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The Color Naming Effect: How Fancy Color
Names Influence Product Preference
Master Thesis Ilona Idserda July, 2009
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 2 1/7/2009
The Color Naming Effect: How Fancy Color Names Influence Product Preference
Ilona Idserda University of Groningen Ilona Idserda Waltoren 55, 3811 PD Amersfoort 06 13688750 I.R.Idserda@student.rug.nl Student number: 1386980 Marketing Management Master Thesis Completion date: 1/7/2009 1st Supervisor: dr. M.A. Tuk 2nd Supervisor: dr. D. Trampe
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Management Summary
In all sorts of product categories, from wall paint to cosmetics, fancy color names such as
Glamour Green or Vivid Plum are emerging. Clearly, as companies that are dealing in colors
spend enormous amounts of time and money into selecting the most appealing names, this color
naming practice suggests that color names have an influence on product preference. This is
confirmed by previous research, which revealed that color names significantly influence
consumers’ preferences, and that fancy color names lead to significantly higher product
evaluations than generic color names do.
By conducting empirical research, this study examines how fancy color names influence product
preference. Three explanations for how fancy color names affect product preference are
discussed, namely the Attention Theory, the Association Theory, and the Attributes Theory.
By completing an experiment, the participants of the study rated towels with positively associated
unique, negatively associated unique, and neutrally associated common color names attached to
them. Where the results of the main study showed no difference in participants’ rating of product
preference for positively associated unique, negatively associated unique, and neutrally
associated common color names, the results of the follow-up study in which exposure of the color
names was increased did in fact give some more insights into the color naming phenomenon.
More specifically, the results provide an indication of how the color naming practice influences
consumers’ product preference, and so could act as a guidance of how to use the color naming
practice beneficially. First of all, results indicated that the extent of exposure of color names
matters; the better the color name is noticed, the more likely it is that the color name influences
product preference. Second, the uniqueness factor of fancy color names does not seem to
influence product preference for low-involvement products, and negatively associated color
names should be avoided, since they have the least significant impact on product preference.
Third and finally, positively and neutrally associated color names activate positive categories,
which might lead to product preference for low-involvement products.
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Preface
You are holding my master thesis on the influence of color names on product preference. I have
written this thesis as a final project in order to complete the master Business Administration, in
the direction of Marketing Management. Personally, I believe the topic of this thesis is an
interesting and entertaining topic, and by writing this thesis I have developed my knowledge on
the subject, but also on the process of doing empirical research.
Hereby I would like to take the opportunity to thank a couple of people who supported me during
the process.
First of all I would like to thank my first supervisor, dr. Mirjam Tuk. During the whole process
she gave me useful feedback, and interesting ideas in order to improve my thesis. Also, I would
like to thank dr. Debra Trampe for examining my thesis.
Second, I would like to thank my friends and family for their support. My special thanks go out to
my parents Pieter and Hanneke, for giving me the opportunity to study at the university and for
their continuous love and support. Furthermore, I would like to thank Koen for always being
there for me. Also, I would like to thank Carla, Monique, and Henrieke for their support. Finally,
I would like to thank all the respondents for completing the questionnaires. Without their input,
the completion of this study would have been impossible.
The completion of this thesis is at the same time the completion of my study period in Groningen.
A period I will never forget and will always look back on with great pleasure.
Ilona Idserda
Amersfoort, 2009
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Table of Contents
INTRODUCTION .......................................................................................................................... 7
THEORETICAL FRAMEW ORK ............................................................................................. 11
THE ATTENTION THEORY ............................................................................................................ 11 Theory of Conversational Implicature ................................................................................... 11 Incongruency Theory .............................................................................................................. 12 Hypotheses Based on the Attention Theory ............................................................................ 13
THE ASSOCIATION THEORY ......................................................................................................... 14 The Framing Theory ............................................................................................................... 14 The Categorization Theory ..................................................................................................... 15 Self-image Congruence Theory .............................................................................................. 16 Hypotheses Based on the Association Theory ........................................................................ 17
THE ATTRIBUTES THEORY .......................................................................................................... 18 The Need for Uniqueness ....................................................................................................... 18 Hypotheses Based on the Attributes - Uniqueness Theory ..................................................... 19 The Uniqueness Spillover-Effect ............................................................................................ 19 Hypothesis Based on the Attributes - Uniqueness – Spillover Theory ................................... 20
CONCEPTUAL MODEL .................................................................................................................. 20 SUMMARY ................................................................................................................................... 21
RESEARCH DESIGN ................................................................................................................. 23
TERMINOLOGY ............................................................................................................................ 23 PRETEST ...................................................................................................................................... 23
Pre-test Results ....................................................................................................................... 24 RESEARCH METHOD .................................................................................................................... 26 DATA COLLECTION ..................................................................................................................... 27 PROCEDURE ................................................................................................................................. 28
RESULTS ...................................................................................................................................... 29
ASSOCIATIONS, UNIQUENESS, AND PRODUCT PREFERENCE ........................................................ 29 THE COLOR BROWN, ASSOCIATIONS, UNIQUENESS, AND PRODUCT PREFERENCE ........................ 31 THE COLOR BLUE, ASSOCIATIONS, UNIQUENESS, AND PRODUCT PREFERENCE ........................... 33 THE COLOR GREEN, ASSOCIATIONS, UNIQUENESS, AND PRODUCT PREFERENCE ........................ 34
POST STUDY TO RULE OUT THE INFLUENCE OF SURVEY PHRA SING .................. 36
POST STUDY RESULTS ................................................................................................................. 36 Associations, Uniqueness, and Product Preference ............................................................... 36 The Color Brown, Associations, Uniqueness, and Product Preference ................................. 38 The Color Blue, Associations, Uniqueness, and Product Preference .................................... 40 The Color Green, Associations, Uniqueness, and Product Preference ................................. 41
CONCLUSIONS ........................................................................................................................... 43
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CONCLUSIONS & GENERAL DISCUSSION ..................................................................................... 43 MANAGERIAL IMPLICATIONS ....................................................................................................... 46 LIMITATIONS AND FUTURE RESEARCH ........................................................................................ 47
REFERENCES ............................................................................................................................. 48
APPENDIX 1, PRETEST ............................................................................................................ 51
1.1, EXAMPLE SURVEY PRETEST ................................................................................................. 51 1.2, SELECTED NAMES FROM PRETEST ........................................................................................ 57 1.3, PRETEST, ONE-SAMPLE T TESTS .......................................................................................... 58 1.4, PRETEST, DESCRIPTIVES ....................................................................................................... 60 1.5, PRETEST, ONEWAY ANOVA ................................................................................................ 61 1.6, PRETEST, POSTHOC TESTS .................................................................................................... 62
APPENDIX 2, MAIN STUDY ..................................................................................................... 63
2.1, MAIN STUDY, SURVEY ......................................................................................................... 63 2.2, RESULTS MAIN STUDY, DESCRIPTIVES & ONEWAY ANOVA .............................................. 66 2.3, RESULTS MAIN STUDY, CRONBACH’S ALPHA ...................................................................... 67 2.4, RESULTS MAIN STUDY, CORRELATION ANALYSIS ............................................................... 68 2.4, RESULTS MAIN STUDY, CORRELATION ANALYSIS ............................................................... 68 2.5, RESULTS MAIN STUDY, DESCRIPTIVES, REPEATED MEASURES ANOVA, & CORRELATION
ANALYSIS, BROWN ...................................................................................................................... 69 2.6, RESULTS MAIN STUDY, DESCRIPTIVES, REPEATED MEASURES ANOVA, & CORRELATION
ANALYSIS, BLUE ......................................................................................................................... 71 2.6, RESULTS MAIN STUDY, DESCRIPTIVES, REPEATED MEASURES ANOVA, & CORRELATION
ANALYSIS, BLUE ......................................................................................................................... 71 2.7, RESULTS MAIN STUDY, DESCRIPTIVES, REPEATED MEASURES ANOVA, & CORRELATION
ANALYSIS, GREEN ....................................................................................................................... 73 2.7, RESULTS MAIN STUDY, DESCRIPTIVES, REPEATED MEASURES ANOVA, & CORRELATION
ANALYSIS, GREEN ....................................................................................................................... 73
APPENDIX 3, POST STUDY ..................................................................................................... 75
3.1, SURVEY POST STUDY ........................................................................................................... 75 3.2, RESULTS POST STUDY, DESCRIPTIVES, ONEWAY ANOVA & POSTHOC TEST ...................... 78 3.3, RESULTS POST STUDY, CRONBACH’S ALPHA ....................................................................... 80 3.4, RESULTS POST STUDY, CORRELATION ANALYSIS ................................................................ 81 3.5, RESULTS POST STUDY, DESCRIPTIVES, REPEATED MEASURES ANOVA, POST HOC &
CORRELATION ANALYSIS, BROWN .............................................................................................. 82 3.6, RESULTS POST STUDY, DESCRIPTIVES, REPEATED MEASURES ANOVA & CORRELATION
ANALYSIS, BLUE ......................................................................................................................... 84 3.7, RESULTS POST STUDY, DESCRIPTIVES, REPEATED MEASURES ANOVA, POSTHOC TEST &
CORRELATION ANALYSIS, GREEN .............................................................................................. 86
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Introduction
An examination of the color names attached to many product categories reveals an interesting
phenomenon. For example, it is remarkable that hardly any lipstick carries its generic name, such
as pink or red, nor the name that specifically describes its color, such as light pink or dark red.
Instead, most shades of lipstick carry a fancy name, which links a positive emotion to a shade,
such as Red Passion or Golden Toffee or using a positive emotion without even linking it to a
shade, such as Cute Pie or Star.1 These types of fancy color names are more popular than ever,
and are appearing in all sorts of product categories, from wall paint (e.g., Flexa and the color
‘Room Service’) to cosmetics (e.g., Maybelline and the nail polish Metallic Rose) to household
equipment (V&D and the Apple Green towel).
Clearly, as companies that are dealing in colors spend enormous amounts of time and money into
selecting the most appealing names for their products, this naming practice suggests that the color
names attached to products are an important influence on consumers’ decisions. There are various
suggested reasons why color naming has a positive effect. Miller and Kahn (2005) investigated
whether color and flavor names have an effect on consumer’ choice, and they found that color
names indeed influence consumers’ choice, and that consumers prefer atypical and unspecific
color names (e.g., friendly green) to more typical and more specific color names (e.g., lemon
yellow). Their explanation for this finding is that consumers react favorably to unusual color
names because consumers assume that all information offered to them by the marketer is meant
to be relevant and informative. If the message is not informative and does not conform to
expectations (as is an unusual color name), consumers search for the reason for deviation. This
search results in consumers having more attention for the product with the unusual color name,
and thus noticing additional (positive) attributions about the product, leading to a more favorable
response. Besides Miller and Kahn, also Skorinko et. al., (2006) studied the color naming effect.
More specifically, they investigated whether or not fancy names are indeed more appealing than
generic names, and whether the names associated with colors really make a difference in
consumers’ behavior. Also the results of their study showed that names indeed influence how
colors are perceived, and that the fancy-name effect also resulted in the fancy color named
product to be the preferred product, to be the more likely to be purchased product, and also the
1 Examples from the cosmetic line of Maybelline, on www.maybelline.nl
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participants of the study were willing to pay more money for the fancy color named products than
they were for exactly the same products carrying the generic color name. In order to explain their
findings, Skorinko et. al. refer to Tversky and Kahneman (1981), who found that people reliably
opted for those scenarios framed in terms of gains instead of losses. In the study of Skorinko et.
al. the fancy color names can be seen as positive frames, whereas the generic names were just
that – generic. Furthermore, Skorinko et. al. refer to Fiske and Neuberg (1990), who argued that
people use categorization when forming impressions of others as a defaults. In the case of color
naming, the fancy name activates a positive category, and this positive category in turn positively
influences the impression forming of the product.
Even though both above mentioned studies found the preference for unusual, fancy color names,
it is remarkable that their suggested explanations are deviating. Whereas Miller and Kahn (2005)
suggest the incongruency between the message of the color name and the knowledge and
expectation of the consumers leads consumers to search for additional (positive) attributions,
resulting in a more favorable response, Skorinko et. al. (2006) suggest that the positive
association of the fancy name leads to the preference.
Besides the explanations mentioned in previous research on color naming, this research suggests
another explanation for the preference of fancy color names and products carrying fancy color
names. This suggested explanation is based on the product attribute uniqueness, and more
specifically on the concept of individual’s need for uniqueness. As consumers feel a need to be
different from other individuals, they acquire, utilize and dispose products in order to develop and
enhance one’s personal social identity (Tian, Bearden, and Hunter 2001). Color naming is
possibly one of a marketer’s strategies to appeal to this need for uniqueness, by giving the
product in question a unique color name. This in turn conforms to the individuals need for
uniqueness, and as a result, the individual is likely to prefer the unique color name and the
product carrying the unique color name over the generic color name and product carrying the
generic color name.
As there are multiple suggested explanations for the fancy color naming effect, this research will
investigate in more detail how fancy color names affect product preference. Consequently, this
results in the following problem statement:
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How do fancy color names influence product preference?
In particular, this research will address the influence of fancy color names on consumers’ color
preference, purchase intentions and price willingness to pay. In order to get a deeper
understanding of the explanation for the fancy color naming effect, this research will introduce
two new variables: negatively associated color names and uniqueness.
Negatively associated color names - Besides fancy color names with a positive association, such
as Glamour Green or Vivid Plum, there are also fancy color names that do not carry a positive
element. In fact, some fancy color names even carry a negative element, such as Blood Red
(lipstick by Sephora) or Storm (wall paint by VT Wonen). As it has already become clear from
previous research, fancy color names are preferred over generic color names. However, when
examining how fancy color names influence product preference, the question is whether or not
both positively as well as negatively associated fancy color names are preferred over generic
color names, or that it is just the positively associated fancy color names.
Uniqueness – Individuals feel the need to be different from other individuals, which is also
known as the consumers’ need for uniqueness. As a result, individuals acquire, utilize and
dispose goods in order to develop and enhance one’s personal identity (Tian, Bearden, and
Hunter 2001). The color naming practice might be a method of marketers to attach a uniqueness
appeal to a product, in order for the product to conform to the consumer’s need for uniqueness.
By introducing the variable uniqueness in this research, it will become clear whether or not a
fancy color name is indeed a uniqueness appeal, and consequently whether or not it is an
explanation for the color naming effect.
The introduction of the two variables negatively associated color names and uniqueness results in
the following research questions:
� What is the influence of negatively versus neutrally and positively associated color names
on product preference?
� What is the influence of the uniqueness aspect of fancy color names on product
preference?
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By answering these research questions and consequently providing more insight into the above
mentioned problem statement, a new dimension to the already existing literature on color naming
effects will be contributed, namely how fancy color names influence product preference. More
specifically, the results of this research will give more insights into the suggested explanations of
the finding that fancy color names are preferred over generic color names.
When results will show that there is a difference between positively and negatively associated
color names on product preference, this supports the Association Theory of Skorinko et. al.
(2006), as they claim it is the positive association of a fancy color name that leads consumers to
prefer the fancy color name. When however the results will show that uniqueness is the main
explanation for the color naming effect, this will support the newly suggested Attributes –
Uniqueness Theory. When results show that there is in fact no significant difference between
positively and negatively associated color names on decision making and also uniqueness is not
significant in explaining the color naming effect, both theories can be rejected while the Attention
theory of Miller and Kahn (2005) cannot be rejected. As it is not the association in the name nor
the uniqueness that leads to preferring the fancy color name, it can still be the additional search
for attributions. Finally, it is also possible that both positively and negatively associated color
names are preferred over generic color names, however additionally the positively associated
color names are preferred over the negative ones. In this case, a combination of the Association
theory of Skorinko et. al. (2006) with the Attention theory of Miller and Kahn (2005) or the
newly suggested Attributes – Uniqueness theory is possible.
In practice, the results of this study will provide marketers with the empirical evidence of why
fancy color naming is advantageous. As a result, knowing whether is the attention, association, or
uniqueness that leads to product preference, this makes it more comprehensible for marketers to
select an appealing color name to accompany their products.
The following chapter presents the theoretical framework, in which different theories and a
conceptual model will be presented. Subsequently, the research design will be presented in order
to investigate how color names influence product preference. This paper will end with a review of
the results, and a conclusion.
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Theoretical Framework
In this theoretical framework, the explanations suggested in previous research in the field of color
naming will be discussed. Besides the explanations suggested in previous research, this
theoretical framework offers and discusses an alternative explanation based on previous
consumer behavior research. Moreover, hypotheses on how fancy color names influence product
preference are stated.
The Attention Theory A first explanation why consumers might prefer atypical, fancy color names, is that due to the
ambiguity of the color name, the product carrying the atypical fancy color name receives more
attention from the consumer as the consumer engages in an extra thought process in order to
explain for the ambiguous color name. Due to this extra thought process consumers might notice
additional (positive) attributions about the product that they would not have noticed otherwise
(Theory of Conversational Implicature), or the consumer might discover the connection of how
the adjective of the atypical color name describes the color, leading to a feeling of proud and
resulting in a positive affect and evaluation of the product (Incongruency Theory). It should be
noted that these two theories are not mutually exclusive, however that the Theory of
Conversational Implicature applies for names that are uninformative in a literal sense (ambiguous
color names) and the Incongruency Theory applies for names which are unfamiliar due to their
atypicality (unexpected descriptive color names). (Miller and Kahn 2005). Both theories are
discussed in more detail below.
Theory of Conversational Implicature
According to the theory of Grice (1975), conversations are guided by a set of assumptions,
among which that listeners interpret speakers’ messages based on the assumption that the speaker
is being cooperative, unless they have reason to believe otherwise. Moreover, all information
offered to the listener is assumed to be relevant to the goal of the ongoing conversation. An
example of these assumptions is when somebody asks you where you are going tonight, and you
answer with ‘There is a great play in the theatre’. If taken literally, this is not an answer to the
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question, however rather than assuming the respondent has changed the topic, the listener
assumes that the information is relevant to the goal of the ongoing conversation and the
respondent is going to the theatre that night to see a great play. These same assumptions hold for
marketing messages as well. The consumer may assume that all information offered by the
marketer is meant to be relevant and/or informative, and they will consequently try to make sense
of it. If however a color name is uninformative in the literal or semantic sense, consumers will
search for the meaning of the communication by paying more attention to the product, and
consequently noticing additional (positive) attributions about the product that they would not
have noticed otherwise. As a result, ambiguous color names will yield more positive attributions
about the product than will a common name, which does not require any additional search for
attributions. (Miller and Kahn 2005)
Incongruency Theory
According to the Incongruency Theory, people make judgments by evaluating new encounters
against existing expectations. When their existing expectations deviate from the new encounters,
individuals will engage in more effortful or elaborative processing to solve the incongruency
(Heckler and Childers 1992). Applying this to color naming, the Incongruency Theory suggests
that when consumers encounter an unfamiliar name that is deviating from their expectation, they
will try to determine how the adjective describes the color. When the consumer discovers a
connection, the consumer might experience a feeling of proud, resulting in positive affect and a
positive valuation of the product (Miller and Kahn 2005). However, preferences are thought to be
related to incongruity in an inverted U-shape manner (Meyers-Levy et. al. 1994), so the most
positive affect should result when the name is mildly incongruent. This is also suggested by
Mandler (1982), who stated that congruent items will produce mildly favorable responses with
little arousal because no resolution is required, while on the other hand moderate incongruity will
lead to more extensive processing as people try to resolve and find meaning in the incongruity.
Besides the feeling of pride and the positive affect when resolving the incongruity, such
incongruity can make items appear more interesting which might lead to positive valuations.
However, if the deviation from consumers’ expectation is so large that it is unlikely that the
consumer can solve the connection, the consumer might experience a feeling of frustration and
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helplessness, resulting in a negative affect and negative product valuations. To conclude, a color
name that is mildly incongruent, will lead consumers to pay more attention to the color name in
order to resolve the incongruity. This in turn might make the item in question more interesting,
and when the consumer is able to resolve the incongruity, this is likely to lead to a feeling of
proud and a positive affect, and in the end a more positive evaluation of the product.
Hypotheses Based on the Attention Theory
According to the theories discussed above, it is the extra attention the customer gives to the
atypical fancy color name and the product with the atypical fancy color name, what leads
consumers to prefer products with fancy color names. Therefore, according to the Attention
Theory, it is likely to assume that it makes no difference whether the fancy name encompasses a
positive or a negative association, as it is the atypicality of a color name which leads to an extra
thought process and consequently to a more positive product evaluation. As a consequence, the
following hypotheses are proposed:
H1: Positively associated fancy color names have a significantly more positive influence on
product preference than neutrally associated generic color names have
H2: Negatively associated fancy color names have a significantly more positive influence on
product preference than neutrally associated generic color names have
H3: There is no significant difference between the influence of positively and negatively
associated fancy color names on product preference
Besides the fact that the theory of Conversational Implicature applies for names that are
uninformative in a literal sense (ambiguous color names) and the Incongruency Theory applies
for names which are unfamiliar due to their atypicality (unexpected descriptive color names), also
the timing of revealing a picture of the particular color plays an important role on the influence of
both theories on color and product preference. More specifically, the effect of the Theory of
Conversational Implicature decreases when a picture of the color is simultaneously shown with
the color name, and the effect of the Incongruency Theory increases when a picture of the color is
simultaneously shown together with the color name (for more information about this process see
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Miller and Kahn, 2005). Therefore, as these theories make a distinction between different types
of fancy color names, namely ambiguous and unexpected descriptive color names, and also the
timing effect is important, investigating which theory better accounts for the overall Attention
Theory is beyond the scope of this research.
Furthermore, with respect to the Incongruency Theory, for this research it should be considered
that there are a variety of fancy color names, of which some are in general more or less often and
to a smaller or larger extent incongruent than others. And in this line of reasoning, it is reasonable
to assume that negatively associated color names are more often, and perhaps also to a larger
extent, incongruent with consumers’ expectations, as negatively associated color names are less
common and therefore less likely to be anticipated. Even though it is beyond the scope of this
research to investigate whether or not negatively associated fancy color names indeed are more
often and to a larger extent incongruent than positively associated color names, current research
will make sure that the extent of incongruency of both positively and negatively associated
selected color names are in balance in order to ensure that the extent of incongruency does not
play a role in explaining why fancy color names are preferred over generic color names.
The Association Theory A second explanation why consumers prefer fancy names over generic names, might be due to
the fact that most fancy names used by marketers are positively framed. Products with these
positively associated color names might lead consumers to experience a positive affect, activate a
positive category which influences impression making and/or identify this positively associated
product with their desired end states, and consequently to prefer this product. This Association
Theory is further explored in the following theories.
The Framing Theory
In the widest sense of the word, framing can be defined as the context within which information
is presented. However, when using the concept framing in the context of research about decision
making, framing generally refers to presenting one or two equivalent value outcomes to different
groups of decision makers, where one outcome is presented in positive or gain terms, and the
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other in negative or loss terms (Donovan and Jalleh 1999). A considerable body of research has
already investigated whether or not a positively or gain presented outcome, or a negatively or loss
presented outcome affects judgment and decision making. Levin et al. (1998) suggested that
attribute framing effects occur when evaluations of an object or event are more favorable if a key
attribute within any given context is framed in positive rather than negative terms. Furthermore,
Levin et. al. (1998) argue that these attribute framing effects indeed do occur, because
information is encoded relative to its descriptive valence. Positive labeling of an attribute will
thus lead to an encoding of the information that tends to evoke favorable associations in memory,
whereas negative labeling of the same attribute will cause an encoding that evokes unfavorable
associations. In other words, positive framing supports more favorable evaluations and negative
framing supports less favorable evaluations. Translating this to the color naming effect and
assuming that fancy color names are in general more often positive than negative, the preference
of fancy names over generic names may reflect the fact that the fancy names can be seen as
positive frames, where the generic names were just that – generic. The positive frame of the fancy
color name may result in encoding of the information that tends to evoke favorable associations
in memory, resulting in more favorable evaluations of the color name and the product in question.
On the contrary however, the negative frame of a negatively associated fancy color name may
result in encoding that tends to evoke unfavorable associations in memory, resulting in more
negative evaluations of the color name and the product in question.
The Categorization Theory
As most fancy names used by marketers are positively associated color names, categorization
may also explain why fancy color names are preferred over generic color names. Fiske and
Neuberg (1990) argue that people use categorization when forming impressions of others as a
default. As mentioned above, most fancy color names are positively associated color names and
so this activates a positive category. This positive category in turn positively influences
impression formation of the product. On the other hand, according to this theory the results would
be the other way around when the fancy name would have a negative association.
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Self-image Congruence Theory
A considerable body of research has shown that consumers’ attitudes and purchase intentions
toward brands that match particular aspects of their self-concepts will be more positive and
purchase of these brands will be more likely (Bosnjak and Brand 2008). Even though much of
this research has been focusing on the positive, desirable self-concept, Bosnjak and Brand (2008)
suggest that consumers have a multitude of brand related beliefs, which can be valenced
positively, negatively, and ambivalently. So besides only focusing on the desirable self-concept,
researchers should also keep in mind the undesired end states. Ogilvie (1987) introduced the
concept ‘undesired self’, which he defined as a least desired identity, comprising the sum of
negatively valenced traits, memories of dreaded experiences, embarrassing situations, fearsome
events, and unwanted emotions the individual is consistently motivated to avoid. Banister and
Hogg (2004) introduced this undesired-self concept into the field of consumer behavior, and
showed empirical evidence that the consumption activities of the respondents of their study
seemed to be predominantly informed by the motivation to avoid consuming (or being identified
with) negative images, rather than reflecting attempts to achieve a positive image. In addition,
Bosnjak and Brand (2008) examined the influence of the undesired-self on attitudes towards
consumption and intentions to consume. What they found was that undesired congruity is
negatively related to consumption-related attitudes, and indirectly related to consumption-related
intentions since attitudes predict intentions substantially. Translating this to the color-naming
concept, these findings suggest that as consumers are motivated to avoid consuming negative
images, rather than attempting to achieve a positive image, it is reasonable to expect that
consumers would be less likely to prefer a product that carries a negatively associated color
name. Furthermore, as undesired congruity is directly negatively related to consumption-related
attitudes and indirectly negatively related to purchase intentions, a product with a negatively
associated color name might lead to consumers having a more negative attitude towards
consumption of the product, and thus more negative consumption-related intentions. To illustrate
this with an example, when a consumer sees or wants to see himself as a happy, cheerful person,
he will feel that the wall paint color ‘Storm’ contradicts with his personality, and consequently he
will probably not be inclined to purchase this color of wall paint.
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It should be noted that there are exceptions to the above-mentioned translation of the undesired
self and color naming. For example, tough guys would not like to be associated to the color
‘sweet pink’ as this is incongruent with their self-image, even though the association of the color
name is a positive association. However, albeit the exceptions, it can be assumed that in general
people prefer to identify themselves with positive associations instead of negative associations.
Hypotheses Based on the Association Theory
According to the theories discussed above, the positive associations used in most fancy color
names are the reason why consumers prefer the fancy color names and products carrying the
fancy color names over generic color names and products carrying a generic color name.
Therefore, according to the Association Theory, it is likely to assume that it does in fact make a
difference whether or not the fancy name encompasses a positive or a negative association. As a
consequence, the following hypotheses are proposed:
H4: Positively associated fancy color names have a significantly more positive influence on
product preference than neutrally associated generic color names have
H5: Generic color names have a significantly more positive influence on product preference
than negatively associated fancy color names have
However, as explained in the theories above, it is suggested that associations can influence
product preference in multiple ways. In order to develop a deeper understanding of how fancy
color names influence product preference, the following hypotheses are stated:
H6: As suggested by the Categorization Theory, positively associated fancy names activate a
positive category which in turn leads consumers to prefer the product with the positively
associated color name
H7: As suggested by the Self-image Congruence Theory, when people can better identify
themselves with certain color names, this leads to the preference of the products carrying
these color names
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The Attributes Theory
A number of previously published studies have identified a wide range of product attributes
relevant to individual consumers. The attribute that is expected to be the most influenced by the
color naming practice is ‘uniqueness’. As marketers strive to come up with original,
differentiating color names in order for their products to stand out, this results in an enormous
pile of color names, all unique in its kind. Besides the fact that individuals pursue to be different
from other people – the need for uniqueness –, this uniqueness attribute also could spill over to
other products attributes. The concept of the need for uniqueness and its spillover effect will be
discussed in more detail below.
The Need for Uniqueness
As people seek to be different from other individuals, the products that they purchase and their
uses and displays may serve as recognizable symbols of uniqueness or specialty. For example, the
clothing that people purchase and wear contribute to the style that person wants to portray in
order to enhance the person’s unique identity. More specifically, individuals pursue
differentiation relative to others by acquisition, utilization, and disposition of consumer goods in
order to develop and enhance one’s personal social identity, also known as the consumers’ need
for uniqueness (Tian, Bearden, and Hunter 2001). This need to be different from other people is
driven by the so called ‘counter conformity motivation’. According to this motivation individuals
feel a threat to their identity, as occurs when they perceive that they are highly similar to others
(Snyder and Fromkin 1977).
Marketers have also detected this need for uniqueness. Consequently, in order to appeal to the
individual’s desire to be different from others, marketers develop advertising messages that
employ product-scarcity and uniqueness appeals (Tian, Bearden, and Hunter 2001). This could
also be the case with color naming, as marketers try to give every product of a different shade a
fancy, original color name. This fancy color name in turn will conform to an individual’s desire
to be unique more than a generic color name would, and hence, the consumer would be likely to
prefer a product with a fancy name more compared to a product carrying a generic name.
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Hypotheses Based on the Attributes - Uniqueness Theory
According to the theory discussed above, a fancy color name leads consumers to perceive the
product carrying this fancy color name to be unique, and this unique image which conforms with
the consumers need to be different is what leads consumers to prefer products with fancy color
names. Therefore, according to the Attributes Theory, it is likely to assume that it makes no
difference whether the fancy name encompasses a positive or a negative association, as long as
the color name employs a product-scarcity and uniqueness appeal. As a consequence, the
following hypotheses are proposed:
H8: Unique fancy color names have a significantly more positive influence on product
preference than common generic color names have
H9: There is no significant difference between the influence of positively and negatively
associated unique fancy color names on product preference
The Uniqueness Spillover-Effect
Besides the fact that unique fancy color names might conform more to an individual’s desire to
be unique than common generic color names do, the unique image a product gets from a fancy
color name is also likely to influence consumer’s perceptions of other product attributes.
First of all, a unique product is a product with a special element to it and which you will probably
not find in every store. As a consequence, uniqueness influences the product’s availability. To
illustrate, consumers are likely to perceive a difference in availability of a pink lipstick, or a ‘rose
dust’ lipstick, as they probably expect to successfully purchase a pink lipstick at any cosmetic
department, however finding a ‘rose dust’ shade is more challenging. Second, uniqueness of a
product may influence the product’s image. Besides the fact that a fancy color name makes a
product more unique, the fancy color name might also lead consumers to perceive that the
product is more exclusive and special. Third, as the product is perceived to be unique and more
exclusive, this can subconsciously influence consumers’ evaluation of the product appearance.
This is confirmed by Skorinko et. al. (2006), who showed that consumers prefer a mocha towel
over a brown towel, even when the actual product is exactly the same. Fourth, as a unique
product might be perceived more exclusive, special and beautiful, overall this might lead
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consumers to believe that the quality of the product is higher. Last, as a unique product might be
perceived as more exclusive, beautiful, and having a better quality, the price consumers are
willing to pay is probably higher as well. In fact, this has also been confirmed by Skorinko et. al.
(2006), who showed that consumers were willing to pay a higher price for products carrying a
fancy, and thus original, color name compared to products carrying a generic color name.
Hypothesis Based on the Attributes - Uniqueness – Spillover Theory
According to the Spillover Theory suggested above, fancy color names give a product a unique
image, and this uniqueness might spill over to other product attributes and lead consumers to
believe the product is more exclusive, more beautiful, more expensive, and of a better quality. As
a consequence, the following hypothesis is proposed:
H10: A color name that results in the product carrying the name to be perceived as unique
significantly influences other product attributes and in turn product preference indirectly
Conceptual Model
The above-proposed hypotheses are visualized in figure 1, the conceptual model.
Figure 1, Conceptual model, how fancy color names influence product preference
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Summary As this research suggests different theories which could explain the preference of fancy color
names over generic color names, this theoretical framework ends with a summary of the
discussed theories and their effects.
According to the Attention Theory, due to their atypicality, fancy color names lead to an extra
thought process about the product and the color name in question. This results in the noticing of
additional (positive) attributions and/or solving the discrepancy between the color name and
consumers’ expectations, which in the end results in product preference. So for the Attention
Theory to hold, as it is the atypicality in the fancy color name which leads to product preference,
this research should show that both positively and negatively associated color names equally have
a significant stronger positive influence on product preference than generic color names have.
According to the Association Theory, it is the positive association of fancy color names that leads
to product preference. This can be explained by three theories, namely the Framing Theory, the
Categorization Theory, and the Self-image Congruence Theory. Besides investigating the general
effect of whether positively associated color names are indeed preferred over neutrally and
negatively associated color names and that neutral color names are preferred over negatively
associated color names, current research will also investigate whether the Categorization or the
Self-image Congruence Theory explains for the preference of fancy over generic color names
(testing whether or not the Framing Theory explains for the effect is beyond the scope of this
research). In order for the Categorization Theory to hold, current research should show that
positively associated color names indeed activate a positive category, resulting in product
preference. In order for the Self-image Congruence Theory to hold, current research should show
that when people can identify themselves with a product carrying a specific color name, they will
prefer the product carrying this color name.
According to the Attributes Theory, it is the unique aspect of fancy color names that lead
consumers to prefer the product carrying the fancy color name. More specifically, it is the unique
image which conforms with the consumers need to be different what leads consumers to prefer
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the product with the fancy color name. Consequently, in order for the Attributes Theory to hold,
current research should show that it makes no difference whether the fancy name encompasses a
positive or a negative association, as long as the color name employs a product-scarcity and
uniqueness appeal. Furthermore, it is suggested that this unique aspect of fancy color names
could spill over to other product attributes, and could also indirectly influence product preference.
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Research Design The current research is interested in how fancy color names influence product preference. In
order to investigate the explanation for this effect, the influence of negatively versus positively
associated color names, and the influence of the product attribute uniqueness are investigated in
more detail.
Terminology
As in previous research various definitions for fancy and generic names were used, first it will be
explained what in this research is meant by fancy and generic color names. Following Miller and
Kahn (2005), there are four categories of color names, namely common (typical, unspecific; e.g.
dark green, light yellow), common descriptive (typical, specific; e.g. pine green, lemon yellow),
unexpected descriptive (atypical, specific; e.g. Kermit green, rainslicker yellow), and ambiguous
color names (atypical, unspecific; e.g. friendly green, party yellow). In this research, common
and common descriptive color names are categorized as generic color names, whereas unexpected
descriptive and ambiguous names are categorized as fancy color names. As the following
research is a within- and between participants design, and it should be avoided that consumers see
through the purpose of the research and consequently answer in line of expectations, for generic
color names only common descriptive color names will be used, as they blend in more with the
fancy color names. Furthermore, the generic color names are naturally less unique compared to
the fancy color names. Consequently, for the purpose of this research, generic color names can be
seen as common color names, whereas fancy color names can be seen as more unique color
names.
Pretest
The purpose of the pretest was to determine which color names to use in the main study. More
specifically, the intention was to determine which color names people feel match the different
color name categories used in the main study; positively associated unique color names;
negatively associated unique color names; and neutrally associated common color names. For
example, it needed to be determined that an assumed to be positively associated unique color
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name is indeed labeled as positively associated and unique by the participants. Furthermore, with
the pretest the extent of incongruency with people’s expectations of the color and the actual color
was measured. The purpose of testing the incongruency for positively associated unique,
negatively associated unique, and neutrally associated common color names was to guarantee that
all color names are more or less equally incongruent, so that it could be excluded that the extent
of incongruency as suggested by the Incongruency Theory would influence product preference.
The questionnaire the participants received contained pictures of the three colors and its three
shades, and also a variety of color names and statements to go together with these pictures. An
example of such a statement is ‘I believe the color name ‘Zandstorm’ is common / unique. These
color name statements were given so that the participants could rate the extent to which they
considered each color name to be positively or negatively associated and unique or common on a
semantic differential scale (1 = common, positive.; 9 = unique, negative). Furthermore, in order
to measure the extent of incongruency, respondents were asked to rate the extent to which they
believed the color names match the displayed colors. See appendix 1.1 for the pretest
questionnaire.
Pre-test Results
A total of 26 people completed the questionnaire. Out of these 26 questionnaires, three
participants’ data were not used (due to not fully completing the questionnaire), so that the results
are based on 23 participants. Of these 23 respondents, 6 respondents were male and 17
respondents were female. The average age of the respondents was 40.
By conducting One-sample T-tests, 9 color names turned out to fit the color name categories as
intended. The color names that were selected to be significantly positively associated and unique
were ‘Belangrijk’ (brown; important), ‘Passie’ (blue; passion), and ‘Rust’ (green; serenity). The
color names selected to be significantly negatively associated and unique were ‘Moeras’ (brown;
bog), ‘Tyfoon’ (blue; typhoon), and ‘Adder’ (green; viper). Finally, the color names selected to
be neutrally associated and common were ‘Hout’ (brown; wood), ‘Marine’ (blue; navy), and
‘Appel’ (green; apple). For more extensive results of the conducted tests see Appendix 1.3.
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Limitation
Besides analyzing the data by conducting T-tests in order to see whether or not a color name is
significantly positively associated unique, negatively associated unique or neutrally associated
common, it is also constructive to see whether or not the color names significantly differ from
each other on these dimensions. The reason why this is of interest is that when respondents do not
experience a significant difference between for example a positively associated color name and a
negatively associated color name, it can be expected that there will not be a significant difference
between their ratings of product preference.
By conducting Oneway ANOVA tests en Post hoc tests, results showed that the selected unique
names indeed significantly differ from the selected common color names. However, on the other
hand not all positively associated color names differ significantly from the neutral color names.
More specifically, ‘Belangrijk’ (brown; important) does not differ significantly from ‘Hout’
(brown; wood) (p = .751), and ‘Rust’ (green; serenity) does not significantly differ from ‘Appel’
(green; apple) (p = .148). Even though all the other positively, negatively and neutrally associated
color names do differ significantly from each other, it should be kept in mind that the difference
between the brown and the green positively and neutrally associated color names is not
significant, which may result in the fact that the evaluations of the respondents will not differ
significantly between these color names. For more extensive results of the Oneway ANOVA tests
see appendices 1.4, 1.5 and 1.6.
Brown Blue Green
Positiveness Uniqueness Positiveness Uniqueness Positiveness Uniqueness
Positive Unique
Color Name
3.78a 5.96a 3.70a 6.09a 3.78a 6.83a
Negative Unique
Color Name
6.13b 6.30b 6.70b 7.04b 6.78b 6.30b
Neutral Common
Color Name
3.96a 3.96c 5.22c 3.91c 4.61a 4.09c
Tabel 1, Mean scores of the brown, blue, and green color names on positiveness and uniqueness
Superscripts only apply to columns. Means with the same superscript do not significantly differ, p <. 05
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Research Method
First, in preparation for the current research, a product that is available in multiple colors and
shades was selected. Besides the availability of multiple colors and shades, the product should
also be unisex – interesting to both sexes –, due to the random selection of the sample population.
Consequently, the product chosen for this research was a towel, which is in the same style
available in three colors and three shades. In order to avoid color preferences, the method for
color selection suggested by Skorinko et. al. (2006) was applied. Accordingly, the colors brown
and green were chosen because they are less standard, and the color blue was chosen because past
research has shown the preference for non-primary colors and a preference for the color blue in
particular. Three colors instead of one color were chosen in order to be able to determine the
effect on product preference for multiple colors.
Second, for each color towel three different but closely resembling shades were selected. For all
shades names were selected, where one shade was given a positively associated unique fancy
color name, one a negatively associated unique fancy color name, and one a neutrally associated
common generic color name (see appendix 1.2 for the selected color names).
Besides investigating color preference, purchase intentions and price willingness to pay, also the
spillover effect of uniqueness on other product attributes will be studied by using the different
colors and shades of towels. More specifically, whether or not a fancy name directly leads
consumers to perceive the product has a lower availability, better image, more beautiful
appearance, a higher quality and a higher price, or whether these product attributes are indirectly
affected through the fact that the fancy name triggers the association uniqueness will be
examined. This scenario of the spillover effect is visualized in figure 2, The Uniqueness Spillover
Effect.
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Figure 2, The Uniqueness Spillover Effect
Current research can be described as a within- and between-participants design, as each
respondent only views one color of towel (either brown, blue, or green) but views three shades
(light, medium, dark). The first towel was given a positively associated unique color name, the
second towel was given a negatively associated unique color name, and the third towel was given
a neutrally associated common generic color name. The names are counterbalanced for all three
shades of towels, so that 1/3 of the participants will see the light shaded towel with a positively
associated unique color name, 1/3 will see the medium shaded towel with a positively associated
unique color name, and 1/3 will see the dark shaded towel with a positively associated unique
color name.
Data Collection
A questionnaire was constructed, and a total of 92 participants completed the questionnaire. In
order to reach this number of respondents, people in the streets were randomly selected and asked
to participate in the research. By randomly assigning the participants, each participant has an
equal chance of being assigned to one particular condition of the experiment. As a result, all
groups are equal on practically every dimension. Of the completed 92 surveys, 2 surveys were
excluded from the research (due to not fully completing the survey) leaving a sample size of 90.
Of this sample, 40 respondents were male, and 50 respondents female. The average age of the
sample was 39.
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Procedure
When participants stated their willingness to participate in the research they received one of the
nine versions of questionnaires (for an example of a questionnaire see Appendix 2.1). In this
questionnaire the participants viewed the images of the three shades of one color towel, shade per
shade, and answered a series of questions about the products (also shade per shade). First,
participants were instructed to rate statements regarding the extent to which they liked each shade
on a 7-point Likert scale (1 = totally disagree, and 7 = totally agree). After rating the color shade,
participants were asked to rate statements regarding the extent they would consider to buy each
towel, supposing they were going to purchase a towel, on a 7-point Likert scale (1 = totally
disagree, and 7 = totally agree). Also, they indicated for every shade the price they were willing
to pay for the towel (open question). Furthermore, respondents answered questions regarding
their evaluation of certain aspects of the different shades of towels such as availability, image,
price and quality on a 7-point Likert scale anchored by 1 = totally disagree and 7 = totally agree.
Finally, in order to get more insights into how associations could impact product preference,
respondents were asked to rate to what extent they thought about other positive things and
products when looking at each shade of towel, and to what extent they could identify themselves
with each shade of towel on a 7-point Likert scale ( 1 = totally disagree, 7 = totally agree).
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Results As suggested by previous research, fancy names influence product preference in a positive
manner. The theoretical framework of this research has suggested some explanations on how
fancy color names influence product preference, and consequently this chapter discusses the tests
used to analyze the data and its resulting outcomes, in order to attempt to explain how fancy color
names influence product preference.
Associations, Uniqueness, and Product Preference
It is suggested by the Attention Theory, the Association Theory, and the Attributes Theory in the
theoretical framework, that there is a difference between the influence of positively associated
unique color names, negatively associated unique color names, and neutrally associated common
color names on product preference. In order to study this deviation, and thus contribute to the
explanation of how fancy color names influence product preference, first the overall effect of
positively associated unique, negatively associated unique, and neutrally associated common
color names on product preference will be studied. In other words, first, no difference will be
made between the effect of brown color names, blue color names, and green color names, but all
color names will be taken together.
Even though differences between the influence of positively associated unique, negatively
associated unique, and neutrally associated common color names on product preference were
hypothesized, current research revealed no significant difference between the different types of
color names on color preference. More specifically, current research performed three Oneway
ANOVA tests, which showed that there is no significant difference between the effect of
positively associated unique, negatively associated unique, and neutrally associated common
color names on color preference F(2,267) = .456, p = .634, purchase intentions F(2,267) = .075,
p = .928, and price willingness to pay F(2,267) = .230, p = .795. Consequently, as there is no
significant difference between positively associated unique, negatively associated unique, and
neutrally associated common color names product preference, this results in the rejection of the
hypotheses H1, H2, H4, H5, H8 and H9. Hypothesis H3 can be accepted on the basis of these
results, although it should be noted that even though there is no significant difference between the
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effect of positively and negatively associated color names on product preference, these positively
and negatively associated color names also do not significantly differ from neutrally associated
color names. For more extensive results, see Appendix 2.2.
Furthermore, current research investigated the effect of different types of color names on the
activation of positive categories and in turn on product preference. In order to measure the effect
of the activation of positive categories on product preference, two different questions were asked
in the survey. The first question would measure the extent the color name made the respondent
think of fun things, the second question would measure the extent the color name made the
respondent think of positive products. In order to study the effect of the activation of positive
categories on product preference, first it should be explored whether or not the two questions
from the survey statistically could be combined so that together they could account for the extent
the color name made the respondent activate positive categories. In order to test whether these
two variables could be combined, a Cronbach’s Alpha was computed, as the Cronbach’s Alpha
measures how well a set of items (or variables) measures a single unidimensional latent construct.
In the case of color naming, the reliability of thinking of fun things and of thinking about positive
products is very high (0.938), and also the inter-item correlation is high (0.884). As a
consequence, the two variables thinking of fun things and thinking of positive products can be
combined to create one scale; the extent the color name leads to the activation of positive
categories.
Next, to see whether there is a significant difference between the effect of positively, negatively
and neutrally associated color names on the activation of positive categories, a Oneway ANOVA
was performed. This test however illustrated that on average neither positively as well as
negatively as well as neutrally associated color names activate a positive category (respectively
M = 3.59, M = 3.33, and M = 3.51) and that they do not significantly differ F(2,267) = .521, p =
.594. As a result, this indicates that H6 can be rejected, since positively associated color names do
not activate positive categories which result in product preference more than negatively and
neutrally associated color names do. For more extensive results see Appendices 2.2 and 2.3.
Besides the effect of associations, uniqueness, and positive categories, also the effect of the
extent that people can identify themselves with a color name on product preference was studied.
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In order to test that people prefer products with which they can identify themselves, a Correlation
Analysis was performed. This Correlation Analysis indicated that the extent to which people can
identify themselves with the product and the evaluation of the product is indeed significantly
positively correlated. More specifically, the extent to which people can identify themselves with
the product and color preference is positively correlated, (Pearson Correlation .566, p = .000),
and the extent to which people can identify themselves with the product and their purchase
intentions are positively correlated (Pearson Correlation .678, p = .000), and finally the extent to
which people can identify themselves with the product and the price they are willing to pay is
positively correlated (Pearson Correlation .518, p = .000). As a result, H7 is accepted. Also see
Appendix 2.4 for these results.
Finally, the Attributes Theory mentioned in the theoretical framework also suggested an indirect
effect of uniqueness on product preference. More specifically, it was suggested that uniqueness
could also spill over to other product attributes (availability, image, appearance, quality, and
price) and so indirectly influence product preference. In order to test this spillover effect,
mediation of the variable uniqueness should be analyzed. However, in order to test for mediation,
4 requirements have to be fulfilled (Baron and Kenny, 1986). The first requirement is that the
independent variable should significantly influence the dependent variable. Second, the
independent variable also should have a significant influence on the mediator. Third, this
mediator should have a significant effect on the dependent variable when being controlled for the
effect of the independent variable. Fourth, the remaining effect of the independent variable
should decrease or disappear when the mediator is included in the analysis. Unfortunately, as
already shown in current research, the independent variable uniqueness does not have a
significant influence on the dependent variable product preference. As a result, it is unfeasible to
test the mediator effect, and hypothesis H10 can be rejected.
The Color Brown, Associations, Uniqueness, and Product Preference
Now that, in contradiction to previous research, the overall analysis (taking all colors together)
did not show a significant difference between the effect of positively associated unique,
negatively associated unique, and neutrally associated common color names on product
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preference, this part of the research will discuss the effect of the different types of color names of
one color on product preference. By doing so, the variance becomes smaller and consequently, it
is more likely to find a significant difference between the different types of color names.
First of all, three Repeated Measures ANOVA’s were performed, in order to find out whether or
not there is a significant difference between the effect of positively associated unique, negatively
associated unique, and neutrally associated common brown color names on product preference.
However, despite the smaller variance, again no significant difference was found between the
effect of the different types of brown color names on color preference F(2,87) = 1.544, p = .222,
purchase intentions F(2,87) = 1.321, p = .275, and price willingness to pay F(2,87) = 0.568, p =
.570. Consequently, again H1, H2, H4, H5, H8, and H9 can be rejected, and H3 can be accepted. For
more extensive results, see Appendix 2.5.
Second, the effect of the different kinds of brown color names on the activation of positive
categories was studied. To see whether or not there is a significant difference between the effect
of positively, negatively and neutrally associated brown color names on the activation of positive
categories, a Repeated Measures ANOVA test was performed. However, again this test illustrated
that on average neither positively, negatively, nor neutrally associated color names activate a
positive category (respectively M = 3.133, M = 2.850, and M = 2.967) and also that they do not
significantly differ F(2,87) = .389, p = .680. As a result, again H6 can be rejected. (Also see
Appendix 2.5)
Third, in order to test that people prefer products with which they can identify themselves, a
Correlation Analysis was performed. This Correlation Analysis indicated that the extent to which
people can identify themselves with a brown color name and the evaluation of the product is
indeed significantly positively correlated. More specifically, the extent to which people can
identify themselves with the color name and color preference is positively correlated, (Pearson
Correlation .561, p = .000), and the extent to which people can identify themselves with the color
name and their purchase intentions is positively correlated (Pearson Correlation .710, p = .000),
and finally the extent to which people can identify themselves with the color name and the price
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they are willing to pay is positively correlated (Pearson Correlation .347, p = .000). As a result,
again H7 can again be accepted. Also see Appendix 2.5 for these results.
Finally, the indirect effect of uniqueness on product preference as hypothesized by the Attributes
Theory could not be tested for mediation, as the independent variable uniqueness does not have a
significant influence on the dependent variable product preference, resulting in the rejection of
H10.
The Color Blue, Associations, Uniqueness, and Product Preference
In order to test whether there is a significant difference between the effect of positively associated
unique, negatively associated unique, and neutrally associated common blue color names on
product preference, three Repeated Measures ANOVA tests were performed. However despite
the suggested differences by the Attention Theory, the Association Theory, and the Attributes
Theory, again no significant differences were found between the effect of the different types of
blue color names on color preference F(2,87) = .501, p = .608, purchase intentions F(2,87) =
.095, p = .909, and price willingness to pay F(2,87) = .379 , p = .686. As a result, again H1, H2,
H4, H5, H8 and H9 can be rejected, and again H3 can be accepted. (Also see Appendix 2.6).
Furthermore, the effect of the different types of blue color names, –positively associated unique,
negatively associated unique, and neutrally associated common-, on the activation of positive
categories and in turn on product preference was studied. By conducting a Repeated Measures
ANOVA test, it became clear that also the different types of blue color names on average do not
activate positive categories (respectively M = 3.600, M = 3.267, and M = 3.317), and in addition,
the effect of the different types of blue color names also do not significantly differ from each
other F(2,87) = .480, p = .621. Consequently, it can be concluded that also just for the blue color
names, compared to the negatively associated unique and the neutrally associated common color
names, the positively associated unique color names do not lead to the activation of positive
categories and thus product preference more than the other color names do. As a result, again H6
can be rejected. (Also see Appendix 2.6).
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Additionally, in order to investigate whether the extent people can identify themselves with a
blue color name and its influence on product preference, a Correlation Analysis has been
performed. Again a significant positive relation has been found, which means that the more a
consumer can identify him or herself with a color name, the higher the color preference (Pearson
.405, p = .000), purchase intentions (Pearson .516, p = .000), and price willingness to pay
(Pearson .455, p = .000). Consequently, again H7 can be accepted. (Also see Appendix 2.6)
Finally, again the indirect effect of uniqueness on product preference as hypothesized by the
Attributes Theory could not be tested for mediation, because the independent variable uniqueness
does not have a significant influence on the dependent variable product preference, resulting in
the rejection of H10.
The Color Green, Associations, Uniqueness, and Product Preference
Finally, also for the green color names three Repeated Measures ANOVA’s were performed in
order to evaluate whether or not there is a significant difference between the effect of positively
associated unique, negatively associated unique, and neutrally associated common green color
names on product preference. Again the results showed that also for the green color names there
is no significant difference between the different types of color names on color preference
F(2,87) = .775, p = .465, purchase intentions F(2,87) = .145, p = .866, and price willingness to
pay F(2,87) = .286, p = .752. As a result, again H1, H2, H4, H5, H8, and H9 can be rejected, and H3
can again be accepted. For more extensive results see Appendix 2.7.
Besides the effect of associations and uniqueness on color names, also the effect of the different
kinds of green color names, -positively associated, negatively associated, and neutrally
associated-, on the activation of positive categories and in turn on product preference have been
studied. By conducting a Repeated Measures ANOVA test, it became clear that also for the
positively associated, negatively associated, and neutrally associated green color names no
positive categories were activated (respectively M = 4.050, M = 3.883, and M = 4.233) and that
there is no significant difference between the effect of the different types of color names on the
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activation of positive categories. F(2,87) = .677, p = .512. Therefore, again H6 can be rejected.
(Also see Appendix 2.7)
Furthermore, in order to investigate whether the extent people can identify themselves with a
green color name affects product preference, a Correlation Analysis has been performed. Also for
the green color names a significant positive relation has been found. In other words, the more a
consumer can identify him or herself with a color name, the higher the color preference (Pearson
.767, p = .000), purchase intentions (Pearson .856, p = .000), and price willingness to pay
(Pearson .698, p = .000), and therefore again H7 can be accepted. (Also see Appendix 2.7)
Finally, also for the green color names the indirect effect of uniqueness on product preference
could not be tested for mediation, since the independent variable uniqueness does not have a
significant influence on the dependent variable product preference. Again, this results in the
rejection of H10.
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Post Study to Rule Out the influence of Survey Phrasing
As in this research no significant difference has been found between the effect of positively
associated unique, negatively associated unique, and neutrally associated common color names
on product preference, the results of this study deviate from previous studies. One of the possible
explanations why the results of the current study deviate from previous studies might be the
phrasing used in the questionnaires. The questionnaire used for current research displays a picture
of a towel accompanied with the color name. Subsequently, in the questions below, the color
name is not mentioned again, however the phrasing ‘the depicted towel above’ is used. This is
done on purpose, as in real life when purchasing a towel the color name is also stated just on for
example the price tag. In other words, for current study it was deliberately chosen not to put more
focus on the color name than would happen in real life. However, the risk of the used phrasing is
that respondents base their answers more on the picture, and more or less overlook the color
name.
In order to rule out the phrasing used in the questionnaires as the explanation for the deviation of
current results with results from previous research, a post study will be done. For this post study,
the questionnaires used in the main study will be rephrased, so that the wording ‘the depicted
towel above’ is replaced by the color name of the towel. For an example of the questionnaire, see
Appendix 3.1.
Post Study Results Associations, Uniqueness, and Product Preference
Just as in the main study, again all 9 versions of the survey, so all three colors brown, blue and
green, were distributed. A total of 28 respondents completed the questionnaires, of which 27
proved to be useful (1 survey was not useful due to not fully completing the questionnaire). Of
these 27 respondents, 10 were male and 17 were female. The average age of the sample is 46.
The purpose of this post study was to evaluate whether or not it would make a difference when
the color name of the towel would be repeated more often. In other words, whether or not an
increase in exposure of the color name would have an influence on product preference.
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First of all, just as in the main study, the overall effects of positively associated unique,
negatively associated unique, and neutrally associated common color names on product
preference will be discussed. In other words, no distinction will be made between the effect of
brown, blue, and green color names on product preference.
In order to study the effect of the different types of color names on product preference, three
Oneway ANOVA tests were performed, and the results showed again that there is no significant
difference between the effect of positively associated unique, negatively associated unique, and
neutrally associated common color names on purchase intentions F(2,78) = 2.181, p = .120, and
price willingness to pay F(2,78) = 1.080, p = .345. However, when employing an alpha level of
.10, the results also showed that there is in fact a marginally significant difference between the
effect of the different types of color names on color preference F(2,78) = 2.631, p = .078,. More
specifically, by conducting a Post hoc test it became clear that the color of the product with the
positively associated color name (M = 4.70) is preferred more than the color of the product with
the negatively associated color name (M = 3.48), p = .027. Consequently, this could imply that -
when investigated on a larger scale and with the right extent of color name exposure- associations
influence color preference and thus in turn product preference.
As a result, again H1, H2, H4, H5, and H8 can be rejected and now H3 and H9 can be partially
rejected. For more extensive results about the ANOVA tests, see Appendix 3.2.
Second, the effect of the different types of color names, -positively associated unique, negatively
associated unique, and neutrally associated common-, on the activation of positive categories and
in turn on product preference was evaluated. In order to do so, first just as in the main study, a
Cronbach’s Alpha was calculated in order to asses whether or not the two questions from the
survey about the activation of positive categories could be combined. As the Cronbach’s Alpha
turned out to be .902, the two variables could indeed be combined, and by conducting a Oneway
ANOVA test, it became clear that in contrary to the main study, a significant difference between
the different types of color names on the activation of positive categories exists, F(2,78) = 3.501,
p = .035. Next, in order to reveal which types of color names differed from each other, a Posthoc
test was performed. From this test is became clear that products with positively associated color
names (M = 4.481) are more likely to lead to the activation of positive categories than products
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with negatively associated color names (M = 3.185) are, and products with neutrally associated
color names (M = 3.907) did not differ from products with positively nor negatively associated
color names on the activation of positive categories. As a result, it can be concluded that
positively associated color names indeed slightly activate positive categories, however, not
significantly more than neutrally associated common color names do. Also, from the ANOVA
test in the previous paragraph it can be derived that even though the positively associated color
names slightly activate a positive category, this does not lead to a significantly different effect on
product preference compared to negatively and neutrally associated color names. As a result,
again H6 cannot be accepted. (See Appendices 3.2 and 3.3 for more extensive results).
Third, in order to investigate whether or not the extent people can identify themselves with a
color name and its influence on product preference, a Correlation Analysis has been performed.
From this analysis, it became clear that just as in the main study, a significant positive
relationship exists. In other words, the better people can identify themselves with a certain color
name, the higher the color preference (Pearson Correlation .762, p = .000), purchase intentions
(Pearson Correlation .783, p = .000) and price willingness to pay (Pearson Correlation .513, p =
.000). As a result, also H7 can again be accepted. For more extensive results of the Correlation
Analysis, see Appendix 3.4.
Finally, as in the main study, the indirect effect of uniqueness on product preference as
hypothesized by the Attributes Theory could not be tested for mediation, as the independent
variable uniqueness does not have a significant influence on the dependent variable product
preference.
The Color Brown, Associations, Uniqueness, and Product Preference
For this post study, besides the overall effect, -all colors taken together-, also the effect of the
different types of color names per color were investigated in order to reduce the variance and
increase the chance of finding significant effects of the different types of color names on product
preference.
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First, three Repeated Measures ANOVA’s were performed to see whether or not there is a
significant difference between the effect of positively associated unique, negatively associated
unique, and neutrally associated common brown color names on product preference. However, as
in the main study, again no significant difference was found between the effect of the different
types of brown color names on color preference F(2,24) = .370, p = .696, and purchase intentions
F(2,24) = .288, p = .753. On the other hand, when employing an alpha level of .10, current results
did show a marginally significant difference between the effect of the different types of color
names on price willingness to pay F(2,24) = 2.890, p = 0.085. More specifically, by conducting a
Post hoc test it became clear that respondents were willing to pay significantly more money for
the product with the neutrally associated common color name (M = 5.77) than they were for
exactly the same product with the negatively associated unique color name (M = 4.77). No
significant difference was found between the effect of positively associated unique color names
(M = 5.44) and negatively or neutrally associated color names on price willingness to pay.
As a result, again H1, H2, H4, and H8 can be rejected, while H5 can be partially accepted and H3, ,
and H9 can be fully accepted. (Also see Appendix 3.5).
Second, the effect of the different types of brown color names on the activation of positive
categories and consequently on product preference was studied by conducting a Repeated
Measures ANOVA. This test showed that just as in the main study, there is no significant
difference between positively associated unique brown color names (M = 5.17), negatively
associated unique brown color names (M = 3.78) and neutrally associated brown common color
names (M = 4.56) on the activation of positive categories F(2,24), p = .337, resulting again in the
rejection of H6.
Third, a Correlation Analysis has been performed in order to test whether or not there is a relation
between the extent people can identify themselves with a brown color name and product
preference. Again, just as in the main study, significant positive results have been found,
indicating that the more people can identify themselves with a brown color name, the higher the
color preference (Pearson Correlation .875, p = .000), and the higher the purchase intentions
(Pearson Correlation .891, p = .000). However, in contradiction with the main study, even though
also a positive relation between the extent people can identify themselves with a color name and
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price willingness to pay was found, this positive relation was not significant (Pearson Correlation
.361, p = .064). As a result, H7 can only be partially accepted. (Also see Appendix 3.5)
Finally, also for the brown color names, the indirect effect of uniqueness on product preference
could not be tested for mediation, as the independent variable uniqueness does not have a
significant influence on the dependent variable product preference.
The Color Blue, Associations, Uniqueness, and Product Preference
Just as for the brown color names, also the effect of the different types of blue color names on
product preference has been studied in this post study. More specifically, three Repeated
Measures ANOVA’s have been performed to find out whether or not there is a significant
difference between the effect of positively associated unique, negatively associated unique, and
neutrally associated common blue color names on product preference. Just as in the main study,
this post study shows that there is no significant difference between the effect of the different
types of blue color names on color preference F(2,24) = 1.396, p = .276, and purchase intentions
F(2,24) = 2.141, p = .150. However, this post study did find a marginally significant difference
between the effect of the different types of color names on price willingness to pay F(2,24) =
3.173, p = .069. More specifically, a Post hoc test showed that respondents were willing to pay
significantly more for products with a positively associated color name (M = 6.27) than they were
for exactly the same product with a negatively associated color name (M = 4.11), p = .085. As a
result, H1, H2, H4, H5, H8, and H9 can be rejected and H3 can be partially rejected. (Also see
Appendix 3.6).
Furthermore, differences between the effect of the different types of blue color names on the
activation of positive categories and in turn product preference have been studied. By conducting
a Repeated Measures ANOVA, it however became clear that just as in the main study there is no
significant difference between positively associated unique blue color names (M = 3.83),
negatively associated unique blue color names (M = 3.33), and the neutrally associated common
blue color names (M = 3.94) on the activation of positive categories F(2,24) = .371, p = .696,
leading again to the rejection of H6. For more extensive results, see Appendix 3.6.
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Also, the relationship between the extent people can identify themselves with a blue color name
and product preference has been studied. By conducting a Correlation Analysis it became clear
that, just as in the main study, the more people can identify themselves with a blue color name,
the higher the color preference (Pearson Correlation .759, p = .000), the higher the purchase
intentions (Pearson Correlation .728, p = .000), and the higher the price willingness to pay
(Pearson Correlation .612, p = .001). As a result, again H7 can be accepted. (Appendix 3.6)
Finally to conclude the analysis for the blue color names, again the indirect effect of uniqueness
on product preference as hypothesized by the Attributes Theory could not be tested for mediation,
as the independent variable uniqueness does not have a significant influence on the dependent
variable product preference.
The Color Green, Associations, Uniqueness, and Product Preference
Last, the effect of the different types of green color names, -positively associated unique,
negatively associated unique, and neutrally associated common-, on product preference was
studied. First of all, the influence of associations and uniqueness of green color names on product
preference was examined, by conducting three Repeated Measures ANOVA’s. Just as in the main
study, no significant difference was measured between the different types of green color names
on color preference, F(2,24) = 2.266, p = .136, purchase intentions F(2,24) = 1.773, p = .202, and
price willingness to pay F(2,24) = .582, p = .570, leading again to the rejection of H1, H2, H4, H5,
H8, and H9, and the acceptance of H3 (Also see Appendix 3.7). However, it should be noted that
even though the differences between the different types of green color names are not significant,
these differences are fairly larger than the differences measured in the main study.
Besides the influence of associations and uniqueness, also the effect of the activation of positive
categories on product preference was studied. More specifically, by conducting a Repeated
Measures ANOVA, it was studied whether or not positively associated green color names indeed
lead to the activation of positive categories and in turn product preference. Where in the main
study no significant difference between the different types of (green) color names was observed,
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there was a significant difference found during the post study, F(2,24) = 5.305, p = .017. More
specifically, by conducting a Post hoc test it became evident that products with positively
associated color names (M = 4.44) and products with neutrally associated common color names
(M = 4.17) are more likely to activate positive categories than products with negatively associated
color names (M = 2.44) (Appendix 3.7). However, as positively associated color names only
slightly activate positive categories, and this research also already has shown that positively
associated color names do not lead to a more positive product evaluation than negatively and
neutrally associated color names do, still H6 cannot be accepted.
Furthermore, the relation between the extent people can identify themselves with a green color
name and product preference was evaluated. By conducting a Correlation Analysis, it became
clear that, just as in the main study, there was a significant positive relation. More specifically,
the more people could identify themselves with a green color name, the higher the color
preference (Pearson Correlation .734, p = .000), the higher the purchase intentions (Pearson
Correlation .676, p = .000), and the higher the price willingness to pay (Pearson Correlation .607,
p = .001), resulting in the acceptance of H7. For more extensive results of this Correlation
Analysis, see Appendix 3.7.
Finally, also for the green color names, the indirect effect of uniqueness on product preference as
hypothesized by the Attributes Theory could not be tested for mediation, as the independent
variable uniqueness does not have a significant influence on the dependent variable product
preference.
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Conclusions
Conclusions & General Discussion
As previous research has revealed that fancy color names influence consumers’ preferences in a
positive way, the current research explored how fancy color names influence product preference.
The theoretical framework of this study suggested three theories in order to explain the fancy
color naming phenomenon. These three suggested theories were the Attention Theory, the
Association Theory, and the Attributes Theory. Briefly summarized, these three theories suggest
the following explanations for fancy color naming effect:
According to the Attention Theory, due to their atypicality, fancy color names lead to an extra
thought process about the product and the color name in question. This results in the noticing of
additional (positive) attributions and/or solving the discrepancy between the color name and
consumers expectations, which in the end results in product preference (Miller and Kahn 2005).
The Association Theory suggests that it is the positive association of fancy color names that leads
to product preference (Skorinko et. al. 2006), where the current research has made a discrepancy
between the Categorization Theory and the Self-image Congruence Theory. Finally, the
Attributes Theory suggests it is the unique aspect of fancy color names that lead consumers to
prefer the product carrying the fancy color name. Furthermore, it is suggested that this unique
aspect of fancy color names could spill over to other product attributes, and could also indirectly
influence product preference.
The main study of this research demonstrated that, as well on the overall level as on the color
level, participants’ product preference was not influenced by the different types of color names, -
positively associated unique, negatively associated unique, and neutrally associated common-.
More specifically, participants did not prefer the color of the positively associated unique named
product, the positively associated unique color named product was not more likely to be
purchased, and participants were not willing to pay more for the product with the positively
associated unique color name than they were for the same product with a neutrally or negatively
associated common color name. Consequently, as the main study of this research does not
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provide a strong evidence that fancy color names do influence product preference, it still remains
unclear which theory best accounts for the fancy color naming effect found in previous research.
The post study of the current research does however provide more insights into the fancy color
naming phenomenon. The purpose of this post study was to examine whether the nonexistence of
the fancy color naming effect in the main study could be explained by the phrasing used in the
survey of the main study. Therefore, the survey for the post study was adjusted so that the
exposure of the color name increased, and distributed to a small sample of 27 persons.
The results of this post study showed marginally significant effects on product preference. First
of all, participants preferred colors with a positively associated unique color name over colors
with a negatively associated unique color name. Second, in one case participants were willing to
pay more for the towel with a positively associated unique color name than they were for exactly
the same towel with a negatively associated unique color name, and in the other case participants
were willing to pay more for the towel with a neutrally associated common color name than they
were for exactly the same towel with a negatively associated unique color name.
From these results it can be excluded that the variable uniqueness influences product preference
in a positive way, as the effect of positively associated unique and negatively associated unique
color names differs significantly in two out of the three cases. As a result, the Attributes Theory
which suggested that the attribute uniqueness would appeal to the customers’ need for uniqueness
and in turn would influence product preference in a positive way can be rejected. An explanation
for this finding might be that the product used for this study was a towel. A towel can be
perceived to be a low-involvement product, which in turn does not have a great impact on a
consumer’s lifestyle. As a result, even though the towel might have had a unique color name, the
product itself is not related with the consumers need for uniqueness, and so the unique color
name does not lead to product preference.
It can on the other hand be assumed that associations do play a role in product preference. In all
three cases there is no significant difference between the effect of positively and neutrally
associated color names on product preference, but either the positively or the neutrally associated
color names always differ significantly from negatively associated color names. This is partially
consistent with the Association Theory -based on the suggested explanation of Skorinko et. al.
(2006)- which suggests that products with positively associated color names are preferred over
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the same products with neutrally associated color names, and that products with neutrally
associated color names are preferred over the same products with a negatively associated color
name. The reason why it is merely partially consistent with the Associations Theory is that there
is only a difference between the effect of either positively or neutrally associated color names and
negatively associated color names, and no mutual difference between positively and neutrally
associated color names as suggested by the Association Theory. An explanation for this finding
could be the limitation already mentioned in the pretest section of this study. This limitation
revealed that for two out of the three colors, the selected positively associated and neutrally
associated color names did not significantly differ from each other, which could result in the fact
that participants would not rate product preference for these color names differently.
Furthermore, as mentioned before, the Association Theory was founded by two underlying
theories: the Self-Image Congruence Theory, and the Categorization Theory.
First of all, both the main study and the post study found a significant positive relation between
the extent participants could identify themselves with the color name and product preference,
suggesting an acceptance of the Self-Image Congruence Theory. Moreover, besides suggesting a
positive relation between the extent participants can identify themselves with a color name and
product preference, this theory also discussed that consumers seem to be predominantly
motivated to avoid consuming negative images, rather than reflecting attempts to achieve a
positive image (Banister and Hogg 2004). This in turn could also explain the finding of this post
study that negatively associated color names, compared to positively and neutrally associated
color names, influence product preference significantly less positive.
Second, the results of the post study demonstrated that both positively associated as well as
neutrally associated color names activate positive categories significantly more than negatively
associated color names do. However, results also showed that this does not necessary lead to
product preference. Consequently, the results are partially in line with the Categorization Theory,
which suggests that positively associated color names activate positive categories and in turn
positively influence impression formation of a product (Fiske and Neuberg 1990). An explanation
for this finding could be the setup of current research, which resulted in a considerable amount of
thought before participants rated product preference, even though the product in question was a
low-involvement product. So instead of letting emotions such as positive categories influence
product preference as would happen with the evaluation of low-involvement products that require
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a minimum of thought and effort, participants rated the product as a high-involvement product by
spending a considerable time and effort in evaluating. Consequently, as the amount of time and
effort spent by respondents might influence product evaluations, it might be interesting for future
research to asses the influence of the extent of involvement on the effect of fancy color names.
Managerial Implications
The color naming practice employed by companies that are dealing in colors is certainly useful.
The current study provides marketers an indication of how the color naming practice influences
consumers’ product preference, and thus a guidance of how to use the color naming practice to
their advantage.
First of all, the results suggest that it should be certain that the color name is noticeable, since the
effect of the different types of color names on product preference only became visible when the
exposure of the color names was increased. Second, unique color names are most likely not
effective in combination with low-involvement products, as low-involvement products do not
have a great impact on a consumers lifestyle. On the other hand it might be that unique color
names do have a positive influence on the evaluation on high-involvement products, since unique
color names might appeal to a consumer’s need for uniqueness and high-involvement products do
have a great impact on a consumer’s lifestyle. Third, results suggest that associations to some
extent influence product preference. More specifically, positively and neutrally associated color
names have a positive influence on product preference. It is recommended to avoid negatively
associated color names, since consumers tend to avoid consuming negative images and
negatively associated color names have a significantly less positive influence on product
preference than positively or neutrally associated color names have. Finally, results suggest that
positively associated and neutrally associated color names activate positive categories.
Consequently, as low-involvement products are purchased intuitively and with a low amount of
thought, positively and neutrally associated color names might lead to the activation of positive
categories and in turn the purchase of low-involvement products.
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Limitations and Future Research
The first limitation of this research has been mentioned before, and concerns the selection of
color names. Whereas in this research some positively associated and neutrally associated color
names do not significantly differ from each other, in future research it should made sure that the
selected color names differ on both the association as on the uniqueness dimension.
Furthermore, the color naming effect investigated in this research is only a small part of a
consumers product evaluation process. Due to the relative small scope of this research, it is
possible that the effect of color names on product preference was not fully observed.
Furthermore, as there were three different theories suggested in order to explain for the effect, for
future research it is recommended to split up current research in multiple studies, in order to get a
more profound insight into the subject.
Also, future research might assess the influence of the different types of color names on high-
involvement products. For example, it has already been suggested that unique color names might
have a significant effect on high-involvement products, as both can contribute to a consumers’
need for uniqueness.
Finally, future research might asses the effect of exposure of color names as suggested in our post
study with a larger sample size.
Taken as a whole, the results from this study suggest a guidance as to how to use the fancy color
naming effect in order to influence product preference. When the visibility of the color name,
associations, and product involvement are taken into account, the color naming practice might be
a value adding phenomenon, resulting in positive product evaluations and a shopping
environment with a great variety of fancy color names.
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Appendix 1, Pretest 1.1, Example Survey Pretest Door middel van deze enquête probeer ik, master marketing student aan de Rijksuniversiteit Groningen, meer inzicht te krijgen in de evaluaties van kleurnamen. Denkt u er aan dat er bij het invullen van deze enquête geen juiste of onjuiste antwoorden mogelijk zijn. Ik dank u voor uw medewerking. Geslacht: Man / Vrouw Leeftijd: ………………
Hieronder vindt u verschillende namen voor de kleuren bruin, blauw en groen. Ga er bij iedere kleurnaam vanuit dat dit een kleurnaam is die gepaard gaat met een product dat verkrijgbaar is in meerdere tinten, denk hierbij bijvoorbeeld aan muurverf of een handdoek. Geef voor iedere kleurnaam aan of u deze alledaags of uniek, positief of negatief, en passend vindt. BRUIN Ik vind de kleurnaam “Profijt” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Duister” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Aarde” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Waarde” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Splinter” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C
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Ik vind de kleurnaam “Hout” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Subtiel” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Zandstorm” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Meel” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Chocoladevla” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Droevig” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Eik” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Belangrijk” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C
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Ik vind de kleurnaam “Moeras” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C BLAUW Ik vind de kleurnaam “Passie” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Storm” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Bosbes” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Royaal” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Tyfoon” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Denim” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C
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Ik vind de kleurnaam “Hemel” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Regen” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Baby blauw” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Pino” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Zeezicht” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Marine” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Vrede” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Bont en blauw” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C
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GROEN Ik vind de kleurnaam “Natuur” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Adder” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Limoen” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Rust” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Zeewier” alledaags 1 2 3 4 5 6 7 8 9 uniek
positief 1 2 3 4 5 6 7 8 9 negatief
passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A
passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Mos” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Lente” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C
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Ik vind de kleurnaam “Gif” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Kermit” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Harmonie” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Gras” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Rups” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Kerst” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C Ik vind de kleurnaam “Appel” alledaags 1 2 3 4 5 6 7 8 9 uniek positief 1 2 3 4 5 6 7 8 9 negatief passen bij tint A 1 2 3 4 5 6 7 8 9 niet passen bij tint A passen bij tint B 1 2 3 4 5 6 7 8 9 niet passen bij tint B passen bij tint C 1 2 3 4 5 6 7 8 9 niet passen bij tint C
- Dit is het einde van de vragenlijst, hartelijk bedankt voor uw medewerking -
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1.2, Selected Names from Pretest
COLOR NAME CATEGORY COLOR SELECTED COLOR NAME
Positive unique Brown Belangrijk
Blue Passie
Green Rust
Negative unique Brown Moeras
Blue Tyfoon
Green Adder
Neutral common Brown Hout
Blue Marine
Green Appel
* Color names are derived from HISTOR color swatches collected from the local hardware store
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1.3, Pretest, One-Sample T Tests
One-Sample T Tests, significant at confidence interval 90%, n=23, test value=5
Mean pos (1)
vs. neg (7) Sig.
(two-tailed)
Mean Common (1)
vs. Unique (7) Sig.
(two-tailed) Brown Belangrijk 3.78 0.002 5.96 0.080 Moeras 6.13 0.006 6.30 0.001 Hout 4.57 0.195 3.96 0.026 Blue Passie 3.70 0.018 6.09 0.045 Tyfoon 6.70 0.003 7.04 0.000 Marine 5.22 0.487 3.91 0.025 Green Rust 3.78 0.011 6.83 0.000 Adder 6.78 0.000 6.30 0.011 Appel 4.61 0.296 4.09 0.058
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One-Sample T Tests, significant at confidence interval 90%, n=23, test value=5
Mean Fit (1=fit,
9=no fit) Sig.
(two-tailed) Brown Belangrijk Fits shade A 5.61 0.196 Fits shade B 5.83 0.122 Fits shade C 5.26 0.672 Moeras Fits shade A 5.18 0.765 Fits shade B 5.83 0.148 Fits shade C 5.78 0.165 Hout Fits shade A 4.35 0.122 Fits shade B 4.43 0.198 Fits shade C 5.04 0.936 Blue Passie Fits shade A 5.74 0.138 Fits shade B 5.65 0.214 Fits shade C 5.04 0.936 Tyfoon Fits shade A 4.09 0.131 Fits shade B 5.04 0.936 Fits shade C 5.78 0.156 Marine Fits shade A 4.57 0.403 Fits shade B 4.43 0.297 Fits shade C 5.26 0.613 Green Rust Fits shade A 4.78 0.710 Fits shade B 5.17 0.750 Fits shade C 4.30 0.207 Adder Fits shade A 5.30 0.620 Fits shade B 5.35 0.528 Fits shade C 5.61 0.323 Appel Fits shade A 5.70 0.141 Fits shade B 4.52 0.307 Fits shade C 4.43 0.319
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1.4, Pretest, Descriptives
N Mean SD Associations Brown Positive 23 3.78 1.650
Negative 23 6.13 1.766
Neutral 23 3.96 2.099
Blue Positive 23 3.70 2.439
Negative 23 6.70 2.476
Neutral 23 5.22 1.476
Green Positive 23 3.78 2.110
Negative 23 6.78 1.858
Neutral 23 4.61 1.751
Uniqueness Brown Positive unique 23 5.96 2.495
Negative unique 23 6.30 1.550
Common 23 3.96 2.099
Blue Positive unique 23 6.09 2.448
Negative unique 23 7.04 1.846
Common 23 3.91 2.172
Green Positive unique 23 6.83 1.723
Negative unique 23 6.30 2.265
Common 23 4.09 2.193
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1.5, Pretest, Oneway ANOVA
Sum of
Squares df Mean
Square F Sig. Associations Brown Between Groups 78.725 2 39.362 11.522 0.000
Within Groups 225.478 66 3.416
Total 304.203 68
Blue Between Groups 103.507 2 51.754 10.890 0.000
Within Groups 313.652 66 4.752
Total 417.159 68
Green Between Groups 110.464 2 55.232 15.107 0.000
Within Groups 241.304 66 3.656
Total 351.768 68
Uniqueness Brown Between Groups 73.855 2 36.928 8.498 0.001
Within Groups 286.783 66 4.345
Total 360.638 68
Blue Between Groups 118.377 2 59.188 12.577 0.000
Within Groups 310.609 66 4.706
Total 428.986 68
Green Between Groups 97.304 2 48.652 11.306 0.000
Within Groups 284.000 66 4.303
Total 381.304 68
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1.6, Pretest, Posthoc Tests
95%
Confidence
Mean
Difference Std.
Error Sig. Upper Bound
Lower Bound
Associations Brown Positive Negative -2.348(*) 0.545 0.000 -3.44 -1.26
Neutral -0.174 0.545 0.751 -1.26 0.91
Negative Positive 2.348(*) 0.545 0.000 1.26 3.44
Neutral 2.174(*) 0.545 0.000 1.09 3.26
Neutral Positive 0.174 0.545 0.751 -0.91 1.26
Negative -2.174(*) 0.545 0.000 -3.26 -1.09
Blue Positive Negative -3.000(*) 0.643 0.000 -4.28 -1.72
Neutral -1.522(*) 0.643 0.021 -2.81 -0.24
Negative Positive 3.000(*) 0.643 0.000 1.72 4.28
Neutral 1.478(*) 0.643 0.025 0.19 2.76
Neutral Positive 1.522(*) 0.643 0.021 0.24 2.81
Negative -1.478(*) 0.643 0.025 -2.76 -0.19
Green Positive Negative -3.000(*) 0.564 0.000 -4.13 -1.87
Neutral -0.826 0.564 0.148 -1.95 0.30
Negative Positive 3.000(*) 0.564 0.000 1.87 4.13
Neutral 2.174(*) 0.564 0.000 1.05 3.30
Neutral Positive 0.826 0.564 0.148 -0.30 1.95
Negative -2.174(*) 0.564 0.000 -3.30 -1.05
Brown Positive unique Negative unique -0.348 0.615 0.573 -1.58 0.88
Common 2.000(*) 0.615 0.002 0.77 3.23
Negative unique Positive unique 0.348 0.615 0.573 -0.88 1.58
Common 2.348(*) 0.615 0.000 1.12 3.58
Common Positive unique -2.000(*) 0.615 0.002 -3.23 -0.77
Negative unique -2.348(*) 0.615 0.000 -3.58 -1.12
Blue Positive unique Negative unique -0.957 0.640 0.140 -2.23 0.32
Common 2.174(*) 0.640 0.001 0.90 3.45
Negative unique Positive unique 0.957 0.640 0.140 -0.32 2.23
Common 3.130(*) 0.640 0.000 1.85 4.41
Common Positive unique -2.174(*) 0.640 0.001 -3.45 -0.90
Negative unique -3.130(*) 0.640 0.000 -4.41 -1.85
Green Positive unique Negative unique 0.522 0.612 0.397 -0.70 1.74
Common 2.739(*) 0.612 0.000 1.52 3.96
Negative unique Positive unique -0.522 0.612 0.397 -1.74 0.70
Common 2.217(*) 0.612 0.001 1.00 3.44
Common Positive unique -2.739(*) 0.612 0.000 -3.96 -1.52
Negative unique -2.217(*) 0.612 0.001 -3.44 -1.00
*. The mean difference is significant at the .05 level.
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 63 1/7/2009
Appendix 2, Main Study 2.1, Main Study, Survey
VERSIE 1.1 Door middel van deze enquête probeer ik, master marketing student aan de Rijksuniversiteit Groningen, meer inzicht te krijgen in kleur- en productvoorkeur. Denkt u er aan dat er bij het invullen van deze enquête geen juiste of onjuiste antwoorden mogelijk zijn. Ik dank u voor uw medewerking. GESLACHT: MAN / VROUW LEEFTIJD: ………………... Gepaard met onderstaande vragen ziet u enkele afbeeldingen van handdoeken. Kijk hier alstublieft goed naar, en beantwoord vervolgens de vragen.
Kleur: Belangrijk Omcirkel voor iedere stelling het voor u juiste antwoord (1 = zeer mee oneens, 7 = zeer mee eens).
1. Ik vind de kleur van de bovenstaande handdoek mooi 1 2 3 4 5 6 7
2. Ik zou de bovenstaande handdoek graag aanschaffen 1 2 3 4 5 6 7
3. De bovenstaande handdoek doet me denken aan andere leuke dingen 1 2 3 4 5 6 7
4. De bovenstaande handdoek doet me denken aan positieve producten 1 2 3 4 5 6 7
5. Ik kan me identificeren met de bovenstaande handdoek 1 2 3 4 5 6 7
Stel u zou de ‘Belangrijk’ handdoek aanschaffen. Welke prijs zou u bereid zijn te betalen?
6. De prijs die ik bereid bent te betalen voor de bovenstaande handdoek is € ……………. Ten slotte vind u hieronder nog enkele stellingen met betrekking de ‘Belangrijk’ handdoek. Omcirkel voor iedere stelling het voor u juiste antwoord (1 = zeer mee oneens, 7 = zeer mee eens) Ik geloof dat de bovenstaande handdoek….
7. een unieke handdoek is 1 2 3 4 5 6 7 8. in veel winkels verkrijgbaar is 1 2 3 4 5 6 7 9. een exclusief imago heeft 1 2 3 4 5 6 7 10. mooi is 1 2 3 4 5 6 7 11. van hoge kwaliteit is 1 2 3 4 5 6 7 12. prijzig is 1 2 3 4 5 6 7 13. een zachte handdoek is 1 2 3 4 5 6 7
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 64 1/7/2009
Kleur: Moeras Omcirkel voor iedere stelling het voor u juiste antwoord (1 = zeer mee oneens, 7 = zeer mee eens).
14. Ik vind de kleur van de bovenstaande handdoek mooi 1 2 3 4 5 6 7
15. Ik zou de bovenstaande handdoek graag aanschaffen 1 2 3 4 5 6 7
16. De bovenstaande handdoek doet me denken aan andere leuke dingen 1 2 3 4 5 6 7
17. De bovenstaande handdoek doet me denken aan positieve producten 1 2 3 4 5 6 7
18. Ik kan me identificeren met de bovenstaande handdoek 1 2 3 4 5 6 7
Stel u zou de ‘Moeras’ handdoek aanschaffen. Welke prijs zou u bereid zijn te betalen?
19. De prijs die ik bereid bent te betalen voor de bovenstaande handdoek is € ……………. Ten slotte vind u hieronder nog enkele stellingen met betrekking tot de ‘Moeras’ handdoek. Omcirkel voor iedere stelling het voor u juiste antwoord (1 = zeer mee oneens, 7 = zeer mee eens) Ik geloof dat de bovenstaande handdoek….
20. een unieke handdoek is 1 2 3 4 5 6 7 21. in veel winkels verkrijgbaar is 1 2 3 4 5 6 7 22. een exclusief imago heeft 1 2 3 4 5 6 7 23. mooi is 1 2 3 4 5 6 7 24. van hoge kwaliteit is 1 2 3 4 5 6 7 25. prijzig is 1 2 3 4 5 6 7 26. een zachte handdoek is 1 2 3 4 5 6 7
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
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Kleur: Hout Omcirkel voor iedere stelling het voor u juiste antwoord (1 = zeer mee oneens, 7 = zeer mee eens).
27. Ik vind de kleur van de bovenstaande handdoek mooi 1 2 3 4 5 6 7
28. Ik zou de bovenstaande handdoek graag aanschaffen 1 2 3 4 5 6 7
29. De bovenstaande handdoek doet me denken aan andere leuke dingen 1 2 3 4 5 6 7
30. De bovenstaande handdoek doet me denken aan positieve producten 1 2 3 4 5 6 7
31. Ik kan me identificeren met de bovenstaande handdoek 1 2 3 4 5 6 7
Stel u zou de ‘Hout’ handdoek aanschaffen. Welke prijs zou u bereid zijn te betalen?
32. De prijs die ik bereid bent te betalen voor de bovenstaande handdoek is € ……………. Ten slotte vind u hieronder nog enkele stellingen met betrekking tot de ‘Hout’ handdoek. Omcirkel voor iedere stelling het voor u juiste antwoord (1 = zeer mee oneens, 7 = zeer mee eens) Ik geloof dat de bovenstaande handdoek….
33. een unieke handdoek is 1 2 3 4 5 6 7 34. in veel winkels verkrijgbaar is 1 2 3 4 5 6 7 35. een exclusief imago heeft 1 2 3 4 5 6 7 36. mooi is 1 2 3 4 5 6 7 37. van hoge kwaliteit is 1 2 3 4 5 6 7 38. prijzig is 1 2 3 4 5 6 7 39. een zachte handdoek is 1 2 3 4 5 6 7
- Dit is het einde van de vragenlijst, hartelijk bedankt voor uw medewerking -
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 66 1/7/2009
2.2, Results Main Study, Descriptives & Oneway ANOVA
N Mean SD Color Preference Positive Unique 90 4.31 1.619 Negative Unique 90 4.22 1.907 Neutral Common 90 4.47 1.677 Purchase Intentions Positive Unique 90 3.66 1.749 Negative Unique 90 3.73 1.901 Neutral Common 90 3.76 1.801 Price Willing to Pay Positive Unique 90 4.54 3.084 Negative Unique 90 4.25 2.737 Neutral Common 90 4.44 2.965
Activating Positive Categories
Positive Unique 90 3.59 1.807 Negative Unique 90 3.33 1.767 Neutral Common 90 3.51 1.655
1 = totally disagree, 7 = totally agree
Sum of
Squares df Mean
Square F Sig. Color Preference Between Groups 2.756 2 1.378 0.456 0.634 Within Groups 807.244 267 3.023 Total 810.000 269 Purchase Intentions Between Groups 0.496 2 0.248 0.075 0.928 Within Groups 882.544 267 3.305 Total 883.041 269 Price Willing to Pay Between Groups 3.954 2 1.977 0.230 0.795 Within Groups 2,296.051 267 8.599 Total 2,300.005 269 Activating Positive Categories Between Groups 3.172 2 1.586 0.521 0.594 Within Groups 812.194 267 3.042 Total 815.367 269
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 67 1/7/2009
2.3, Results Main Study, Cronbach’s Alpha
Case Processing Summary
N % Cases Valid 270 99.6
Excluded(a) 1 0.4 Total 271 100.0
a. Listwise deletion based on all variables in the procedure.
Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha Based on
Standardized Items N of Items 0.938 0.939 2
Inter-Item Correlation Matrix
Extent thinking about other positive things
Extent thinking about other positive products
Extent thinking about other positive things
1.000 0.884
Extent thinking about other positive products
0.884 1.000
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
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2.4, Results Main Study, Correlation Analysis
Correlations
Ability to Identify
with Product Color
Preference
Ability to Identify with Product
Pearson Correlation 1 .566(**) Sig. (2-tailed) 0.000 N 270 270
Color Preference
Pearson Correlation .566(**) 1 Sig. (2-tailed) 0.000 N 270 270
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
Ability to Identify
with Product Purchase Intentions
Ability to Identify with Product
Pearson Correlation 1 .678(**) Sig. (2-tailed) 0.000 N 270 270
Purchase Intentions
Pearson Correlation .678(**) 1 Sig. (2-tailed) 0.000 N 270 270
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
Ability to Identify
with Product Price Willing
to Pay
Ability to Identify with Product
Pearson Correlation 1 .518(**) Sig. (2-tailed) 0.000 N 270 270
Price Willing to Pay
Pearson Correlation .518(**) 1 Sig. (2-tailed) 0.000 N 270 270
**. Correlation is significant at the 0.01 level (2-tailed).
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
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2.5, Results Main Study, Descriptives, Repeated Measures ANOVA, & Correlation Analysis, Brown
N Mean SD Brown Color Preference Positive Unique 30 4.033 1.671
Negative Unique 30 3.767 2.029
Neutral Common 30 4.400 1.610
Purchase Intentions Positive Unique 30 3.533 1.737
Negative Unique 30 3.433 1.906
Neutral Common 30 3.967 1.629
Price Willing to Pay Positive Unique 30 4.271 2.962
Negative Unique 30 3.905 2.891
Neutral Common 30 4.055 2.944
Activating Positive Categories
Positive Unique 30 3.133 1.697
Negative Unique 30 2.850 1.753
Neutral Common 30 2.967 1.313 1 = totally disagree, 7 = totally agree
Type III Sum of
Squares df Mean
Square F Sig. Brown Color Preference Sphericity Assumed 6.067 2 3.033 1.544 0.222 Purchase Intentions Sphericity Assumed 4.822 2 2.411 1.321 0.275 Price Willing to Pay Sphericity Assumed 2.039 2 1.019 0.568 0.570 Activating Positive Categories Sphericity Assumed 1.217 2 0.608 0.389 0.680
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 70 1/7/2009
Correlations
Ability to Identify
with Product
Color Preference
Brown
Ability to Identify with Product
Pearson Correlation 1 .561(**)
Sig. (2-tailed) 0.000
N 90 90
Color Preference Brown
Pearson Correlation .561(**) 1
Sig. (2-tailed) 0.000
N 90 90
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
Ability to Identify
with Product Purchase
Intentions Brown
Ability to Identify with Product
Pearson Correlation 1 .710(**)
Sig. (2-tailed) 0.000
N 90 90
Purchase Intentions Brown
Pearson Correlation .710(**) 1
Sig. (2-tailed) 0.000
N 90 90
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
Ability to Identify
with Product Price Willing to Pay Brown
Ability to Identify with Product
Pearson Correlation 1 .374(**)
Sig. (2-tailed) 0.000
N 90 90
Price Willing to Pay Brown
Pearson Correlation .374(**) 1
Sig. (2-tailed) 0.000
N 90 90
**. Correlation is significant at the 0.01 level (2-tailed).
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2.6, Results Main Study, Descriptives, Repeated Measures ANOVA, & Correlation Analysis, Blue
N Mean SD Blue Color Preference Positive Unique 30 4.633 1.586
Negative Unique 30 4.967 1.520
Neutral Common 30 4.733 1.617
Purchase Intentions Positive Unique 30 3.967 1.564
Negative Unique 30 3.833 1.859
Neutral Common 30 3.833 1.840
Price Willing to Pay Positive Unique 30 4.067 2.292
Negative Unique 30 3.817 2.091
Neutral Common 30 4.017 2.045
Activating Positive Categories Positive Unique 30 3.600 1.719
Negative Unique 30 3.267 1.746
Neutral Common 30 3.317 1.679 1 = totally disagree, 7 = totally agree
Type III Sum of
Squares df Mean
Square F Sig. Blue Color Preference Sphericity Assumed 1.756 2 0.878 0.501 0.608 Purchase Intentions Sphericity Assumed 0.356 2 0.178 0.095 0.909 Price Willing to Pay Sphericity Assumed 1.050 2 0.525 0.379 0.686 Activating Positive Categories Sphericity Assumed 1.939 2 0.969 0.480 0.621
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Ilona Idserda Page 72 1/7/2009
Correlations
Ability to Identify
with Product Color
Preference Blue
Ability to Identify with Product
Pearson Correlation 1 .405(**)
Sig. (2-tailed) 0.000
N 90 90
Color Preference Blue
Pearson Correlation .405(**) 1
Sig. (2-tailed) 0.000
N 90 90
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
Ability to Identify
with Product Purchase
Intentions Blue
Ability to Identify with Product
Pearson Correlation 1 .516(**)
Sig. (2-tailed) 0.000
N 90 90
Purchase Intentions Blue
Pearson Correlation .516(**) 1
Sig. (2-tailed) 0.000
N 90 90
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
Ability to Identify
with Product Price Willing to Pay Blue
Ability to Identify with Product
Pearson Correlation 1 .455(**)
Sig. (2-tailed) 0.000
N 90 90
Price Willing to Pay Blue
Pearson Correlation .455(**) 1
Sig. (2-tailed) 0.000
N 90 90
**. Correlation is significant at the 0.01 level (2-tailed).
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 73 1/7/2009
2.7, Results Main Study, Descriptives, Repeated Measures ANOVA, & Correlation Analysis, Green
N Mean SD Green Color Preference Positive Unique 30 4.267 1.596
Negative Unique 30 3.933 1.964
Neutral Common 30 4.267 1.818
Purchase Intentions Positive Unique 30 3.467 1.943
Negative Unique 30 3.300 1.725
Neutral Common 30 3.467 1.943
Price Willing to Pay Positive Unique 30 5.290 3.779
Negative Unique 30 5.032 3.052
Neutral Common 30 5.257 3.621
Activating Positive Categories Positive Unique 30 4.050 1.936
Negative Unique 30 3.883 1.705
Neutral Common 30 4.233 1.726 1 = totally disagree, 7 = totally agree
Type III Sum of
Squares df Mean
Square F Sig. Green Color Preference Sphericity Assumed 2.222 2 1.111 0.775 0.465 Purchase Intentions Sphericity Assumed 0.556 2 0.278 0.145 0.866 Price Willing to Pay Sphericity Assumed 1.185 2 0.592 0.286 0.752 Activating Positive Categories Sphericity Assumed 1.839 2 0.919 0.677 0.512
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 74 1/7/2009
Correlations
Ability to Identify
with Product
Color Preference
Green
Ability to Identify with Product
Pearson Correlation 1 .767(**)
Sig. (2-tailed) 0.000
N 90 90
Color Preference Green
Pearson Correlation .767(**) 1
Sig. (2-tailed) 0.000
N 90 90
**. Correlation is significant at the 0.01 level (2-tailed). Correlations
Ability to Identify
with Product Purchase
Intentions Green
Ability to Identify with Product
Pearson Correlation 1 .856(**)
Sig. (2-tailed) 0.000
N 90 90
Purchase Intentions Green
Pearson Correlation .856(**) 1
Sig. (2-tailed) 0.000
N 90 90
**. Correlation is significant at the 0.01 level (2-tailed). Correlations
Ability to Identify
with Product Price Willing to Pay Green
Ability to Identify with Product
Pearson Correlation 1 .698(**)
Sig. (2-tailed) 0.000
N 90 90
Price Willing to Pay Green
Pearson Correlation .698(**) 1
Sig. (2-tailed) 0.000
N 90 90
**. Correlation is significant at the 0.01 level (2-tailed).
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 75 1/7/2009
Appendix 3, Post Study
3.1, Survey Post Study VERSIE 1.1
Door middel van deze enquête probeer ik, master marketing student aan de Rijksuniversiteit Groningen, meer inzicht te krijgen in kleur- en productvoorkeur. Denkt u er aan dat er bij het invullen van deze enquête geen juiste of onjuiste antwoorden mogelijk zijn. Ik dank u voor uw medewerking. GESLACHT: MAN / VROUW, LEEFTIJD: ………………... Gepaard met onderstaande vragen ziet u enkele afbeeldingen van handdoeken. Kijk hier alstublieft goed naar, en beantwoord vervolgens de vragen.
Kleur: Belangrijk Omcirkel voor iedere stelling het voor u juiste antwoord (1= zeer mee oneens, 7= zeer mee eens).
40. Ik vind de kleur ‘Belangrijk’ mooi voor een handdoek
1 2 3 4 5 6 7 41. Ik zou de handdoek in de kleur ‘Belangrijk’ graag aanschaffen
1 2 3 4 5 6 7 42. De handdoek in de kleur ‘Belangrijk’ doet me denken aan andere leuke dingen
1 2 3 4 5 6 7 43. De handdoek in de kleur ‘Belangrijk’ doet me denken aan producten waar ik een positief beeld van heb
1 2 3 4 5 6 7 44. Ik kan me identificeren met de handdoek in de kleur ‘Belangrijk’
1 2 3 4 5 6 7
Stel u zou de handdoek in de kleur ‘Belangrijk’ aanschaffen. Welke prijs zou u bereid zijn te betalen? 45. De prijs die ik bereid bent te betalen voor
de handdoek in de kleur ‘Belangrijk’ is € ……………. Ten slotte vind u hieronder nog enkele stellingen met betrekking tot de handdoek in de kleur ‘Belangrijk’. Omcirkel voor iedere stelling het voor u juiste antwoord (1 = zeer mee oneens, 7 = zeer mee eens) Ik geloof dat de handdoek in de kleur ‘Belangrijk’….
46. een unieke handdoek is 1 2 3 4 5 6 7 47. in veel winkels verkrijgbaar is 1 2 3 4 5 6 7 48. een exclusief imago heeft 1 2 3 4 5 6 7 49. mooi is 1 2 3 4 5 6 7 50. van hoge kwaliteit is 1 2 3 4 5 6 7 51. prijzig is 1 2 3 4 5 6 7 52. een zachte handdoek is 1 2 3 4 5 6 7
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
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Kleur: Moeras
Omcirkel voor iedere stelling het voor u juiste antwoord (1= zeer mee oneens, 7= zeer mee eens).
53. Ik vind ‘Moeras’ een mooie kleur voor een handdoek 1 2 3 4 5 6 7
54. Ik zou de handdoek in de kleur ‘Moeras’ graag aanschaffen 1 2 3 4 5 6 7
55. De handdoek in de kleur ‘Moeras’ doet me denken aan andere leuke dingen 1 2 3 4 5 6 7
56. De handdoek in de kleur ‘Moeras’ doet me denken aan producten waar ik een positief beeld van heb 1 2 3 4 5 6 7
57. Ik kan me identificeren met de handdoek in de kleur ‘Moeras’ 1 2 3 4 5 6 7
Stel u zou de handdoek in de kleur ‘Moeras’aanschaffen. Welke prijs zou u bereid zijn te betalen?
58. De prijs die ik bereid bent te betalen voor de handdoek in de kleur ‘Moeras’ is € …………….
Ten slotte vind u hieronder nog enkele stellingen met betrekking tot de handdoek in de kleur ‘Moeras’. Omcirkel voor iedere stelling het voor u juiste antwoord (1 = zeer mee oneens, 7 = zeer mee eens) Ik geloof dat de handdoek in de kleur ‘Moeras’….
59. een unieke handdoek is 1 2 3 4 5 6 7 60. in veel winkels verkrijgbaar is 1 2 3 4 5 6 7 61. een exclusief imago heeft 1 2 3 4 5 6 7 62. mooi is 1 2 3 4 5 6 7 63. van hoge kwaliteit is 1 2 3 4 5 6 7 64. prijzig is 1 2 3 4 5 6 7 65. een zachte handdoek is 1 2 3 4 5 6 7
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
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Kleur: Hout Omcirkel voor iedere stelling het voor u juiste antwoord (1= zeer mee oneens, 7= zeer mee eens).
66. Ik vind ‘Hout’een mooie kleur voor een handdoek 1 2 3 4 5 6 7
67. Ik zou de handdoek in de kleur ‘Hout’ graag aanschaffen 1 2 3 4 5 6 7
68. De handdoek in de kleur ‘Hout’ doet me denken aan andere leuke dingen 1 2 3 4 5 6 7
69. De handdoek in de kleur ‘Hout’ doet me denken aan producten waar ik een positief beeld van heb 1 2 3 4 5 6 7
70. Ik kan me identificeren met de handdoek in de kleur ‘Hout’ 1 2 3 4 5 6 7
Stel u zou de handdoek in de kleur ‘Hout’ aanschaffen. Welke prijs zou u bereid zijn te betalen?
71. De prijs die ik bereid bent te betalen voor de handdoek in de kleur ‘Hout’is € …………….
Ten slotte vind u hieronder nog enkele stellingen met betrekking tot de handdoek in de kleur ‘Hout’. Omcirkel voor iedere stelling het voor u juiste antwoord (1 = zeer mee oneens, 7 = zeer mee eens) Ik geloof dat de handdoek in de kleur ‘Hout’….
72. een unieke handdoek is 1 2 3 4 5 6 7 73. in veel winkels verkrijgbaar is 1 2 3 4 5 6 7 74. een exclusief imago heeft 1 2 3 4 5 6 7 75. mooi is 1 2 3 4 5 6 7 76. van hoge kwaliteit is 1 2 3 4 5 6 7 77. prijzig is 1 2 3 4 5 6 7 78. een zachte handdoek is 1 2 3 4 5 6 7
- Dit is het einde van de vragenlijst, hartelijk bedankt voor uw medewerking -
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3.2, Results Post Study, Descriptives, Oneway ANOVA & Posthoc Test
N Mean SD Associations Color Preference Positive Unique 27 4.704 1.815
Negative Unique 27 3.481 2.101
Neutral Common 27 4.296 2.053
Purchase Intentions Positive Unique 27 4.556 1.867
Negative Unique 27 3.444 2.063
Neutral Common 27 4.111 1.968
Price Willing to Pay Positive Unique 27 5.978 3.908
Negative Unique 27 4.517 3.686
Neutral Common 27 5.459 3.504
Activating Positive Categories
Positive Unique 27 4.481 1.821
Negative Unique 27 3.185 1.967
Neutral Common 27 3.907 1.606
1 = totally disagree, 7 = totally agree
Sum of
Squares df Mean
Square F Sig. Color Preference Between Groups 20.914 2 10.457 2.631 0.078
Within Groups 310.000 78 3.974
Total 330.914 80
Purchase Intentions Between Groups 16.889 2 8.444 2.181 0.120
Within Groups 302.000 78 3.872
Total 318.889 80
Price Willing to Pay Between Groups 29.630 2 14.815 1.080 0.345
Within Groups 1,069.697 78 13.714
Total 1,099.327 80
Activating Positive Categories Between Groups 22.784 2 11.392 3.501 0.035
Within Groups 253.833 78 3.254
Total 276.617 80
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 79 1/7/2009
90% Confidence
Mean
Difference Std. Error Sig.
Upper Bound
Lower Bound
Color Preference Positive Unique Negative Unique 1.222(*) 0.543 0.027 0.32 2.13
Neutral Common 0.407 0.543 0.455 -0.50 1.31
Negative Unique Positive Unique -1.222(*) 0.543 0.027 -2.13 -0.32
Neutral Common -0.815 0.543 0.137 -1.72 0.09
Neutral Common Positive Unique -0.407 0.543 0.455 -1.31 0.50
Negative Unique 0.815 0.543 0.137 -0.09 1.72
95% Confidence
Mean
Difference Std. Error Sig.
Upper Bound
Lower Bound
Activating Positive Categories Positive Unique Negative Unique 1.296(*) 0.491 0.010 0.32 2.27
Neutral Common 0.574 0.491 0.246 -0.40 1.55
Negative Unique Positive Unique -1.296(*) 0.491 0.010 -2.27 -0.32
Neutral Common -0.722 0.491 0.145 -1.70 0.26
Neutral Common Positive Unique -0.574 0.491 0.246 -1.55 0.40
Negative Unique 0.722 0.491 0.145 -0.26 1.70
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3.3, Results Post Study, Cronbach’s Alpha
Case Processing Summary
N % Cases Valid 81 100.0
Excluded(a) 0 0.0
Total 81 100.0
a. Listwise deletion based on all variables in the procedure.
Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha Based on
Standardized Items N of Items 0.902 0.902 2
Inter-Item Correlation Matrix
Extent thinking about other positive things
Extent thinking about other positive products
Extent thinking about other positive things
1.000 0.822
Extent thinking about other positive products
0.822 1.000
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
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3.4, Results Post Study, Correlation Analysis
Correlations
Ability to Identify
with Product Color
Preference
Ability to Identify with Product
Pearson Correlation 1 .762(**)
Sig. (2-tailed) 0.000
N 81 81
Color Preference
Pearson Correlation .762(**) 1
Sig. (2-tailed) 0.000
N 81 81
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
Ability to Identify
with Product Purchase Intentions
Ability to Identify with Product
Pearson Correlation 1 .783(**)
Sig. (2-tailed) 0.000
N 81 81
Purchase Intentions
Pearson Correlation .783(**) 1
Sig. (2-tailed) 0.000
N 81 81
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
Ability to Identify
with Product Price Willing
to Pay
Ability to Identify with Product
Pearson Correlation 1 .513(**)
Sig. (2-tailed) 0.000
N 81 81
Price Willing to Pay
Pearson Correlation .513(**) 1
Sig. (2-tailed) 0.000
N 81 81
**. Correlation is significant at the 0.01 level (2-tailed).
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
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3.5, Results Post Study, Descriptives, Repeated Measures ANOVA, Post Hoc & Correlation Analysis, Brown
N Mean SD Brown Color Preference Positive Unique 9 5.00 1.871
Negative Unique 9 4.22 2.279
Neutral Common 9 4.89 1.833
Purchase Intentions Positive Unique 9 5.11 1.691
Negative Unique 9 4.44 2.128
Neutral Common 9 4.56 1.878
Price Willing to Pay Positive Unique 9 5.4389 3.50658
Negative Unique 9 4.7722 3.70195
Neutral Common 9 5.7222 3.19287
Activating Positive Categories
Positive Unique 9 5.17 2.062
Negative Unique 9 3.78 2.123
Neutral Common 9 4.56 1.685
Type III Sum of
Squares df Mean
Square F Sig. Brown Color Preference Sphericity Assumed 3.185 2 1.593 0.370 0.696
Purchase Intentions Sphericity Assumed 2.296 2 1.148 0.288 0.753
Price Willing to Pay Sphericity Assumed 4.282 2 2.141 2.890 0.085
Activating Positive Categories Sphericity Assumed 8.722 2 4.361 1.164 0.337
90% Confidence
Mean
Difference Std. Error Sig.
Upper Bound
Lower Bound
Price Willing to Pay, Brown Positive Unique Negative Unique 0.667 0.441 0.169 -0.153 1.487
Neutral Common -0.283 0.300 0.373 -0.841 0.275
Negative Unique Positive Unique -0.667 0.441 0.169 -1.487 0.153
Neutral Common -.950(*) 0.458 0.072 -1.801 -0.099
Neutral Common Positive Unique 0.283 0.300 0.373 -0.275 0.841
Negative Unique .950(*) 0.458 0.072 0.099 1.801
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 83 1/7/2009
Correlations
Ability to Identify
with Product
Color Preference
Brown
Ability to Identify with Product
Pearson Correlation 1 .875(**)
Sig. (2-tailed) 0.000
N 27 27
Color Preference Brown
Pearson Correlation .875(**) 1
Sig. (2-tailed) 0.000
N 27 27
**. Correlation is significant at the 0.01 level (2-tailed). Correlations
Ability to Identify
with Product
Purchase Intentions
Brown
Ability to Identify with Product
Pearson Correlation 1 .891(**)
Sig. (2-tailed) 0.000
N 27 27
Purchase Intentions Brown
Pearson Correlation .891(**) 1
Sig. (2-tailed) 0.000
N 27 27
**. Correlation is significant at the 0.01 level (2-tailed). Correlations
Ability to Identify
with Product
Price Willing to Pay Brown
Ability to Identify with Product
Pearson Correlation 1 0.361
Sig. (2-tailed) 0.064
N 27 27
Price Willing to Pay Brown
Pearson Correlation 0.361 1
Sig. (2-tailed) 0.064
N 27 27
**. Correlation is significant at the 0.01 level (2-tailed).
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 84 1/7/2009
3.6, Results Post Study, Descriptives, Repeated Measures ANOVA & Correlation Analysis, Blue
N Mean SD Blue Color Preference Positive Unique 9 4.56 1.878
Negative Unique 9 3.44 2.242
Neutral Common 9 4.67 2.398
Purchase Intentions Positive Unique 9 4.44 1.740
Negative Unique 9 3.22 2.224
Neutral Common 9 4.56 2.297
Price Willing to Pay Positive Unique 9 6.2722 4.35582
Negative Unique 9 4.1111 4.68227
Neutral Common 9 5.7667 4.10663
Activating Positive Categories Positive Unique 9 3.83 1.785
Negative Unique 9 3.33 2.107
Neutral Common 9 3.94 1.722
Type III Sum of
Squares df Mean
Square F Sig. Blue Color Preference Sphericity Assumed 8.222 2 4.111 1.396 0.276
Purchase Intentions Sphericity Assumed 9.852 2 4.926 2.141 0.150
Price Willing to Pay Sphericity Assumed 23.001 2 11.500 3.173 0.069
Activating Positive Categories Sphericity Assumed 1.907 2 0.954 0.371 0.696
90% Confidence
Mean
Difference Std. Error Sig.
Upper Bound
Lower Bound
Price Willing to Pay, Blue Positive Unique Negative Unique 2.161(*) 1.101 0.085 0.113 4.209
Neutral Common 0.506 0.577 0.407 -0.568 1.579
Negative Unique Positive Unique -2.161(*) 1.101 0.085 -4.209 -0.113
Neutral Common -1.656 0.933 0.114 -3.390 0.079
Neutral Common Positive Unique -0.506 0.577 0.407 -1.579 0.568
Negative Unique 1.656 0.933 0.114 -0.079 3.390
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 85 1/7/2009
Correlations
Ability to Identify
with Product
Color Preference
Blue
Ability to Identify with Product
Pearson Correlation 1 .759(**)
Sig. (2-tailed) 0.000
N 27 27
Color Preference Blue
Pearson Correlation .759(**) 1
Sig. (2-tailed) 0.000
N 27 27
**. Correlation is significant at the 0.01 level (2-tailed). Correlations
Ability to Identify
with Product
Purchase Intentions
Blue
Ability to Identify with Product
Pearson Correlation 1 .728(**)
Sig. (2-tailed) 0.000
N 27 27
Purchase Intentions Blue
Pearson Correlation .728(**) 1
Sig. (2-tailed) 0.000
N 27 27
**. Correlation is significant at the 0.01 level (2-tailed). Correlations
Ability to Identify
with Product
Price Willing to Pay Blue
Ability to Identify with Product
Pearson Correlation 1 .612(**)
Sig. (2-tailed) 0.001
N 27 27
Price Willing to Pay Blue
Pearson Correlation .612(**) 1
Sig. (2-tailed) 0.001
N 27 27
**. Correlation is significant at the 0.01 level (2-tailed).
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 86 1/7/2009
3.7, Results Post Study, Descriptives, Repeated Measures ANOVA, Posthoc Test & Correlation Analysis, Green
N Mean SD Green Color Preference Positive Unique 9 4.33 1.803
Negative Unique 9 2.78 1.716
Neutral Common 9 3.33 1.732
Purchase Intentions Positive Unique 9 4.11 2.205
Negative Unique 9 2.67 1.581
Neutral Common 9 3.22 1.563
Price Willing to Pay Positive Unique 9 6.2222 4.22870
Negative Unique 9 4.6667 2.87228
Neutral Common 9 4.8889 3.50694
Activating Positive Categories Positive Unique 9 4.44 1.530
Negative Unique 9 2.44 1.609
Neutral Common 9 4.17 1.581
Type III Sum of
Squares df Mean
Square F Sig. Green Color Preference Sphericity Assumed 11.185 2 5.593 2.266 0.136
Purchase Intentions Sphericity Assumed 9.556 2 4.778 1.773 0.202
Price Willing to Pay Sphericity Assumed 12.741 2 6.370 0.582 0.570
Activating Positive Categories Sphericity Assumed 21.130 2 10.565 5.304 0.017
95% Confidence
Mean
Difference Std. Error Sig.
Upper Bound
Lower Bound
Activating Positive Categories, Green Positive Unique Negative Unique 2.000(*) 0.799 0.037 0.157 3.843
Neutral Common 0.278 0.442 0.547 -0.741 1.297
Negative Unique Positive Unique -2.000(*) 0.799 0.037 -3.843 -0.157
Neutral Common -1.722(*) 0.703 0.040 -3.343 -0.102
Neutral Common Positive Unique -0.278 0.442 0.547 -1.297 0.741
Negative Unique 1.722(*) 0.703 0.040 0.102 3.343
The Color Naming Effect: How Fancy Master Thesis Color Names Influence Product Preference Marketing Management
Ilona Idserda Page 87 1/7/2009
Correlations
Ability to Identify
with Product
Color Preference
Green
Ability to Identify with Product
Pearson Correlation 1 .734(**)
Sig. (2-tailed) 0.000
N 27 27
Color Preference Green
Pearson Correlation .734(**) 1
Sig. (2-tailed) 0.000
N 27 27
**. Correlation is significant at the 0.01 level (2-tailed). Correlations
Ability to Identify
with Product
Purchase Intentions
Green
Ability to Identify with Product
Pearson Correlation 1 .676(**)
Sig. (2-tailed) 0.000
N 27 27
Purchase Intentions Green
Pearson Correlation .676(**) 1
Sig. (2-tailed) 0.000
N 27 27
**. Correlation is significant at the 0.01 level (2-tailed). Correlations
Ability to Identify
with Product
Price Willing to Pay Green
Ability to Identify with Product
Pearson Correlation 1 .607(**)
Sig. (2-tailed) 0.001
N 27 27
Price Willing to Pay Green
Pearson Correlation .607(**) 1
Sig. (2-tailed) 0.001
N 27 27
**. Correlation is significant at the 0.01 level (2-tailed).