Eindhoven University of Technology

MASTER

The moderating role of consumers' need for uniqueness on context-dependent choice

'the high-quality-focus'

Oudenhooven, P.G.J.

Award date:2009

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The moderating role of consumers' need for uniqueness

on context-dependent choice:

‘The high-quality-focus’

P.G.J. Oudenhooven

Running head: CNFU AND CONTEXT EFFECTS

The moderating role of consumers' need for uniqueness on context-dependent choice:

‘The high-quality-focus’

P.G.J. Oudenhooven

s031935

Eindhoven University of Technology

School of Innovation Sciences

HTI group

Supervisors:

Dr. ir. Martijn C. Willemsen (1st supervisor)

Dr. Jaap R. C. Ham (2nd supervisor) 2009-11-16

Acknowledgements

With this master thesis, I complete both my empirical research and a fantastic period

at Eindhoven University of Technology. Therefore, I would like to thank some people for

their inspiration and support throughout my entire study, not just, because it is a custom to do

so, but because I sincerely mean it. As most of these people are Dutch, I prefer to express my

appreciation in Dutch.

In de eerste plaats bedank ik mijn eerste begeleider, dr. ir. Martijn Willemsen. De

uitzonderlijke begeleiding die je me hebt geboden is iets waar menig afstudeerder van

droomt. Je hebt me op voortreffelijke wijze geïnspireerd, gedoceerd en waar nodig

gecorrigeerd. Verder wil ik mijn tweede begeleider, dr. Jaap Ham, bedanken voor zijn

kritische en eerlijke blik op deze scriptie.

Zowel de materiële als immateriële steun van mijn ouders en de ouders van Tamara,

heeft er voor gezorgd dat ik deze opleiding überhaupt heb kunnen voltooien. Jacqueline,

Adry, Anita en Ad, dergelijke steun is niet zo vanzelfsprekend als door jullie vaak werd

gesuggereerd. Ik ben jullie dan ook zeer erkentelijk. Daarnaast hebben een aantal personen op

verschillende manieren pro Deo hun steentje bijgedragen: Jolien Peters, Lieke Janssen,

Berend van den Berge, Coen Oudenhooven, David van der Pol, Johan Datema, Koen

Crommentuijn en mijn medebewoners van studentenhuis ‘Hotel Saint-Tropez’, waarvan in

het bijzonder Bart Hofman en Iain Aitchison. Ik heb jullie hulp zeer gewaardeerd.

Tamara, mijn studie is ook voor jou een enorme investering geweest. Je steun

tijdens het onderzoek naar ‘voorkeuren’ en ‘beslissingen’ heeft de voorkeur voor jou alleen

maar versterkt (gelukkig hebben wij onze keuze al lang gemaakt).

Dit onderzoek heeft andermaal bewezen dat de beste dingen niet volledig op

individuele basis ontstaan, maar altijd in samenwerking met anderen.

Bedankt.

I

Abstract

Context effects influence many decisions we make in everyday life. In some cases,

modifying the context by adding new alternatives to an existing choice set changes our

preferences of the original options, even if the alternative seems irrelevant. For example

research on decision making and consumer behaviour showed that the compromise effect and

the attraction effect systematically violate most rational choice models (in both cases the

addition of a new alternative, increases shares of one of the original choice options).

Simonson and Nowlis (2000) have shown that the strength of the compromise effect

depends on the individual difference measure ‘need for uniqueness’ (NFU). The current paper

investigates how NFU moderates context-dependent choices (for as well the compromise

effect as the attraction effect). It is expected that people with high NFU have a strong

preference for quality over price (the high-quality-focus). This would particularly facilitate

choosing between equally attractive choice options, like with the compromise effect. The

existence of the high-quality-focus is tested by looking at the influence of NFU on two

different versions of the compromise effect and the attraction effect, and by studying the

information acquisition processes.

Most data supports the high-quality-focus into the right direction. Nevertheless, in

contrast to our hypotheses, there is not enough statistical evidence to confirm the existence of

it. The information acquisition data does not show significantly more attention to the ‘quality’

than to ‘price’ for people with high NFU. This questions the role of NFU as an important

moderator of context-dependent choice.

II

III

Index

Acknowledgements I 

Abstract II 

1.  Introduction 1 

2.  Context effects 4 

2.1  Compromise and attraction effect 4 

2.2  Moderating variables 9 

2.3  Need for uniqueness 10 

2.4  Hypotheses 11 

3.  Method 18 

3.1  Participants 18 

3.2  Stimuli, design, and procedure 18 

4.  Results 21 

Discussion 35 

References 38 

Appendix I:  CNFU scale translation and validation 43 

Appendix II:  Translated CNFU-S survey 46 

Appendix III:  Pilots 48 

Appendix IV:  Online MouselabWEB experiment 50 

Appendix V:  Experimental design 54 

1. Introduction

In an online shopping environment, marketers do not have the same marketing tools

at their disposal as in a physical shop. Internet shops lack the possibility to influence

consumers with the smell of fresh bread or the soft feel of a new blanket. Then again, the

internet does offer better control over what non-physical information people get and in which

configuration (context) it is offered. There are countless ways of describing products (list

properties, compare attributes, describe advantages and disadvantages or show consumer

reviews: Chen & Xie, 2008; Kleinmuntz & Schkade, 1993; Schkade & Kleinmuntz, 1994)

and altering the context (presenting products alone or in an array with other options, changing

the layout of the web shop or selecting defaults: Chang & Liu, 2008; Johnson, Bellman &

Lohse, 2002; Johnson & Goldstein, 2004; Samuelson & Zeckhauser, 1988). With the internet

increasingly becoming a market for consumer decisions, this context becomes more

important.

This research focuses in particular on two remarkable ways in which context

influences choices people make (context effects) and it explores the mediating role of the

individual variable ‘need for uniqueness’ (NFU; Snijder & Fromkin, 1977). These context

effects concern the influence of other available options (the compromise effect and the

attraction effect). Both the compromise and the attraction effect show that adjusting the

context by adding a new alternative to the existing choice set, enhances the popularity of one

of the original options (Simonson, 1989; Huber, Payne & Puto, 1982).

However, individuals differ strongly in how they are affected by these context

effects. Continuing research of Simonson and Nowlis (2000), this paper explores the

influence of NFU on the compromise and the attraction effect. That is, Simonson and Nowlis

(2000) demonstrate that people with high NFU show a relatively smaller compromise effect

than people with low NFU. However, the mechanisms causing these differences might not be

1

as proposed by Simonson and Nowlis (2000). They claim that people with high NFU use

unconventional reasons and therefore prefer both extreme options (the option with the lowest

quality and lowest price and the option with the highest quality and highest price) and not the

middle compromise option. This paper proposes that the difference in compromise effect

results from the fact that people with high NFU prefer quality to price (Tian, Bearden &

Hunter, 2001) and thus an asymmetrical choice distribution is expected (lowest shares for low

quality options, medium shares for the middle options and highest shares for the options with

the highest quality). This is what we label the ‘high-quality-focus’. Indeed, earlier research

(Oudenhooven & Willemsen, 2009) showed this choice pattern. By analysing two versions of

the compromise effect (promoting an option with relative low quality and promoting an

option with high quality) and two versions of the attraction effect (also promoting both the

high and the low quality options) the high-quality-focus is tested. Additionally, this paper also

looks at differences in information processing during decision making to gain additional

insights into how NFU influences context effects. We argue that people with high and low

NFU might show different search behaviour.

As companies are able to track click streams of people visiting their web shop, they

often experiment with presentation of options, to see which format provides the highest

revenues. With the increasing possibilities to personalise the web environment adapting it to

the individual visitor, this knowledge can be applied to adaptive web shops. With this

knowledge, one could personalise websites to meet the same goals among different types of

consumers.

Companies already use compromise and attraction effects for different reasons and

it is nowadays almost commonplace on the internet to offer specific information depending on

who visits the website. Visitor characteristics are measured by simply asking the visitor to fill

in some personal information, or by tracing information about the geographical location

associated to the IP-address.

2

To be able to specify choice options depending on the amount of need for

uniqueness it is necessary to ‘detect’ the need for uniqueness of the visitor. Therefore, in

addition, this paper examines potential differences in search behaviour between high NFU

and low NFU. This way it will be possible to measure the amount of NFU of the visitor and

act accordingly.

The goal of this research is to explore how differences in NFU moderate context

effects in consumer decision-making. Discovering boundary conditions by answering this

question will bring better understanding of human decision-making.

The next chapter outlines the theoretical context of this research. Compromise and

attraction effects, moderating variables and specifically the moderating variable ‘need for

uniqueness’ are important subjects leading to the hypotheses, describes in section 2.4. The

setup and the experimental design are discussed in chapter 3, followed by a summary of the

results and hypotheses testing (chapter 4). Finally, this thesis concludes with a discussion and

some final remarks.

3

2. Context effects

In the field of decision-making and consumer behaviour, a substantial amount of

research is dedicated to investigating the compromise effect, the attraction effect and

moderating variables influencing these context effects. To understand findings from

Simonson and Nowlis (2000) (the starting point of the present paper), it is important to first

understand the compromise effect. The ‘alternative explanation’ this paper offers for the

influence of NFU on the compromise effect, is tested by applying it to both the compromise

effect and the attraction effect. Therefore, this section outlines the theoretical framework

including the compromise effect, the attraction effect, moderating variables (in particular need

for uniqueness) and section 2.4 explains how different hypotheses evolved from it.

2.1 Compromise and attraction effect

Context effects show the influence of the decision context on peoples’ preferences

and on choices people make. The compromise and attraction effect (resp. Simonson, 1989;

Huber et al., 1982) are especially interesting, because these phenomena do not match most

rational choice models. ‘Independence of irrelevant alternatives’ (Luce, 1959) suggests that

the addition of an irrelevant alternative to an existing choice set should only take shares of

these options relative to their original shares. ‘Regularity’ (Luce, 1977) states that the addition

of an alternative to a choice set cannot increase the relative share of one of the original

options. The compromise and attraction effect systematically violate these principles: after the

addition of a new alternative to an existing choice set, both the attraction effect and the

compromise effect show an increase in shares of one of the original options and/or the ratio of

the original options changes.

Attraction and compromise effects are typically observed when the available choice

options imply a trade-off between different attributes. Figure 1 shows a simplified graph of

4

this principle. In the illustration the indifference curve1 (Edwards, 1954) represents a virtual

trade-off between attribute 1 and attribute 2, such that all options on the line are equally

attractive. When we look for instance at the attributes ‘price’ and ‘quality’, a decrease in price

is offset by a decrease in quality, keeping options A and B in theory equally attractive.

Figure 1. Simplified illustration of the compromise and attraction effect.

The compromise effect is observed when a choice set (A and B) is extended with an

extreme option (C1 or C2) on the same indifference curve. Theoretically, options A, B and C1

or C2 should be just as attractive. However, the location of option C1 or C2 on the indifference

curve makes one of the original options a compromise option (B when C1 is added and A

when C2 is added). Interestingly, when an option becomes a compromise option, it gains share

compared with the original two-options set (Simonson, 1989).

1 Towards the extremes, the indifference curve follows a hyperbolic shape and not a linear one like in

figure 1. This explains the name ‘indifference curve’. However, since we operate on a relatively small

section of the curve, a linear representation suffices.

5

The attraction effect is observed when decoy D1 or D2 is added to choice set AB.

This increases share of the relative superior alternative (B when decoy D1 is added and A

when D2 joins the set) (Huber et al., 1982). The decoy option is an option that no rational

decision maker ever chooses. Still this ‘irrelevant’ option could have a big influence on the

share of the superior alternative (the dominating option). To be inferior to the existing choice

options, decoys D1 or D2 should be placed within the shaded areas of Figure 1.

In essence, the compromise effect and the attraction effect show the same cause-

and-effect pattern: adding a third option to an existing choice set of two options, subsequently

increases the share of the adjacent option resolving the difficult trade-off. However, as Dhar

and Simonson (2003), Sheng, Parker and Nakamoto (2005) and Yoon and Simonson (2008)

discuss, it might not be legitimate to assume that the underlying mechanisms causing these

effects are the same. The attraction effect is considered a ‘perceptual’ effect; with the specific

configuration of an attraction choice set, the advantage of the target over the decoy is obvious.

Choosing from a ‘compromise choice set’ requires more complex cognitive processing. In

this situation, there is no alternative superior to another. People choosing the compromise

option explain their choice comparing it with both the extremes. Choosing involves reasoning

and comparing of all the options. Therefore, the compromise effect is considered a ‘cognitive’

effect (Sheng et al., 2005).

Figure 2 shows examples of real life choice options, placed in a compromise and an

attraction structure.

6

Figure 2. Real life examples of an attraction context (top panel) and compromise context (bottom panel).

The addition of a decoy D1 or D2 (attraction) makes the decision to choose the

adjacent option explainable for one of the two original options. This option is superior on at

least one of the attributes of the decoy: like the first image in Figure 2. Why would one

choose ‘Classico’ if for the same price one could get the (seemingly higher quality)

‘Delicato’? However, when we look at choice set ABC1 or ABC2 (compromise choice sets) it

7

is not that clear cut. There are no obvious superior options - as with the attraction effect -

since all three options are placed on the same indifference curve (second image Figure 2).

Theoretically, they are equally attractive.

There is no general agreement about what causes people to prefer the compromise

option in this difficult situation. Different explanations exist for the underlying mechanisms

causing the compromise effect (Huber & Puto, 1983; Simonson, 1989; Simonson & Tversky,

1992; Sheng et al., 2005). According to Simonson (1989) and Huber and Puto (1983) people

choose the compromise option because of a search for reasons and the need to be positively

evaluated by others. Later Simonson and Tversky (1992) introduced a more fundamental

explanation based on ‘loss aversion’, or as they call it ‘extremeness aversion’. To clarify this

well accepted explanation we look for instance at choice set ABC1. ‘Extremeness aversion’

states that options C1 and A have only minor advantages and disadvantages compared with

option B, but when we compare option A with C1, these advantages and disadvantages are

twice as big. Compromise option B does not have these big disadvantages relative to either of

the extremes and since disadvantages loom larger than advantages (loss-aversion), option B

seems the better choice.

These context effects are very robust. Kivetz, Netzer and Srinivasan (2004a &

2004b) even integrated these effects in new choice models, ignoring underlying cognitive

processes causing these context effects. Their mathematical models are based on the notion of

diminishing sensitivity (Meyer & Johnson, 1995) and prospect theory (Tversky & Kahneman,

1991). In search for better explanations and boundary conditions, a lot of research focused on

moderating variables that influence these context effects. The examination of moderating

variables undertaken in this thesis can add to a robust explanation of both the attraction and

compromise effects.

8

2.2 Moderating variables

In the past, the attraction effect got considerably more research attention than the

compromise effect. Working towards a better understanding of the mechanisms causing the

compromise effect, recent research has focused primarily on all sorts of moderating variables

that influence this context effect. Some existing research focused on the decision task itself

(e.g. Dhar, Nowlis & Sherman, 2000; Dhar & Simonson, 2003; Chang & Lui, 2008;

Simonson & Tversky, 1992). Others emphasise the influence of prior knowledge of the choice

options on the compromise effect and the choice processes (Bettman, Johnson & Payne, 1990;

Sheng et al., 2005) The more expertise/experience people have with a product category, the

better they interpret the describing attributes, particularly when choice sets have a

compromise structure (Sheng et al., 2005). This decreases the compromise effect and

therefore ‘expertise/experience’ is also taken into account during this research. Furthermore,

certain cultural values seem to have moderating influence on the compromise effect (Briley,

Morris & Simonson, 2000; Simonson, 1989).

In addition, several individual differences moderate the compromise effect

(Simonson & Nowlis, 2000; Mourali, Böckenholt & Laroche, 2007). Simonson and Nowlis

(2000), the base for this paper, were one of the first to investigate the individual difference

‘need for uniqueness’ and the influence on the compromise effect. They showed that people

with low NFU show a significantly larger compromise effect than people with high NFU.

Shafir, Simonson and Tversky (1993) illustrated that consciously considering reasons as a

base for choices increases the share of a compromise option. Simonson and Nowlis (2000)

argued that this conscious reasoning is an important part of the explanation for the influence

of NFU on the compromise effect. The current study explores the underlying processes of the

influence of NFU on the compromise effect, because explanations from Simonson and Nowlis

(2000) are incomplete (as argued in section 2.4). To explain this influence of NFU on the

compromise effect, it is important first to understand the concept of need for uniqueness.

9

2.3 Need for uniqueness

Like Simonson and Nowlis (2000), the moderating variable of interest in the current

thesis is ‘need for uniqueness’. Snijder and Fromkin (1977) proposed ‘need for uniqueness’

(NFU) as a term for being different or distinctive from the average social environment. Need

for uniqueness was used as a substitute for terms like ‘abnormality’ or ‘deviance’ that carry

negative connotations. Every individual strives for uniqueness to some extent, ranging from

being “like everybody else” to “being as different and distinct from others as possible”

(Ruvio, 2008, p. 445). Snijder and Fromkin developed a scale to measure the amount of

uniqueness, consisting of 31 items divided over three factors. The first factor measuring the

lack of concern about others’ evaluations of one’s ideas, factor two measures the desire to

diverge from existing rules and the third factor measures a person’s willingness to (publicly)

defend his or her beliefs. Since NFU is something that is best expressed by showing and using

consumer products (clothing, cars, watches, etc.; Belk, 1988), Tian et al. (2001) revised the

NFU scale into a measure of ‘consumer need for uniqueness’ (CNFU). Another reason for the

development of this new measure was the lack of empirical support from different consumer

investigations for the original NFU scale. The revised items formed a specific application of

the original NFU-items. Tian et al. (2001) defined CNFU as: “The trait of pursuing

differences relative to others though the acquisition, utilization, and disposition of consumer

goods for the purpose of developing and enhancing one’s self-image and social image” (p.

52). This measure consists of factors, comparable to the original: ‘creative choices’,

‘unpopular choices’ and ‘avoidance of similarity’. The CNFU-scale showed considerably

better validity and reliability and it gained good empirical support. The only disadvantage was

the lack of usability. The scale of 31 items was too ‘bulky’ to be incorporated in combined

surveys. Ruvio, Shoham and Brenčič (2008) developed a shortened version, named the

‘consumers’ need for uniqueness short-form’ (CNFU-S), preserving the original concept. The

CNFU-S scale consists of 12 items, 4 items per factor. The applicability increased, not only

because of the reduced amount of items, but also because this scale was tested in three

10

different countries. The present paper will use this measure, but because it is quite new, the

internal consistency is checked and a factor analyses will verify the factor structure.

Throughout this thesis, the scale is abbreviated as ‘CNFU’.

2.4 Hypotheses

Simonson and Nowlis (2000) illustrate that participants with high NFU show a

weaker compromise effect than people with low NFU. According to Simonson and Nowlis

people with low NFU want to be evaluated as making conventional or not novel choices.

People think of conventional reasons for choosing compromise options as for example “Both

price and features are important, so I’ll take the middle one,” or “The middle option combines

the two factors” (p. 55). Simonson and Nowlis claim that people with low NFU use these

reasons to justify their choices and people with high NFU use unconventional reasons

(anything but the reasons just mentioned) which causes them to avoid the compromise option.

Therefore, Simonson and Nowlis argue that people with high NFU prefer the extreme options

(e.g. option A and C from choice set ABC1 in Figure 1) but not the compromise option.

Simonson and Nowlis fail to show the actual choice data that led to their conclusions. They

only indicate differences in compromise effect and change in shares of the compromise

options, but they do not show the distribution of shares among the three choice options (A, B

and C). Their paper describes that the increase of shares of the compromise option (after the

addition of a third option to the choice set) is bigger for people with low NFU than for people

with high NFU. To be able to draw conclusions about the cause of this phenomenon, one has

to know the distribution of shares over the three options. The assumption that ‘people with

high NFU use unconventional reasons causing them to choose both extreme options’ cannot

be checked because Simonson and Nowlis only describe shares of the middle compromise

option; they do not show information about shares of the two extreme options.

Earlier research (Oudenhooven & Willemsen, 2009) reproduced part of the study of

Simonson and Nowlis (2000). The most important differences from the original study were

11

the use of a scale for consumers need for uniqueness (CNFU) instead of NFU and people first

had to match the choice options before choosing an option. This research resulted in the same

main conclusion as the one from Simonson and Nowlis. People with low CNFU indeed

showed a stronger compromise effect than people with high CNFU. However, choice

frequencies showed a rather interesting pattern. Low CNFU behaved as expected; low shares

for the extreme options and high shares for the middle compromise option. People with high

CNFU on the other hand, prefer the option with the highest price and best quality, followed

by the compromise option, and the option with the lowest price and quality was chosen the

least often. This directional preference differs from the suggestion of Simonson and Nowlis,

that high CNFU would prefer both extreme options.

A possible explanation for this asymmetrical distribution of high CNFU appeared

from literature review on individual differences and need for uniqueness (Snyder & Fromkin,

1977; Belk, 1988; Tian et al., 2001). This review indicates another, more obvious reason for

the observed difference in compromise effect, inherent to the application of choice options

described on the attributes ‘price’ and ‘quality’ (like Simonson and Nowlis do). People with

high NFU have the need to show their uniqueness to their social environment. These people

strive for reactions from others to confirm their uniqueness (even if reactions are negative).

Consumer products/services are pre-eminently suitable to serve this goal. The self-concept of

someone who strives to be different will be “sustained and buoyed if he believes the good he

has purchased is recognized publicly and classified in a manner that matches and supports his

self-concept” (Grubb & Grathwohl, 1967, p. 25). Others could observe possessions or the use

of possessions/services. In that sense, choosing and using the ‘right’ products can make all the

difference. When choice options are only defined by their ‘price’ and ‘quality’, then one of

these attributes (quality) could be observed by the social environment and the other attribute

(price) not. Combined with findings from Oudenhooven and Willemsen (2009), it is expected

that people with high CNFU have a predetermined preference for ‘quality’ to ‘price’ (the

‘high-quality-focus’), something people with low CNFU do not have. The notion of a high-

quality-focus differs fundamentally from the idea’s of Simonson and Nowlis (2000).

12

Especially the absence of an obvious preference like with a compromise choice set, resulting

in a difficult decision, would be the ideal situation in which the high-quality focus provides ‘a

way out’.

Based on the above, we expect that the high-quality-focus would result in different

shares for high CNFU and low CNFU in initial choice set AB. People with high CNFU would

select high quality option B (Figure 1) more than people with low CNFU. Simonson and

Nowlis (2000) do not predict specific differences in shares between option A and option B.

Since the AB choice is the base-rate for calculating the effect size of the context effects, it

might also be part of the explanation of differences in compromise effect, found by Simonson

and Nowlis (2000). Despite the drawbacks of self-report (Dobbs, Sloan & Karpinski, 2007;

Lilienfeld & Fowler, 2005) people might even be able to (directly) report how important they

find price versus quality. If so, a conscious consideration of the importance of price and

quality could give a direct indication in favour of the high-quality-focus. Therefore:

H1: People with high CNFU prefer ‘quality’ to ‘price’, relative to people with low

CNFU.

Unfortunately, the experimental designs of Simonson and Nowlis (2000) and

Oudenhooven and Willemsen (2009) do not allow for testing the existence of the high-

quality-focus. Both these experiments used a setup comparable with choice set ABC1 (Figure

1), in which choice set AB is extended with a high quality alternative, C1. With these designs,

the high-quality-focus influences the compromise effect the same way as predicted by

Simonson and Nowlis: Option C1 is one of the two extremes and it is the option with the

highest quality. According to both theories (Simonson and Nowlis and the high-quality-

focus), option C1 takes most of its share from compromise option B (option B is not an

extreme and it does not have the highest quality). Therefore, this paper extends these

experiments by also looking at the addition of low quality option C2. When the ‘added’ option

is an extreme with the lowest quality and price (C2 in choice set ABC2), the theories predict

13

different outcomes. For high CNFU participants, Simonson and Nowlis would in this

situation, again predict that mainly the compromise option (this time option A) loses share to

option C2. However, according to the high-quality-focus people with high CNFU would

initially prefer high quality option B, but the addition of low quality option C2 is no better

alternative. Thus, consistent with ‘independence of irrelevant alternatives’ (Luce, 1959), it is

expected that the relative share of options A and B is not affected and that option C2 only

takes proportional share. Then again, people with low CNFU would show a ‘normal’

compromise effect for both choice set ABC1 and ABC2. As Drolet, Simonson and Tversky

(2000) show, the compromise effect should be independent of the location of the choice set

on the indifference curve. The effective difference between choice set ABC1 and ABC2 is a

slight shift along the indifference curve. In general, choice set ABC2 enables to see if the

compromise effect is bounded to an absolute reference point. Testing these expectations will

be done at three levels. First, to verify the main result from Simonson and Nowlis (2000) the

average compromise effect from low CNFU and high CNFU is compared. Second, for low

CNFU and high CNFU the effect sizes of both ABC1 and ABC2 are evaluated. Finally, we

focus on the difference in distribution of shares among all choice options from the

compromise choice sets.

H2a: People with high CNFU show a smaller compromise effect than people with

low CNFU.

When comparing the separate effect sizes from choice set ABC1 and ABC2, no

significant differences are expected for people with low CNFU, but for people with high

CNFU the compromise effect will be smaller in choice set ABC1 than in choice set ABC2.

This comparison enables to test the explanation by Simonson and Nowlis (2000) with the

high-quality-focus explanation.

14

H2b: People with high CNFU show a smaller compromise effect after the addition

of a high quality alternative (ABC1), than after the addition of a low quality

alternative (ABC2).

Finally, we focus on shares of the different choice options independent of the AB

choices. This enables to, explicitly, test the explanations from Simonson and Nowlis versus

the high-quality focus. The high-quality-focus predicts a different origin for the dissimilarity

in compromise effect between high CNFU and low CNFU, than Simonson and Nowlis (2000)

do. One way to (statistically) test the different explanations, is by comparing the shares of the

low quality options with the high quality options. According to Simonson and Nowlis (2000)

the shares of high and low quality options for people with high CNFU do not differ (these

people prefer extreme options independent which of the two extremes). In contrast, the high-

quality-focus predicts an asymmetrical distribution. That is, bigger shares for the high quality

option than for the low quality option. Therefore hypothesis 2c states:

H2c: According to the high-quality-focus the relative difference in choice shares

between the high and low quality options of a compromise set is larger for

high CNFU than for low CNFU, in favour of the high quality alternative.

Exploration of different versions of an attraction effect in combination with high

and low CNFU provides an additional opportunity to analyse the existence of the high-

quality-focus. The attraction effect is a more robust context effect than the compromise effect,

thereby offering a better chance to demonstrate behaviour contrary to ‘independence of

irrelevant alternatives’. Like with the compromise effect, the attraction effect shows by

promoting option A or by promoting option B. The specific setup of D1 and D2 (Figure 1)

makes it possible to compare both results. Decoy D1 promotes high quality option B, whereby

the attraction effect and the high-quality-focus complement each other. In case of ABD2,

decoy D2 promotes low quality option A, causing opposing forces between the attraction

15

effect and the high-quality-focus, predicting different outcomes for high CNFU. It is known

that in general decoys increase shares of higher-quality targets more than they increase shares

of low-quality targets (Heath & Chatterjee, 1995), but additional to that difference, the current

paper also suggests differences in target shares depending on CNFU. When a choice set

promotes the option with low price and quality, people with high CNFU face the trade-off

between a ‘high-quality-focus’ and the ‘strength’ of the context effect.

H3: For people with high CNFU the attraction effect is reduced when a decoy

targets the low quality alternative.

A fourth way the high-quality-focus would show is by means of the decision

process. For this purpose, we collect information acquisition data using process tracing.

Choosing from a compromise choice set requires complex cognitive processing, ‘all choice

options are equally attractive’ (Yoon & Simonson, 2008). According to the theory of the

high-quality-focus, one way to avoid this effort is to use a shortcut. If people use the heuristic

of preferring ‘quality’ to ‘price’, then this would simplify their decision. It would decrease the

amount of attention (viewing time and frequency) for some of the information about the

choice options. When studying why people with high CNFU show a smaller compromise

effect, one has to focus on why people with high CNFU do not choose the compromise

option. Again, Simonson and Nowlis (2000) predict that the decision processes of high CNFU

people choosing any of the extreme options does not differ; since both groups would use the

same reasoning. However, the high-quality-focus predicts an interaction effect of CNFU and

the choice people make on the amount of attention for the describing information. The high-

quality-focus is an internalised shortcut/ a standard decision rule: one only has to find the

option with the best quality. A quick scan should therefore be enough to make a decision,

while in general choosing the compromise option requires comparing all options, a complex

and time consuming cognitive process. Consequently, an interaction effect between CNFU

and people choosing the low quality option versus people choosing the high quality option is

16

expected. Relatively large amount of attention is expected for people with high CNFU,

choosing the low quality alternative and less attention for those choosing the high quality

alternative. The opposite is expected for low CNFU.

H4: People with high CNFU, choosing the high quality option, pay less attention

to attribute information than those choosing the low quality option, relative to

people with low CNFU.

An important application of hypothesis 4 would be the possibility to check what

‘kind’ of person visits a web shop, based on his clicking behaviour. One could alter the virtual

shopping environment, adapting it to suit each particular visitor.

17

3. Method

3.1 Participants

147 Participants took part in the experiment (77 men and 70 women, age ranging

from 20 till 60). Of those, 145 were included in the analyses. Two participants were left out,

since they did not attend to all the information necessary to base a decision on, or because

they finished assignments unrealistically fast. The 145 participants were split into a group

with low CNFU (n=70) and a group with high CNHU (n=75), based on a median split at a

CNFU-value of 34 (participants with a CNFU-value of 33 are part of the group with low

CNFU and a value of 34 is add to the high CNFU group). The amount of CNFU was

measured with a Dutch version of the CNFU-S scale from Ruvio et al. (2008). Translation

and validation the CNFU-S scale (Cronbach’s α = 0,747) is explained in more detail in

appendix I & II. The experiment took about 10 minutes to complete, and participants were

rewarded €1,50.

3.2 Stimuli, design, and procedure

To construct suitable stimuli (choice options A, B, C1, C2, D1 and D2, for 5 different

product categories) several pilot studies were conducted (Appendix III). This resulted in the

product categories and choice options described in Table 1.

18

Choice options:

Product category: Attribute: A B C1 C2 D1 D2

TFT wide screen (product cat.1)

Price € 150,- € 183,- € 216,- € 117,- € 193,- € 160,- Size (inch) 22,0 24,0 26,0 20,0 23,4 21,4

Mobile internet (product cat.2)

Price (per month) € 31,- € 37,- € 43,- € 25,- € 39,- € 33,- Download speed (Mb/sec) 1,7 2,3 2,9 1,1 2,1 1,5

Projector (product cat.3)

Price € 950,- € 1070,- € 1190,- € 830,- € 1110,- € 990,- Image quality (1-10) 7,0 8,0 9,0 6,0 7,7 6,7

Folding bike (product cat.4)

Price € 152,- € 200,- € 248,- € 104,- € 217,- € 169,- Weight (kg) 12,0 9,0 6,0 15,0 10,1 13,1

Food processor (product cat.5)

Price € 210,- € 240,- € 270,- € 180,- € 250,- € 220,- Quality (1-10) 7,0 8,0 9,0 6,0 7,7 6,7

Table 1. Specified product categories and choice options.

The experiment consisted of nine tasks that were presented in an online web-

environment, designed with MouselabWEB (Willemsen & Johnson, 2008) (Appendix IV).

MouselabWEB enables to monitor information acquisition processes of the participants. It

indicates which information people use to make a decision, by registering how long people

pay attention to that information, how many times they attend to the information and it shows

the transitions between the different types of information. To get acquainted with a task

designed with MouselabWEB, participants were first presented with a practice task. This task

showed that the information about price and quality from the different choice options is

masked behind ‘boxes’. When participants move the cursor of the mouse over these boxes,

they ‘open’ and the information is displayed (see Figure 3). Only data from boxes, opened for

more that 150 milliseconds is used for the analyses. In less than 150 milliseconds one would

not be able to read the information. Screenshots of all pages of the experiment are presented

in appendix IV.

19

Figure 3. Screenshot of the practice task.

The setup of the next five decision tasks was the same as in the practice task. In five

different choice sets (AB, ABC1, ABC2, ABD1 and ABD2; Figure 1), divided over five

product categories (TFT wide screen, mobile internet for laptop, projector, folding bike and

food processor), participants were asked to choose their favourite option. That is, participants

made five choices, each in a different choice set, and for a different product category. Choice

set and product category were partially counterbalanced using a ‘Latin squares’ design with

twenty-five conditions for ‘between subject research’ (see Appendix V for a detailed

overview). Presentation order of the attributes and the options in the display was randomized.

The choice assignments were followed by two pages measuring the price-partworths

(P-partworths) and the quality-partworths (Q-partworths) of the three choice options. Each

participant got the product categories presented in the same order as in the choice

assignments. We did not analyse these partworths, as many subjects indicated in the comment

section that they did not understand the parthworth questions.

Next, participants were asked to report on a 5-point scale, the relative importance of

price versus quality of each product category. Experience/expertise with the product

categories was measured on a 5-point scale, ranging from ‘no experience at all’ to ‘very

experienced’.

20

4. Results

Since part of this paper has an explorative character, some findings are beyond the

expectations as described in section 2.4. Therefore, some results are explained with further

elaboration.

Testing hypothesis 1: People with high CNFU prefer ‘quality’ to ‘price’, relative to

people with low CNFU.

To verify hypothesis 1 three different tests are performed. First, the importance

measure for ‘price’ versus ‘quality’ is compared between low CNFU and high CNFU.

Second, we looked at differences between low CNFU and high CNFU in attention for the

attributes ‘price’ and ‘quality’ when choosing from compromise choice sets. Finally, shares of

choice set AB from low CNFU are compared with high CNFU.

With a mean importance for low CNFU of 3,24 (STD = 0,61) and for high CNFU of

3,31 (STD = 0,70) people with low and high CNFU both prefer ‘quality’ a bit more than

‘price’ (scale ranging from 1 till 5). However, repeated measures ANOVA revealed other

interesting results, best interpreted with a graphical display:

21

low CNFU high CNFU

Figure 4. Importance of price versus quality per product category.

As Figure 4 shows, only for category ‘TFT screens’ do people with high CNFU

prefer ‘quality’ more than people with low CNFU. CNFU does not have a significant

between-subjects-effect on ‘importance’: F(1, 143) = 0,47, p > 0,05, but there is a significant

main effect of ‘product category’, F(4, 572) = 15,63, p < 0,00 and an interaction of ‘product

category’ with CNFU, F(4, 572) = 2,66, p < 0,05. In line with Figure 4, the parameter

estimate is significant for CNFU*TFT screen t (143) = 3,22, p = 0,002. This partially (for

TFT widescreens) supports hypothesis 1. The other product categories do not trigger the need

to be unique enough (the most important aspect of CNFU). This should be taken into account

as a drawback for the rest of the results and therefore this topic will be discussed in more

detail in the discussion section of this thesis.

Second, and more in favour of hypothesis 1, low CNFU and high CNFU differ in

the amount of attention for the attributes ‘price’ and ‘quality’. On average people attend more

22

to the attribute ‘price’ than ‘quality’. Nevertheless, the high-quality-focus predicts that for

people with high CNFU this difference would be reduced. Especially when people deal with a

compromise choice set, decision-making takes a lot of cognitive effort. It is expected that

those with high CNFU, avoid the effort by using the high-quality-focus as a shortcut.

Consequently, one compares the information about quality to detect the option with the

highest quality. To be able to test whether the interaction effect is significant, a repeated

measures ANOVA is applied with a 2*2*3 [2 choice sets (ABC1 and ABC2), 2 attributes

(price and quality), 3 options (low, medium and high quality/price)] within factor design. The

dependent variables are ‘time’2 and ‘frequency’ represent the ‘attention for the information’.

Combining the data from choice set ABC1 and ABC2, indeed shows the predicted interaction

effect (Figure 5). Unfortunately, for the dependent variable ‘time’ the small differences are

not significant and for ‘frequency’ they are only marginal significant. Results for the

interaction of attribute*CNFU are respectively Ftime (1, 136) = 1,017, p > 0,1 and Ffrequency (1,

136) = 3,485, p < 0,1.

2 One of the assumptions for this analysis is a normally distributed dependent variable. The variable

‘time’ is highly positively skewed (skewness ranging from 1,7 till 5,0) and therefore a log

transformation is applied: log_time = ln (time+500 ms). This new measure is normally distributed

(Shapiro-Wilk tests have significance values larger than 0,05) on all cells for both choice set ABC1 and

ABC2.

23

Average time Average frequency

low CNFU high CNFU

low CNFU high CNFU

Figure 5. Average time and frequency for boxes containing the attribute information ‘price’ and ‘quality’.

The third way to (indirectly) verify the high-quality focus is by looking at the

relative shares of choice set AB. The AB-distribution, forming the base rate for the effect size

calculations, should differ for high CNFU and low CNFU. The high-quality-focus states that

high CNFU people prefer high quality options more than low CNFU people do. Indeed,

people with high CNFU choose option B 60% of the times whereas people with low CNFU

choose option B 53% of the time (see Figure 6). A logistic regression shows however that this

difference is not significant. The non-significant residual chi-square statistic of χ2(1) = 0,752,

p = 0,386, indicates that the addition of CNFU does not increase the power of the model to

predict if people choose option A or option B.

All-in-all, the qualitative data seems to be in favour of hypothesis 1. However, the

tests do not show enough statistical support to confirm it.

To verify hypothesis 2a till 3 it is important to keep the experimental design as

shown in Figure 1 in mind. In choice sets ABC1 and ABD1 option B is the target option, but

ABC2 and ABD2 promote option A as the target. In addition, the options representing high

quality/high price and low quality/low price vary per choice set. In choice set ABC1 for

example, option A represents the option with the lowest quality and the lowest price. In

24

choice set ABC2 the low quality/ low price –option is option C1. In general, the choice options

are referred to relative to the other options in the choice set:

Low quality option = LQ

High quality option = HQ

Target option = T

Decoy option = D

Testing hypothesis 2a: People with high CNFU show a smaller compromise effect

than people with low CNFU.

In conformation of hypothesis 2a, frequency distributions of the data indicate a

replication of findings from Simonson and Nowlis (2000). Results from the choice sets are

visualised with Figure 6.

25

Choice set AB

low CNFU high CNFU

low quality high quality

choice

Figure 6. Shares of respectively choice sets AB, ABC1 and ABC2 .

For both compromise choice sets ABC1 and ABC2 the increase in share of the target

option seems larger for low CNFU than for high CNFU. To calculate the effect size we

employ a method by Mourali et al (2007). This method looks at changes in shares of the

target option (option B in choice set ABC1 and A in choice set ABC2) relative to the AB

choice.

low quality target high quality

choice

low quality target high quality

choice

Choice set ABC2 Choice set ABC1

low CNFU low CNFU high CNFU high CNFU

26

Based on Mourali et al. (2007):

( ) ( )( ) ( ) %100

others target;-nonothers target;

others target;targetnontarget; ×

+=−

PPPPC and

. ( ) ( )targetnontarget;targetnontarget;target −− −=Δ PPP C

Where effect size refers to the change in share of the target option relative

to the non-target option as a result of adding option C. For choice set ABC1

represents the increase in shares of option B, while for choice set ABC2 it represents the

increase in option A. Computations in Table 2 and 3 are based on the combined sample of all

five product categories.

targetPΔ

targetPΔ

Low CNFU High CNFU

Shares (%) Choice set ABC1 Choice set ABC2 Choice set ABC1 Choice set ABC2

P(LQ; HQ) 47,1 47,1 40,0 40,0 P(LQ; HQ) 52,9 52,9 60,0 60,0 P(LQ; T,HQ) 29,4 23,5 31,9 27,0 P(T; LQ,HQ) 39,7 39,7 33,3 29,7 P(HQ; LQ,T) 30,9 36,8 34,7 43,2 PC(target; non-target) 57,5 51,9 51,1 40,7

targetPΔ 4,7 4,8 -8,9 0,7

Average targetPΔ 4,8 -4,1 Table 2. Compromise effects for high and low CNFU.

Table 2 shows a smaller average effect size for low CNFU (average low CNFU =

4,8) than high CNFU (average high CNFU = -4,1). The negative effect sizes for choice set

ABC1 (‘ ’ and ‘Average ’), found for people with high CNFU, indicate a

decrease in share of option B relative to option A. These results confirm hypothesis 2a.

targetPΔ

targetPΔ

targetPΔtargetPΔ

27

Testing hypothesis 2b: People with high CNFU show a smaller compromise effect

after the addition of a high quality alternative (ABC1), than after the addition of a

low quality alternative (ABC2).

The fact that choice set ABC1 offers an alternative of even better quality than the

original AB set, caused people with high CNFU to ‘move’ from option B to option C1 (34,7%

of high CNFU selected option C1). As Table 2 shows, this decrease in relative shares of the

compromise option causes the negative effect size of targetPΔ = -8,9. Compared with a

compromise effect of 0,7 for choice set ABC2, this confirms hypothesis 2b. As expected

people with low CNFU show hardly any difference in effect size: targetPΔ ABC1 = 4,7 and

ABC2 = 4,8. The different choice sets hardly influence the effect size ( ) for low

CNFU, but do influence the effect size for high CNFU.

targetPΔ targetPΔ

Testing hypothesis 2c: According to the high-quality-focus the relative difference in

choice shares between the high and low quality options of a compromise set is

larger for high CNFU than for low CNFU, in favour of the high quality alternative.

A short recap: In general, people with low CNFU show larger compromise effects

than people with high CNFU. The fact that high CNFU does not show a compromise effect

with choice set ABC2 and a negative effect with choice set ABC1 was a first indication in

favour of the high-quality-focus. Especially because, unlike high CNFU, the effect size of

people with low CNFU do not differs between ABC1 and ABC2. Choice set ABC2 does not

offer a better alternative for high CNFU, causing these people to preserve the AB-ratio. This

results in only a tiny effect size of 0,7 (Table 2). For people with low CNFU the compromise

effect seems to remain steady between the two scenarios.

However, due to the experimental design, one should be careful interpreting the

effect sizes. Calculating the compromise effect can be done with a between subject design or

a within subject design, as long as one compares choices from the same product category. The

setup of this experiment is a combination of within subject design and between subject design

28

(mixed model/ Latin squares design). Participants chose from an AB-choice-set in one

product category, while choosing from an ABC-choice-set in another category3 (as outlined

in appendix V). Therefore, hypothesis 2c looks at shares of all separate choice options,

independent of the AB choice.

To test the presumption that high CNFU prefer the high quality option of a

compromise set, shares of the low and high quality options are compared (only looking at the

compromise choice sets and not the initial AB choice). Remember that for high CNFU,

Simonson and Nowlis (2000) expect equal shares for both extreme options, while the high-

quality-focus predicts larger shares for the high quality option. Hypothesis 2c compares the

ratio between those extreme options between people with low CNFU and people with high

CNFU. If shares of the middle compromise option are left out, then for choice set ABC1,

51,2% of low CNFU choose the high quality option relative to the ones choosing the low

quality option, while for high CNFU this is 52,1%. For choice set ABC2, 61,0% of low CNFU

chooses the high quality option and 61,5 % of high CNFU. These obvious similarities

between low CNFU and high CNFU choices reject hypothesis 2c.

Testing hypothesis 3: For people with high CNFU the attraction effect is reduced

when a decoy targets the low quality alternative.

The typical asymmetric distribution of an attraction choice set helps identifying the

existence of a high-quality-focus. It is expected that shares of the target relative to the non-

target differ between high and low CNFU for choice set ABD2, but not for ABD1. With decoy

D1 promoting the high quality option, the attraction effect and the high-quality-focus both

3 Because of this mixed design, we also performed a multilevel logistic analysis to test the significance

of the shifts in target choice, taking into account within subject observations. The multilevel model

directionally supported the main findings in Table 2, but confirmed that the differences in choice shares

were not significant.

29

favour the target. Option D2 promotes the low quality option causing for high CNFU

conflicting forces between the high quality non-target and the promoted target (section 2.4).

Before we test hypothesis 3, first an overview of the attraction choice sets. The

results of the attraction choice sets are reported in the same configuration as with the

compromise choice sets (Table 3). The effect sizes (average targetPΔ low CNFU = 14,0, average

high CNFU = 12,2) are calculated the same way as with the ‘compromise choice sets’.

The effect sizes ( , shares of options A and B relative to the base rate) do not differ

considerably between low CNFU and high CNFU. However, the rest of the outcomes from

the ‘attraction choice sets’ (choice set ABD1 and ABD2) reveal interesting results. The

attraction effect is considered a much stronger context effect, something that shows clearly

for choice set ABD1. When decoy D1 promotes the high quality/ high price -option B, low

CNFU and high CNFU both reveal a typical attraction effect, without considerable

differences between low CNFU and high CNFU (Figure 7).

targetPΔ

targetPΔ

Figure 7. Shares of respectively choice sets ABD1 and ABD2 .

Choice set ABD1 Choice set ABD2

low CNFU high CNFU

low CNFU high CNFU

low quality target decoy

choice

decoy target high quality

choice

30

Low CNFU High CNFU

Shares (%) Choice set ABD1 Choice set ABD2 Choice set ABD1 Choice set ABD2

P(LQ; HQ) 47,1 47,1 40,0 40,0 P(HQ; LQ) 52,9 52,9 60,0 60,0 P(LQ; HQ,D) 26,5 53,7 22,2 44,6 P(HQ; LQ,D) 73,5 44,8 77,8 51,4 P(D; LQ,HQ) 0,0 1,5 0,0 4,1 PD(target; non-target) 73,5 54,5 77,8 46,5

targetPΔ 20,6 7,4 17,8 6,5

Average targetPΔ 14,0 12,2 Table 3. Attraction effects for high and low CNFU.

Choice set ABD2, demonstrates different results for high and low CNFU. Now that

decoy D2 promotes low quality/ low price –option A, low CNFU shows the attraction effect as

expected, but people with high CNFU still prefer option B over option A, despite the fact that

decoy D2 promotes option A (PD(target; non-target) < 50%). Like compromise choice set ABC2,

it seems that regardless of the ‘strong’ decoy, most people with high CNFU still choose high

quality/ high price –option B (even though the attraction effect is a much stronger context

effect than the compromise effect).

To test hypothesis 3 one compares the relative shares of options A and B from

choice set ABD2. It is expected that these shares differ between low CNFU and high CNFU,

such that with high CNFU shares of the target are reduced. Like with hypothesis 2c these tests

are again independent of the AB choice. The differences in shares of the target option

(PD(target; non-target)) between high CNFU and low CNFU with choice set ABD2 are in line

with the predictions. 54,5% Of low CNFU choose the target option relative to the ones

choosing the non-target, while for high CNFU this is 46,5%. Significance of these differences

is tested with binary logistic regression. It appears that CNFU is no significant predictor for

‘choice’ in choice set ABD2: χ2ABD2(1)= 0,890, p= 0,220. Despite the fact that the data shows

an effect into the right direction, the effect is too small, thereby rejecting hypothesis 3.

31

Testing hypothesis 4: People with high CNFU, choosing the high quality option, pay

less attention to attribute information than those choosing the low quality option,

relative to people with low CNFU.

Hypothesis 4 focuses on the information acquisition process when choosing from a

compromise choice set. Simonson and Nowlis (2000) predict that people with high CNFU

pay equal amounts of attention to the extreme options (the non-compromise options).

However, according to the high-quality-focus people with high CNFU choosing the high

quality option used the high-quality-focus as a shortcut to resolve the difficult decision. This

would show by relatively less attention to the attribute information. People choosing the low

quality options would pay more attention (they do not use the shortcut) than people choosing

the high quality options of high CNFU relative to low CNFU. The expected interaction of

‘attention’ between CNFU and people choosing low quality alternatives versus people

choosing high quality alternatives (‘choice’) is tested for both choice set ABC1 and ABC2.

The variable ‘attention’ for choice information is again a combination of ‘time’ (average

duration one looks at the choice information) and ‘frequency’ (average amount of times one

views the choice information). Hypothesis 4 is tested with four separate analyses; comparing

‘time’ and ‘frequency’ between people choosing the low and those choosing the high quality

alternatives for both choice set ABC1 and ABC2.

To accomplish this we applied repeated measures ANOVA’s with a 2*3 [2

attributes (price and quality) and 3 options (low, medium and high quality/price)] within

subjects design. The between-subject factors included in the model are high vs. low CNFU

and people choosing the low quality option versus people choosing the high quality option.

Figure 8 and Figure 9 clarify the results with graphical representations for respectively time

and frequency. Figure 8 shows a decrease in ‘time’ for high CNFU towards the participants

that choose the high quality option. low CNFU seems to show the opposite:

32

Choice set ABC1 Choice set ABC2

low CNFU high CNFU

low CNFU high CNFU

People choosing LQ

People choosing HQ

People choosing LQ

People choosing HQ

Figure 8. Average duration the boxes are opened of respectively choice sets ABC1 and ABC2 .

First, the interactions for ‘time’, as illustrated by Figure 8, are tested. The repeated

measures ANOVA indicates that the interaction between CNFU and ‘choice’ is not

significant for choice set ABC1: Ftime (1, 85) = 1,336, p > 0,1. Results from choice set ABC2

are more in favour of hypothesis 4. The expected between-subjects interaction of

CNFU*choice: Ftime (1, 85) = 6,300, p < 0,05.

The non-significant result of the dependent variable ‘time’ for choice set ABC1

seems to be no different for the variable ‘frequency’. As the first image in Figure 9 illustrates,

there is no interaction effect of ‘frequency’ for choice set ABC1, CNFU*choice: Ffrequency (1,

85) = 0,076, p > 0,1. Despite the promising shape of the second image, for choice set ABC2

the interaction effect is not significant either: Ffrequency (1, 85) = 1,936, p > 0,1:

33

Choice set ABC1 Choice set ABC2

low CNFU high CNFU

low CNFU high CNFU

People choosing LQ

People choosing HQ

People choosing LQ

People choosing HQ

Figure 9. Average frequency the boxes are opened of respectively choice sets ABC1 and ABC2.

Summarised, most of the graphical representations seem to support hypothesis 4.

Unfortunately, only with choice set ABC2 the dependent variable ‘time’ is significantly

influenced by CNFU and the choices people make. This only partially confirms hypothesis 4.

In general, one has to conclude that the ‘high-quality-focus’ does not receive

substantial statistical support. If the focus/ heuristic exist at all, then the experimental setup

and the number of observations are not able to show it.

On the other hand, some general results can be obtained from the above. First, as

expected the attraction effect seems much stronger than the compromise effect. Second, the

results from Simonson and Nowlis (2000) are replicated, meaning that the average effect size

of the compromise effect (Average targetPΔ ) is smaller for high CNFU than for low CNFU. It

should be noted however, that the influence of CNFU on the compromise effect is only

marginal. Third, despite the fact that the attraction effect is such a robust and strong context

effect, people with high CNFU still favour the high quality option when the target is a low

price/ low quality-option.

34

Discussion

The main goal of this research was exploration of how CNFU moderates the context

effects in consumer decision-making. As a possible cause, literature on individual differences

and need for uniqueness (Snyder & Fromkin, 1977; Belk, 1988; Tian et al., 2001) and earlier

research on this topic (Oudenhooven & Willemsen, 2009) showed a predetermined preference

of ‘quality’ to ‘price’ of people with high CNFU (the high-quality-focus). With an online

experiment, we measured people’s preferences and information acquisition processes to be

able to test the existence of the high-quality focus.

Due to the explorative character of this paper, it accomplished to gain more insight

into the processes of choosing from compromise and attraction choice sets and moderating

variables influencing these choices. Unfortunately, results do not confirm the existence of the

‘high-quality-focus’. One could argue that this failure is due to certain properties in the

experimental design, like the selection of ‘unpopular’ product categories or the relatively

small amount of participants given the complex within subjects Latin square design.

When testing hypothesis 1 it became clear that of the five product categories, only

the TFT screens showed the expected pattern. That is, people with low CNFU were expected

to prefer ‘price’ to ‘quality’, relative to people with high CNFU. As a post hoc ‘explanation’

the high-quality-focus might only influence the decision of high CNFU when the product

category and quality attribute enable people to display their uniqueness. For that reason, we

take a closer look at the theory about ‘need for uniqueness’ and the expertise measure (the

knowledge people have about each product category). From the quality measures of the five

product categories, only the one from TFT screens is obviously visible (size of the screen).

Additionally, TFT screens are part of a general hype in the world of electronics. By the end of

2009 it is expected that 83% of the Dutch households has a TFT screen, causing record sales

this year (iMMovator, 2009). The ‘expertise’ measure illustrates this hype, since participants

are more familiar with TFT screens than with any of the other product categories. The

35

repeated measures ANOVA shows a main effect of product category: (F(4, 143) = 28,26, p <

0,000), with the largest measure of expertise for TFT screens (average expertise measure of

2,92 on a scale from 1 till 5 and STD = 1,32). One can conclude that the hype, causing this

product and its attributes to be well known, makes TFT widescreens perfect products to

display to the social environment. Therefore, the high-quality-focus might only influence this

product category.

Other drawbacks of this research are the amount of experimental conditions and the

mixed design. With five different product categories five choice sets (twenty-five conditions)

and one hundred forty-five participants, the power of the analyses is relatively low. Also, the

Latin-square design did not allow for perfect between subjects testing. Additionally, when

testing why people did NOT choose a compromise option, only those choosing the non-target

options were analysed. This reduction in the amount of participants decreased the power of

certain tests even more.

Despite these points of discussion, it is more reasonable to accept the absence of the

high-quality-focus for the simple reason that it did not receive enough statistical support. As

outlined in the introduction, there were enough theoretical and practical reasons to carry out

this research. Nevertheless, despite some disappointments with overall conclusions, the

phrase ‘also no result is some result’ provides some cold comfort.

Somewhat different from the general line of this paper, but still important to note,

are the overall differences in shares between choice set ABC1 and ABC2 and between ABD1

and ABD2. This adds limitations to research from Drolet et al. (2000). They claim that the

absolute location of a choice set in the ‘attribute space’ (eg. ABC1 versus ABC2) should not

affect the compromise effect (i.e. context effects are ‘relative’). This would mean that a

context effect is unaffected as long as the relative location of the choice options remains the

same (eg. choice set ABC, A’B’C’ or A”B”C”, Figure 10)

36

Figure 10. Location of a choice set in attribute space.

Unlike findings from Drolet et al. (2000), Heath and Chatterjee (1995) proved, for

the attraction effect, that the absolute location of a choice set does influences the effect size.

Comparison of the frequency distributions of choice sets ABD1 and ABD2 confirms Heath

and Chatterjee’s findings, but the experimental design of the current research also allowed for

testing the same claim for the compromise effect (comparison between ABC1 and ABC2).

Specifically, people with high CNFU show variation in compromise effect when the choice

set as a whole moves along the indifference curve. Apparently, people with low CNFU meet

the expectations from Drolet et al. (2000), while choices of people with high CNFU depend

on the absolute attribute values. This demonstrates the dependence on the absolute location

for the compromise effect as well.

Finally, the use of CNFU for adaptive websites is not very promising. This paper is

not able to show enough differences in search behaviour between low CNFU and high CNFU.

This makes automatic detection of CNFU difficult. In addition, choices people make do not

differ enough between people with low CNFU and people with high CNFU. Therefore,

adaptation of a website to the amount of CNFU of a visitor would probably be ineffective.

37

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42

Appendix I: CNFU scale translation and validation

To create a reliable measure of need for uniqueness, the CNFU-S scale (Ruvio et al.,

2008) is translated and validated. Using ‘back-translation’ (Brislin, 1970), all 12 items from

the CNFU-S scale (Ruvio et al., 2008) were translated from English into Dutch. Five

colleagues translated, independently of each other, the items into Dutch and another group of

five converted these translations back into English again. The new CNFU-S survey only

included Dutch translations, of which the gist of the (back) translation was comparable to the

original. In two cases, parts of different translations were combined to create the best Dutch

translation.

To be able to test the reliability and the consistency of the Dutch version two

surveys were conducted. In an online internet survey, set up using Virtual Lab (Willemsen &

van Bragt, 2006), participants evaluated the items one-by-one. For each item participants

were asked to respond on a five-point Likert scale (strongly agree to strongly disagree). The

factor structure was checked with ‘principal component analyses’ and compared with the

factor structure of the original survey from Ruvio et al. (2008). The expected correlation

between the items allowed for ‘oblique rotation’, since the dimensions (‘creative choices’,

‘unpopular choices’ and ‘avoidance of similarity’) all refer to the same concept; ‘consumer

need for uniqueness’. Five months later the same participants again filled in the same survey

to see if the CNFU-S scale is robust enough to base long-term conclusions on. Different from

the first survey, wording of four items was reversed to avoid response bias. Participation was

rewarded with €0,40 per participant, per survey.

Two hundred and four participants (85 men and 119 women, age ranging from 19

till 46) responded to twelve items of the CNFU-S survey, on a five-point Likert scale.

Appendix II shows the Dutch version of the CNFU-S survey (at this stage items 1, 6, 7 and 9

were not yet phrased negatively). Principal component analysis with oblique rotation resulted

43

in the same three factors that Ruvio et al. (2008) found. Factor loadings ranged from 0,562 till

0,867 and the internal consistency (Cronbach’s α = 0,801) proved to be sufficient (Kline,

1999).

Five months later, a majority of the initial participants responded to an adapted

version of the CNFU-S survey, designed to test the robustness and consistency of the scale. In

total 174 people (90 men and 84 women, age ranging from 20 till 60) participated in the

second survey (120 participated in both surveys, for 54 this was the first time). These 120

participants were used to check the robustness of the scale. This time four of the items (items

1, 6, 7 and 9) were phrased negatively to check if participants read the instructions and gave

ample consideration to each item. Three of the four negatively phrased items formed an extra

factor, indicating that these minor changes did have some influence on the interpretation of

the items. Still factor loadings ranged from 0,507 till 0,887, with Cronbach’s α = 0,747.

Because one should be cautious interpreting only the internal consistencies (Cronbach’s α)

(Cortina, 1993), an adequate test-retest correlation increases reliability. Results from the first

CNFU-S survey show an average CNFU of 32,09 (on a scale from 12 to 60) with a standard

deviation of 6,48. The second survey resulted in an average CNFU of 33,35 with a standard

deviation of 5,77. The two surveys showed a significant test-retest relationship, r = 0,59, p <

0,001 (n = 120). Overall, these results show that the Dutch version of the CNFU-S scale is a

reliable and consistent measuring tool.

The 174 participants that filled in the second survey (average CNFU = 33,35,

standard deviation = 5,97) formed the sample from which participants for the main

experiment were recruited. The median of 34 served as the split value, dividing the sample in

high CNFU and low CNFU. As can be seen in Figure 10, the frequency distribution slightly

forms a bimodal shape, splitting low CNFU and high CNFU around a CNFU-value of about

33.

44

Median

Figure 10. Frequency distribution of total CNFU-scores. Figure 11. Q-Q plot of total CNFU-scores.

Despite the shape of the distribution, the Q-Q plot is acceptable (Figure 11) and the

test for normality (Shapiro-Wilk, n < 2000) proved adequate (W = 0,99, p = 0,205). That is,

the CNFU-data is normally distributed.

45

Appendix II: Translated CNFU-S survey

Participants were introduced with the following (Dutch) text:

Welkom!

Dit onderzoek bestaat uit 12 stellingen. We zijn geïnteresseerd in hoeverre elk van deze

stellingen bij jou persoonlijk past.

Het zou zo kunnen zijn dat dit onderzoek je bekend voorkomt. Toch zijn er verschillen met

een voorgaand onderzoek, dus lees de stellingen goed door.

Geef aan in hoeverre je het eens bent met elke stelling, waarbij je gebruik maakt van een

schaal waarbij 1 'helemaal oneens' betekent, 5 'helemaal eens' betekent, en 2, 3 en 4 zijn

beoordelingen daartussenin. Klik onder elke stelling een getal aan in de vakjes op de volgende

schaal:

1. Helemaal oneens

2. Oneens

3. Eens noch oneens

4. Eens

5. Helemaal eens

Er zijn geen ‘goede’ of ‘foute’ antwoorden, dus selecteer bij elke stelling het getal dat zo goed

mogelijk bij je past. Neem de tijd en denk goed na over elk antwoord.

Succes.

46

Translated and restructured questions:

1. Vaak combineer ik dingen op een zodanige manier, dat ik een uniek imago creëer dat

niet kan worden nagedaan.

2. Ik ben niet iemand die het leuk vind om origineel te zijn, door een interessantere

versie van standaard/doorsnee producten te zoeken. (negative phrased)

3. Ik ben actief bezig met het ontwikkelen van mijn unieke persoonlijkheid, door

speciale producten of merken te kopen.

4. Een oog hebben voor producten die interessant en ongebruikelijk zijn, helpt me in het

creëren van een onderscheidend imago.

5. Als het gaat om producten die ik koop en de situaties waarin ik ze gebruik, dan heb ik

ongewone gebruiken en regels.

6. Ik schend de ongeschreven regels van mijn sociale groep niet, als het gaat om wat ik

koop of bezit. (negative phrased)

7. Ik ben zelden tegen de ongeschreven regels van mijn sociale groep ingegaan, als het

gaat om wanneer en hoe bepaalde producten gebruikt zouden moeten worden.

(negative phrased)

8. Ik houd ervan om de heersende smaak van mensen die ik ken uit te dagen/ te

prikkelen, door het kopen van dingen die zij niet zouden accepteren.

9. Wanneer een product dat ik bezit populair wordt bij de rest van de bevolking, dan ga

ik het niet minder gebruiken. (negative phrased)

10. Ik probeer vaak producten of merken te vermijden waarvan ik weet dat een groot deel

van de bevolking ze koopt.

11. Ik heb voor mezelf de regel dat ik niet van producten of merken houd die door

iedereen gekocht worden.

12. Hoe gangbaarder een product of merk is onder de bevolking, des te minder

geïnteresseerd ik ben in het kopen ervan.

47

Appendix III: Pilots

The final experiment focused on compromise and attraction effects, the process by

which people construct their preferences and potential moderating variables. To find suitable

product categories for this experiment, a pen-and-paper pilot study tested several stimuli. A

category is ‘suitable’, when shares of different choice options show an indifferent

distribution, that is, shares are equally large. Compromise and attraction effects can only

occur as a way to resolve the difficult trade-off between equally attractive options.

Additionally, indeterminate distributions indicate that other factors influence the

attractiveness of choice options.

Participants for the pilot study were students from Eindhoven University of

Technology, recruited in different canteens on the university campus. Twenty participants

matched (Luce, Payne & Bettman, 2000; Willemsen & Keren, 2003) products in twelve

different product categories. Those products were described by their ‘price’ and a measure of

quality. Familiarity with the attribute ‘quality’ has a diminishing influence on the compromise

effect (Sheng et al.,2005). Therefore, for some product categories the attribute ‘quality’ was

represented with an abstract property (like ‘ease of use’/ ‘usability’) ranging from 1 to 10. In

general, the attributes matched the “range of typical attribute values offered in the

marketplace” (Assar & Chakravarti, 1984) to ensure a realistic experiment. Participants

matched two products/services within each category. To avoid bias from upwards versus

downwards matching (Willemsen & Keren, 2003) half the participants matched the prices of

the high quality options and the other half matched the prices of the low quality options.

Outcomes were averaged and for each category, an indifference curve was created. Next, per

product category, the two matched products were presented to another thirty students in the

form of two choice options. Participants were asked to indicate how much they preferred one

option to the other. Participants indicated their preferences by placing a cross on a line

48

between the two options (option A: relatively low quality and low price and option B:

relatively high quality and high price). A cross placed near A, indicated that option A was

preferred over B, vice versa and all options in between. After all pilots were filled in, the

answers were converted to values from 1 to 7. Frequency distributions of these values

determined whether a product category was ‘suitable’ or not.

The main goal of the pilot studies was the construction of the stimuli for the actual

experiment. The search for ‘suitable’ product categories resulted in five different categories:

TFT wide screens, contracts for mobile internet (for laptops), projectors, folding bikes and

food processors. For these categories, both choice options received about equal shares.

Stimuli construction:

Relative to the indifference curve of each product category, five choice options (A,

B, C1, C2, D1 and D2, in Figure 1) were created. It is important to note that the location of

decoys D1 and D2, relative to options A and B, combines range and frequency strategies

(Huber et al., 1982). These locations diminish the strength of the attraction effect, compared

with a range strategy (choice set ABX, Figure 1) or a frequency strategy (choice set ABY,

Figure 1), however, this is necessary to viably compare ABD1 and ABD2. A range strategy

would offer an alternative for the same price as option A, but with lower quality. Extending

the range promoting option B, would mean adding an alternative with the same quality as

option B, but for a higher price. The opposite would be the case with a frequency strategy.

Either a range or a frequency strategy would promote one option by comparing the quality,

but the other option by comparing the price (and vice versa). At the current locations of D1

and D2, both decoys promote an original options in the same way; the target options are

always superior on both attributes. Only this way one can compare results from choice set

ABD1 with choice set ABD2. The decoys are positioned on a line with transposed (negative)

slope compared to the indifference curve, starting from the target option. This resulted in the

product categories and choice options described in Table 1 (Section 3.2).

49

Appendix IV: Online MouselabWEB experiment

Example of an experiment of participants with modulus number 1 (Appendix V):

50

51

52

53

Appendix V: Experimental design

54

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prod

uct c

at.1

(11.

php)

AB

C2

prod

uct c

at.2

(12.

php)

16

AB

C2

prod

uct c

at.1

(16.

php)

AB

C1

prod

uct c

at.4

(19.

php)

AB

D2

prod

uct c

at.2

(17.

php)

AB

pr

oduc

t cat

.3 (1

8.ph

p)

ABD

1 pr

oduc

t cat

.5 (2

0.ph

p)

17

A

BD

2 pr

oduc

t cat

.2 (1

7.ph

p)

AB

prod

uct c

at.3

(18.

php)

AB

D1

prod

uct c

at.5

(20.

php)

AB

C2

prod

uct c

at.1

(16.

php)

AB

C1

prod

uct c

at.4

(19.

php)

18

AB

prod

uct c

at.3

(18.

php)

AB

D1

prod

uct c

at.5

(20.

php)

AB

C2

prod

uct c

at.1

(16.

php)

AB

C1

prod

uct c

at.4

(19.

php)

AB

D2

prod

uct c

at.2

(17.

php)

19

AB

C1

prod

uct c

at.4

(19.

php)

AB

D2

prod

uct c

at.2

(17.

php)

AB

pr

oduc

t cat

.3 (1

8.ph

p)

ABD

1 pr

oduc

t cat

.5 (2

0.ph

p)

ABC

2 pr

oduc

t cat

.1 (1

6.ph

p)

20

A

BD

1 pr

oduc

t cat

.5 (2

0.ph

p)

ABC

2 pr

oduc

t cat

.1 (1

6.ph

p)

ABC

1 pr

oduc

t cat

.4 (1

9.ph

p)

ABD

2 pr

oduc

t cat

.2 (1

7.ph

p)

AB

pr

oduc

t cat

.3 (1

8.ph

p)

21

AB

D2

prod

uct c

at.1

(21.

php)

AB

pr

oduc

t cat

.2 (2

2.ph

p)

ABD

1 pr

oduc

t cat

.4 (2

4.ph

p)

ABC

2 pr

oduc

t cat

.5 (2

5.ph

p)

ABC

1 pr

oduc

t cat

.3 (2

3.ph

p)

22

AB

pr

oduc

t cat

.2 (2

2.ph

p)

ABD

1 pr

oduc

t cat

.4 (2

4.ph

p)

ABC

2 pr

oduc

t cat

.5 (2

5.ph

p)

ABC

1 pr

oduc

t cat

.3 (2

3.ph

p)

ABD

2 pr

oduc

t cat

.1 (2

1.ph

p)

23

AB

C1

prod

uct c

at.3

(23.

php)

AB

D2

prod

uct c

at.1

(21.

php)

AB

pr

oduc

t cat

.2 (2

2.ph

p)

ABD

1 pr

oduc

t cat

.4 (2

4.ph

p)

ABC

2 pr

oduc

t cat

.5 (2

5.ph

p)

24

AB

D1

prod

uct c

at.4

(24.

php)

AB

C2

prod

uct c

at.5

(25.

php)

AB

C1

prod

uct c

at.3

(23.

php)

AB

D2

prod

uct c

at.1

(21.

php)

pr

oduc

t cat

.2 (2

2.ph

p)

AB

25

AB

C2

prod

uct c

at.5

(25.

php)

AB

C1

prod

uct c

at.3

(23.

php)

AB

D2

prod

uct c

at.1

(21.

php)

AB

pr

oduc

t cat

.2 (2

2.ph

p)

prod

uct c

at.4

(24.

php)

AB

D1

Tim

e

Par

tial c

ount

erba

lanc

ed ‘L

atin

squa

res’

des

ign

with

25

cond

ition

s for

‘bet

wee

n su

bjec

t’ re

sear

ch