Download Influence and interpretation: The variance in perception of

Influence and interpretation: The variance in perception
of advertising text between genders
Wasae Shahid
Hanken School of Economics
Department of Business & Management
Helsinki
2017
HANKEN SCHOOL OF ECONOMICS
Department of: Business & Management
Type of work: Masters
Thesis
Author: Wasae Shahid
Date: 31/03/2017
Title of thesis: Influence and interpretation: The variance in perception of
advertising text between genders
Abstract:
While advertising has been heavily explored with respect to gender and language
individually, this thesis argues that there is still room for research into the interplay
between these three factors from a perceptual viewpoint. More specifically, an
understanding into whether different text and language styles employed in
advertisements are interpreted by each gender in a dissimilar way was required. The
aim of the study therefore was to ascertain whether each gender perceives the text within
advertisements differently. Furthermore, the study also aimed to examine if cognitive
and affective text frameworks were favored differently by each gender.
The theoretical foundation was built on aspects drawn from recent research pertaining
to information processing differences between genders, along with studies based on
conventional advertising language. The theoretical framework results in two hypotheses
on the differential effect of cognitively vs. affectively framed messages on females’ and
males’ perception of ads.
To address the hypotheses, an experiment was designed by constructing two mock
advertisements of which one was cognitively framed and the other affectively framed.
Data were collected from 70 business students. The results supported the two
hypotheses and show that there is a significant interaction effect of gender and cognitive
vs. affective ads on ad perceptions. Men respond more positively to advertising text
framed in a cognitive format whereas women respond more favorably towards
advertising text constructed in an affective format.
Keywords: Gender, Cognitive, Affective, Advertising, Text, Language, Perception, Attitude
Table of Contents
1. INTRODUCTION ................................................................................................................................... 1
1.1 Research Problem ............................................................................................................................. 1
1.2 Aim of the Study ............................................................................................................................... 2
1.3 Delimitations .................................................................................................................................... 3
1.4 Definitions ......................................................................................................................................... 4
1.5 Structure of Paper ............................................................................................................................ 5
2. LITERATURE REVIEW ........................................................................................................................ 6
2.1 Gender in advertisements ............................................................................................................... 6
2.1.1 Evolution of gender based advertisements ............................................................................ 7
2.1.2 The Social Role Theory............................................................................................................. 7
2.1.3 The Selectivity Model ............................................................................................................... 8
2.1.4 Perceptual differences ............................................................................................................ 11
2.2 Text in advertisements .................................................................................................................. 12
2.2.1 Cognitive and affective text frameworks in messages........................................................ 13
2.2.2 Linguistic triggers in advertisements .................................................................................. 14
2.2.3 The language of global advertising....................................................................................... 15
2.3 Gender and language..................................................................................................................... 15
2.3.1 Gender differences in language production ........................................................................ 16
2.3.2 Gender differences in language perception ........................................................................ 17
2.4 Summary ......................................................................................................................................... 19
2.5 Hypotheses ..................................................................................................................................... 21
3. METHODOLOGY................................................................................................................................. 22
3.1 Research Design ............................................................................................................................. 22
3.1.1 Product Selection ..................................................................................................................... 23
3.1.2 Advertisement Selection ........................................................................................................ 23
3.1.3 Treatments ............................................................................................................................... 24
3.2 Sample ............................................................................................................................................. 26
3.3 Measures and Constructs ............................................................................................................. 27
3.3.1 Internal Reliability of Scale ................................................................................................... 30
4. RESULTS .............................................................................................................................................. 31
4. 1 Manipulation Confirmation ......................................................................................................... 31
4.2 Two Way MANOVA ....................................................................................................................... 32
4.2.1 Assessing Normality ............................................................................................................... 33
4.2.2 Linearity & Correlation .......................................................................................................... 33
4.2.3 Homogeneity of variance-covariance matrices .................................................................. 34
4.2.4 Multivariate Tests ................................................................................................................... 35
5. DISCUSSION ........................................................................................................................................ 41
5.1 Contribution of the study .............................................................................................................. 42
5.2 Managerial implications ............................................................................................................... 44
5.3 Limitations and future research directions ................................................................................ 45
REFERENCES .......................................................................................................................................... 47
APPENDICES ........................................................................................................................................... 57
Appendix I – Ad Treatments .............................................................................................................. 57
Appendix II – Questionnaire .............................................................................................................. 59
Appendix III – Internal Reliability SPSS Output ............................................................................ 60
Appendix IV – Manipulation Check SPSS Output .......................................................................... 70
Appendix V – MANOVA Assumptions SPSS Output ...................................................................... 71
Appendix VI – Two-way MANOVA SPSS Output............................................................................ 79
TABLES
Table 1. Findings summary on gender differences ....................................................................... 20
Table 2. Constructs and Measures ................................................................................................ 28
Table 3. Internal Reliability of Scale ............................................................................................. 30
Table 4. Manipulation Check Independent Samples Test ............................................................ 32
Table 5. Multivariate Tests ........................................................................................................... 35
Table 6. Tests of between-subjects effects .................................................................................... 36
Table 7. Estimated Marginal Means ............................................................................................. 37
FIGURES
Figure 1. Cognitive Treatment Text .............................................................................................. 24
Figure 2. Affective Treatment Text ............................................................................................... 25
Figure 3. Matrix scatterplots for linearity..................................................................................... 34
Figure 4. Estimated Marginal Means of Attitude towards the Ad ................................................ 38
Figure 5. Estimated Marginal Means of Attitude towards the Product........................................ 38
Figure 6. Estimated Marginal Means of Emotions from Ad ........................................................ 39
Figure 7. Estimated Marginal Means of Perception of Text in Ad ............................................... 39
Figure 8. Estimated Marginal Means of Purchase Intent ............................................................ 40
1. INTRODUCTION
With the abundance of ads consumers are exposed to nowadays, advertisers are
constantly looking to tailor specific advertisements for targeted demographics - such as
gender - to catch the eye of their current and potential customers (Duboviciene &
Skorupa, 2014). The role of gender in advertising is one employed by practitioners and
researchers alike as a prime differentiating factor in consumer marketing. Sun, Lim,
Jiang, Peng and Chen (2010, p. 1614) refer to gender as an “individual characteristic
within the advertising evaluation process”, whilst Rakow (1986) delved into how men and
women can be measurably compared when researching aspects like behavior or
communication. The eventual aim of advertising is to positively affect consumers’ attitude
towards the ad and lead them to a purchase decision (Mackenzie & Lutz, 1989; Mitchell
& Olson, 1981). This has become exceedingly difficult in modern times for advertisers as
consumers’ attitudes towards advertising are in a constant state of flux due to a plethora
of cultural and societal differences (Boateng & Okoe, 2015). Advertisers therefore need to
understand the distinction between genders’ thought processes in order to define the
market in a manner which allows for more effective connection and communication with
their target segment (Kraft & Weber, 2012). An important element of the advertising
message is the text employed in it. Hence, this thesis will study how genders are affected
by differences in advertising text.
1.1 Research Problem
There are numerous ways advertisers can impact consumer behavior, such as the use of
visual cues (Metallinos, 1998; Pieters, Wedel & Batra, 2010) and sound effects (Ding,
2003). Nevertheless, Cheng, Chandramouli and Subbalakshmi (2010) claim that
language and text continues to be the most prevalent form of marketing communication
even with the shift from traditional to more current forms of media. Goddard (1998, p. 7)
proposes that the text used in advertising encompasses complexly intertwined concepts,
based on the relationship between the “Addressers, Message and Addressees”. The
dynamic between textual language and the effect it has on the perception of these
addressees - namely the mass consumers – is particularly interesting. Understanding the
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masses, though, requires taking into consideration multiple individual traits and sociocultural characteristics (Zaller, 1992), including gender.
While there is a plethora of research on the difference in production of language between
genders (Danner, Snowdon & Freisen, 2001; Newman, Groom, Handelman &
Pennebaker, 2008; Waters, 1975), there is a noticeable lack of it when it comes to its
perception, especially in an advertising context. Stokar von Neuforn (2007) reported
there is indeed a difference between the manner in which male and female students
perceive various characteristics of written or text-based communication. Another study
by Mayer and Tormala (2010) concluded that a difference in message perception between
genders existed in terms of persuasiveness based on think vs feel messages. Although
there are plenty of studies which show that genders perceive texts differently, this
difference has not been tested specifically for advertising messages in terms of affecting
the perception towards the ad. This is surprising, since it is important for advertisers to
know if a change in the text content or structure affects how it is perceived by genders. A
difference based on gender in perception of the advertisement can inadvertently lead to
conflicting messages being born about the brand or product (Levit, 2012).
Two overall framings of persuasive language are typically utilized in advertisement texts
to appeal to consumers - more specifically those framed in either a Cognitive or Affective
format. The general assumption from previous studies, whilst at times mixed, tends to
lean towards the fact that females are more favorable towards emotional insights (Dube
& Morgan, 1998) and prefer advertisements which are more subjective and affective in
nature (Haas, 1979; Danner et al., 2001). Men, contrastingly, depict an affiliation towards
both producing language and perceiving ads which are cognitive and provide objective
facts of a product (Haas, 1979). The extent to which this variance stretches to specifically
the text employed in advertising is still relatively unexplored and forms the basis of this
study.
1.2 Aim of the Study
In lieu of this, the study aims to examine whether the textual language employed within
advertisements impacts each gender’s perception of the advertisement differently.
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Primarily, the research will look to ascertain if such a difference exists, while an extended
aim of this study would gauge whether each gender responds more favorably to either the
text employed in a cognitive ad scenario or an affective ad scenario. The empirical study
will investigate the research questions by means of an experiment.
The following primary research question has been framed for the purpose of this study:
RQ1: Is there a difference in perception of advertisement text between genders?
Based on previous studies of gender differences between ad perceptions in general - not
text in particular - the following supplementary research questions were formulated:
RQ2: Do males respond more positively to cognitive text in an ad message?
RQ3: Do females respond more positively to affective text in an ad message?
Examining this problem is appealing from a psycho-social context as well, due to the very
essence of our societal notions of relationships and communication being constructed on
the basis of gender distinctiveness (Sierpe, 2005). Considering that gender is readily
identifiable and its segments are both easier to access and measure (Meyers-Levy &
Maheswaran, 1991), advertisers deem evaluating and comprehending gender differences
of pivotal importance (Darley & Smith, 1995). This study will benefit advertisers in
understanding the role textual language plays in their marketing campaigns by evaluating
gender responses to affective and cognitive stimuli, thereby allowing more insight into
how campaigns with gender as a foundation should be constructed. It will also contribute
to advertising research by empirically investigating the effect of cognitive vs affective ad
text messages on consumer attitudes towards ads.
1.3 Delimitations
In terms of delimitations, the advertisement used for the study itself will be restricted to
print advertisements. This is because an analysis of text implies the removal of television
and audio advertisements from consideration in the study, leaving us with social media
and print advertisements. Between these, print advertisements will be the focus of this
study. The reasoning behind this is multifold; social media advertising is beneficial in
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terms of its interactivity and accessibility, but often comes with numerous considerations
to be considered for analysis (Okazaki & Taylor, 2013), some of which would distract the
participants from the text, and would be beyond the scope of this study.
Studies have shown that consumers are already more responsive to advertising on social
media platforms when measuring cognitive responses (Voorveld & Noort, 2014). Unlike
print advertisements, the text employed in online advertisements is more oral and
colloquial in nature, in an attempt to close the distance between the ad and the consumer
(Janoschka, 2004), making it difficult to effectively measure the perception of individuals
based on cognitive or affective orientations. Moreover, the providers of social media
platforms often find themselves in between balancing the free flow of content against
increasing individual user privacy demands (Stutzman, Capra & Thompson, 2011). This
is also why social media is not the most ideal platform with respect to this study as the
perceived intrusiveness can negatively affect the perception of the advertisement before
the viewer gets a chance to even interpret it (Li, Edwards & Lee, 2002).
Coupling this reasoning with claims that men are more sophisticated in interacting with
social media (Weiser, 2000; Shaw & Gant, 2002), this medium would not allow for
neutral evaluation of perception between the genders within the study itself. These
arguments, therefore, provide a foundation to exclude social media advertisements from
this study and placing the focus on print advertisements as the selected medium to
evaluate textual perception differences within genders.
1.4 Definitions
For the purpose of this study, the pertinent term to correctly define is that of gender. The
term “gender” here will denote the traditional notions of “man” and “woman”, as opposed
to more modern interpretations of genders, such as lesbian, gay, bi-sexual and
transvestites prevalent in most current societies. The distinction between gender and sex
is also to be noted as the latter is biologically based while the former is constructed via
sociological norms (Crawford, 1995). This would allow for easier access to data required
in line with gender being readily identifiable, as stated previously.
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With respect to defining the type of advertisement text language classes explored in this
study, the explanation proposed by Fabrigar and Petty (1999) will be adopted; affective
language in ad messages is one which instills an emotional reaction in line with feeling,
while cognitive language ad messages are more in line with describing tangible and
objective information about product attributes.
1.5 Structure of Paper
The paper will be structured in the following manner: this section will be followed by a
review of previous literature to construct a theoretical framework for this study. It draws
upon theories which work to elaborate current topics on gender, language and advertising
that form a better foundation to understand their interconnectivity. Proceeding that, the
design of the experiment, measurement, sample and data collection will be explained. The
results section will provide an answer to the research questions. The paper will be
concluded by a section outlining overall discussions, implications, limitations and future
research direction.
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2. LITERATURE REVIEW
This chapter will form a theoretical basis to build the foundation for the empirical study
by reviewing previous literature in relation to the research questions. The section will look
to address the research gap by shedding light on literature encompassing the individual
dynamics between the perceptual aspect of advertising, gender and language and
converging them together for the study.
Whilst some of the studies examined for this purpose belonged to the field of marketing
research and consumer behavior, literature pertaining to non-marketing studies was also
included to cater to a more comprehensive understanding of the concepts not explained
by marketing studies. These included studies from the fields of psychology, languages and
sociology.
The review starts by describing previous findings on gender in advertisements, followed
by a review of studies focusing on the text within advertisements. The final part reviews
findings from studies pertaining to gender and language. A summary of the findings and
the proposed hypotheses concludes the chapter.
2.1 Gender in advertisements
The interplay between advertising and gender has been examined from various angles
before, with prior research usually restricted to the portrayal of gender roles within
advertising – such as analyses into gender stereotyping (Eisend, 2010) or the advertising
appeals of sexual and non-sexual imagery (Severn, Belch & Belch, 1990). What has been
relatively lacking in the field however, is a deeper look into the different ways advertising
affects each gender’s interpretation of the advertisement itself
A consideration into how gender has been traditionally portrayed within advertisements
will be expanded upon here. This will be supported by research highlighting socio-cultural
theories to explain how these accepted notions of gender and advertisements have been
formulated. The studies presented here also explore differences in interpretation of
advertisements between men and women, along with the reasoning behind them. Leading
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from that, a deeper look into research outlining perceptual differences between men and
women in advertisements will be provided.
2.1.1 Evolution of gender based advertisements
The role of gender in advertisements, whilst heavily researched, has usually been focused
around the imagery, visual effects and sexual connotations related to the advertisements
themselves (First, 1998; Furnham & Bitar, 1993). Allan and Coltrane (1996) conducted
research covering the mid-90’s whereby it was found that while the manner in which
gender was visually portrayed on television had altered to some extent, it had still
remained stereotypical with respect to gender bias.
Even the perception of advertisements from a consumer behavior standpoint has been
usually examined to gauge the differences between men and women reacting to visual
images within advertisements, such as how women display more liberal attitudes than
men (Rossi & Rossi, 1985). A deviation from research into visual gender role portrayals
did gradually take place, in the form of an increased interest in research of gendered
products by consumers, such as Alreck, Settle and Belch’s (1982) findings on how men
strictly preferred masculine soap brands and did not embrace feminine soap brands as
readily.
A significant amount of research in this field suggests a prominent distinction between
men and women in terms of advertisements, which this study will look to examine
regarding text to assess whether the difference is still prevalent in modern times. Different
explanatory models have been proposed to explain differences between genders. Two of
these are the social role theory and the selectivity model, which will be discussed next.
2.1.2 The Social Role Theory
An understanding into the development of the concept of gender can be applied as a
foundation for comprehending variation in gender roles in more detail. The social role
theory constructs itself around the concept of understanding gender differences by
evaluating how societal notions of gender roles work towards fostering behavioral
differences between men and women (Eckes & Trautner, 2000). Putrevu, Gentry, Fischer
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and Palan’s (2001) research, for example, builds upon the assumption that from an early
age, children learn to identify with a specific gender after which they try and inculcate the
same attributes within themselves as they deem appropriate – attributes which are
usually shaped by the society they find themselves a part of. This is supported further by
evidence that each gender is exposed to different societal pressures, with females
generally expected to adopt a more submissive role as opposed to the dominant role taken
on by the majority of males in the past (Meyers-Levy & Sternthal, 1991).
With the evolving roles of gender in modern society, the current study can work towards
understanding whether this individual self-perception each gender possesses has altered
enough to lead towards a difference in terms of perception in consumer behavior
alongside a socio-cultural context as well.
2.1.3 The Selectivity Model
An important sociological theory to frame the concept of differences in information
processing between genders is the selectivity model, which states that women are more
comprehensive in their ability to process information and pick up subtle cueing, whilst
men are more selective in their information processing (Meyers-Levy, 1989; Meyers-Levy
& Maheswaran 1991). A study conducted by Ambrose and Gross (2016), for example,
depicted how men and women differ at all levels of social information processing in sexual
dating encounters.
The results of the selectivity model also depict how females fare better in both visual cues
and verbal/linguistic activities than their male counterparts (Meyers-Levy, 1989), with
males opting for specific heuristics – often even a solitary cue - to substitute for
interpretation of more comprehensive information (Darley & Smith, 1995). However, the
model is also flexible in the sense that it takes into consideration the fact that under
certain conditions, the information processing differences would not necessary hold true
– such as how females would be more likely than males to both notice and alter their
processing strategies when perceived product risk is higher (Wolin, 2003; Darley &
Smith, 1995)
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Based on the results of the selectivity model, Meyers-Levy (1989) posits that males
respond more to advertising that highlights product features in detail by referring to
certain heuristics as cues. These cues are deemed sufficient to have perceived the message
effectively enough, resulting in men making decisions about the product more quickly
(Meyers-Levy & Sternthal, 1991). Conversely, the model suggests that females are
appealed by the user benefits associated with the product itself and depict greater
sensitivity to interpreting all available information and cues effectively (Meyers-Levy,
1989).
Within a series of experiments on the selectivity model, one examined the difference in
language production between advertising campaigns developed by male and female
copywriters (Carsky & Zuckerman, 1991). Students were asked to evaluate ads developed
by copywriting groups of each gender, with the results portraying no major difference in
the style of the ads apart from the ad appeals produced by the women’s group being
relatively “more emotional than rational or economic” (Carsky & Zuckerman, 1991, p. 46).
An additional experiment in the same study measured differences in information
processing of one-sided (providing only one point of view) and two-sided messages
(providing two opposing points of view). The assumption here was that women would
have a greater change in attitude with two-sided messages. The results however did not
yield any particular difference between gender in terms of message type. However, some
evidence was present to support the theory of women being more comprehensive in
information processing, such as taking a longer time to read the ad and noting more
details in it than men. It was also reported that males felt there was too much information
in the ads overall and wanted the presence of more statistical information.
Also, Darley and Smith (1995) suggest that the selectivity model extends to advertisement
perceptions and purchase behaviors as well, meaning that men and women perceive
objective vs subjective advertising claims differently. According to Darley and Smith
(1993) an advertising claim can be considered objective when it describes tangible
features of the product, with the claim itself usually consisting of factual information.
The basis on which an advertisement claim can be considered as providing factual
information is when not only is it quantified on a conventional scale, but is also “not
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subject to individual interpretation” (Darley & Smith, 1993, p. 42). Examples of this can
be “a straight discount of 15%” or “Graphics Processor - Quadro NVS 290 with DirectX
10, OpenGL 21”. Alternately, subjective claims encompass intangible features which
cannot be readily determined by physical inspection and are meant to be more
descriptive, emotional and impressionistic (Darley & Smith, 1995). Moreover, the entire
premise of subjective advertisement claims is that they are supposed to be open to
individual interpretation (Darley & Smith, 1993). Examples of these would include
“become a princess by wearing this radiant piece of jewelry” or “feel the world at your
fingertips”.
The experiment conducted by Darley and Smith (1995) on claim objectivity difference
between genders slightly refuted some aspects of the selectivity model and its associated
research. They discovered that females, possessing higher comprehensive ability,
portrayed no difference in response for objective and subjective claims when the product
was low-risk but were more responsive to objective claims with moderate-risk products.
Males however, whilst having consistent levels of responses for both forms of product
risk, did not favor objective claims over subjective claims, which contests the assertion of
the selectivity model whereby males respond more favorably to objective and cognitive
claims.
More recent studies (Meyers-Levy & Loken, 2015), have used the selectivity theory along
with three other gender differentiating theories (evolutionary, socio-cultural and
hormone-brain) to identify gender differences in more detail. Alongside supporting the
results of the selectivity model, an additional conclusion attained from this research was
that women are more “other-oriented” while men are more “self-oriented” (Meyers-Levy
& Loken, 2015, p. 129). This notion supports the fact that women portray the tendency of
including the insights of others into the majority of their own decision-making processes
(Carsky & Zuckerman, 1991; Meyers-Levy & Maheswaran, 1991). The claim of being otheroriented can also be attributed to why women are more appreciative of companies
engaging in socially responsible behaviors and more receptive to company affiliations
working towards a socially beneficial cause (Shayon, 2011). Men, meanwhile are more
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selective in allowing other people’s decisions to influence their own while constructing
and validating their own opinions (Baker, 2012 cited in Kraft & Weber, 2012, p.248).
In addition, it has been shown that while men can be more easily swayed by marketing
campaigns employing the use of humor or a bad-boy outlook, aspects such as family and
security appeal to women more (Kraft & Weber, 2012). In accordance with the selectivity
model, because women are more comprehensive in processing information, they are also
more likely to pick up any inconsistencies within advertisements (Meyers-Levy & Loken,
2015; Darley & Smith, 1995). In conjunction with this, Howland and Anderson (2006)
imply that women are more sensitive to product or brand message not matching user
expectation and feel a loss of trust, even with women generally possessing a higher
possibility of long-term brand relationship and loyalty (Sundari, 2014).
2.1.4 Perceptual differences
Putrevu et al. (2001) claim that the selective processing approach adopted by males
implies that they benefit more from advertisements framed in a nonverbal structure
which are relatively simple and direct. In contrast to this, they posit that the detailed
processing ability of females indicates that ads containing a more elaborate verbal
description and greater information would be more appealing to women. Hirschmann
and Thompson (1997) conducted a study pertaining to the effect mass media and
advertising had on individual interpretation, in which during the interviews they
discovered that women and men generally have altered perceptions of how media
institutions affects them respectively. The males considered themselves as being more
analytical and maintaining a logical stance, thereby perceiving themselves as being more
immune to the effect of mass media than others. Females, alternately, perceived
themselves as being more persuadable and influenced by it.
Advertising content is believed to influence respondent’s (cognitive or affective) answers
and attitude towards the ad/product/brand and resultantly the purchase intention (Cyril
de Run & Gray 2005). A difference in perception manifested through an advertisement
can affect the eventual purchase decision of the consumers themselves (Kraft & Weber
2012). Women generally lean towards looking to fulfill long-term needs when making a
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purchase decision, while men tend to resolve immediate purchase solutions and address
short-term needs at this stage (Baker, 2012 cited in Kraft & Weber, 2012, p.248).
According to Levit (2012), this is why men generally tend to make a larger number of
impulsive purchase decisions than women. There is a gender difference when it comes to
e-commerce as well, with women being more affected by online levels of trust when it
comes to purchase intent than men (Awad & Ragowski, 2008)
In concurrence with these studies, it would seem that men respond more favorably to
objective and logically phrased advertisements. Females, whereas, consider detailed,
subjective advertisements - aimed towards appealing more to the affective, emotional
state – to be of higher preference. Hence, it might be prudent for marketers to formulate
differently structured advertisements and campaigns directed towards men and women
respectively (Wolin, 2003). This is especially imperative in modern times whereby
internet marketing and e-commerce is so prevalent. It has been suggested that a
significant amount of difference exists in the online consumer behavior patterns of males
and females for marketers to now focus on a more individual, customized consumer
experience for each gender (McMahan, Hovland & McMillan, 2009).
This study aims to shed further light on whether these information processing differences
between genders can be detected for text advertisements.
2.2 Text in advertisements
This part will proceed by focusing on advertising in accordance with the two textual
frameworks highlighted in the aim of the study – cognitive and affective types - by
examining studies which have previously taken them into consideration. Leading from
this, research encompassing the use of text as specific triggers in advertisements will be
reviewed to expand on the role of text in altering consumer interpretation. This part will
then be finished off by an inspection into the global language of advertising and
communication.
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2.2.1 Cognitive and affective text frameworks in messages
The text employed in advertisements usually contains – either separately or together – a
two-fold message; the product or campaign description and the persuasive attempt to
make it appealing to consumers (Labrador, Ramon, Alaiz-Moreton & Sanjurjo-Gonzalez,
2014). The advertising language itself is generally sub-branched into affective and
cognitive classes based on either the content or the terms and expressions employed in
the phrasing (Mayer & Tormala, 2010; Kronrod & Danziger 2013; Byun & Jan, 2015). Ad
messages associating with feelings and invoking an emotive reaction are considered
affective, while messages constructed around a description of beliefs about the product
attributes are cognitive (Fabrigar & Petty 1999). Drolet, Williams and Lau-Gesk (2007)
studied the perception of cognitive and affective messages further and found that
customers viewed messages describing greeting cards containing emotional language as
affective (an example of this is “the greeting cards will bring happiness to the special
people in your life… to melt their hearts”). Alternately, messages about the same product
but containing a more rational language style were considered to be cognitive by readers
(an example being “crafted on quality paper stock with colors that won’t fade”) (Drolet
et al., 2007, p. 10).
A series of studies were conducted based on how words such as “think” may allow the
consumer to associate towards a cognitive perspective, whereas the use of “feel” may
invoke a more affective side (Mayer & Tormala, 2010). The results of the studies also
indicated how the impact of the “think” and “feel” messages were dependent on the
respondents’ own orientation being of a cognitive or affective inclination respectively.
Similarly, altering literal expressions to become more figurative in nature by changing a
few terms can also allow the advertisement to be perceived as affective (Kronrod &
Danziger 2013). Studies also brought to light the finding that figurative language is more
conducive for hedonic products while literal language is more useful for utilitarian
product choice. An additional interesting finding was that even study respondents writing
product reviews post-purchase adopted a more figurative language for hedonic products
than utilitarian ones (Kronrod & Danziger, 2013).
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Byun and Jang (2015) examined a similar effect in their study by delving into whether or
not a significant difference in consumer attitude existed between tourism ads framed in a
cognitive and affective language structure respectively. The results depicted no specific
change in attitude based on the language class only, however the destination type
appeared to alter the attitudes; cognitive language was received more positively in
utilitarian destination advertisements whilst affective advertisements were considered
more favorable by travelers when the destination advertisement was more hedonic in
nature. Therefore, the language class, when in an interaction effect with another variable
– such as destination type in the mentioned study – was shown to alter perception and
attitude.
2.2.2 Linguistic triggers in advertisements
Specific linguistic characteristics present within the headline of the advertisement can
often work to establish a relationship towards the reader from the onset; Talbot (1992)
introduced the concept of “voice” used in an advertisement by the writer. She
hypothesized that the advertisement speaks to the reader on the basis of three broad
distinctions: Interactants (people addressing one another, such as the reader and the
writer), Characters (Individuals whose opinions are represented in an advertisement) and
Subject Positions (the stance the writer opts to take when addressing the reader, e.g. as a
friend, relative, co-worker etc.)(Talbot, 1992). The expectation therefore is that the more
“intimate” the language style used is, the more rapport is established between the
advertisement and the reader (Maynard, 1995). This is often as simple as using the word
“You” in an advertisement in an attempt to make the reader feel more inclusive.
The use of text-only advertisements has gradually seen an increase in previous years
(MacMillan, 2010) with advertisers now needing to look at both the presence and amount
of text as a decisive factor in their advertisements. Flores, Chen and Ross (2014) studied
the effect and extent certain advertisement characteristics (including language) have on
consumer attitude, and reported that consumers deem low-involvement products more
appealing if the advertisement consists of text only.
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2.2.3 The language of global advertising
The use of English as a primary language in advertisements within both the applied and
research communities stems from the language being considered a worldwide lingua
franca, generally being referred to as the international language of communication
(Baumgardner, 2008; Bogdanova, 2010). This is often attributed to the fact that English
as a language is widely understood across a range of regions and cultures, as a result of
which there is a higher probability that most individuals would effectively be able to
comprehend any creative-linguistic variations to it (Kuppens, 2010).
Hornikx, Van Meurs and De Boer (2010) portrayed that even in the presence of a local
language, English is preferred as the language of communication within international
advertising by comparing English slogans with Dutch slogans in car ads and evaluating
consumer preference based on difficulty of comprehension. The results depicted that
English was preferred over Dutch when it was easy to comprehend. Even when the
difficulty in comprehension was harder, it was acknowledged to be at par with Dutch in
terms of preference. Resultantly, most organizations commonly employ the strategy of
utilizing English as a marketing tool in standardizing their advertisements across not only
a range of platforms but regions as well (Nickerson & Camiciottoli, 2013).
It is based on these assumptions that this study will use English as the language of textual
inference when measuring changes between gender perceptions.
2.3 Gender and language
The literature discussed previously has examined studies describing the interactions
between both gender and advertising and language and advertising respectively. The next
course of action is to attain a deeper insight into research covering differences between
men and women when it comes to language.
Studies show that women prefer to both employ and respond to the use of affective
language which is subjective and evaluative, such as expressive words involving domestic
topics and “psychological state” (Haas, 1979, p.1). This includes the use of more adjectives
and adverbs in their communication, alongside being more inclined towards claims
15
evoking more feeling and intuition. Men, however, adopted a more logical and cognitive
approach, resorting to selective, objective language (Haas, 1979) and opting not to engage
in comprehending the entire details of the message (Meyers-Levy, 1989).
Whilst language usage in this field has usually been centered on differences with respect
to production by each gender - such as the presence of a difference in writing attitudes of
students where females scored higher than males (Lee, 2013) or a significant difference
in composition styles between students of different genders in online platforms such as
Facebook (Shepherd, 2016) – there is still room for more research into perception of
language between genders.
By reviewing the findings from both approaches in these studies, this paper aims to
empirically examine how men and women differ specifically in terms of the latter –
language perception – when considering text in advertisements.
2.3.1 Gender differences in language production
A study investigated whether the gender of an individual can be identified by an
examination of text, using writings from employees of a specific organization and also
authors of news articles as the basis (Cheng et al., 2010). Analyzing the text based on
specific psycho-linguistic features, it was noted that men and women adopt the usage of
different language styles while communicating via both personal writing content such as
e-mails and more public formats such as news articles.
This phenomenon was explored in greater detail by an extensive study whereby they data
was collected from 70 individual studies, extracting 14,000 text files as a database to
establish whether a difference in language usage based on gender was present (Newman
et al., 2008). The results indicated that males discussed more neutral topics, often using
words to describe objective properties. Females referred to words associated with thought
processes, society and psychology more.
Pennebaker, Mehl and Niederhoffer (2003) reported that aspects such as emotions and
senses - alongside first-person pronouns - were more prevalent within female language
styles. Alternately, men exhibit greater emphasis on topics along the lines of “career,
16
money, sports” etc., and also outweigh their gender counterparts in using technical
language consisting of numbers, statistics and even swear words. Males refer to one form
of emotion more than women in their language styles, however – that of anger
(Pennebaker et al., 2003). Flynn’s (1983) findings pertaining to gender differences in the
essays of freshman students studying composition revealed that male subjects wrote more
about aspects such as rebellion, gun control and exploration, while female subjects’
writing revolved around topics such as clothing, accommodation and personal
interaction.
An earlier study conducted involved relying on a group of college professors as a panel of
judges assigned to analyze textual style differences between genders by basing
judgements on the text provided (Waters, 1975). The findings here were in accordance
with most research that followed suite, with males generally deemed as being writing in a
reserved format, scarce of emotion and more mechanical in their writing styles. Similarly,
the analysis of female writing also held true to eventual research, where papers written by
women were considered to be more friendly and emotional, discussing notions such as
societal values (Waters, 1975). In line with associated research, women use more affective
and emotional language in a positive sense (Danner et al., 2001), but this extends to the
other extreme in terms of negative emotions as well. (Newman et al., 2008).
2.3.2 Gender differences in language perception
While it would be a broad generalization to simply state that gender is perfectly divided
between either a cognitive or affective orientation, prior research does suggest that
females tend to be more responsive to the affective side than their male counterparts
(Mayer & Tormala, 2010; Hall & Mast, 2008; Fisher & Dube, 2005). A study delved
deeper into this by hypothesizing that women – due to being more affectively oriented –
would have greater chances of being influenced by messages framed in a “feel” context,
while men would be more persuaded by “think” framed messages due to their cognitive
orientation (Mayer & Tormala, 2010). The study revolved around exposing
undergraduate students to movie reviews in both “think” (cognitive) and “feel” (affective)
17
message orientations, with the results confirming the hypothesis to be true as a significant
difference in response was reported.
Stokar von Neuforn (2007) studied the variation between university students of different
genders in interpretation of text within virtual learning environments, with the most
salient results being that women prefer greater length of both text and sentences, while
men opted for shorter sentences and text. The reasoning attributed to this was females
perceiving shorter sentences as being rushed and depicting a lack of interest. On the
opposing end, men seemed to appreciate shorter texts as being more “precise and goalorientated”, with longer sentences being deemed – fittingly - “typically female” (Stokar
von Neuforn, 2007, p. 215). This seems to be in line with some of the earlier studies on
the matter as well, with Voss (1983) noting in his reassessment of Janet Emig’s “The
Composing Processes of Twelfth Graders” (1971) how women seemed to indicate a
marked preference for writing more expressive assignments, whilst their male peers
within the same class group favored forms of informative writing more.
In keeping with previous research, Stokar von Neuforn (2007) also reported that women
displayed a greater preference towards empathetic textual communication, however
males rated the use of jokes higher than females. Women, similarly, were more
appreciative of elements such as the correct use of punctuation marks and appropriate
grammar. The presentation of the introduction of the text (the address) was perceived as
the primary impression marker of the “outside appearance” of the message itself – with
women highlighting it as being important more than men (Stokar von Neuforn, 2007).
Meyers-Levy (1989) however suggested that females construct judgements based on the
last piece of information whereas males utilize the first piece of information in framing
their initial mindset.
Sierpe (2005) studied the role of gender distinctiveness being interpreted within textbased communication in electronic environments. This entailed the separation of gender
“traces” and gender “cues” - the former being associated with specific markers of
production in texts and the latter being utilized as a tool of textual interpretation. These
gender markers generally involve characteristics including – but not limited to – message
18
length, grammatical attributes, content, opinion on a topic and friendliness. It was
postulated that the formation of cognitive skills framed by “social communicative
competence” (Sierpe, 2005, p. 133) since early childhood enables the transformation of
gender traces to gender cues. The results depict that texts deemed to be written by women
are interpreted in accordance with societal notions of women being “polite, kind and
caring” (Sierpe, 2005, p. 142), all characteristics that the author suggests stem from
females expected to adopt a subordinate role in society. This is incidentally also in keeping
with the social role theory discussed previously (Eckes & Trautner, 2000; Putrevu et al.,
2001). Gender cues therefore, may be considered as characteristics within a text that serve
the purpose of being specific markers from the reader’s point of view (Sierpe, 2005).
2.4 Summary
This study will aim to address whether the inclusion of specific gender cues can work
towards manipulating the perception of individuals reading it. The cues will relate to how
affective or cognitive the language in the message is. This also relates to previous findings
on information processing between genders (Meyers-Levy, 1989; Meyers-Levy &
Maheswaran 1991). The pertinent findings on gender differences attained from the
literature review are summarized in Table 1 on the next page.
19
Table 1. Findings summary on gender differences
Reference Source
Findings for females
Findings for males
More comprehensive in
information processing
More selective in information
processing
Prefer intangible features in
advertising (user benefits etc.)
Prefer tangible features in
advertising (product information
etc.)
Prefer presence of more
information
Prefer presence of less information
and more numbers/statistics
Emotional ad appeals preferred
Rational, objective ad appeals
preferred
Subjective advertising claims
Objective advertising claims
More likely to note inconsistencies
Less likely to note inconsistencies
Prefer descriptive, emotional
information
Prefer factual information
“Other-oriented”, social benefit
view
“Self-oriented”, personal benefit
Make calculated purchase
decisions for the long term
Make impulsive purchase decisions
for the short term
Refer to words associated with
sociology, psychology, personal
interaction, emotions, thoughts
and senses
Refer to words associated with
logic, objective properties, career,
sports, exploration, rebellion etc.
More emotive, elaborate and
friendly language style
Less emotive, mechanical and
reserved language style
More affectively oriented
More cognitively oriented
More persuaded by affectively
framed words such as “feel”
More persuaded by cognitively
framed words such as “think”
Prefer greater length of text and
sentences
Prefer shorter length of text and
sentences.
Prefer more empathetic text
Prefer less empathetic text
Prefer more expressive language
Prefer more informative language
Meyers-Levy (1989)
Carsky & Zuckerman (1991)
Darley & Smith (1995)
Meyers-Levy & Loken (2015)
Shayon (2011)
Kraft & Weber (2012)
Newman et al. (2008)
Pennebaker et al. (2003)
Haas (1979)
Flynn (1983)
Waters (1975)
Mayer & Tormala (2010)
Stokar von Neuforn (2007)
Voss (1983)
20
2.5 Hypotheses
In accordance with the literature review, there are numerous studies related to the
dynamics among Gender, Language and Advertisements, but the paucity of concrete
scientific data evaluating the difference in perception of especially text in advertisements
between genders is noticeable. Based on the findings attained from the literature review
- and in keeping with the ideology of quantitative research requiring the formulation of a
hypothesis (Williams, 2007) – the following hypotheses were constructed:
H1: A cognitive ad message will lead to more positive responses in men than
women.
H1-0: A cognitive ad message will have no differential effect on men and women.
H2: An affective ad message will lead to more positive responses in women than
men.
H2-0: An affective ad message will have no differential effect on men and women.
21
3. METHODOLOGY
This chapter sheds light on the approach applied towards gathering and analyzing the
data required for the study. First, the research design is discussed, after which the data
collection process is presented. The section is concluded with a brief description of the
measures and constructs that form the basis of this study.
3.1 Research Design
The objective of this study was to ascertain whether there was a significant difference
present between the perception of males and females when it comes to interpreting the
text in advertisements. In light of this, a quantitative research approach was adopted as
this method allows for quantifiable, accurate results based on statistical treatments that
can be objectively extrapolated towards formulating generalizations based on measuring
certain phenomenon (Creswell, 2003; Silverman, 2006). Furthermore, the use of
experiments to gather statistical data to analyze and build on pre-existing theory was
opted for as the primary research method (Creswell, 2003; Leedy & Ormrod, 2001). As
the aim of the study revolves around establishing the presence (or lack thereof) of a
pertinent observable difference between the perception of two genders, the quantitative
method further motivates the use of experimentation for this study.
The use of an experiment format to evaluate consumer responses in advertising is
common in both the academic and practical fields due to its ability to manipulate multiple
variables and scientifically analyze any effects present, thereby providing concrete results
to generalize from (Senior, 2013). Moreover, this form of research design is considered as
the “gold standard” (Johnson, Lewis & Reiley, 2016, p. 2) in evaluating ad effectiveness
as it allows for an investigation into the causal effect of an isolated independent variable
(in this case, gender or cognitive/affective text) on other variables (such as attitude
towards the ad, purchase intentions etc.). As one variable does not affect the results of the
other, this form of design also increases the internal validity.
22
By assessing gender perception based on cognitive and affective ad scenarios, it is hoped
that viable results and information can be achieved from this experiment format on the
basis of which the proposed hypotheses can be accepted or rejected.
3.1.1 Product Selection
The study was aimed to be conducted on the basis of an advertisement portraying a
gender-neutral product. To cater to this, an advertisement layout was constructed
whereby a product would be displayed which has no inclination towards being perceived
as more masculine or feminine. Choosing the product itself was a precarious task, as
socio-cultural contexts meant that the product selected had to be truly gender-neutral
from a global standpoint. Xue and Yen (2007) studied how men often associate
themselves more with products depicting masculine traits such as tools and vehicles,
whereas women prefer products which are unique and more refined. Keeping all this in
consideration – and after eliminating an array of potential products - the final product
selected was a biscuit, more specifically “Crackers”. The use of this product is justified as
it avoids falling into a pitfall of being classified as being more preferred by one gender
over the other and has no gender-based connotations associated with it. Being a light,
edible snack to be devoured has no specific weightage when it comes towards gender bias.
3.1.2 Advertisement Selection
A biscuit and cracker manufacturing company from South Asia, EBM, was utilized to form
the basis of the advertisement, but due to access issues pertaining to consent of the
product, the advertisement was kept unbranded. However, to make the advertisement
seem as authentic as possible, the design of the ad was kept very close to the layout set by
EBM. A mockup advertisement of a cracker brand was made, which depicted two flavors
of the same brand, along with accompanying text. Recent findings have shown that blue
is considered to be the most preferred color by both men and women, (Hallock, 2003) on
the basis of which the background of the advertisement was kept blue. Two variations of
the advertisement were made, with text being the differentiating factor in each, based on
which difference in perception was to be measured. It was important that the image and
visual aspect of the advertisement remained the same in both treatments as visuals
23
usually alter the perception of individuals by the most considerable degree. (Severn, Belch
& Belch, 1990). In order to study the causal effect of the text on gender perceptions, all
other factors had to be equal. The only piece of text that remained the same in both
variations of the advertisement was the heading “New Look, New Flavour!”
3.1.3 Treatments
The two treatments were constructed in accordance with past research on gender
differences described in the literature review and were framed in cognitive and affective
texts respectively. The text in the cognitive treatment was developed using objective
language which the findings portray men to be more inclined towards. The affective
treatment was formulated in a manner in which the text was more emotional, which - in
theory - should be more appealing to women.
The final ad treatments can be found in Appendix I, whereas the text employed within
each are displayed in Figure 1 and Figure 2. After the figures, the different texts are
motivated based on the earlier review.
Figure 1. Cognitive Treatment Text
A feast for the eyes
A treat for the taste buds
2 flavors to choose from + New Packaging!
Our original crackers are made from fresh butter, fresh eggs and the perfect blend of coconut oil, whey
powder and sugar.
The new veggie flavor adds on all this by introducing a whole assortment of vegetables and spices to
give it that unique taste! Don't wait, buy Butter Puff crackers today!
Butter Puff - Providing the perfect crackers since 1974.
24
Figure 2. Affective Treatment Text
Ever find yourself thinking about that perfect first bite from a cracker? Time to make that a reality,
because Butter Puff crackers are back with vibrant new packaging which will make you reaching for
them every time!
But that's not all - we've come out with an all new flavor just for YOU! This new veggie flavor is sure to
tantalize your taste buds and have you itching for another bite! Using the freshest of ingredients and
organically sourced vegetables, we can guarantee that the perfect cracker will be yours to savor!
Listen to the gentle crunch before it melts in your mouth in all of its buttery goodness.
Let yourself be immersed by something which tastes so rich yet feels so light.
So what are you waiting for? Go take a bite of your favorite cracker today!
The basis upon which this textual alteration was accomplished was by using the findings
established in section 2.4; the cognitively oriented advertisement had its text transformed
into one which was more logical and objective. Hence, the cognitively framed text can be
seen to be more succinct, shorter in length by 59 words, and to-the-point - which males
supposedly respond more to (Von Neuforn, 2007). The information processing
differentiation proposed by the selectivity model (Meyers-Levy, 1989) states how men are
more selective in what they want to process from the information they are exposed to.
Therefore, the text in the cognitive treatment also contained more tangible features such
as product and ingredient based information (“made from fresh butter, fresh eggs and the
perfect blend of coconut oil, whey powder and sugar”) which studies have shown men to be
more interested in when viewing advertisements (Darley & Smith, 1993). Special care was
placed in ensuring that a first-person communication approach was not adopted, which
can be seen via the lack of words such as “You” or “Your”. Also, numbers were introduced
in the cognitive treatment text (“2” and “1974”) as it has been posited that men respond
to their presence more (Newman et al., 2001).
Similarly, the text in the affective treatment was made in a manner to make it more
expressive, emotional and subjective – to cater towards the female persona (Hirschman
& Thompson, 1997; Haas, 1979; Darley & Smith, 1995; Meyers-Levy, 1989; Meyers-Levy
& Sternthal, 1991). This was accomplished by consistently referring to the reader in the
25
first-person to initiate a more intimate rapport with the reader (“Ever find yourself
thinking...”, “just for YOU…”, “tantalize your taste buds” etc.). The language employed
here was also structured around a sense of “feeling” the text (“Listen to the gentle crunch”,
“have you itching for another bite!”), which is consistent with the use of subjective claims
to invoke an affective feel within the language in advertisements (Darley & Smith, 1995).
“Organically sourced vegetables” were mentioned here as the findings from the literature
review also indicated how women respond more favorably to brands involved in being
socially and environmentally responsible (Shayon, 2011). In keeping with Von Neuforn’s
(2007) analysis and Meyers-Levy’s (1989) selectivity model, the text in the affective
treatment was more comprehensive and longer in both sentence structure and word count
(cognitive: 79 words, affective: 138 words).
3.2 Sample
The sample consists of a convenience sample of 70 business university students, including
a systematic sample of 35 students for each of the treatments (19 males and 16 females in
the cognitive treatment, 16 males and 19 females in the affective treatment). The initial
plan was to sample students within a single course lecture, but this approach had to be
replaced with an alternative strategy due to only 10% of the students being present for the
lecture. Therefore, data were collected from an international mix of business students
within the university, still using convenience sampling as it offered ease of accessibility
and has been referred to as being a valid technique to gauge the testing of theories (Mittal,
1995).
The choice of business students as the sample means that they are relatively homogenous.
Students can be considered appropriate for the product, since they are consumers and
buyers of biscuits and therefore the type of product in the advertisement – crackers – was
something considered to be accessible and known to students. In addition, business
students are appropriate responders to advertising perception not only in the present, but
in the years to come (Christian, Zdenek & Lucie, 2014).
As the students were part of an international university, the respondents also varied in
terms of their cultures and backgrounds. Due to there being a need for an equal number
26
of respondents in each treatment and for a relatively equal distribution of men and
women in the overall sample, systematic sampling was chosen as the preferred method of
data collection. To achieve this end, the pile of questionnaires was placed in a systematic
order of Cognitive and Affective treatments, so that every second one was cognitive vs.
affective. In this way, the next respondent got a different treatment from the one
preceding it. A concentrated emphasis was also placed in distributing the questionnaires
to an equal amount of male and female students so that the gender ratio in each treatment
would relatively balance out.
The business students were told that they were evaluating an ad about a product from
South Asia that was looking to enter into the international market, so as to ensure that
the difference in gender perception was not identified as the purpose of the study.
3.3 Measures and Constructs
The gender differences in perception based on language were measured across five broad
response constructs, which tapped into measures commonly used in advertising studies,
and an added measure on the text. These were: Attitude toward the Ad (aA), Attitude
toward the Product (pA), Emotions from the Ad (eA), Perception of Text in the Ad (tA)
and Purchase Intention (pI), depicted with their respective measures and references in
Table 2.
Arguably one of the primary means to gauge perception in advertisements is via
measuring attitude towards the advertisement, for which Statements 1 to 4 were
constructed. The attitude towards the product statements (5 to 7) were included to extract
opinions towards Crackers themselves. Statement 5, which assessed product familiarity,
was included as a filler item to check whether respondents were aware of the product, and
this item was removed from the scale analysis later on. The purchase intention portrays
whether the advertisement has affected the reader enough to try the product. The
purchase intention construct here (Statements 15 to 17) works towards evaluating
whether the “objective” claim of the cognitively treated ad fares better for males, while
the “subjective” claim of the affectively treated ad is preferred by women.
27
As the differentiating factor between each treatment was the text, three measures to
evaluate its effectiveness and interpretation (Statements 12 to 14) were included.
Statement 12 was later removed to improve scale reliability. The statements in the
emotion construct (8 to 11) were aimed to evaluate how the respective treatments made
the respondents feel. Statement 11 was included as the manipulation check in this study,
to measure if the affective treatment invoked more emotions than the other treatment.
Table 2. Constructs and Measures
Constructs
Attitude towards Ad
(aA)**
Measures
1. The advertisement is interesting
2. The advertisement left a positive impression
3. The quality of the advertisement is very good
4. The advertisement is unappealing*
Attitude towards
Product (pA)
Emotions from Ad
(eA)
Perception of Text
in Ad (tA)
Purchase Intentions
(pI)
5. The product in the advertisement is familiar
6. The product in the advertisement is something I
like
7. The product in the advertisement is important
to me
8. The advertisement made me feel good
9. The advertisement made me feel pleased
10. The advertisement made me feel irritated*
11. The advertisement did not induce any
emotions within me
12. The text used within the advertisement was
persuasive
13. The text within the advertisement was easy to
understand and interpret
14. The text within the advertisement was
informative
15. The product in the advertisement is something
I would want to buy
16. The information provided in the
advertisement is useful for my purchase decision
17. The probability of me purchasing this product
is very low*
Source
Mitchell and Olson (1981)
Wright (1980)
Anand and Sternthal
(1990)
Mitchell and Olson (1981)
Wright (1980)
Abelson, Kinder, Peters
and Fiske (1982)
Holbrook (1978)
Mitchell and Olson (1981)
Batra and Ray (1986)
Mackenzie, Lutz and
Belch (1986)
*Statements 4, 10 and 17 were reverse coded to align them with the scale in terms of the other statements
present.
**The abbreviations of the constructs will be used in the tables presenting the data analysis results.
28
The measures and scales used were adopted from studies which have been extensively
utilized in marketing research. Internal reliability tests on the collected data were
conducted to further ascertain scale suitability. The final questionnaire – attached in
Appendix II - consisted of these statements and questions on age and gender.
The respondents were requested to indicate the degree to which they agreed or disagreed
with each statement on a 1 to 7 point Likert-type scale (1 = Strongly Disagree, 2 =
Disagree, 3 = Slightly Disagree, 4 = Neutral, 5 = Slightly Agree, 6 = Agree, 7 = Strongly
Agree). A 5-point scale was not used as a wider scale is more ideal for internal reliability
tests, which are generally sensitive to the number of items in the scale (Pallant, 2010).
29
3.3.1 Internal Reliability of Scale
Five internal consistency tests were conducted for each of the dependent constructs to see
if the variables in each effectively load on the expected constructs. As stated previously,
statement 5 was included to assess familiarity with the product as a filler item and hence
was not included in the final scale analysis. Statement 11 played the role of a manipulation
check and was evaluated separately, and hence also not included in the final analysis.
Statement 12 was removed from the construct measuring evaluation of text in the ad, to
improve overall scale reliability as it did not load with the other variables. The adopted
method to evaluate internal consistency was Cronbach’s alpha coefficient. The relevant
results are condensed in Table 3 below, with the SPSS output of these tests included in
Appendix III.
Table 3. Internal Reliability of Scale
Construct
No. of respondents
No. of items in scale
Cronbach’s Alpha for
the final scale
Attitude towards Ad
(aA)
70
4
0.916
Attitude towards
Products (pA)
70
2
0.858
Emotions from Ad (eA)
70
3
0.904
Perception of Text in
Ad (tA)
70
2
0.867
Purchase Intentions
(pI)
70
3
0.791
According to DeVellis (2003, cited in Pallant, 2010), the ideal value of Cronbach’s alpha
coefficient within a scale should be greater than 0.7. As is evident by the table above, all
the scales in the constructs had good internal consistency with a value higher than 0.7,
therefore being suitable to use in the study.
30
4. RESULTS
The research questions in the aim of study are built around establishing, firstly, the
presence of a gender difference in perception of advertising text. Secondly, they also look
to address whether males respond more positively to cognitive advertising text and
females to affective advertising text. To achieve this end, a two-way MANOVA analysis
was performed after meeting the required assumptions associated with such an analysis.
A two-way MANOVA is ideal for when there are two independent variables present, such
as gender and cognitive/affective treatment in this study. Moreover, the presence of
multiple dependent variables in the study further motivates the use of this form of
analysis to answer the research questions (Pallant, 2010).
Not only will this two-way design allow for an analysis of the main effect by both gender
and cognitive/affective treatments separately, it will also provide data on an interaction
effect between the two. This interaction effect will be crucial in answering the
supplementary research questions in this study, to evaluate the extent of the effect a
cognitive/affective treatment has on each gender type. An extended advantage of this
analysis is that a significant interaction effect can then be further explored with the results
of the between-subjects test, which allows for evaluating the effect of each dependent
variable on the interaction individually as well.
4. 1 Manipulation Confirmation
The first step of the analysis was to conduct a manipulation check to gauge whether or not
the respondents accurately perceived each variation of the ad so that the affective
treatment invoked more feelings than its cognitive counterpart. Statement 11, “the
advertisement did not induce any emotions within me” was included as the dependent
variable manipulation check within the questionnaire. As there were only two variations
of the treatments, an independent samples t-test was done to achieve this end (Pallant,
2010). The independent variable was the type of ad treatment each respondent was
exposed to, thereby comparing presence of emotion with cognitive or affective ad
conditions. Selective results from this manipulation check are presented below, with the
overall SPSS output included in Appendix IV.
31
Table 4. Manipulation Check Independent Samples Test
Dependent
Variable
The
advertisement
did not induce
any emotions
within me
Type of Ad
Treatment
Respondent
was Exposed
to
No. of
Respondents
Mean
Standard
Deviation
Cognitive
35
4.31
1.367
Affective
35
3.40
tvalue
Df
Significance
3.06
68
0.003
1.117
There was a statistically significant difference in scores between the Cognitive (M = 4.31,
SD = 1.37) and Affective (M = 3.40, SD = 1.12) conditions; t (68) = 3.06, p = 0.003. These
results show that the type of ad treatment did have an effect on the presence of emotions.
Specifically, in the affective treatment conditions, a lower mean value (below the scale
mean of 4), indicates that the ad resulted in greater stimulation of emotions compared to
the cognitive counterpart, which received a higher mean value for this variable. This
indicates that the manipulation was successful.
4.2 Two Way MANOVA
The dependent variables were categorized into five broad constructs: Ad attitude, Product
Attitude, Emotions from Ad, Perception of Text in Ad and Purchase Intent. All five
constructs were used as dependent variables to test for differences in the results between
the ads and gender.
A two-way MANOVA was executed to cater to the presence of more than one independent
variable and multiple dependent variables (Pallant, 2010). The primary aim of this was to
ascertain whether there was an interaction effect between gender and type of ad treatment
on the five categorized dependent variables. However, to perform MANOVA successfully,
several assumptions were required to be met, which were eventually tested and satisfied
before moving on to the actual two-way multivariate analysis. These preliminary
assumption tests were conducted to check normality, linearity, univariate and
32
multivariate outliers, homogeneity of variance-covariance matrices and multicollinearity
(Pallant, 2010). The complete respective SPSS outputs of these assumption tests are
present within the appendices, with a selected few displayed below
4.2.1 Assessing Normality
As MANOVA is relatively sensitive to the presence of any noticeable outliers (Pallant,
2010), measures had to be taken to determine their existence in both univariate and
multivariate forms. Univariate outliers were checked for the dependent variables using
box plots to filter out any potential discrepancies (refer to Appendix V). An evaluation of
these plots depicted no observable univariate outliers for any of the dependent variables,
thereby satisfying part of this assumption. Checking for multivariate normality required
an alternate approach which consisted of employing Regression in IBM SPSS Statistics
software to calculate Mahalanobis distance and comparing it with critical values
summarized by Pallant (2010) and based on values originally established by Pearson &
Hartley (1958).
The Residuals Statistics table (presented in Appendix V) portrays a maximum value of
Mahalanobis Distance of 15.63. According to Pallant (2010), the critical value that this
needs to be compared to - based on the number of dependent variables present in this
study (five) - is 20.52. Therefore, as the Mahalonobis distance value is less than the critical
value, the assumption can be made that there are no prominent multivariate outliers
either.
4.2.2 Linearity & Correlation
This assumption was required to be fulfilled to ensure some form of straight-line
relationship between each corresponding pair of the five dependent variables (Pallant,
2010). This was assessed by generating matrix scatterplots of the dependent variables for
each group of independent gender and treatment variables:
33
Figure 3. Matrix scatterplots for linearity
The separate matrix scatterplots do not indicate any observable evidence of non-linearity,
thereby correctly satisfying this assumption as well. Moreover, a correlation analysis was
run on SPSS which portrayed moderate levels of correlation between the dependent
variables which satisfied the assumption as multicollinearity and singularity were not
present. The correlation results are attached in Appendix V.
4.2.3 Homogeneity of variance-covariance matrices
The results obtained from Box’s test as part of the MANOVA output were useful in
evaluating the fulfillment of the homogeneity of variance-covariance matrices
assumption, which resulted in deriving a significance value of 0.174 (SPSS output table
attached in Appendix VI). As the value of p > 0.001, it can be assumed that this
assumption has not been violated (Pallant, 2010).
34
4.2.4 Multivariate Tests
After the above-mentioned assumptions were satisfactorily tested, the two-way MANOVA
was run on the data using SPSS to determine the extent of the effect, if any, that the
interaction between gender and ad treatment had on the dependent variables. The entire
SPSS output of the MANOVA can be found attached within Appendix VI, while specific
results are depicted in Table 5. The table shows that all three effects on the dependent
variables were significant: the direct effect of gender, the direct effect of the ad treatment,
and the interaction effect of gender and treatment.
Table 5. Multivariate Tests
Effect
Value
F
Hypothesis
df
Partial
Error df
Significance
eta
squared
Gender
Wilks’ Lambda
0.735
4.461
5
62
0.02
0.265
Treatment
Wilks’ Lambda
0.747
4.193
5
62
0.02
0.253
Gender *
Wilks’ Lambda
0.408
18.029
5
62
0.000
0.592
Treatment
For the above multivariate tests, the significance threshold was set at the standard 0.05
value. There was a statistically significant effect of gender on the combined dependent
variables, F (5, 62) = 4.461, p = 0.02; Wilks’ Lambda = 0.735; partial eta squared = 0.265,
as well as a statistically significant effect of cognitive and affective ad treatments on the
combined dependent variables, F (5, 62) = 4.193, p = 0.02; Wilks’ Lambda = 0.747; partial
eta squared = 0.253. Moreover, there was a statistically significant interaction effect of
gender and treatment on the combined dependent variables, F (5, 62) = 18.029, p < 0.001;
Wilks’ Lambda = 0.408; partial eta squared = 0.592. It is worth noting that while both
independent variables have a statistically significant effect, the partial eta squared value
for the combined interaction effect is higher, representing 59.2% of the variance in
dependent variables explained by the gender and treatment interaction.
35
When studying the impact of the interaction effect on each of the dependent variables, it
is pertinent to mention that a Bonferroni adjustment was applied to attain a higher alpha
value to mitigate chances of a Type 1 error (Pallant, 2010). Based on the number of
dependent variables present in this study, a new alpha value was calculated at 0.01, thus
allowing for significance only when results were lesser than this value. The results in
accordance with the gender and treatment interaction are displayed below, whilst the
extended SPSS output for the between-subjects tests is attached in Appendix VI.
Table 6. Tests of between-subjects effects
Df
F
Significance
Partial eta
squared
Gender*Treatment Attitude towards
Ad (aA)
1
66.533
0.000
0.502
Attitude towards
Product (pA)
1
0.008
0.928
0.000
Emotions from
Ad (eA)
1
69.852
0.000
0.514
Perception of
Text in Ad (tA)
1
59.571
0.000
0.474
Purchase
Intentions (pI)
1
35.295
0.000
0.348
Source
Dependent
Variable
Table 6, which reports the results for the dependent variables separately using a
Bonferroni adjusted alpha level of 0.01, shows that there was a statistically significant
effect of the interaction between gender and type of ad treatment on Attitude towards ad
(F (1, 66) = 66.533, p < 0.001, partial eta squared = 0.502), Emotions from ad (F (1, 66)
= 69.852, p < 0.001, partial eta squared = 0.514), Perception of text in ad (F (1, 66) =
59.571, p < 0.001, partial eta squared = 0.474) and Purchase intentions (F (1, 66) =
35.295, p < 0.001, partial eta squared = 0.348), all of which reached statistical
significance. Attitude towards the product (F (1, 66) = 0.008, p = 0.928, partial eta
squared < 0.001) was the only variable that did not reach statistical significance.
36
These results are followed by a comparison of group means to indicate which gender
responded more favorably to each respective ad treatment based on the four dependent
variables portraying a statistically significant interaction effect. The salient results are
listed in the Table 7, with the complete SPSS output for the estimated marginal means are
included within Appendix VI.
Table 7. Estimated Marginal Means
Dependent Variable
Attitude towards Ad
(aA)
Attitude towards
Product (pA)
Gender
Male
Female
Male
Female
Male
Emotions from Ad (eA)
Female
Perception of Text in
Ad (tA)
Purchase Intentions
(pI)
Male
Female
Male
Female
Type of Ad Treatment
Respondent was Exposed to
Cognitive
Affective
Cognitive
Affective
Cognitive
Affective
Cognitive
Affective
Cognitive
Affective
Cognitive
Affective
Cognitive
Affective
Cognitive
Affective
Cognitive
Affective
Cognitive
Affective
Mean
4.724
3.031
3.469
4.789
4.132
4.063
3.500
3.395
4.456
3.021
3.417
4.947
5.605
3.406
4.375
5.211
4.702
3.271
3.312
4.035
An inspection into these differences in mean scores can also be visualized by the plots
constructed in the IBM SPSS Statistics software, which clearly show the interaction effects
as depicted below:
37
5
4.789
4.724
Ad Treatment
4.5
4
Cognitive
Affective
3.469
3.5
3.031
3
Male
Female
Gender
Figure 4. Estimated Marginal Means of Attitude towards the Ad
An inspection into the mean scores indicate that males had a more favorable attitude towards the
Cognitive ad (M = 4.724) as opposed to the Affective ad (M = 3.031). Females however reported a
more positive attitude towards the Affective ad (M = 4.789) than the Cognitive ad (M = 3.469).
Meanwhile, Figure 5 portrays the absence of any significant difference in perception between
genders when it comes to attitude towards the product.
4.5
4.132
4.063
Ad Treatment
4
3.5
3.395
3.5
Cognitive
Affective
3
Male
Female
Gender
Figure 5.Estimated Marginal Means of Attitude towards the Product
38
Figure 5 also shows that males have a higher attitude towards the product for both the Cognitive
(M = 4.132) and Affective ad (M = 4.063) than females (Cognitive ad = 3.5 and Affective ad M=
3.395).
4.947
5
Ad Treatment
4.5
4.456
4
Cognitive
Affective
3.417
3.5
3.021
3
Male
Female
Gender
Figure 6.Estimated Marginal Means of Emotions from Ad
Males also had a higher mean score in Emotions for the Cognitive ad (M = 4.456) than the
Affective ad (M = 3.021) meaning that the former made them feel more good and pleased. By
contrast, females scored lower on emotional responses to the Cognitive ad (M = 3.417) and higher
to the Affective ad (M = 4.947), meaning that the latter made them feel more good and pleased.
6
5.605
5.5
5.211
Ad Treatment
5
4.375
4.5
Cognitive
Affective
4
3.5
3.406
3
Male
Female
Gender
Figure 7.Estimated Marginal Means of Perception of Text in Ad
39
With respect to the evaluation of the textual message content (easy to understand and
informative), males scored higher on the Cognitive ad (M = 5.605) by a much larger degree
compared to the Affective ad (M = 3.406). The pattern was the opposite for females, who
responded more favorably to the text in the Affective ad (M = 5.211) than the Cognitive ad (M =
4.375).
5
4.702
Ad Treatment
4.5
4.035
4
Cognitive
Affective
3.5
3.271
3.312
Male
Female
3
Gender
Figure 8.Estimated Marginal Means of Purchase Intent
Finally, males reported lower intent to purchase for the Affective ad (M = 3.271) than the
Cognitive ad (M = 4.702). Females had a lower score for purchase intent in the Cognitive
ad (M = 3.312) and were more likely to purchase based on the Affective ad (M = 4.035).
In accordance with these results, males responded more positively to the Cognitive ad,
whereas females responded more positively to the Affective ad. Consequently, hypotheses
H1 and H2 were supported, while both null hypotheses were rejected.
40
5. DISCUSSION
This study revealed that men and women differ significantly in their interpretation of
texts utilized within advertisements. Furthermore, the results portrayed a significant
interaction effect between gender and type of ad treatment, supporting both H1 and H2.
Men respond more favorably to advertising text constructed in a cognitive format, whilst
women are more persuaded by advertising text framed in an affective sense.
The findings also depict how the variation between genders occurred in terms of attitude
towards the advertisement, emotions experienced based on the advertisement,
perceptions of text within the advertisement and the purchase intentions. The only facet
where a significant difference was not present was both genders’ attitude towards the
product. However, as this construct measured reaction towards the product itself, this can
be attributed to either personal preference or lack of product awareness in terms of the
product and brand of choice for this study - crackers.
The results showed that men clearly favor cognitively framed text in advertisements,
while women favor affectively framed ones. This phenomenon is also witnessed in
women’s attitudes toward the text in cognitively framed advertisements being much lower
than in affectively framed advertisements. The descriptive and expressive language
employed in the affective treatments was not considered as useful or informative by most
males, whereas the same language style was deemed easy to understand and informative
by females. The variable measuring the usefulness and informativity of the text in the
cognitive treatment attained the highest absolute rating by males among all the
constructs. In line with all the other findings, the cognitive treatment had a more positive
effect on males when it came to purchase intent, and the affective treatment was more
likely to make women want to purchase the product. This demonstrates that the framing
of the advertisement text has an important impact on consumers’ intentions to act and
buy the product. Hence, this framing has a direct impact on concepts affecting the
economics of a product.
41
5.1 Contribution of the study
The study used gender based theories such as the selectivity model (Meyers-Levy, 1989)
and explored gender roles in accordance with cognitive and affective advertising
language. By utilizing a body of relevant research from which hypotheses could be
formulated and eventually investigated via an empirical study, grounded findings
supporting the proposed hypotheses were extracted, providing relevant implications to
the marketing and advertising community. The study has three key findings, which will
be discussed next.
First, this study unveiled the presence of a difference between males and females in terms
of processing and interpreting the text within the advertisement. Women preferred the
affective ad which possessed more information to interpret and included more intangible
features compared to the cognitive ad. It was also found that males preferred the cognitive
ad which placed greater emphasis on tangible features within the text, such as product
and ingredient information. These findings add to the conclusions derived from earlier
studies of the selectivity model (Meyers-Levy, 1989) which stated that women were more
comprehensive in information processing than men and favored intangible features in
advertising compared to men’s preference of lesser information and more tangible
features.
Another key finding from this study was that females responded more favorably to the
affective advertisement text which was more expressive and employed the use of
emotional language. Similarly, males clearly had a more positive response towards the
cognitive ad text, which was framed using objective and rational language. Again, these
findings add to the ones attained from previous studies by Darley and Smith (1995) and
Carsky and Zuckerman (1991), which depicted how women prefer descriptive and
emotional information in ad appeals and men preferred fact-based information based on
objective ad appeals.
The third important finding attained from this study was that females were more
responsive to affectively framed words and sentences, while men were persuaded by
cognitively framed words and sentences. These contributed to current research by
42
reinforcing Mayer and Tormala’s (2010) suggestions of women being more affectively
oriented in terms of interpretation while men are more cognitively oriented. They further
posited that cognitive and affective text frameworks were preferred by males and females
respectively. This study therefore further expands upon the findings by Mayer and
Tormala (2010) by portraying how these cognitive and affective text perceptions hold true
in an advertising context as well.
Along with the key findings, some additional findings were also attained from this study
which will be expanded upon next.
In keeping with prior research, women were appealed by the expressive and empathetic
language in the affective ad treatment, while men felt the use of such language was not
informative and opted for the more to-the-point text within the cognitive treatment (Voss,
1983; Stokar von Neuforn, 2007; Waters, 1975). Females were also more responsive to
the affective ad message which contained some text concerning social benefit, which
Meyers-Levy and Loken (2015) and Shayon (2011) maintain as being more appealing to
women.
The study supports the positive effect of subjective text on women; the affective ad text
incorporated a first-person rapport to make the interaction seem more personal and
included words relating to thoughts, senses and emotions which women are known to
respond more positively to in previous studies (Newman et al., 2008; Pennebaker et al.,
2003; Haas, 1979).
Finally, it was revealed that women preferred greater length of text as the affective ad was
longer than the cognitive ad not only in sentence structure, but also in length by 59 words.
Men preferred the text which was shorter in size, to-the-point and contained numbers.
These further add to previous research suggesting that women prefer greater amount of
information in text than men, while men prefer more direct text and the inclusion of
statistics (Carsky & Zuckerman, 1991; Stokar von Neuforn, 2007).
43
5.2 Managerial implications
This study further builds on past research by depicting how even in modern times - and
with more varied forms of advertising - the difference in male and female perception and
attitude is still present. The implications for advertisers here are multifold, the primary
one being that text in advertisements is still a powerful tool upon which perception
towards the advertisement can be altered. Moreover, advertising is more effective when
it targets men and women separately based on the intended ad appeal. This may be easier
to apply online, where ads can be varied more easily and targeted based on viewer profiles.
In some cases of print ads, it may be possible to alter the text depending on the placement
of the ad itself (e.g. in women’s magazines vs. men’s magazines).
Men continue to be more persuaded by logical, objective and cognitive text which
provides more tangible information and appeals to their buying behavior. The use of
affective text constructed by emotive, descriptive and expressive words will have a greater
chance of being more appealing to women. While this study focused on a single gender
neutral product, the implications can be extended to advertising text employed for
products being catered specifically to each gender as well. Ads depicting personal hygiene
products, for example, can be structured to provide more objective product benefits for
men, and constructed differently for women by depicting more user benefits and a sense
of feeling.
Considering this, advertisers should continue to place a higher emphasis on promoting
their products using cognitive or affective language based on which gender they intend to
target. The use of expressive and elaborate language might seem more in line with
structuring advertisements in the modern era, but when being targeted towards males, it
can seem off-putting and do more harm than good. The same effort needs to be placed to
ensure that advertisements targeted to women do not lack expression and an affective
context as this would alter their perception of the ad in a positive sense by a noticeable
degree.
44
5.3 Limitations and future research directions
As with any research, there are limitations enveloping the research which require
addressing. Five important limitations should be kept in mind when interpreting the
results of this thesis. These limitations are also sources of future study directions.
First, while the use of business students has been previously justified in this paper, it is
still worth noting that the findings from this convenience sample cannot effectively be
generalized to a broader population other than students. Second, while crackers as the
choice of gender neutral product were selected after proper deliberation, it is pertinent to
acknowledge that the study focuses on only one type of product and therefore the scope
of the research is limited. Additionally, the level of product risk associated with crackers
needs to be considered; it has been discussed how males and females might interpret
information differently depending on level of product risk associated with it (Darley &
Smith, 1995). Therefore, as crackers can be considered a low-risk product, results attained
for more expensive or complex products might be substantially different.
A third facet restricting the scope of this study is the focus on only one form of advertising
medium by removing television, audio and social media advertisements from
consideration. Additional research on the topic in the future could therefore expand into
an exploration of gender differences within these mediums as well, especially in terms of
social media which is gaining more popularity and is slowly becoming the primary
medium of advertising.
Fourth, the aim of the study included identifying whether cognitive text in advertising
appeals more to men and affective text to women. However, the use of multiple
dimensions (such as length of text, addition of numbers etc.) as the basis of variation
makes it difficult to accurately ascertain if any specific cue leads to the differences in
perception. Future research could hence also consider studying the factors in this
spectrum – such as length of text – separately in conjunction with gender variance to
further refine which aspects affect perception most and by what degree.
45
Fifth, what this study also could not take into consideration was the natural orientation
(cognitive or affective) of the individual itself. Based on findings from prior research, it
was hypothesized that in certain conditions men may on average be more appealed by
cognitive ads and females by affective ads – hypotheses which were eventually proven.
However, this is by no means enough to correctly assess whether the innate individual
orientation lies more towards cognition or affection, and to what degree that played a role
in altering perception. Further research could work towards investigating this matter
more by employing techniques such as priming to first gauge where the individual’s
natural orientation lies, and then measure the effects of a cognitive or affective ad appeal.
Finally, future direction of research could be more exploratory in nature; the purpose of
this study was to ascertain the existence of these respective gender differences via close
ended questions. By utilizing the findings attained from this study, more open ended
questions can be constructed to expand on understanding the reasoning behind these
differences in attitudes and perception, the results of which would no doubt be
illuminating.
46
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56
APPENDICES
Appendix I – Ad Treatments
Ad 1: Cognitive Treatment
The following brand from Asia is looking to expand into the international market and has constructed the
advertisement below to cater to potential customers. In light of this, carefully review the advertisement and the
information within it, after which the accompanying questions in the back need to be answered.
57
Ad 2 - Affective Treatment
The following brand from Asia is looking to expand into the international market and has constructed the
advertisement below to cater to potential customers. In light of this, carefully review the advertisement and the
information within it, after which the accompanying questions in the back need to be answered.
58
Appendix II – Questionnaire
Age:
A) 16 – 25
B) 26 – 40
Gender:
Male
Female
Strongly
Disagree
C) Above 40
Disagree
Slightly
Disagree
Neutral
Slightly
Agree
Agree
Strongly
Agree
The advertisement is interesting
The advertisement left a positive
impression
The quality of the advertisement is
very good
The advertisement is unappealing
The product in the advertisement is
familiar
The product in the advertisement is
something I like
The product in the advertisement is
important to me
The advertisement made me feel
good
The advertisement made me feel
pleased
The advertisement made me feel
irritated
The advertisement did not induce
any emotions within me
The text used within the
advertisement was persuasive
The text within the advertisement
was easy to understand and
interpret
The text within the advertisement
was informative
The product in the advertisement is
something I would want to buy
The information provided in the
advertisement is useful for my
purchase decision
The probability of me purchasing
this product is very low
59
Appendix III – Internal Reliability SPSS Output
Scale: ALL VARIABLES
Case Processing Summary
N
Cases
%
Valid
Excludeda
Total
70
100.0
0
.0
70
100.0
a. Listwise deletion based on all variables in the
procedure.
Reliability Statistics
Cronbach's Alpha
Based on
Standardized
Cronbach's Alpha
Items
.916
N of Items
.917
4
Item Statistics
Mean
The advertisement is interesting
The advertisement left a
positive impression
The quality of the advertisement
is very good
The advertisement is
unappealing
Std. Deviation
N
4.23
1.332
70
3.99
1.148
70
4.01
1.173
70
4.04
1.160
70
Inter-Item Correlation Matrix
The advertisement is interesting
The advertisement left a
positive impression
The quality of the advertisement
is very good
The
The advertisement
The quality of the
The
advertisement is
left a positive
advertisement is
advertisement is
interesting
impression
very good
unappealing
1.000
.827
.731
.707
.827
1.000
.699
.708
.731
.699
1.000
.734
60
The advertisement is
.707
unappealing
.708
.734
1.000
Summary Item Statistics
Maximum /
Mean
Minimum
Maximum
Range
Minimum
Variance
N of Items
Item Means
4.068
3.986
4.229
.243
1.061
.012
4
Item Variances
1.454
1.319
1.773
.454
1.345
.046
4
Inter-Item Covariances
1.064
.942
1.264
.322
1.342
.015
4
Inter-Item Correlations
.734
.699
.827
.127
1.182
.002
4
Item-Total Statistics
Corrected Item-
Squared
Cronbach's
Scale Mean if
Scale Variance
Total
Multiple
Alpha if Item
Item Deleted
if Item Deleted
Correlation
Correlation
Deleted
The advertisement is
interesting
The advertisement left a
positive impression
The quality of the
advertisement is very good
The advertisement is
unappealing
12.04
9.810
.839
.736
.882
12.29
10.961
.828
.719
.885
12.26
11.034
.791
.635
.897
12.23
11.164
.783
.622
.900
Scale Statistics
Mean
16.27
Variance
Std. Deviation
18.577
N of Items
4.310
4
Scale: ALL VARIABLES
Case Processing Summary
N
%
61
Cases
Valid
Excludeda
Total
70
100.0
0
.0
70
100.0
a. Listwise deletion based on all variables in the
procedure.
Reliability Statistics
Cronbach's Alpha
Based on
Standardized
Cronbach's Alpha
Items
.858
N of Items
.875
2
Item Statistics
Mean
Std. Deviation
N
The product in the
advertisement is something I
3.96
1.055
70
3.59
.807
70
like
The product in the
advertisement is important to
me
Inter-Item Correlation Matrix
The product in the The product in the
advertisement is
advertisement is
something I like
important to me
The product in the
advertisement is something I
1.000
.778
.778
1.000
like
The product in the
advertisement is important to
me
Summary Item Statistics
62
Maximum /
Mean
Item Means
Minimum
Maximum
Range
Minimum
Variance
N of Items
3.771
3.586
3.957
.371
1.104
.069
2
Item Variances
.883
.652
1.114
.462
1.709
.107
2
Inter-Item Covariances
.663
.663
.663
.000
1.000
.000
2
Inter-Item Correlations
.778
.778
.778
.000
1.000
.000
2
Item-Total Statistics
Corrected Item-
Squared
Cronbach's
Scale Mean if
Scale Variance
Total
Multiple
Alpha if Item
Item Deleted
if Item Deleted
Correlation
Correlation
Deleted
The product in the
advertisement is
3.59
.652
.778
.605
.
3.96
1.114
.778
.605
.
something I like
The product in the
advertisement is important
to me
Scale Statistics
Mean
Variance
7.54
Std. Deviation
3.092
N of Items
1.759
2
Scale: ALL VARIABLES
Case Processing Summary
N
Cases
Valid
Excludeda
Total
%
70
100.0
0
.0
70
100.0
a. Listwise deletion based on all variables in the
procedure.
Reliability Statistics
63
Cronbach's Alpha
Based on
Standardized
Cronbach's Alpha
Items
.904
N of Items
.916
3
Item Statistics
Mean
The advertisement made me
feel good
The advertisement made me
feel pleased
The advertisement made me
feel irritated
Std. Deviation
N
3.99
.985
70
3.87
1.102
70
4.21
1.361
70
Inter-Item Correlation Matrix
The
The advertisement made me
feel good
The
advertisement
The advertisement
advertisement
made me feel
made me feel
made me feel
good
pleased
irritated
1.000
.839
.802
.839
1.000
.714
.802
.714
1.000
The advertisement made me
feel pleased
The advertisement made me
feel irritated
Summary Item Statistics
Maximum /
Mean
Minimum
Maximum
Range
Minimum
Variance
N of Items
Item Means
4.024
3.871
4.214
.343
1.089
.030
3
Item Variances
1.346
.971
1.852
.881
1.908
.207
3
Inter-Item Covariances
1.019
.911
1.076
.164
1.180
.007
3
Inter-Item Correlations
.785
.714
.839
.125
1.175
.003
3
Item-Total Statistics
64
Corrected Item-
Squared
Cronbach's
Scale Mean if
Scale Variance
Total
Multiple
Alpha if Item
Item Deleted
if Item Deleted
Correlation
Correlation
Deleted
The advertisement made
me feel good
The advertisement made
me feel pleased
The advertisement made
me feel irritated
8.09
5.210
.883
.788
.823
8.20
4.974
.806
.709
.865
7.86
4.008
.788
.649
.909
Scale Statistics
Mean
Variance
12.07
Std. Deviation
10.154
N of Items
3.187
3
Scale: ALL VARIABLES
Case Processing Summary
N
Cases
%
Valid
Excludeda
Total
70
100.0
0
.0
70
100.0
a. Listwise deletion based on all variables in the
procedure.
Reliability Statistics
Cronbach's Alpha
Based on
Standardized
Cronbach's Alpha
.867
Items
N of Items
.878
2
Item Statistics
65
Mean
Std. Deviation
N
The text within the
advertisement was easy to
4.97
1.103
70
4.46
1.359
70
understand and interpret
The text within the
advertisement was informative
Inter-Item Correlation Matrix
The text within the
advertisement
was easy to
The text within the
understand and
advertisement
interpret
was informative
The text within the
advertisement was easy to
1.000
.783
.783
1.000
understand and interpret
The text within the
advertisement was informative
Summary Item Statistics
Maximum /
Mean
Minimum
Maximum
Range
Minimum
Variance
N of Items
Item Means
4.714
4.457
4.971
.514
1.115
.132
2
Item Variances
1.531
1.217
1.846
.629
1.517
.198
2
Inter-Item Covariances
1.173
1.173
1.173
.000
1.000
.000
2
Inter-Item Correlations
.783
.783
.783
.000
1.000
.000
2
Item-Total Statistics
Corrected Item-
Squared
Cronbach's
Scale Mean if
Scale Variance
Total
Multiple
Alpha if Item
Item Deleted
if Item Deleted
Correlation
Correlation
Deleted
The text within the
advertisement was easy to
4.46
1.846
.783
.612
.
4.97
1.217
.783
.612
.
understand and interpret
The text within the
advertisement was
informative
66
Scale Statistics
Mean
Variance
9.43
Std. Deviation
5.408
N of Items
2.325
2
Scale: ALL VARIABLES
Case Processing Summary
N
Cases
%
Valid
Excludeda
Total
70
100.0
0
.0
70
100.0
a. Listwise deletion based on all variables in the
procedure.
Reliability Statistics
Cronbach's Alpha
Based on
Standardized
Cronbach's Alpha
Items
.791
N of Items
.807
3
Item Statistics
Mean
Std. Deviation
N
The product in the
advertisement is something I
3.96
.875
70
3.87
1.284
70
3.80
1.187
70
want to buy
The information provided in the
advertisement is useful for my
purchase decision
The probability of me
purchasing this product is very
low
Inter-Item Correlation Matrix
67
The information
The product in the
provided in the
The probability of
advertisement is
advertisement is
me purchasing
something I want
useful for my
this product is
to buy
purchase decision
very low
The product in the
advertisement is something I
1.000
.627
.578
.627
1.000
.544
.578
.544
1.000
want to buy
The information provided in the
advertisement is useful for my
purchase decision
The probability of me
purchasing this product is very
low
Summary Item Statistics
Maximum /
Mean
Minimum
Maximum
Range
Minimum
Variance
N of Items
Item Means
3.876
3.800
3.957
.157
1.041
.006
3
Item Variances
1.275
.766
1.650
.884
2.153
.209
3
Inter-Item Covariances
.711
.600
.829
.229
1.382
.011
3
Inter-Item Correlations
.583
.544
.627
.083
1.152
.001
3
Item-Total Statistics
Corrected Item-
Squared
Cronbach's
Scale Mean if
Scale Variance
Total
Multiple
Alpha if Item
Item Deleted
if Item Deleted
Correlation
Correlation
Deleted
The product in the
advertisement is
7.67
4.717
.686
.472
.703
7.76
3.375
.650
.442
.711
7.83
3.825
.616
.388
.737
something I want to buy
The information provided
in the advertisement is
useful for my purchase
decision
The probability of me
purchasing this product is
very low
68
Scale Statistics
Mean
11.63
Variance
8.092
Std. Deviation
2.845
N of Items
3
69
Appendix IV – Manipulation Check SPSS Output
T-Test
Group Statistics
Type of Ad Treatment
Respondent Was Exposed
Std. Error
To
The advertisement did not
N
Cognitive
induce any emotions within Affective
me
Mean
Std. Deviation
Mean
35
4.31
1.367
.231
35
3.40
1.117
.189
Independent Samples Test
Levene's Test
for Equality of
Variances
t-test for Equality of Means
95%
Confidence
Interval of the
Sig.
(2F
The
Sig.
t
df
Mean
Std. Error
tailed) Difference Difference
Difference
Lower
Upper
Equal
advertisement variances
2.524
.117 3.064
68
.003
.914
.298
.319
1.510
3.064 65.395
.003
.914
.298
.318
1.510
did not induce assumed
any emotions
Equal
within me
variances not
assumed
70
Appendix V – MANOVA Assumptions SPSS Output
Box Plots
71
72
73
74
75
Regression
Variables Entered/Removeda
Variables
Model
Variables Entered
1
MeanPurchaseInt
Removed
Method
ent,
MeanProductAttitu
. Enter
de, MeanText,
MeanEmotion,
MeanAdAttitudeb
a. Dependent Variable: Participant ID
b. All requested variables entered.
Model Summaryb
Model
R
.417a
1
R Square
Adjusted R
Std. Error of the
Square
Estimate
.174
.109
27.197
a. Predictors: (Constant), MeanPurchaseIntent, MeanProductAttitude,
MeanText, MeanEmotion, MeanAdAttitude
b. Dependent Variable: Participant ID
ANOVAa
Model
1
Sum of Squares
Regression
df
Mean Square
F
9963.348
5
1992.670
Residual
47338.724
64
739.668
Total
57302.071
69
2.694
Sig.
.028b
a. Dependent Variable: Participant ID
b. Predictors: (Constant), MeanPurchaseIntent, MeanProductAttitude, MeanText, MeanEmotion,
MeanAdAttitude
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Std. Error
52.863
21.960
Coefficients
Beta
t
Sig.
2.407
.019
76
MeanAdAttitude
-13.064
6.609
-.488
-1.977
.052
MeanProductAttitude
-10.346
4.961
-.316
-2.085
.041
-1.234
6.349
-.045
-.194
.846
4.394
4.164
.177
1.055
.295
19.067
6.247
.627
3.052
.003
Mean
Std. Deviation
MeanEmotion
MeanText
MeanPurchaseIntent
a. Dependent Variable: Participant ID
Residuals Statisticsa
Minimum
Predicted Value
Maximum
N
21.08
75.67
50.36
12.017
70
-2.436
2.106
.000
1.000
70
4.058
13.347
7.729
1.926
70
19.30
82.83
50.56
12.391
70
-51.761
60.064
.000
26.193
70
Std. Residual
-1.903
2.208
.000
.963
70
Stud. Residual
-1.964
2.281
-.004
1.003
70
-55.109
64.091
-.204
28.418
70
-2.010
2.361
-.003
1.015
70
Mahal. Distance
.551
15.631
4.929
3.022
70
Cook's Distance
.000
.094
.014
.020
70
Centered Leverage Value
.008
.227
.071
.044
70
Std. Predicted Value
Standard Error of Predicted
Value
Adjusted Predicted Value
Residual
Deleted Residual
Stud. Deleted Residual
a. Dependent Variable: Participant ID
Correlations
Correlations
MeanAdAttitu
de
MeanAdAttitude
MeanProductAttitu MeanEmotio MeanTe
de
n
xt
MeanPurchaseInte
nt
Pearson
Correlatio
1
-.134
.859**
.692**
.645**
.267
.000
.000
.000
70
70
70
70
n
Sig. (2tailed)
N
70
77
MeanProductAttitu
Pearson
de
Correlatio
-.134
1
-.069
-.047
.400**
.570
.699
.001
n
Sig. (2tailed)
N
MeanEmotion
.267
70
70
70
70
70
.859**
-.069
1
.692**
.647**
.000
.570
.000
.000
70
70
70
70
70
.692**
-.047
.692**
1
.587**
.000
.699
.000
70
70
70
70
70
.645**
.400**
.647**
.587**
1
.000
.001
.000
.000
70
70
70
70
Pearson
Correlatio
n
Sig. (2tailed)
N
MeanText
Pearson
Correlatio
n
Sig. (2tailed)
N
.000
MeanPurchaseInte Pearson
nt
Correlatio
n
Sig. (2tailed)
N
70
**. Correlation is significant at the 0.01 level (2-tailed).
78
Appendix VI – Two-way MANOVA SPSS Output
General Linear Model
Between-Subjects Factors
Value Label
Gender
N
1
Male
35
2
Female
35
Type of Ad Treatment
2
Cognitive
35
Respondent Was Exposed To
3
Affective
35
Descriptive Statistics
Type of Ad Treatment
MeanAdAttitude
Gender
Respondent Was Exposed To
Male
Cognitive
4.7237
.71635
19
Affective
3.0313
.91686
16
Total
3.9500
1.17229
35
Cognitive
3.4687
.72958
16
Affective
4.7895
.71813
19
Total
4.1857
.97646
35
Cognitive
4.1500
.95332
35
Affective
3.9857
1.19734
35
Total
4.0679
1.07754
70
Cognitive
4.1316
.68399
19
Affective
4.0625
.81394
16
Total
4.1000
.73565
35
Cognitive
3.5000
.93095
16
Affective
3.3947
.89099
19
Total
3.4429
.89748
35
Cognitive
3.8429
.85553
35
Affective
3.7000
.90910
35
Total
3.7714
.87925
70
Cognitive
4.4561
.69576
19
Affective
3.0208
.96201
16
Total
3.8000
1.09126
35
Cognitive
3.4167
.43033
16
Affective
4.9474
.77191
19
Female
Total
MeanProductAttitude
Male
Female
Total
MeanEmotion
Male
Female
Mean
Std. Deviation
N
79
Total
MeanText
Male
Female
Total
MeanPurchaseIntent
Male
Female
Total
Total
4.2476
.99785
35
Cognitive
3.9810
.78359
35
Affective
4.0667
1.29302
35
Total
4.0238
1.06219
70
Cognitive
5.6053
.56713
19
Affective
3.4063
1.14337
16
Total
4.6000
1.40796
35
Cognitive
4.3750
.74162
16
Affective
5.2105
.76948
19
Total
4.8286
.85700
35
Cognitive
5.0429
.89419
35
Affective
4.3857
1.31219
35
Total
4.7143
1.16274
70
Cognitive
4.7018
.56541
19
Affective
3.2708
.70152
16
Total
4.0476
.95364
35
Cognitive
3.3125
.91464
16
Affective
4.0351
.81570
19
Total
3.7048
.92451
35
Cognitive
4.0667
1.01557
35
Affective
3.6857
.84769
35
Total
3.8762
.94821
70
Box's Test of Equality of
Covariance Matricesa
Box's M
F
62.558
1.195
df1
45
df2
10196.089
Sig.
.174
Tests the null hypothesis
that the observed covariance
matrices of the dependent
variables are equal across
groups.
80
a. Design: Intercept +
GENDER + TREATMENT +
GENDER * TREATMENT
Multivariate Testsa
Hypothesis
Effect
Value
Intercept
Error df
Sig.
Squared
Pillai's Trace
.987
Wilks' Lambda
.013
916.137b
5.000
62.000
.000
.987
73.882
916.137b
5.000
62.000
.000
.987
73.882
916.137b
5.000
62.000
.000
.987
.265
4.461b
5.000
62.000
.002
.265
Wilks' Lambda
.735
4.461b
5.000
62.000
.002
.265
Hotelling's Trace
.360
4.461b
5.000
62.000
.002
.265
.360
4.461b
5.000
62.000
.002
.265
.253
4.193b
5.000
62.000
.002
.253
Wilks' Lambda
.747
4.193b
5.000
62.000
.002
.253
Hotelling's Trace
.338
4.193b
5.000
62.000
.002
.253
.338
4.193b
5.000
62.000
.002
.253
Roy's Largest
Root
Pillai's Trace
Roy's Largest
Root
TREATMENT
df
916.137b
Hotelling's Trace
GENDER
F
Partial Eta
Pillai's Trace
Roy's Largest
Root
5.000
62.000
.000
.987
GENDER *
Pillai's Trace
.592
18.029b
5.000
62.000
.000
.592
TREATMENT
Wilks' Lambda
.408
18.029b
5.000
62.000
.000
.592
1.454
18.029b
5.000
62.000
.000
.592
1.454
18.029b
5.000
62.000
.000
.592
Hotelling's Trace
Roy's Largest
Root
a. Design: Intercept + GENDER + TREATMENT + GENDER * TREATMENT
b. Exact statistic
Levene's Test of Equality of Error Variancesa
F
df1
df2
Sig.
MeanAdAttitude
.303
3
66
.823
MeanProductAttitude
.668
3
66
.575
MeanEmotion
1.093
3
66
.358
MeanText
2.795
3
66
.047
81
MeanPurchaseIntent
1.746
3
66
.166
Tests the null hypothesis that the error variance of the dependent variable is
equal across groups.
a. Design: Intercept + GENDER + TREATMENT + GENDER * TREATMENT
Tests of Between-Subjects Effects
Type III
Sum of
Source
Dependent Variable
Corrected Model
MeanAdAttitude
TREATMENT
F
Sig.
Squared
3
13.667
23.062
.000
.512
3
2.565
3.709
.016
.144
MeanEmotion
41.751c
3
13.917
25.445
.000
.536
MeanText
48.979d
3
16.326
24.320
.000
.525
MeanPurchaseIntent
24.377e
3
8.126
14.240
.000
.393
1113.601
1
1113.601 1879.087
.000
.966
988.749
1
988.749 1429.578
.000
.956
MeanEmotion
1089.786
1
1089.786 1992.499
.000
.968
MeanText
1501.977
1
1501.977 2237.367
.000
.971
MeanPurchaseIntent
1019.302
1
1019.302 1786.277
.000
.964
MeanAdAttitude
1.100
1
1.100
1.856
.178
.027
MeanProductAttitude
7.332
1
7.332
10.601
.002
.138
MeanEmotion
3.417
1
3.417
6.248
.015
.086
MeanText
1.431
1
1.431
2.132
.149
.031
MeanPurchaseIntent
1.696
1
1.696
2.973
.089
.043
MeanAdAttitude
.600
1
.600
1.013
.318
.015
MeanProductAttitude
.132
1
.132
.191
.664
.003
MeanEmotion
.040
1
.040
.072
.789
.001
MeanText
8.074
1
8.074
12.027
.001
.154
MeanPurchaseIntent
2.179
1
2.179
3.819
.055
.055
39.429
1
39.429
66.533
.000
.502
.006
1
.006
.008
.928
.000
MeanEmotion
38.205
1
38.205
69.852
.000
.514
MeanText
39.991
1
39.991
59.571
.000
.474
MeanPurchaseIntent
20.140
1
20.140
35.295
.000
.348
MeanAdAttitude
39.113
66
.593
MeanProductAttitude
45.648
66
.692
MeanAdAttitude
GENDER *
MeanAdAttitude
TREATMENT
MeanProductAttitude
Error
Square
7.695b
MeanProductAttitude
GENDER
df
Partial Eta
41.002a
MeanProductAttitude
Intercept
Squares
Mean
82
Total
Corrected Total
MeanEmotion
36.098
66
.547
MeanText
44.307
66
.671
MeanPurchaseIntent
37.662
66
.571
MeanAdAttitude
1238.438
70
MeanProductAttitude
1049.000
70
MeanEmotion
1211.222
70
MeanText
1649.000
70
MeanPurchaseIntent
1113.778
70
MeanAdAttitude
80.115
69
MeanProductAttitude
53.343
69
MeanEmotion
77.849
69
MeanText
93.286
69
MeanPurchaseIntent
62.038
69
a. R Squared = .512 (Adjusted R Squared = .490)
b. R Squared = .144 (Adjusted R Squared = .105)
c. R Squared = .536 (Adjusted R Squared = .515)
d. R Squared = .525 (Adjusted R Squared = .503)
e. R Squared = .393 (Adjusted R Squared = .365)
Estimated Marginal Means
1. Gender
95% Confidence Interval
Dependent Variable
Gender
MeanAdAttitude
Male
3.877
.131
3.617
4.138
Female
4.129
.131
3.868
4.390
Male
4.097
.141
3.815
4.379
Female
3.447
.141
3.166
3.729
Male
3.738
.125
3.488
3.989
Female
4.182
.125
3.932
4.433
Male
4.506
.139
4.228
4.783
Female
4.793
.139
4.515
5.070
Male
3.986
.128
3.730
4.242
Female
3.674
.128
3.418
3.930
MeanProductAttitude
MeanEmotion
MeanText
MeanPurchaseIntent
Mean
Std. Error
Lower Bound
Upper Bound
83
2. Type of Ad Treatment Respondent Was Exposed To
95% Confidence Interval
Type of Ad Treatment
Dependent Variable
Respondent Was Exposed To
MeanAdAttitude
Cognitive
4.096
.131
3.835
4.357
Affective
3.910
.131
3.650
4.171
Cognitive
3.816
.141
3.534
4.097
Affective
3.729
.141
3.447
4.010
Cognitive
3.936
.125
3.686
4.187
Affective
3.984
.125
3.734
4.235
Cognitive
4.990
.139
4.713
5.268
Affective
4.308
.139
4.031
4.586
Cognitive
4.007
.128
3.751
4.263
Affective
3.653
.128
3.397
3.909
MeanProductAttitude
MeanEmotion
MeanText
MeanPurchaseIntent
Mean
Std. Error
Lower Bound
Upper Bound
3. Gender * Type of Ad Treatment Respondent Was Exposed To
Type of Ad Treatment
95% Confidence Interval
Respondent Was
Dependent Variable
Gender
Exposed To
MeanAdAttitude
Male
Cognitive
Female
MeanProductAttitude Male
Female
MeanEmotion
Male
Female
MeanText
Male
Female
MeanPurchaseIntent Male
Mean
Std. Error
Lower Bound
Upper Bound
4.724
.177
4.371
5.076
Affective
3.031
.192
2.647
3.416
Cognitive
3.469
.192
3.084
3.853
Affective
4.789
.177
4.437
5.142
Cognitive
4.132
.191
3.751
4.513
Affective
4.063
.208
3.647
4.478
Cognitive
3.500
.208
3.085
3.915
Affective
3.395
.191
3.014
3.776
Cognitive
4.456
.170
4.117
4.795
Affective
3.021
.185
2.652
3.390
Cognitive
3.417
.185
3.048
3.786
Affective
4.947
.170
4.609
5.286
Cognitive
5.605
.188
5.230
5.981
Affective
3.406
.205
2.997
3.815
Cognitive
4.375
.205
3.966
4.784
Affective
5.211
.188
4.835
5.586
Cognitive
4.702
.173
4.356
5.048
Affective
3.271
.189
2.894
3.648
84
Female
Cognitive
3.312
.189
2.935
3.690
Affective
4.035
.173
3.689
4.381
85