,10474* ,31165 ,000 -4,4952 -1,7143

car -2,99205* ,30960 ,000 -4,3734 -1,6107

chocolate bar -2,24500* ,30763 ,000 -3,6175 -,8725

paper tissues -,59718 ,30960 ,977 -1,9785 ,7841

printer -1,24333 ,30960 ,141 -2,6246 ,1380

soft drink insurance 2,00500* ,30763 ,000 ,6325 3,3775

perfume -1,01000 ,30763 ,464 -2,3825 ,3625

detergent 1,22321 ,30960 ,161 -,1581 2,6045

mobile phone -,79500 ,30763 ,823 -2,1675 ,5775

toothpaste ,53824 ,31380 ,991 -,8618 1,9383

beer ,17068 ,31380 1,000 -1,2294 1,5708

computer -1,09974 ,31165 ,334 -2,4902 ,2907

car -,98705 ,30960 ,517 -2,3684 ,3943

chocolate bar -,24000 ,30763 1,000 -1,6125 1,1325

paper tissues 1,40782* ,30960 ,040 ,0265 2,7891

printer ,76167 ,30960 ,869 -,6196 2,1430

perfume insurance 3,01500* ,30763 ,000 1,6425 4,3875

soft drink 1,01000 ,30763 ,464 -,3625 2,3825

detergent 2,23321* ,30960 ,000 ,8519 3,6145

mobile phone ,21500 ,30763 1,000 -1,1575 1,5875

toothpaste 1,54824* ,31380 ,013 ,1482 2,9483

beer 1,18068 ,31380 ,229 -,2194 2,5808

15��

computer -,08974 ,31165 1,000 -1,4802 1,3007

car ,02295 ,30960 1,000 -1,3584 1,4043

chocolate bar ,77000 ,30763 ,854 -,6025 2,1425

paper tissues 2,41782* ,30960 ,000 1,0365 3,7991

printer 1,77167* ,30960 ,001 ,3904 3,1530

detergent insurance ,78179 ,30960 ,846 -,5995 2,1631

soft drink -1,22321 ,30960 ,161 -2,6045 ,1581

perfume -2,23321* ,30960 ,000 -3,6145 -,8519

mobile phone -2,01821* ,30960 ,000 -3,3995 -,6369

toothpaste -,68496 ,31573 ,944 -2,0936 ,7237

beer -1,05253 ,31573 ,436 -2,4612 ,3562

computer -2,32294* ,31359 ,000 -3,7221 -,9238

car -2,21026* ,31155 ,000 -3,6003 -,8202

chocolate bar -1,46321* ,30960 ,024 -2,8445 -,0819

paper tissues ,18462 ,31155 1,000 -1,2054 1,5746

printer -,46154 ,31155 ,998 -1,8516 ,9285

mobile phone insurance 2,80000* ,30763 ,000 1,4275 4,1725

soft drink ,79500 ,30763 ,823 -,5775 2,1675

perfume -,21500 ,30763 1,000 -1,5875 1,1575

detergent 2,01821* ,30960 ,000 ,6369 3,3995

toothpaste 1,33324 ,31380 ,084 -,0668 2,7333

beer ,96568 ,31380 ,579 -,4344 2,3658

computer -,30474 ,31165 1,000 -1,6952 1,0857

car -,19205 ,30960 1,000 -1,5734 1,1893

chocolate bar ,55500 ,30763 ,987 -,8175 1,9275

paper tissues 2,20282* ,30960 ,000 ,8215 3,5841

printer 1,55667* ,30960 ,010 ,1754 2,9380

toothpaste insurance 1,46676* ,31380 ,028 ,0667 2,8668

soft drink -,53824 ,31380 ,991 -1,9383 ,8618

perfume -1,54824* ,31380 ,013 -2,9483 -,1482

detergent ,68496 ,31573 ,944 -,7237 2,0936

mobile phone -1,33324 ,31380 ,084 -2,7333 ,0668

beer -,36757 ,31986 1,000 -1,7947 1,0595

computer -1,63798* ,31775 ,006 -3,0557 -,2203

16��

car -1,52529* ,31573 ,018 -2,9340 -,1166

chocolate bar -,77824 ,31380 ,862 -2,1783 ,6218

paper tissues ,86958 ,31573 ,749 -,5391 2,2783

printer ,22342 ,31573 1,000 -1,1853 1,6321

beer insurance 1,83432* ,31380 ,000 ,4342 3,2344

soft drink -,17068 ,31380 1,000 -1,5708 1,2294

perfume -1,18068 ,31380 ,229 -2,5808 ,2194

detergent 1,05253 ,31573 ,436 -,3562 2,4612

mobile phone -,96568 ,31380 ,579 -2,3658 ,4344

toothpaste ,36757 ,31986 1,000 -1,0595 1,7947

computer -1,27041 ,31775 ,146 -2,6881 ,1473

car -1,15773 ,31573 ,269 -2,5664 ,2510

chocolate bar -,41068 ,31380 ,999 -1,8108 ,9894

paper tissues 1,23714 ,31573 ,171 -,1715 2,6458

printer ,59099 ,31573 ,982 -,8177 1,9997

computer insurance 3,10474* ,31165 ,000 1,7143 4,4952

soft drink 1,09974 ,31165 ,334 -,2907 2,4902

perfume ,08974 ,31165 1,000 -1,3007 1,4802

detergent 2,32294* ,31359 ,000 ,9238 3,7221

mobile phone ,30474 ,31165 1,000 -1,0857 1,6952

toothpaste 1,63798* ,31775 ,006 ,2203 3,0557

beer 1,27041 ,31775 ,146 -,1473 2,6881

car ,11269 ,31359 1,000 -1,2865 1,5118

chocolate bar ,85974 ,31165 ,747 -,5307 2,2502

paper tissues 2,50756* ,31359 ,000 1,1084 3,9067

printer 1,86140* ,31359 ,000 ,4623 3,2605

car insurance 2,99205* ,30960 ,000 1,6107 4,3734

soft drink ,98705 ,30960 ,517 -,3943 2,3684

perfume -,02295 ,30960 1,000 -1,4043 1,3584

detergent 2,21026* ,31155 ,000 ,8202 3,6003

mobile phone ,19205 ,30960 1,000 -1,1893 1,5734

toothpaste 1,52529* ,31573 ,018 ,1166 2,9340

beer 1,15773 ,31573 ,269 -,2510 2,5664

computer -,11269 ,31359 1,000 -1,5118 1,2865

17��

chocolate bar ,74705 ,30960 ,884 -,6343 2,1284

paper tissues 2,39487* ,31155 ,000 1,0048 3,7849

printer 1,74872* ,31155 ,001 ,3587 3,1387

chocolate bar insurance 2,24500* ,30763 ,000 ,8725 3,6175

soft drink ,24000 ,30763 1,000 -1,1325 1,6125

perfume -,77000 ,30763 ,854 -2,1425 ,6025

detergent 1,46321* ,30960 ,024 ,0819 2,8445

mobile phone -,55500 ,30763 ,987 -1,9275 ,8175

toothpaste ,77824 ,31380 ,862 -,6218 2,1783

beer ,41068 ,31380 ,999 -,9894 1,8108

computer -,85974 ,31165 ,747 -2,2502 ,5307

car -,74705 ,30960 ,884 -2,1284 ,6343

paper tissues 1,64782* ,30960 ,004 ,2665 3,0291

printer 1,00167 ,30960 ,490 -,3796 2,3830

paper tissues insurance ,59718 ,30960 ,977 -,7841 1,9785

soft drink -1,40782* ,30960 ,040 -2,7891 -,0265

perfume -2,41782* ,30960 ,000 -3,7991 -1,0365

detergent -,18462 ,31155 1,000 -1,5746 1,2054

mobile phone -2,20282* ,30960 ,000 -3,5841 -,8215

toothpaste -,86958 ,31573 ,749 -2,2783 ,5391

beer -1,23714 ,31573 ,171 -2,6458 ,1715

computer -2,50756* ,31359 ,000 -3,9067 -1,1084

car -2,39487* ,31155 ,000 -3,7849 -1,0048

chocolate bar -1,64782* ,30960 ,004 -3,0291 -,2665

printer -,64615 ,31155 ,959 -2,0362 ,7439

printer insurance 1,24333 ,30960 ,141 -,1380 2,6246

soft drink -,76167 ,30960 ,869 -2,1430 ,6196

perfume -1,77167* ,30960 ,001 -3,1530 -,3904

detergent ,46154 ,31155 ,998 -,9285 1,8516

mobile phone -1,55667* ,30960 ,010 -2,9380 -,1754

toothpaste -,22342 ,31573 1,000 -1,6321 1,1853

beer -,59099 ,31573 ,982 -1,9997 ,8177

computer -1,86140* ,31359 ,000 -3,2605 -,4623

car -1,74872* ,31155 ,001 -3,1387 -,3587

18��

chocolate bar -1,00167 ,30960 ,490 -2,3830 ,3796

paper tissues ,64615 ,31155 ,959 -,7439 2,0362

Utilitarian insurance soft drink 2,66372* ,23377 ,000 1,6207 3,7067

perfume 1,49500* ,23229 ,000 ,4586 2,5314

detergent -,63885 ,23377 ,759 -1,6818 ,4041

mobile phone -,45868 ,23533 ,975 -1,5086 ,5912

toothpaste -,84397 ,23377 ,295 -1,8870 ,1990

beer 3,26885* ,23377 ,000 2,2259 4,3118

computer -,91064 ,23377 ,179 -1,9536 ,1324

car -,80000 ,23229 ,377 -1,8364 ,2364

chocolate bar 2,89000* ,23229 ,000 1,8536 3,9264

paper tissues ,10974 ,23533 1,000 -,9402 1,1597

printer -,72090 ,23377 ,575 -1,7639 ,3221

soft drink insurance -2,66372* ,23377 ,000 -3,7067 -1,6207

perfume -1,16872* ,23377 ,011 -2,2117 -,1257

detergent -3,30256* ,23525 ,000 -4,3521 -2,2530

mobile phone -3,12240* ,23679 ,000 -4,1789 -2,0659

toothpaste -3,50769* ,23525 ,000 -4,5573 -2,4581

beer ,60513 ,23525 ,828 -,4444 1,6547

computer -3,57436* ,23525 ,000 -4,6239 -2,5248

car -3,46372* ,23377 ,000 -4,5067 -2,4207

chocolate bar ,22628 ,23377 1,000 -,8167 1,2693

paper tissues -2,55398* ,23679 ,000 -3,6104 -1,4975

printer -3,38462* ,23525 ,000 -4,4342 -2,3350

perfume insurance -1,49500* ,23229 ,000 -2,5314 -,4586

soft drink 1,16872* ,23377 ,011 ,1257 2,2117

detergent -2,13385* ,23377 ,000 -3,1768 -1,0909

mobile phone -1,95368* ,23533 ,000 -3,0036 -,9038

toothpaste -2,33897* ,23377 ,000 -3,3820 -1,2960

beer 1,77385* ,23377 ,000 ,7309 2,8168

computer -2,40564* ,23377 ,000 -3,4486 -1,3626

car -2,29500* ,23229 ,000 -3,3314 -1,2586

chocolate bar 1,39500* ,23229 ,000 ,3586 2,4314

paper tissues -1,38526* ,23533 ,000 -2,4352 -,3353

19��

printer -2,21590* ,23377 ,000 -3,2589 -1,1729

detergent insurance ,63885 ,23377 ,759 -,4041 1,6818

soft drink 3,30256* ,23525 ,000 2,2530 4,3521

perfume 2,13385* ,23377 ,000 1,0909 3,1768

mobile phone ,18016 ,23679 1,000 -,8763 1,2366

toothpaste -,20513 ,23525 1,000 -1,2547 ,8444

beer 3,90769* ,23525 ,000 2,8581 4,9573

computer -,27179 ,23525 1,000 -1,3214 ,7778

car -,16115 ,23377 1,000 -1,2041 ,8818

chocolate bar 3,52885* ,23377 ,000 2,4859 4,5718

paper tissues ,74858 ,23679 ,532 -,3079 1,8050

printer -,08205 ,23525 1,000 -1,1316 ,9675

mobile phone insurance ,45868 ,23533 ,975 -,5912 1,5086

soft drink 3,12240* ,23679 ,000 2,0659 4,1789

perfume 1,95368* ,23533 ,000 ,9038 3,0036

detergent -,18016 ,23679 1,000 -1,2366 ,8763

toothpaste -,38529 ,23679 ,994 -1,4417 ,6712

beer 3,72753* ,23679 ,000 2,6711 4,7840

computer -,45196 ,23679 ,979 -1,5084 ,6045

car -,34132 ,23533 ,998 -1,3912 ,7086

chocolate bar 3,34868* ,23533 ,000 2,2988 4,3986

paper tissues ,56842 ,23833 ,892 -,4949 1,6317

printer -,26221 ,23679 1,000 -1,3187 ,7942

toothpaste insurance ,84397 ,23377 ,295 -,1990 1,8870

soft drink 3,50769* ,23525 ,000 2,4581 4,5573

perfume 2,33897* ,23377 ,000 1,2960 3,3820

detergent ,20513 ,23525 1,000 -,8444 1,2547

mobile phone ,38529 ,23679 ,994 -,6712 1,4417

beer 4,11282* ,23525 ,000 3,0632 5,1624

computer -,06667 ,23525 1,000 -1,1162 ,9829

car ,04397 ,23377 1,000 -,9990 1,0870

chocolate bar 3,73397* ,23377 ,000 2,6910 4,7770

paper tissues ,95371 ,23679 ,138 -,1027 2,0102

printer ,12308 ,23525 1,000 -,9265 1,1727

20��

beer insurance -3,26885* ,23377 ,000 -4,3118 -2,2259

soft drink -,60513 ,23525 ,828 -1,6547 ,4444

perfume -1,77385* ,23377 ,000 -2,8168 -,7309

detergent -3,90769* ,23525 ,000 -4,9573 -2,8581

mobile phone -3,72753* ,23679 ,000 -4,7840 -2,6711

toothpaste -4,11282* ,23525 ,000 -5,1624 -3,0632

computer -4,17949* ,23525 ,000 -5,2291 -3,1299

car -4,06885* ,23377 ,000 -5,1118 -3,0259

chocolate bar -,37885 ,23377 ,995 -1,4218 ,6641

paper tissues -3,15911* ,23679 ,000 -4,2156 -2,1027

printer -3,98974* ,23525 ,000 -5,0393 -2,9402

computer insurance ,91064 ,23377 ,179 -,1324 1,9536

soft drink 3,57436* ,23525 ,000 2,5248 4,6239

perfume 2,40564* ,23377 ,000 1,3626 3,4486

detergent ,27179 ,23525 1,000 -,7778 1,3214

mobile phone ,45196 ,23679 ,979 -,6045 1,5084

toothpaste ,06667 ,23525 1,000 -,9829 1,1162

beer 4,17949* ,23525 ,000 3,1299 5,2291

car ,11064 ,23377 1,000 -,9324 1,1536

chocolate bar 3,80064* ,23377 ,000 2,7576 4,8436

paper tissues 1,02038 ,23679 ,073 -,0361 2,0768

printer ,18974 ,23525 1,000 -,8598 1,2393

car insurance ,80000 ,23229 ,377 -,2364 1,8364

soft drink 3,46372* ,23377 ,000 2,4207 4,5067

perfume 2,29500* ,23229 ,000 1,2586 3,3314

detergent ,16115 ,23377 1,000 -,8818 1,2041

mobile phone ,34132 ,23533 ,998 -,7086 1,3912

toothpaste -,04397 ,23377 1,000 -1,0870 ,9990

beer 4,06885* ,23377 ,000 3,0259 5,1118

computer -,11064 ,23377 1,000 -1,1536 ,9324

chocolate bar 3,69000* ,23229 ,000 2,6536 4,7264

paper tissues ,90974 ,23533 ,189 -,1402 1,9597

printer ,07910 ,23377 1,000 -,9639 1,1221

chocolate bar insurance -2,89000* ,23229 ,000 -3,9264 -1,8536

21��

soft drink -,22628 ,23377 1,000 -1,2693 ,8167

perfume -1,39500* ,23229 ,000 -2,4314 -,3586

detergent -3,52885* ,23377 ,000 -4,5718 -2,4859

mobile phone -3,34868* ,23533 ,000 -4,3986 -2,2988

toothpaste -3,73397* ,23377 ,000 -4,7770 -2,6910

beer ,37885 ,23377 ,995 -,6641 1,4218

computer -3,80064* ,23377 ,000 -4,8436 -2,7576

car -3,69000* ,23229 ,000 -4,7264 -2,6536

paper tissues -2,78026* ,23533 ,000 -3,8302 -1,7303

printer -3,61090* ,23377 ,000 -4,6539 -2,5679

paper tissues insurance -,10974 ,23533 1,000 -1,1597 ,9402

soft drink 2,55398* ,23679 ,000 1,4975 3,6104

perfume 1,38526* ,23533 ,000 ,3353 2,4352

detergent -,74858 ,23679 ,532 -1,8050 ,3079

mobile phone -,56842 ,23833 ,892 -1,6317 ,4949

toothpaste -,95371 ,23679 ,138 -2,0102 ,1027

beer 3,15911* ,23679 ,000 2,1027 4,2156

computer -1,02038 ,23679 ,073 -2,0768 ,0361

car -,90974 ,23533 ,189 -1,9597 ,1402

chocolate bar 2,78026* ,23533 ,000 1,7303 3,8302

printer -,83063 ,23679 ,344 -1,8871 ,2258

printer insurance ,72090 ,23377 ,575 -,3221 1,7639

soft drink 3,38462* ,23525 ,000 2,3350 4,4342

perfume 2,21590* ,23377 ,000 1,1729 3,2589

detergent ,08205 ,23525 1,000 -,9675 1,1316

mobile phone ,26221 ,23679 1,000 -,7942 1,3187

toothpaste -,12308 ,23525 1,000 -1,1727 ,9265

beer 3,98974* ,23525 ,000 2,9402 5,0393

computer -,18974 ,23525 1,000 -1,2393 ,8598

car -,07910 ,23377 1,000 -1,1221 ,9639

chocolate bar 3,61090* ,23377 ,000 2,5679 4,6539

paper tissues ,83063 ,23679 ,344 -,2258 1,8871

*. The mean difference is significant at the 0.05 level.

�

22��

�

Appendix 6: Pre test 2 – Mean scores humor scale

Report

Average score humorous of the ad

Adverte

ntienr Mean N Std. Deviation

1,00 2,1222 15 1,53073

2,00 1,4667 15 2,11213

3,00 ,5667 15 2,71811

4,00 2,6333 15 ,96404

5,00 2,6000 15 1,85891

6,00 -,2333 15 2,21449

7,00 2,3222 15 1,28555

8,00 2,6889 15 1,27065

9,00 ,0222 15 2,96398

Total 1,5765 135 2,22294

�

Appendix 7: Outputs Reliability Analyses

�

Scale Involvement

Case Processing Summary

N %

Cases Valid 472 98,3

Excludeda 8 1,7

Total 480 100,0

a. Listwise deletion based on all variables in the

procedure.

Reliability Statistics

Cronbach's

Alpha N of Items

,914 10

23��

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total

Correlation

Cronbach's

Alpha if Item

Deleted

INVBelang 39,2987 171,114 ,782 ,899

INVRelevant 39,3983 172,508 ,757 ,901

INVZegtveel 39,5381 172,720 ,806 ,898

INVWaardevol 39,3602 176,193 ,754 ,902

INVInteressant 39,8898 173,444 ,769 ,900

INVOpwindend 41,2818 184,908 ,511 ,915

INVAantrekkelijk 40,7373 181,421 ,573 ,912

INVFascinerend 41,4258 183,663 ,513 ,916

INVNodig 39,3008 178,818 ,626 ,909

INVBetrokken 39,8877 170,707 ,773 ,900

Scale Hedonism

Case Processing Summary

N %

Cases Valid 470 97,9

Excludeda 10 2,1

Total 480 100,0

Reliability Statistics

Cronbach's

Alpha N of Items

,948 5

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance if

Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

HEDEffectief 20,0021 56,053 ,870 ,934

HEDProbleemopl 20,2617 52,983 ,888 ,931

HEDFunctioneel 19,9447 53,758 ,898 ,928

HEDNoodzakelijk 20,1106 57,826 ,801 ,946

HEDPraktisch 19,7660 59,122 ,839 ,940 �

24��

Scale Utilitarianism

Case Processing Summary

N %

Cases Valid 468 97,5

Excludeda 12 2,5

Total 480 100,0

a. Listwise deletion based on all variables in the

procedure.

Reliability Statistics

Cronbach's

Alpha N of Items

,944 5

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance if

Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

HEDPrettig 14,6218 46,643 ,825 ,935

HEDSpannend 15,4915 47,163 ,835 ,933

HEDVermakelijk 14,9530 44,191 ,880 ,925

HEDOpwindend 15,1175 47,432 ,861 ,929

HEDLeuk 14,4402 46,256 ,839 ,932

Scale Perceived humour

Case Processing Summary

N %

Cases Valid 135 97,8

Excludeda 3 2,2

Total 138 100,0

a. Listwise deletion based on all variables in the

procedure. � �

25��

Reliability Statistics

Cronbach's

Alpha N of Items

,924 6

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance if

Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Humor 7,8667 125,146 ,795 ,909

Grap 7,7481 122,011 ,852 ,901

Speels 8,0370 127,260 ,775 ,911

Leuk 7,9111 120,768 ,837 ,903

Recoded Saai 7,9185 127,031 ,756 ,914

Recoded Vervelend 7,8148 130,227 ,678 ,924

�

Scale Attitude towards the ad

Case Processing Summary

N %

Cases Valid 255 97,0

Excludeda 8 3,0

Total 263 100,0

a. Listwise deletion based on all variables in the

procedure.

Reliability Statistics

Cronbach's

Alpha N of Items

,952 4

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance if

Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Deze advertentie is positief 11,8980 22,336 ,875 ,939

Ik hou van deze advertentie 12,1137 21,786 ,907 ,929

Deze advertentie is wenselijk 12,1020 22,242 ,881 ,937

Deze advertentie is goed 11,9922 22,087 ,866 ,942

26��

Scale Attitude towards the brand

Case Processing Summary

N %

Cases Valid 259 98,5

Excludeda 4 1,5

Total 263 100,0

a. Listwise deletion based on all variables in the

procedure.

Reliability Statistics

Cronbach's

Alpha N of Items

,929 4

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance if

Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

NOVA is een goed merk 11,6371 7,054 ,854 ,901

Ik hou van het merk NOVA 11,7876 7,145 ,825 ,910

NOVA is wenselijk 11,6873 7,193 ,816 ,913

NOVA is positief 11,6950 6,980 ,840 ,905

Scale Purchase intention

Case Processing Summary

N %

Cases Valid 260 98,9

Excludeda 3 1,1

Total 263 100,0

a. Listwise deletion based on all variables in the

procedure.

Reliability Statistics

Cronbach's

Alpha N of Items

,866 3

27��

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance if

Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Goed idee om het merk te

kopen 6,8692 7,597 ,761 ,799

Waarschijnlijk volgende keer

kopen 7,4154 7,294 ,780 ,780

Mogelijk ooit kopen 6,5462 7,314 ,700 ,857

�

Scale Credibility

Case Processing Summary

N %

Cases Valid 254 96,6

Excludeda 9 3,4

Total 263 100,0

a. Listwise deletion based on all variables in the

procedure.

Reliability Statistics

Cronbach's

Alpha N of Items

,926 4

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance if

Item Deleted

Corrected Item-

Total Correlation

Cronbach's

Alpha if Item

Deleted

Deze advertentie is

betrouwbaar 11,6850 16,209 ,883 ,884

Deze advertentie is oprecht 11,7480 16,766 ,847 ,897

Deze advertentie is

aanvaardbaar 11,0197 18,138 ,720 ,937

Deze advertentie is

geloofwaardig 11,6575 15,775 ,863 ,891

� �

28��

Appendix 8: Output Manipulation check

Correlation

Correlations

Deze advertentie

is grappig

Deze advertentie

is leuk

Deze advertentie is grappig Pearson Correlation 1,000 ,847**

Sig. (2-tailed) ,000

N 260 260

Deze advertentie is leuk Pearson Correlation ,847** 1,000

Sig. (2-tailed) ,000

N 260 262

**. Correlation is significant at the 0.01 level (2-tailed).

T-test

Group Statistics

Humor_Ratio

neel N Mean Std. Deviation Std. Error Mean

Waargenomen_humor Humor 124 4,4073 1,86033 ,16706

Rationeel 136 2,5625 1,25379 ,10751

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Appendix 9: Mediator - effect

Step 1

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 ,323a ,104 ,101 ,83439

a. Predictors: (Constant), Waargenomen_humor

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 20,712 1 20,712 29,750 ,000a

Residual 177,532 255 ,696

Total 198,245 256

a. Predictors: (Constant), Waargenomen_humor

b. Dependent Variable: Ab

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 3,360 ,112 30,106 ,000

Waargenomen_humor ,156 ,029 ,323 5,454 ,000

a. Dependent Variable: Ab

Step 2

b. Dependent Variable: Aad

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 ,682a ,465 ,463 1,13978

a. Predictors: (Constant), Waargenomen_humor

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 282,991 1 282,991 217,839 ,000a

Residual 326,071 251 1,299

Total 609,062 252

30��

a. Predictors: (Constant), Waargenomen_humor

b. Dependent Variable: Aad

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 2,019 ,152 13,271 ,000

Waargenomen_humor ,580 ,039 ,682 14,759 ,000

a. Dependent Variable: Aad

Step 3

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 ,483a ,233 ,230 ,75357

a. Predictors: (Constant), Aad

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 43,238 1 43,238 76,142 ,000a

Residual 141,966 250 ,568

Total 185,204 251

a. Predictors: (Constant), Aad

b. Dependent Variable: Ab

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 2,837 ,132 21,467 ,000

Aad ,268 ,031 ,483 8,726 ,000

a. Dependent Variable: Ab

Step 4

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 ,482a ,233 ,227 ,75771

31��

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 ,482a ,233 ,227 ,75771

a. Predictors: (Constant), Waargenomen_humor, Aad

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 43,024 2 21,512 37,470 ,000a

Residual 141,808 247 ,574

Total 184,832 249

a. Predictors: (Constant), Waargenomen_humor, Aad

b. Dependent Variable: Ab

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 2,834 ,133 21,251 ,000

Aad ,255 ,042 ,460 6,056 ,000

Waargenomen_humor ,015 ,036 ,033 ,433 ,665

a. Dependent Variable: Ab

Appendix 10: Moderating effects (MANOVA)

Between-Subjects Factors

Value Label N

Humor_Rationeel 1,00 Humor 116

2,00 Rationeel 130

Utilitair of Hedonistisch 1,00 Utilitair 121

2,00 Hedonistisch 125

High of low involved 1,00 High involved 115

2,00 Low involved 131

32��

Multivariate Testsb

Effect Value F Hypothesis df Error df Sig.

Intercept Pillai's Trace ,957 1,314E3 4,000 235,000 ,000

Wilks' Lambda ,043 1,314E3 4,000 235,000 ,000

Hotelling's Trace 22,359 1,314E3 4,000 235,000 ,000

Roy's Largest Root 22,359 1,314E3 4,000 235,000 ,000

Appeal Pillai's Trace ,085 5,471a 4,000 235,000 ,000

Wilks' Lambda ,915 5,471a 4,000 235,000 ,000

Hotelling's Trace ,093 5,471a 4,000 235,000 ,000

Roy's Largest Root ,093 5,471a 4,000 235,000 ,000

Producttype Pillai's Trace ,096 6,248a 4,000 235,000 ,000

Wilks' Lambda ,904 6,248a 4,000 235,000 ,000

Hotelling's Trace ,106 6,248a 4,000 235,000 ,000

Roy's Largest Root ,106 6,248a 4,000 235,000 ,000

ProductInvolvement Pillai's Trace ,026 1,595a 4,000 235,000 ,176

Wilks' Lambda ,974 1,595a 4,000 235,000 ,176

Hotelling's Trace ,027 1,595a 4,000 235,000 ,176

Roy's Largest Root ,027 1,595a 4,000 235,000 ,176

Appeal * Producttype Pillai's Trace ,020 1,188a 4,000 235,000 ,317

Wilks' Lambda ,980 1,188a 4,000 235,000 ,317

Hotelling's Trace ,020 1,188a 4,000 235,000 ,317

Roy's Largest Root ,020 1,188a 4,000 235,000 ,317

Appeal * ProductInvolvement Pillai's Trace ,145 9,926a 4,000 235,000 ,000

Wilks' Lambda ,855 9,926a 4,000 235,000 ,000

Hotelling's Trace ,169 9,926a 4,000 235,000 ,000

Roy's Largest Root ,169 9,926a 4,000 235,000 ,000

Producttype *

ProductInvolvement

Pillai's Trace ,009 ,558a 4,000 235,000 ,694

Wilks' Lambda ,991 ,558a 4,000 235,000 ,694

Hotelling's Trace ,009 ,558a 4,000 235,000 ,694

Roy's Largest Root ,009 ,558a 4,000 235,000 ,694

Appeal * Producttype * Pillai's Trace ,032 1,939a 4,000 235,000 ,105

33��

ProductInvolvement Wilks' Lambda ,968 1,939a 4,000 235,000 ,105

Hotelling's Trace ,033 1,939a 4,000 235,000 ,105

Roy's Largest Root ,033 1,939a 4,000 235,000 ,105

a. Exact statistic

b. Design: Intercept + Appeal + Producttype + ProductInvolvement + Appeal * Producttype + Appeal *

ProductInvolvement + Producttype * ProductInvolvement + Appeal * Producttype * ProductInvolvement

Tests of Between-Subjects Effects

Source

Dependent

Variable

Type III Sum of

Squares df Mean Square F Sig.

Corrected Model Aad 17,358a 7 2,480 1,034 ,408

Ab 2,741b 7 ,392 ,511 ,826

PI 18,050c 7 2,579 1,526 ,159

Credibility 64,717d 7 9,245 5,921 ,000

Intercept Aad 4007,826 1 4007,826 1670,603 ,000

Ab 3721,711 1 3721,711 4860,557 ,000

PI 2934,026 1 2934,026 1735,926 ,000

Credibility 3610,891 1 3610,891 2312,502 ,000

Appeal Aad 3,099 1 3,099 1,292 ,257

Ab ,205 1 ,205 ,268 ,605

PI ,164 1 ,164 ,097 ,756

Credibility 7,219 1 7,219 4,623 ,033

Producttype Aad ,799 1 ,799 ,333 ,564

Ab 1,243 1 1,243 1,624 ,204

PI 7,369 1 7,369 4,360 ,038

Credibility 22,180 1 22,180 14,205 ,000

ProductInvolvement Aad 4,137 1 4,137 1,725 ,190

Ab ,478 1 ,478 ,624 ,430

PI 4,527 1 4,527 2,679 ,103

Credibility 8,972 1 8,972 5,746 ,017

Appeal * Producttype Aad 4,907 1 4,907 2,045 ,154

Ab ,005 1 ,005 ,006 ,938

PI ,697 1 ,697 ,412 ,521

Credibility 5,256 1 5,256 3,366 ,068

34��

Appeal * ProductInvolvement Aad 4,501 1 4,501 1,876 ,172

Ab ,286 1 ,286 ,373 ,542

PI 4,366 1 4,366 2,583 ,109

Credibility 18,312 1 18,312 11,728 ,001

Producttype *

ProductInvolvement

Aad ,991 1 ,991 ,413 ,521

Ab ,375 1 ,375 ,490 ,485

PI ,049 1 ,049 ,029 ,865

Credibility 2,008 1 2,008 1,286 ,258

Appeal * Producttype *

ProductInvolvement

Aad ,298 1 ,298 ,124 ,725

Ab ,341 1 ,341 ,446 ,505

PI ,224 1 ,224 ,133 ,716

Credibility 4,302 1 4,302 2,755 ,098

Error Aad 570,969 238 2,399

Ab 182,236 238 ,766

PI 402,263 238 1,690

Credibility 371,629 238 1,561

Total Aad 4622,938 246

Ab 3952,812 246

PI 3403,556 246

Credibility 4087,688 246

Corrected Total Aad 588,327 245

Ab 184,977 245

PI 420,313 245

Credibility 436,346 245

a. R Squared = ,030 (Adjusted R Squared = ,001)

b. R Squared = ,015 (Adjusted R Squared = -,014)

c. R Squared = ,043 (Adjusted R Squared = ,015)

d. R Squared = ,148 (Adjusted R Squared = ,123)

Estimated Marginal Means

1. Humor_Rationeel

Dependent

Variable

Humor_Ratio

neel Mean Std. Error

95% Confidence Interval

Lower Bound Upper Bound

Aad Humor 4,176 ,144 3,891 4,460

Rationeel 3,950 ,137 3,681 4,219

35��

Ab Humor 3,944 ,082 3,783 4,105

Rationeel 3,886 ,077 3,734 4,038

PI Humor 3,502 ,121 3,263 3,741

Rationeel 3,450 ,115 3,224 3,676

Credibility Humor 3,684 ,117 3,454 3,913

Rationeel 4,029 ,110 3,812 4,246

2. Utilitair of Hedonistisch

Dependent

Variable

Utilitair of

Hedonistisch Mean Std. Error

95% Confidence Interval

Lower Bound Upper Bound

Aad Utilitair 4,120 ,142 3,840 4,400

Hedonistisch 4,005 ,139 3,732 4,279

Ab Utilitair 3,987 ,080 3,828 4,145

Hedonistisch 3,843 ,078 3,689 3,998

PI Utilitair 3,650 ,119 3,415 3,886

Hedonistisch 3,302 ,116 3,072 3,531

Credibility Utilitair 4,158 ,115 3,932 4,385

Hedonistisch 3,554 ,112 3,333 3,775

3. High of low involved

Dependent

Variable

High of low

involved Mean Std. Error

95% Confidence Interval

Lower Bound Upper Bound

Aad High involved 3,932 ,145 3,647 4,217

Low involved 4,193 ,136 3,925 4,462

Ab High involved 3,871 ,082 3,710 4,032

Low involved 3,959 ,077 3,808 4,111

PI High involved 3,340 ,121 3,100 3,579

Low involved 3,613 ,114 3,387 3,838

Credibility High involved 3,664 ,117 3,434 3,894

Low involved 4,048 ,110 3,832 4,265

36��

4. Humor_Rationeel * Utilitair of Hedonistisch

Dependent

Variable

Humor_Ratio

neel

Utilitair of

Hedonistisch Mean Std. Error

95% Confidence Interval

Lower Bound Upper Bound

Aad Humor Utilitair 4,375 ,213 3,956 4,794

Hedonistisch 3,976 ,195 3,591 4,361

Rationeel Utilitair 3,865 ,189 3,492 4,238

Hedonistisch 4,034 ,197 3,646 4,423

Ab Humor Utilitair 4,011 ,120 3,774 4,248

Hedonistisch 3,877 ,110 3,659 4,094

Rationeel Utilitair 3,962 ,107 3,751 4,172

Hedonistisch 3,810 ,111 3,591 4,029

PI Humor Utilitair 3,730 ,179 3,378 4,082

Hedonistisch 3,274 ,164 2,951 3,597

Rationeel Utilitair 3,571 ,159 3,258 3,884

Hedonistisch 3,330 ,165 3,004 3,655

Credibility Humor Utilitair 4,133 ,172 3,795 4,471

Hedonistisch 3,234 ,158 2,924 3,545

Rationeel Utilitair 4,184 ,153 3,883 4,484

Hedonistisch 3,874 ,159 3,560 4,187

5. Humor_Rationeel * High of low involved

Dependent

Variable

Humor_Ratio

neel

High of low

involved Mean Std. Error

95% Confidence Interval

Lower Bound Upper Bound

Aad Humor High involved 3,909 ,208 3,500 4,318

Low involved 4,442 ,201 4,046 4,838

Rationeel High involved 3,955 ,202 3,558 4,353

Low involved 3,944 ,184 3,581 4,307

Ab Humor High involved 3,865 ,117 3,634 4,096

Low involved 4,023 ,114 3,799 4,246

Rationeel High involved 3,876 ,114 3,651 4,100

Low involved 3,896 ,104 3,691 4,101

PI Humor High involved 3,500 ,174 3,156 3,843

Low involved 3,504 ,169 3,172 3,837

Rationeel High involved 3,180 ,169 2,846 3,513

37��

Low involved 3,721 ,155 3,416 4,025

Credibility Humor High involved 3,217 ,167 2,887 3,547

Low involved 4,151 ,162 3,831 4,470

Rationeel High involved 4,111 ,163 3,791 4,432

Low involved 3,946 ,149 3,653 4,239

6. Utilitair of Hedonistisch * High of low involved

Dependent

Variable

Utilitair of

Hedonistisch

High of low

involved Mean Std. Error

95% Confidence Interval

Lower Bound Upper Bound

Aad Utilitair High involved 3,926 ,208 3,517 4,334

Low involved 4,314 ,195 3,930 4,698

Hedonistisch High involved 3,939 ,202 3,541 4,336

Low involved 4,072 ,191 3,696 4,448

Ab Utilitair High involved 3,903 ,117 3,672 4,134

Low involved 4,070 ,110 3,853 4,287

Hedonistisch High involved 3,838 ,114 3,614 4,063

Low involved 3,848 ,108 3,636 4,061

PI Utilitair High involved 3,500 ,174 3,156 3,843

Low involved 3,801 ,164 3,479 4,123

Hedonistisch High involved 3,180 ,169 2,846 3,513

Low involved 3,424 ,160 3,109 3,739

Credibility Utilitair High involved 3,875 ,167 3,546 4,205

Low involved 4,442 ,157 4,132 4,751

Hedonistisch High involved 3,453 ,163 3,132 3,773

Low involved 3,655 ,154 3,352 3,958

7. Humor_Rationeel * Utilitair of Hedonistisch * High of low involved

Dependent

Variable Humor_Rationeel

Utilitair of

Hedonistisch

High of low

involved Mean

Std.

Error

95% Confidence Interval

Lower Bound Upper Bound

Aad Humor Utilitair High involved 4,010 ,304 3,411 4,608

Low involved 4,741 ,298 4,154 5,328

Hedonistisch High involved 3,808 ,283 3,251 4,365

Low involved 4,144 ,270 3,613 4,675

Rationeel Utilitair High involved 3,842 ,283 3,285 4,399

Low involved 3,888 ,251 3,393 4,383

38��

Hedonistisch High involved 4,069 ,288 3,502 4,636

Low involved 4,000 ,270 3,469 4,531

Ab Humor Utilitair High involved 3,856 ,172 3,518 4,194

Low involved 4,167 ,168 3,835 4,498

Hedonistisch High involved 3,875 ,160 3,560 4,190

Low involved 3,879 ,152 3,579 4,179

Rationeel Utilitair High involved 3,950 ,160 3,635 4,265

Low involved 3,974 ,142 3,694 4,253

Hedonistisch High involved 3,802 ,162 3,482 4,122

Low involved 3,818 ,152 3,518 4,118

PI Humor Utilitair High involved 3,744 ,255 3,241 4,246

Low involved 3,716 ,250 3,223 4,209

Hedonistisch High involved 3,256 ,237 2,788 3,723

Low involved 3,293 ,226 2,847 3,739

Rationeel Utilitair High involved 3,256 ,237 2,788 3,723

Low involved 3,886 ,211 3,470 4,301

Hedonistisch High involved 3,103 ,241 2,628 3,579

Low involved 3,556 ,226 3,110 4,001

Credibility Humor Utilitair High involved 3,442 ,245 2,960 3,925

Low involved 4,824 ,240 4,350 5,298

Hedonistisch High involved 2,992 ,228 2,542 3,441

Low involved 3,477 ,218 3,049 3,906

Rationeel Utilitair High involved 4,308 ,228 3,859 4,758

Low involved 4,059 ,203 3,660 4,459

Hedonistisch High involved 3,914 ,232 3,457 4,371

Low involved 3,833 ,218 3,405 4,262

39��

Appendix 11: Credibility per product

�

Group Statistics

Advertentienr N Mean Std. Deviation Std. Error Mean

Credibility Advertentie 1 26 3,4423 1,18387 ,23218

Advertentie 2 32 4,2891 1,52017 ,26873

Group Statistics

Advertentienr N Mean Std. Deviation Std. Error Mean

Credibility Advertentie 3 34 2,9706 1,21506 ,20838

Advertentie 4 29 3,9138 1,00729 ,18705

Independent Samples Test

Levene's Test for Equality of

Variances t-test for Equality of Means

F Sig. t df Sig. (2-tailed)

Mean

Difference

Std. Error

Difference

95% Confidence Interval of the

Difference

Lower Upper

Credibility Equal variances assumed 1,446 ,234 -2,324 56 ,024 -,84675 ,36441 -1,57676 -,11675

Equal variances not

assumed

-2,384 55,918 ,021 -,84675 ,35514 -1,55820 -,13531

40��

Independent Samples Test

Levene's Test for Equality of

Variances t-test for Equality of Means

F Sig. t df Sig. (2-tailed)

Mean

Difference

Std. Error

Difference

95% Confidence Interval of the

Difference

Lower Upper

Credibility Equal variances

assumed 1,515 ,223 -3,318 61 ,002 -,94320 ,28424 -1,51157 -,37484

Equal variances not

assumed

-3,368 60,960 ,001 -,94320 ,28002 -1,50314 -,38327

Group Statistics

Advertentienr N Mean Std. Deviation Std. Error Mean

Credibility Advertentie 5 28 4,7946 1,41430 ,26728

Advertentie 6 38 4,0592 1,11263 ,18049

41��

Independent Samples Test

Levene's Test for Equality of

Variances t-test for Equality of Means

F Sig. t df

Sig. (2-

tailed)

Mean

Difference

Std. Error

Difference

95% Confidence Interval of

the Difference

Lower Upper

Credibility Equal variances

assumed 1,307 ,257 2,365 64 ,021 ,73543 ,31103 ,11408 1,35678

Equal variances not

assumed

2,280 49,699 ,027 ,73543 ,32251 ,08755 1,38332

Group Statistics

Advertentienr N Mean Std. Deviation Std. Error Mean

Credibility Advertentie 7 33 3,4773 1,23010 ,21413

Advertentie 8 34 3,8676 1,33177 ,22840

42��

Independent Samples Test

Levene's Test for Equality of

Variances t-test for Equality of Means

F Sig. t df

Sig. (2-

tailed)

Mean

Difference

Std. Error

Difference

95% Confidence Interval of

the Difference

Lower Upper

Credibility Equal variances

assumed ,179 ,674 -1,245 65 ,217 -,39037 ,31345 -1,01639 ,23564

Equal variances not

assumed

-1,247 64,844 ,217 -,39037 ,31308 -1,01566 ,23491

Output 12: Socio-demographic differences

Gender: T-tests

Group Statistics

Wat is uw

geslacht N Mean Std. Deviation Std. Error Mean

Aad Man 59 4,4153 1,68833 ,21980

Vrouw 58 3,7716 1,57090 ,20627

Ab Man 61 3,9057 ,76671 ,09817

Vrouw 60 3,8500 ,96353 ,12439

PI Man 61 3,6284 1,25477 ,16066

43��

Vrouw 59 3,3277 1,25715 ,16367

Credibility Man 61 3,7828 1,39080 ,17807

Vrouw 57 3,4211 1,45095 ,19218

Involvement Man 61 3,8443 1,49525 ,19145

Vrouw 59 4,0212 1,25541 ,16344

Waargenomen_humor Man 61 4,8852 1,76634 ,22616

Vrouw 60 3,8417 1,82379 ,23545

44��

�

Independent Samples Test

Levene's Test for

Equality of

Variances t-test for Equality of Means

F Sig. t df

Sig. (2-

tailed) Mean Difference

Std. Error

Difference

95% Confidence Interval of

the Difference

Lower Upper

Aad Equal variances assumed ,746 ,390 2,134 115 ,035 ,64370 ,30162 ,04626 1,24115

Equal variances not assumed 2,135 114,656 ,035 ,64370 ,30143 ,04661 1,24080

Ab Equal variances assumed 1,394 ,240 ,352 119 ,725 ,05574 ,15816 -,25744 ,36892

Equal variances not assumed ,352 112,476 ,726 ,05574 ,15846 -,25822 ,36969

PI Equal variances assumed ,051 ,822 1,311 118 ,192 ,30073 ,22933 -,15341 ,75488

Equal variances not assumed 1,311 117,851 ,192 ,30073 ,22934 -,15343 ,75490

Credibility Equal variances assumed ,015 ,903 1,383 116 ,169 ,36173 ,26162 -,15644 ,87991

Equal variances not assumed 1,381 114,597 ,170 ,36173 ,26200 -,15726 ,88073

Involvement Equal variances assumed 1,945 ,166 -,701 118 ,485 -,17692 ,25246 -,67686 ,32301

Equal variances not assumed -,703 115,734 ,484 -,17692 ,25172 -,67551 ,32166

Waargenomen_humor Equal variances assumed 2,055 ,154 3,197 119 ,002 1,04358 ,32638 ,39731 1,68985

Equal variances not assumed 3,197 118,719 ,002 1,04358 ,32647 ,39712 1,69004

45��

Level of education: ANOVA

ANOVA

Sum of Squares df

Mean

Square F Sig.

Aad Between Groups 13,281 3 4,427 1,657 ,180

Within Groups 307,188 115 2,671

Total 320,468 118

Ab Between Groups 1,477 3 ,492 ,661 ,578

Within Groups 88,691 119 ,745

Total 90,169 122

PI Between Groups 27,819 3 9,273 6,773 ,000

Within Groups 161,556 118 1,369

Total 189,374 121

Credibility Between Groups 14,480 3 4,827 2,477 ,065

Within Groups 226,007 116 1,948

Total 240,487 119

Involvement Between Groups 6,274 3 2,091 1,054 ,371

Within Groups 234,040 118 1,983

Total 240,314 121

Waargenomen_humor Between Groups 29,214 3 9,738 2,924 ,037

Within Groups 396,302 119 3,330

Total 425,516 122

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46��

Multiple Comparisons

Scheffe

Dependent Variable (I) Hoogt behaalde diploma (J) Hoogt behaalde diploma

Mean Difference

(I-J) Std. Error Sig.

95% Confidence Interval

Lower Bound Upper Bound

Aad Middelbaar onderwijs Hoger onderwijs korte type ,20312 ,34990 ,953 -,7897 1,1959

Hoger onderwijs lange type ,72356 ,41173 ,382 -,4446 1,8918

Post Universitair 1,25625 ,77525 ,456 -,9434 3,4559

Hoger onderwijs korte type Middelbaar onderwijs -,20312 ,34990 ,953 -1,1959 ,7897

Hoger onderwijs lange type ,52043 ,39798 ,636 -,6088 1,6496

Post Universitair 1,05312 ,76804 ,599 -1,1261 3,2323

Hoger onderwijs lange type Middelbaar onderwijs -,72356 ,41173 ,382 -1,8918 ,4446

Hoger onderwijs korte type -,52043 ,39798 ,636 -1,6496 ,6088

Post Universitair ,53269 ,79811 ,930 -1,7318 2,7972

Post Universitair Middelbaar onderwijs -1,25625 ,77525 ,456 -3,4559 ,9434

Hoger onderwijs korte type -1,05312 ,76804 ,599 -3,2323 1,1261

Hoger onderwijs lange type -,53269 ,79811 ,930 -2,7972 1,7318

Ab Middelbaar onderwijs Hoger onderwijs korte type ,04309 ,18018 ,996 -,4679 ,5541

Hoger onderwijs lange type ,28147 ,21355 ,630 -,3241 ,8871

Post Universitair -,04545 ,40743 1,000 -1,2009 1,1100

Hoger onderwijs korte type Middelbaar onderwijs -,04309 ,18018 ,996 -,5541 ,4679

Hoger onderwijs lange type ,23838 ,21022 ,733 -,3578 ,8346

Post Universitair -,08854 ,40570 ,997 -1,2391 1,0620

47��

Hoger onderwijs lange type Middelbaar onderwijs -,28147 ,21355 ,630 -,8871 ,3241

Hoger onderwijs korte type -,23838 ,21022 ,733 -,8346 ,3578

Post Universitair -,32692 ,42158 ,896 -1,5225 ,8686

Post Universitair Middelbaar onderwijs ,04545 ,40743 1,000 -1,1100 1,2009

Hoger onderwijs korte type ,08854 ,40570 ,997 -1,0620 1,2391

Hoger onderwijs lange type ,32692 ,42158 ,896 -,8686 1,5225

PI Middelbaar onderwijs Hoger onderwijs korte type ,45268 ,24569 ,339 -,2442 1,1495

Hoger onderwijs lange type 1,29189* ,29069 ,000 ,4674 2,1164

Post Universitair ,07907 ,55287 ,999 -1,4890 1,6471

Hoger onderwijs korte type Middelbaar onderwijs -,45268 ,24569 ,339 -1,1495 ,2442

Hoger onderwijs lange type ,83921* ,28492 ,038 ,0311 1,6473

Post Universitair -,37361 ,54986 ,927 -1,9332 1,1859

Hoger onderwijs lange type Middelbaar onderwijs -1,29189* ,29069 ,000 -2,1164 -,4674

Hoger onderwijs korte type -,83921* ,28492 ,038 -1,6473 -,0311

Post Universitair -1,21282 ,57139 ,218 -2,8334 ,4078

Post Universitair Middelbaar onderwijs -,07907 ,55287 ,999 -1,6471 1,4890

Hoger onderwijs korte type ,37361 ,54986 ,927 -1,1859 1,9332

Hoger onderwijs lange type 1,21282 ,57139 ,218 -,4078 2,8334

Credibility Middelbaar onderwijs Hoger onderwijs korte type ,38054 ,29544 ,647 -,4576 1,2187

Hoger onderwijs lange type ,88368 ,34994 ,101 -,1091 1,8764

Post Universitair 1,08079 ,73117 ,537 -,9935 3,1551

Hoger onderwijs korte type Middelbaar onderwijs -,38054 ,29544 ,647 -1,2187 ,4576

48��

Hoger onderwijs lange type ,50314 ,33867 ,533 -,4577 1,4639

Post Universitair ,70026 ,72584 ,818 -1,3589 2,7595

Hoger onderwijs lange type Middelbaar onderwijs -,88368 ,34994 ,101 -1,8764 ,1091

Hoger onderwijs korte type -,50314 ,33867 ,533 -1,4639 ,4577

Post Universitair ,19712 ,74968 ,995 -1,9297 2,3239

Post Universitair Middelbaar onderwijs -1,08079 ,73117 ,537 -3,1551 ,9935

Hoger onderwijs korte type -,70026 ,72584 ,818 -2,7595 1,3589

Hoger onderwijs lange type -,19712 ,74968 ,995 -2,3239 1,9297

Involvement Middelbaar onderwijs Hoger onderwijs korte type ,46772 ,29543 ,477 -,3702 1,3056

Hoger onderwijs lange type ,49432 ,34837 ,571 -,4938 1,4824

Post Universitair ,34432 ,66465 ,966 -1,5408 2,2294

Hoger onderwijs korte type Middelbaar onderwijs -,46772 ,29543 ,477 -1,3056 ,3702

Hoger onderwijs lange type ,02660 ,34422 1,000 -,9497 1,0029

Post Universitair -,12340 ,66248 ,998 -2,0024 1,7556

Hoger onderwijs lange type Middelbaar onderwijs -,49432 ,34837 ,571 -1,4824 ,4938

Hoger onderwijs korte type -,02660 ,34422 1,000 -1,0029 ,9497

Post Universitair -,15000 ,68772 ,997 -2,1006 1,8006

Post Universitair Middelbaar onderwijs -,34432 ,66465 ,966 -2,2294 1,5408

Hoger onderwijs korte type ,12340 ,66248 ,998 -1,7556 2,0024

Hoger onderwijs lange type ,15000 ,68772 ,997 -1,8006 2,1006

Waargenomen_humor Middelbaar onderwijs Hoger onderwijs korte type ,09280 ,38088 ,996 -,9873 1,1729

Hoger onderwijs lange type 1,10402 ,45141 ,119 -,1762 2,3842

49��

Post Universitair 1,43864 ,86124 ,429 -1,0038 3,8811

Hoger onderwijs korte type Middelbaar onderwijs -,09280 ,38088 ,996 -1,1729 ,9873

Hoger onderwijs lange type 1,01122 ,44437 ,165 -,2490 2,2714

Post Universitair 1,34583 ,85758 ,485 -1,0862 3,7778

Hoger onderwijs lange type Middelbaar onderwijs -1,10402 ,45141 ,119 -2,3842 ,1762

Hoger onderwijs korte type -1,01122 ,44437 ,165 -2,2714 ,2490

Post Universitair ,33462 ,89115 ,986 -2,1926 2,8618

Post Universitair Middelbaar onderwijs -1,43864 ,86124 ,429 -3,8811 1,0038

Hoger onderwijs korte type -1,34583 ,85758 ,485 -3,7778 1,0862

Hoger onderwijs lange type -,33462 ,89115 ,986 -2,8618 2,1926

*. The mean difference is significant at the 0.05 level.

50��

Age categories: ANOVA

ANOVA

Sum of Squares df Mean Square F Sig.

Aad Between Groups 13,680 4 3,420 1,282 ,281

Within Groups 304,039 114 2,667

Total 317,718 118

Ab Between Groups 5,267 4 1,317 1,646 ,167

Within Groups 94,391 118 ,800

Total 99,659 122

PI Between Groups 9,848 4 2,462 1,591 ,181

Within Groups 181,093 117 1,548

Total 190,941 121

Credibility Between Groups 19,228 4 4,807 2,519 ,045

Within Groups 219,480 115 1,909

Total 238,708 119

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