the color naming effect: how fancy color names influence

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 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 [email protected] Student number: 1386980 Marketing Management Master Thesis Completion date: 1/7/2009 1st Supervisor: dr. M.A. Tuk 2nd Supervisor: dr. D. Trampe



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.



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



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



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



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



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:



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?



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.



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



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



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


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



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



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.



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.



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


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



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.



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



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



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



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.



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



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.



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



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.



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.



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).



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



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.



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



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



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).



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



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.



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.



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



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.



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



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.



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,



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.



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



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



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



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.



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



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



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



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



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



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 -



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



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



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



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


Common 23 3.91 2.172

Green Positive unique 23 6.83 1.723


Common 23 4.09 2.193



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


Total 417.159 68

Green Between Groups 110.464 2 55.232 15.107 0.000


Total 351.768 68

Uniqueness Brown Between Groups 73.855 2 36.928 8.498 0.001


Total 360.638 68

Blue Between Groups 118.377 2 59.188 12.577 0.000


Total 428.986 68

Green Between Groups 97.304 2 48.652 11.306 0.000


Total 381.304 68



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


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


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


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


Negative unique -2.217(*) 0.612 0.001 -3.44 -1.00

*. The mean difference is significant at the .05 level.



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 kleuren 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



Kleur: Moeras Omcirkel voor iedere stelling het voor u juiste antwoord (1 = zeer mee oneens, 7 = zeer mee eens).






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….




Kleur: Hout Omcirkel voor iedere stelling het voor u juiste antwoord (1 = zeer mee oneens, 7 = zeer mee eens).






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….





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



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


1.000 0.884


0.884 1.000



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



Purchase Intentions



Correlations

Ability to Identify

with Product Price Willing

to Pay



Price Willing to Pay





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



Price Willing to Pay Positive Unique 30 4.271 2.962




Positive Unique 30 3.133 1.697


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



Correlations

Ability to Identify

with Product

Color Preference

Brown


Pearson Correlation 1 .561(**)

Sig. (2-tailed) 0.000

N 90 90

Color Preference Brown

Pearson Correlation .561(**) 1


N 90 90


Correlations

Ability to Identify

with Product Purchase

Intentions Brown




N 90 90

Purchase Intentions Brown



N 90 90


Correlations

Ability to Identify

with Product Price Willing to Pay Brown




N 90 90

Price Willing to Pay Brown



N 90 90




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









Activating Positive Categories Positive Unique 30 3.600 1.719



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



Correlations

Ability to Identify

with Product Color

Preference Blue




N 90 90

Color Preference Blue



N 90 90


Correlations

Ability to Identify


Intentions Blue




N 90 90

Purchase Intentions Blue



N 90 90


Correlations

Ability to Identify

with Product Price Willing to Pay Blue




N 90 90

Price Willing to Pay Blue



N 90 90




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












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



Correlations

Ability to Identify

with Product

Color Preference

Green




N 90 90

Color Preference Green



N 90 90

**. Correlation is significant at the 0.01 level (2-tailed). Correlations

Ability to Identify


Intentions Green




N 90 90

Purchase Intentions Green



N 90 90


Ability to Identify

with Product Price Willing to Pay Green




N 90 90

Price Willing to Pay Green



N 90 90




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 kleuren 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’….




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’….




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’….





3.2, Results Post Study, Descriptives, Oneway ANOVA & Posthoc Test

N Mean SD Associations Color Preference Positive Unique 27 4.704 1.815













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


Total 330.914 80

Purchase Intentions Between Groups 16.889 2 8.444 2.181 0.120


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


Total 276.617 80



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


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


Neutral Common -0.722 0.491 0.145 -1.70 0.26


Negative Unique 0.722 0.491 0.145 -0.26 1.70



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




1.000 0.822


0.822 1.000



3.4, Results Post Study, Correlation Analysis

Correlations

Ability to Identify

with Product Color

Preference




N 81 81

Color Preference



N 81 81


Correlations

Ability to Identify

with Product Purchase Intentions




N 81 81

Purchase Intentions



N 81 81


Correlations

Ability to Identify

with Product Price Willing

to Pay




N 81 81

Price Willing to Pay



N 81 81




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













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


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



Correlations

Ability to Identify

with Product

Color Preference

Brown




N 27 27

Color Preference Brown



N 27 27


Ability to Identify

with Product

Purchase Intentions

Brown




N 27 27

Purchase Intentions Brown



N 27 27


Ability to Identify

with Product



Pearson Correlation 1 0.361


N 27 27


Pearson Correlation 0.361 1


N 27 27




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












Type III Sum of

Squares df Mean

Square F Sig. Blue Color Preference Sphericity Assumed 8.222 2 4.111 1.396 0.276




90% Confidence

Mean


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


Neutral Common -1.656 0.933 0.114 -3.390 0.079


Negative Unique 1.656 0.933 0.114 -0.079 3.390



Correlations

Ability to Identify

with Product

Color Preference

Blue




N 27 27

Color Preference Blue



N 27 27


Ability to Identify

with Product

Purchase Intentions

Blue




N 27 27

Purchase Intentions Blue



N 27 27


Ability to Identify

with Product





N 27 27




N 27 27




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












Type III Sum of

Squares df Mean

Square F Sig. Green Color Preference Sphericity Assumed 11.185 2 5.593 2.266 0.136




95% Confidence

Mean


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


Neutral Common -1.722(*) 0.703 0.040 -3.343 -0.102


Negative Unique 1.722(*) 0.703 0.040 0.102 3.343



Correlations

Ability to Identify

with Product

Color Preference

Green




N 27 27

Color Preference Green



N 27 27


Ability to Identify

with Product

Purchase Intentions

Green




N 27 27

Purchase Intentions Green



N 27 27


Ability to Identify

with Product





N 27 27




N 27 27


the color naming effect: how fancy color names influence

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