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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.
5
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
6
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
8
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.
10
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 �
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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
�����������
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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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29��
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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