Intra-Brand Image Confusion- Effects of Assortment Width on a Congruent

Perceived Brand Image in the Light of ExtensiveBuying Decisions

Master Thesis Expose

University of KasselDepartment of Economics

Submitted by:

Malek Simon Grimm(33240651)

Rodinghweg 764287 Darmstadt

info@malekgrimm.de

To review for:

Prof. Dr. Ralf Wagner

Kassel, October 27, 2016

CONTENTS I

Contents

List of Figures II

List of Tables III

1 Introduction 1

2 Theoretical Background 2

2.1 Negative Effects from Consumer Perspective . . . . . . . . . . . . . . 4

2.1.1 Information Overload . . . . . . . . . . . . . . . . . . . . . . . 4

2.1.2 Costs of More Choices . . . . . . . . . . . . . . . . . . . . . . 5

2.1.3 Consumer Confusion . . . . . . . . . . . . . . . . . . . . . . . 6

2.1.4 Brand Image Confusion . . . . . . . . . . . . . . . . . . . . . 7

2.2 Intra-Brand Image Confusion . . . . . . . . . . . . . . . . . . . . . . 7

2.3 Buying Decisions Types . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.4 The German Automotive Market: Characteristics and Developments . 11

3 Literature Review 15

4 Research Questions 18

5 Methodology 21

5.1 Operationalisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

5.2 Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

6 Preliminary TOC 25

7 Schedule 26

References IV

LIST OF FIGURES II

List of Figures

1 Comparison of consumer confusion, brand image confusion and intra

brand image confusion . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2 Different buying decision types . . . . . . . . . . . . . . . . . . . . . 11

3 Assortment comparison of the years 1990 & 2016 for Audi and Mercedes-

Benz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4 Brand architecture of the Volkswagen AG . . . . . . . . . . . . . . . 13

5 Amount of cognitive and affective involvement for automotive purchases 14

LIST OF TABLES III

List of Tables

1 Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

2 Planned schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

1

1 Introduction

Henry Ford once said, “any customer can have a car painted any colour that

he wants so long it is black” (Ford, 2007, p. 72). Today’s economic landscape has

changed a lot since the times of Henry Ford. Industrial and technological improve-

ments made it for companies much easier to produce individualized products on a

large scale. As a result the variety of products has changed significantly over the last

20 – 30 years, especially in the area of consumer and utility goods (Riemenschneider,

2006, p. 3) and the offerings are welcomed by the consumers. For individual’s the

selective consumption of purchasable products is i.a. a well-liked method for self-

fulfilment and demonstration one’s own authenticity (Burmann & Kohtes, 2014, p.

2).

The possibility for customers to choose among many product variants and the

chance to order single customized products is summarized under the term Mass

Customization (Coletti & Aichner, 2011, p. 15).

Over the time the markets have become increasingly opaque for the costumers due

to broader product ranges, more competitors. The benefits for the costumers, like

self-presentation through individualized products are also accompanied by negative

effects. It’s conceivable that through an increased product range a brand’s identity

could be perceived much vaguer than with a narrow assortment. In such a case

it could be presumed that consumers can’t no longer comprehend a central brand

identity due to a confusion that can be described as a Brand Image Confusion (since

brand images are always a consumer-sided perception of a brand’s identity). Even-

tually, a brand forfeits it’s buying behaviour relevance through an unclear perceived

brand image (Burmann, Halaszovich, Schade, & Hemmann, 2015, pp. 113-144).

The proposed thesis aims to examine the influence of large assortments on brand

image perception. Therefore, the thesis will mainly refer to a working-paper of

Burmann and Kohtes (2014) with the title “variant diversity and intra-brand image

confusion” in which the existence of the construct Intra-Brand Image Confusion is

discussed for the first time and side effects of a large assortment are investigated on

a theoretical basis. Burmann and Kohtes suggest that the topic should be further

examined within the context of a further study. However, the purpose of the thesis

would be on the one hand to prove once more the existence of such a construct

and on the other hand to provide additional and hopefully significant insights for

the new research area of Intra-Brand Image Confusion. Object of the investigation

should be at least one automotive brand; because auto-mobile purchases are classified

2

as extensive buying decisions, which are considered to be “real” buying decision,

realized over a relatively long period and with a high amount of personal involvement.

Furthermore, it has to be considered that automotive manufacturers have broaden

their product ranges significantly over the last years. The relatively new offered

variety of Sport Utility Vehicles (SUV) can be seen as one example for the product

range broadening.

An initial literature considers company related reasons for an assortment widen-

ing, positive and negative company related effects of assortment windings, benefits

and disadvantages of a wider product range for costumers, decision-making processes

of costumers, and development of the German automotive market. Therefore, psy-

chological, marketing, and general economic literature will be primarily assessed. A

confirmatory factor analyses will be conducted to test if the theoretical structure of

the Intra-Brand Image Confusion construct can be replicated once again. Addition-

ally, the fitting of further developed items is investigated. Costumer related effects of

the construct (i.a. brand identification, assortment valuation) are as well considered

by the study.

The thesis will be conducted at the SVI Endowed Chair for International Direct

Marketing at the University of Kassel and supervised by Prof. Dr. Ralf Wagner.

Prof. Wagner and his team have extensive experience in the field of quantitative

methodical procedures and “are driven by a consequent quantitative orientation and

the empirical investigation of current developments in international markets” (Chair

of International Direct Marketing, 2016). In the same vein marketing decisions are

taken into consideration, as well as behavioural patterns of costumers. Therefore it

seems appropriate that the thesis is supervised by the Chair of Prof. Wagner.

The following chapter Theoretical Background outlines fundamental theories and

constructs, chapter Literature Review gives an overview over selected literature.

First research questions are formulated in the chapter Research Questions, the chap-

ter Methodology illustrates an approach for the operationalisation. Section Prelimi-

nary TOC presents a first overview of relevant chapters. The last chapter shows the

planned Schedule.

2 Theoretical Background

In this chapter the fundamental theories and constructs are illustrated in

order to provide a comprehensive understanding for Intra-Brand Image Confusion.

3

After an initial elucidation of company related advantages and disadvantages of

an assortment widening, positive consumer related effects are illustrated. Negative

side effects from consumer perspective are investigated separately in chapter 2.1, in

consideration of the central relevance they take place for a sufficient understanding

of the construct. Chapter 2.3 exhibits characteristics of buying decision types on the

level of individuals. In addition, chapter 2.4 displays aspects and developments of

the German automotive market.

It’s a common assumption in Marketing that consumers generally benefit from

wider assortments. In fact, classical economic theories postulate that larger assort-

ments should always be beneficial for consumers since a wide product range is able

to provide a higher potential chance for a sufficient fitting between consumer pref-

erences and product attributes than a narrow assortment (Chernev, 2003, p. 170).

Therefore, lengthening the assortments should result in an increased overall demand

of the companies’ products. However, an assortment expansion could as well have

negative effects for the corporation. An increased complexity of the production pro-

cess and the loss of economies of scales could for example diminish the initial benefits

of the increased product demand (Bayus & Putsis, 1999, p. 142). Thus, lengthen-

ing an assortment can simultaneously have positive as well as negative effects for a

company.

Speaking from the consumer perspective, enlarging the assortment can also en-

hance positive and negative effects. As mentioned before, a large assortment can

provide a better fit between personal preferences and desired product attributes,

and the selective consumption of purchasable products is a well-liked method for

self-fulfilment (Burmann & Kohtes, 2014, p. 2). So with large assortments it’s

more likely that consumers find at least one product that meets their personal re-

quirements. In addition, consumers benefit from larger assortments, because they

have more opportunity’s to display their own personality. The self-expression trough

brands is often associated with brand love, where consumers experience favourable

feelings trough the consumption of a selected brand (Schlobohm, Zulauf, & Wagner,

2016, p. 344). Consumers might also experience a further benefit simply from having

multiple items in their choice set (Kahn, Moore, & Glazer, 1987, p. 103). Analogous

it’s assumed that consumers sense a perception of ‘freedom of choice’ through larger

assortments (Brehm & Brehm, 2013, p. 23). Another advantage for consumers is

accompanied by an effect that larger assortments reduce decision-making uncertain-

ties “of whether the choice set at hand adequately represents all potentially available

options” (Chernev, 2003, p. 171).

2.1 Negative Effects from Consumer Perspective 4

2.1 Negative Effects from Consumer Perspective

A brand image describes the subjective perception of a brand (identity) and

is therefore always a consumer-sided memorization (Burmann et al., 2015, p. 56).

Therefore, the effects of an Intra-Brand Image Confusion focuses mainly on consumer

perceived effects. Negative consumer related side effects play a key role and are

largely psychological based. This chapter illustrates the underlying theories of Intra-

Brand Image Confusion.

2.1.1 Information Overload

Classical economic theories suggest with the concept of the Homo Oeconomicus

that people have i.a. complete market information and no information capacity

restrictions. This concept has been proven insufficient more than one time. Bounded

Rationality – for example – shows that people can have indeed problems with the

processing of information and don’t always chose a value maximizing option (Beck,

2014, pp. 2-3). Similar to the concept of Bounded Rationality, Information Overload

describes an effect where consumers have problems with processing a certain amount

of information. Broadly spoken the effect can be described as ‘someone received too

much information’ in a certain time period (cf. Eppler & Mengis, 2004, p. 326).

The everyday usage of this term within the research community has led to a va-

riety of terms, synonyms, and related constructs like Cognitive Overload (Vollmann,

1991), Sensory Overload (Lipowski, 1975), Communication Overload (Meier, 1963),

Knowledge Overload (Hunt & Newman, 1997), and Information Fatigue Syndrome

(Wurman, Leifer, Sume, & Whitehouse, 2001) (Eppler & Mengis, 2004, p. 326).

Within Marketing Information Overload is described through a comparison of

the information processing capacity and the information supply (like the amount

of displayed brands) (Eppler & Mengis, 2004, p. 326; Scholz & Wagner, 2006, p.

220). An overload finally occurs when the information supply exceeds someone’s

information processing capacity significantly. Chen, Shang, and Kao explain this

effect more simplified through the comparison to a PC. Like the machine a consumer

has a restricted information passing capacity. When the processor is overloaded

due to the amount of information, the CPU’s answer rate drops. In the case of

Information Overload, people first increase their effort to cope with the amount of

information. Once the input (e.g. of product information) surpasses the capacity

restrictions, the ‘answer rate’ (in terms of processed information) drops as well. As

a result, the decision quality, performance, or reasoning in general decreases (Eppler

& Mengis, 2004, p. 326; Scholz & Wagner, 2006, p. 222). Researchers of different

2.1 Negative Effects from Consumer Perspective 5

disciplines could prove a positive correlation between the amount of information

someone receives and decision quality, performance, or general reasoning up to a

certain point. Information that is perceived after this breaking point isn’t further

integrated in the decision-making process (O’Reilly, 1980).

2.1.2 Costs of More Choices

Choosing between a larger variety of products is accompanied by more time

that needs to be spend for the evaluation of the different products (see chapter 2.3

– extensive buying decision). Loewenstein (1999) indicates three different subforms

for ‘Costs of More Choices’: a) Time Costs, b) Error Costs, and c) Psychic Costs.

Time Costs:

Time Costs describe the amount of time someone spends for the decision-making

process (e.g. acquiring product information, product comparison). The time that

has been invested in the process misses for other maybe more enjoyable activities. In

addition, people tend to get increasingly anxious when the time investment demand

rises – uncertain whether “they are making the best use of scarce hours and minutes”

(Loewenstein, 1999, p. 3), a general decline in enjoyment for prior joyful activities

can be therefore the result.

Error Costs:

Error Costs are further subdivided into five decision errors that arise with an

increasing amount of decision options (Loewenstein, 1999, p. 4; Burmann & Ko-

htes, 2014, p. 3). Firstly, people tend to consider a progressively shrinking number

of options when the amount of options increases (Iyengar & Lepper, 2000). Sec-

ondly, consumers use more simplifying decision-making rules when decisions become

more complex (Payne, Bettman, & Johnson, 1993). Thirdly, consumers tend to pro-

crastinate, choose a default option, or even avoid a final decision due to decision

complexity. Furthermore, consumers tend to be short-sighted when they have to

choose between an immediate gratification and long-term gains (Loewenstein, 1999),

even though the long-term effects are significantly more beneficial (Ausubel, 1991).

Finally, it has been proven that people are likely to be risk aversive in situations

where the potential outcome is uncertain (Kahneman, 2012).

Psychic Costs:

Psychic Costs describes an effect where consumers perceive a feeling of regret

and/or recrimination after a prior decision under uncertainty turned out badly

(Loewenstein, 1999, p. 5). Psychic costs are exacerbated through a “hindsight

2.1 Negative Effects from Consumer Perspective 6

bias”; a bias that describes a tendency of people to assume afterwards that the de-

cision conditions were much clearer than they actually were, and that they should

have known better. The possibility of feeling regretful after the (purchase-)decision

is anticipated by the consumers and can have an influence on the decision-making

process or the final outcome (Burmann & Kohtes, 2014, p. 28).

Beside feelings of regret, people experience anxiety in the moment of making a

decision under uncertainty when (a) think they lack in expertise for a special domain

or (b) decisions require difficult trade-offs.

2.1.3 Consumer Confusion

The construct Consumer Confusion has its origin in marketing research. It

pays regard to negative consequences for consumers due to environmental complexity

and assumes a derivation from normal behavioural decision patterns (Weers, 2008,

pp. 10-11). The confusion is triggered through the amount of offered products (Esch

2012, as cited in Esch, 2013, p. 428).

Basically it can be distinguished between two different dissenting positions. On

the one hand, Consumer Confusion is seen as an unconscious confusion due to a

physical similarity of products (Burmann & Kohtes, 2014, p. 30). Apart from that,

newer views assume that Consumer Confusion is unconsciously as well as consciously

perceived and caused by sensory overload (Weers, 2008, p. 11).

Mitchell and Papavassiliou (1999, p. 320) support the view that Consumer Con-

fusion is unconsciously and consciously perceived. They postulate three main sources

for: (a) overchoice of products and stores, (b) similarity of products, and (c) ambigu-

ous, misleading or inadequate information conveyed by marketing communications.

Weers (2008) could as well identify the three main source of Consumer Confusion

which have been postulated by Mitchell and Papavassiliou (1999). However, Weers

termed the causes: (a) Stimulus Similarity (German: ‘Stimulusahnlichkeit’), (b)

Stimulus Overload (German: ‘Stimulusuberlastung’), and (c) Stimulus Ambiguity

(German: ‘Stimulusunklarheit’).

Stimulus Similarity describes a lack of distinction between the physical appear-

ances of products. Wrong product identification and cognitive misjudgements can

be the result. Stimulus Overload pays regard to the amount of single stimuli that

a costumer is exposed to, and focuses additionally to bounded adsorption as well

as processing capacities. Stimulus Ambiguity addresses the difficulty to interpret

stimuli on the cognitive level due to ambiguous or contradictory perceived stimuli

(Weers, 2008, pp. 14-15).

2.2 Intra-Brand Image Confusion 7

2.1.4 Brand Image Confusion

Weers (2008) was the first person that paid attention to Brand Image Confu-

sion on a large scale. Within his Dissertation he was able to formulate a definition

that meets scientific requirements, examine the structures of the construct, and to

proof causal relationships. His definition of Brand Image Confusion can be translated

as follows:

Brand Image Confusion describes a mental state where consumers

perceive during the buying process, consciously information processing

problems for the usage of brands. The brands appear to the consumer

confusing since they’re perceived as ambiguous, similar, or implausible.

Brand Image Confusion can be based on memory or stimulus level. (cf.

Weers, 2008, p. 25)

Brand Image Confusion bases on the construct of Consumer Confusion; the cen-

tral idea is that consumers base, on the one hand, their buying decisions on product

attributes and information, and pay, on the other hand, strong regard to the orienta-

tion, trust, and symbolic function of brands. Usually a brand serves as an orientation

help during a consumer’s buying decision. In the case of a Brand Image Confusion

the brands forfeits its orientation function and is therefore unable to reduce buying

process complexity for the costumer (Burmann & Kohtes, 2014, pp. 35-36).

2.2 Intra-Brand Image Confusion

Unfortunately Burmann and Kohtes (2014, p. 38) haven’t developed a final,

in their opinion, sufficient definition of the concept Intra-Brand Image Confusion.

However, they still formulated a pre-definition in German, but state that a final

definition should be developed within the proposed dissertation. Referring to this

pre-definition is sufficient enough to gain new insights for research area of Intra

Brand-Image Confusion since the purpose of the thesis won’t be the finalization

of a definition that satisfies research requirements. The German pre-definition of

Burmann and Kohtes is as follows:

“Intramarkenimagekonfusion beschreibt einen Geisteszustand der

Verwirrung beim Nachfrager, welcher durch die angebotenen Markenleis-

tungen innerhalb einer Marke ausgelost wird. Das betroffene Marken-

image kann sowohl gedachtnis- als auch stimulusbasiert nur noch diffus

wahrgenommen werden.” (Burmann & Kohtes, 2014, pp. 51-52).

2.3 Buying Decisions Types 8

Within this thesis the following self-generated dictation will be used to further

clarify the understanding of the construct:

“Intra-Brand Image Confusion describes a mental state of confusion

that a demander perceives due to the offered brand performances within

a brand. The affected brand image can be perceived as diffuse on the

base of the memory and/or the stimulus level.”

For a better understanding of the construct illustrates Figure 1 similarities and

differences between the related constructs Consumer Confusion, Brand Image Con-

fusion, and Intra-Brand Image Confusion. It can be obtained that Intra-Brand

Image Confusion is as consciously perceived confusion within one brand which can

be based on the memorized image or triggered through stimuli. The construct is

compiled through the dimensions similarity, ambiguity, and implausibility.

Figure 1: Comparison of the constructs consumer confusion, brand image confusion andintra-brand image confusion; Source: Own representation based on Burmann and Kohtes

(2014, p. 51)

2.3 Buying Decisions Types

Buying decisions can be separated into four different decision types (Extensive

Buying Decision, Limited Buying Decision, Impulsive Buying Decision, and Routine

Buying Decision). This chapter exemplifies a differentiation that is based on prod-

uct types, has more an economical than a psychological origin, and is a commonly

refereed classification to describe or differentiate buying decisions (Felser, 2015, p.

156). The following section outlines each decision types more detailed.

2.3 Buying Decisions Types 9

At the end of the chapter Figure 2 shows a separation of the decision types by us-

ing the dimensions cognitive involvement and affective/emotional involvement. The

term Involvement is defined as “a person’s perceived relevance of the object based

on inherent needs, values, and interests” (Zaichkowsky, 1985, p. 342). The con-

struct was developed by Sherif and Cantril in the 50th century and has been adapted

through Krugman (1965) to the advertising context in 1965. Involvement has nowa-

days an eminent position in the area of consumer behaviour research (Meffert, Bur-

mann, & Kirchgeorg, 2015, p. 109). Since some decision types are more determined

through cognitive or affective aspects, the further distinction between cognitive and

emotional involvement is sufficient.

Extensive Buying Decisions:

Characteristic for an Extensive Buying decision is an indecisiveness of the con-

sumer at the beginning of the buying process, because they aren’t certain which

product should be bought. In addition, consumers are generally high involved into

the buying process. That’s why they pay attention to commercials and product dif-

ferences (Felser, 2015, p. 156). Due to the high Involvement self-initiated information

seeking behaviour can be expected, in order to reduce uncertainty. That’s especially

the case for high quality and durable products, where consumers aren’t able to ref-

erence to prior buying experience (Meffert et al., 2015, pp. 99-100). One typical

example for this buying decision type is the purchase of an automobile. Kroeber-

Riel and Meyer-Hentschel (1982) claim in an older study that only 15-20% of all

buying decisions can be characterized as extensive buying decisions. Nevertheless,

extensive buying decisions are known as ‘real buying decisions’ (Burmann & Kohtes,

2014, p. 24). This can be explained through the high relevance of the product for

the consumer, a longer decision-making process, and high Involvement which leads

to an active information seeking behaviour.

Limited Buying Decisions:

Limited Buying Decisions are also given when a person is highly involved into

the decision-making process. But in addition, the person has to have a lack of

special knowledge for the desired product category and is unable to compensate his

deficient knowledge (e.g. through a lack of time) (Felser, 2015, p. 158). However,

consumers can refer to a ‘general buying decision knowledge’ which has developed

through prior purchases of different products. Through these buying experiences,

consumers have developed certain judgement heuristics that are used to compensate

the knowledge gap for the product category (Felser, 2015, p. 158). Heuristics can be

described as mental short cuts (Myers, Hoppe-Graff, & Keller, 2014, p. 372). One

2.3 Buying Decisions Types 10

of these heuristics could for example claim that expensive products tend to have in

general a higher quality than cheaper products. As a result uncertain consumers

could prefer an expensive product even so product quality hasn’t finally been proven

(Tull, Boring, & Gonsior, 1964, p. 191).

Impulse Buying Decisions:

An Impulse Buying Decision describes a reactive buying behaviour that’s directed

by environmental stimuli (Kroeber-Riel & Meyer-Hentschel, 1982, p. 12). Product

information or arguments for further evaluation aren’t important, because it mat-

ters more what a consumer thinks or feels in the moment when he faces the product

shelf (Felser, 2015, p. 157; Wagner, 2014, p. 11; Schlobohm et al., 2016, p. 346).

Impulse Buying Decisions aren’t planned ahead (Foscht & Swoboda, 2011, p. 179).

However, still two third of all supermarket costumers leave with an impulsively pur-

chased product (Pratkanis & Aronson, 1992, p. 26). These buying decisions underlay

nearly no cognitive control or cognitive regulation which is the main distinction to

the other buying decisions. Furthermore, certain personal traits like impulsiveness

can be beneficial for Impulse Buying Decisions (Foscht & Swoboda, 2011, p. 179).

The impulsive reactions can usually be restricted to a certain amount, but such reg-

ulations cost the organism cognitive energy (keyword: Ego-Depletion) (Baumeister,

2002, p. 673). Vohs and Faber (2007) showed that the probability of an impulse

purchase increases when consumers had – before the purchase temptation – to solve

tasks that requested self-regulation. From consumer perspective impulse purchases

are acceptable when there’s nearly no distinction between the quality of the products.

Therefore, an evaluation of product characteristics is in such a cases not beneficial

(Felser, 2015, p. 157).

Routine Buying Decisions:

Routine Buying Decisions are further simplified than Impulse Buying Decisions.

They are based on already established behavioural patterns which are proceeded

without any further cognitive elaboration. Typical products are mostly from the

food and beverage industry, like for example tobacco, coffee, or beer brands (Felser,

2015, p. 159). Routine Buying Decisions can be the results of prior purchases,

the adaptation of behavioural patterns through socializing processes, a tendency of

someone to build routines, or certain personality traits (Foscht & Swoboda, 2011, p.

178). It’s likely that Routine Buying Decisions are a continuation and a simplification

of prior extensive or limited buying decisions. It’s also possible that a routine buying

pattern is initiated through an impulsive purchase; this could be the case when the

purchased product satisfied the needs of the demander, so a consumer wants to

2.4 The German Automotive Market: Characteristics and Developments 11

further remain costumer of a certain company (Foscht & Swoboda, 2011, p. 178).

Figure 2: Different buying decision types located after involvement type;Source: Own representation based on Kroeber-Riel and Groppel-Klein (2013, p. 463)

2.4 The German Automotive Market: Characteristics and

Developments

The German automotive market is with distance the biggest European auto-

motive market in regard of production & sales and additionally the biggest industry

sector in Germany. In 2014, 5.6 million cars have been produced in Germany and 3.0

million were registered (GTAI, 2015, p. 3). In the same year the German automotive

manufacturers produced around 15 million cars, whereof 77% haven been exported;

a plus of seven percent compared to the prior year. With around 56 billione, the

German automotive companies are responsible for around 60% of all Research & De-

velopment (R&D) investments in Europe. Thanks to that, the German automotive

companies are in the lead for the production of premium cars, whose demand con-

tinues to rises (GTAI, 2015, p. 4). At the time the German automotive companies

produce about 80% of all worldwide sold premium cars (Ebel & Hofer, 2014, p. 181).

The automotive markets of the triads countries (USA, Japan, Germany) are

saturated (Wallentowitz, Freialdenhoven, & Olschewski, 2009, p. 32). This means

that further sales increases can only be accomplished by gaining market shares from

the competition, while the total market sales revenue remains the same. Market

2.4 The German Automotive Market: Characteristics and Developments 12

competition of key segments has evidently become increasingly stronger. In order

to increase sales revenue and foster market positions, automotive companies try

more intensively to cope with customer demands, and serve new or potential market

segments (Ebel & Hofer, 2014, pp. 6-7) (classical market penetration). Therefore, the

automotive assortments have become much wider over time. Nearly every automotive

brand has stretched their assortment significantly over the last century (Wallentowitz

et al., 2009, p. 12). This tendency is also known as ‘brand widening’ (Esch, 2013,

p. 361). Beneath the increased assortments, consumer can nowadays also choose

between a lot of more variants per model. In 2004, Renault offered for example

six different variants of their model Megane (coupe, hatchback, classic, convertible,

minivan, station wagon) in order to serve customer demands (Wallentowitz et al.,

2009, p. 12).

One financial problem that the automotive companies have to face through this

tendency is – like the concept of economic of scales suggests (c.f. Decker, Kroll,

Meißner, & Wagner, 2015, p. 51) – that cost per piece decreases with the total

amount of sold pieces. So as a logical consequence the cost per pieces increase if fewer

models are sold; which is pretty likely if niche segments are served. Furthermore,

production processes have to be more flexible and their complexity rises. However,

some premium manufactures can still be profitable in their key segments, but usually

discounting wars are convenient to sell remaining stocks of less desired product types

(Wallentowitz et al., 2009, p. 7).

Figure 3: Assortment comparison of the years 1990 & 2016 for Audi and Mercedes-Benz;Source: Own and expended representation based on Esch (2013, p. 361) & Wallentowitz

et al. (2009, p. 12)

2.4 The German Automotive Market: Characteristics and Developments 13

Researches suggest that automotive brands have a very high relevance when it

comes to purchase decisions (Fischer, Meffert, & Perrey, 2004, p. 345). Therefore,

brands are in the automotive industry an eminent success factor for sustainable

corporate achievements (Ebel & Hofer, 2014, p. 10).

Kanitz (2013) has further investigated the buying relevance of the corporate

brand image and the product brand image for specific products. For automotive

brands, he could prove a causal connection of β=0.365, t=NA, p<.001 between the

corporate brand-image and the buying relevance, as well as a causal connection of

β=0.415, t=NA,p<.001 between product brand image and buying relevance (Kanitz,

2013, p. 189). These findings suggest that automotive product brand images like

C-Class (Mercedes-Benz), 3 Series (BMW), or A4 (Audi) play a more important role

for a purchase decision than the actual corporate brand image. Figure 4 illustrates

the distinction between different brand levels and uses the brand architecture of the

Volkswagen AG as an example.

Figure 4: Brand architecture of the Volkswagen AG; Source: Own adjustedrepresentation based on (Burmann & Kohtes, 2014, p. 44)

For the costumers their car is not simply a transportation vehicle; it fulfils beside

its functional function, important symbolic and affective functions (Steg, 2005, p.

147).

There’s no clear consensus whether a car can be classified as a status symbol

or not. Ebel and Hofer (2014, p. 294) claim that cars have always been a highly

emotional symbol to represent someone’s status, especially in Germany. Steg (2005,

p. 148) postulate a similar opinion, as they say that “for many people, the car seems

to be a status symbol [...]”.

2.4 The German Automotive Market: Characteristics and Developments 14

For Schumacher (2015, pp. 13-14) luxury goods are equivalent to status goods.

He challenges the status considering perspective of cars in regard of the German

market and states that cars can’t be clearly classified as a status symbols since they

provide no exaggerated social benefit for the German costumers; the social environ-

ment won’t be highly impressed through the ownership of an average car; therefore,

such a car wouldn’t express someone’s social status. It has to be considered that this

is only the case for the German market, and the individual perspectives of the cos-

tumers play always a key role, as well as the social and cultural background (Urkmez

& Wagner, 2015). Schumacher (2015, pp. 14-15) claims that the received social ben-

efit of a car ownership in India is much greater than in Germany. Individuals there

are able to distinct themselves much more from their social environment through a

car than in Germany.

Figure 5: Amount of cognitive and affectiveinvolvement for automotive purchases; Source:

Own adjusted representation based on(Ratchford, 1987, p. 8)

While there may be no consen-

sus whether cars can be clearly clas-

sified as a status symbols or not,

it can be said that they still have

a high relevance for the consumers.

This statement can be underlined

through Figure 5. It shows that peo-

ple are highly cognitive and on aver-

age high affective involved in auto-

motive purchase decisions. Further-

more, the purchase of a car is clearly

classified as an extensive buying de-

cision (c.f. Stolle, 2013, p.10).

The political group chairman

of the German party SPD, Sig-

mar Gabriel proposed for example

to withdraw the driving license of

male parents who refuse to finan-

cially support their children that

live with their single raising moth-

ers (Tagesschau, 2016). The idea to take someone’s driving license as a punishment

for unrelated penal offences even though, not every male adult has a driving licences

and uses his or wants to use his car on regular base. This further indicates how

important cars and their usage are in Germany.

15

While cars and their usage appear to be still important for Germans, their wish

to own a car seems to decline. Especially the automotive affinity of younger people

between 18-24 years, from further developed industrial states like Germany decreased

over the last years and their daily car usage dropped in the time from 2002 to 2008 by

9% to 55% (Ebel & Hofer, 2014, p. 95). Even though, young adults have over decades

been considered as one of the most car oriented age groups (Kuhnimhof, Buehler,

Wirtz, & Kalinowska, 2012, p. 443). However, these people haven’t become less

mobile, the average daily travelled distance has actually risen over the mentioned

time period. The declined car usage can be linked to two central factors: 1.) Data

from the German Income and Expenditure Surveys (EVS) from 1998 to 2008 suggests

that the car access for most of the young people declined over time (Kuhnimhof et

al., 2012, p. 446). Especially households in larger cities don’t own a car – e.g.

29% in Munich, 33% in Hamburg, and 41% in Berlin (Infas/Oko-Institut, 2009, p.

25). 2.) Multimodality mobility of younger people (even of those with car access)

increased (Kuhnimhof et al., 2012, pp. 446-447). Much more young people switch

between car, public transportation, bicycles, and rental cars since these alternatives

have become more attractive. 46% of this aged class, who already know about car

sharing options, claimed for example that they could imagine using car sharing as

an alternative beside the usage of their regular car (Ebel & Hofer, 2014, p. 103).

It can’t be clearly said if the decreasing car affinity of younger people is only a

temporal tendency or a development that will further increase. The overall market

relevance of this progress is still relative small, but has to be further observed (Ebel

& Hofer, 2014, p. 105). Opel (CarUnity), BMW (DriveNow), and Mercedes-Benz

(car2go) have already reacted to the increased consumer demand and offer already

car sharing solutions through own sub-brands or brand alliances; but Audi, however,

still doesn’t plan to launch a own car sharing solution.

3 Literature Review

The following table shows an overview of relevant literature like textbooks,

dissertations, articles and working papers that address the issues product diversity,

information overload, costs of more choice as well as consumer confusion.

16

Table 1: Literature review

Type Authors Title Main Findings

Textbook Burmann,Halaszovich,Schade, andHemmann(2015)

IdentitatsbasierteMarkenfuhrung:Grundlagen - Strategie -Umsetzung - Controlling

Detailed explanation of themodel identity-based brandmanagement and thereofrelated researches

Ebel and Hofer(2014)

Automotive Management I.a. discusses the declining carusage of young adults; decliningaccess to cars of these people;less emotional view of cars

Esch (2013) Strategie und Technik desAutomobilmarketing

I.a. investigation of reasons forassortment widening in theautomotive industry;explanation of consumerconfusion

Felser (2015) Werbe- undKonsumentenpsychologie

I.a. detailed illustration of thebuying decision types(extensive, limited, impulse,routine)

Foscht andSwoboda (2011)

Kauferverhalten:Grundlagen - Perspektiven- Anwendungen

I.a. further explanation ofbuying decision types;differentiation betweencognitive and affectiveinvolvement for buying decisiontypes

Meffert,Burmann, andKirchgeorg(2015)

Marketing: GrundlagenmarktorientierterUnternehmensfuhrung ;Konzepte - Instrumente -Praxisbeispiele

I.a. as well a description ofbuying decision types

Wallentowitz,Freialdenhoven,and Olschewski(2009)

Strategien in derAutomobilindustrie:Technologietrends undMarktentwicklungen

I.a. development of automotivemarkets; effects and reasons forassortment widening in theautomotive industry

Dissertation Kanitz (2013) Gestaltung komplexerMarkenarchitekturen

Investigated the causality ofcorporate brand image (BMW)/ product brand image (3series) and buying relevance fordifferent products

Weers (2008) Markenimagekonfusion alsManagementheraus-forderung: Zum Problemeiner gedachtnisbasiertenund Point of Saleinduzierten verwirrendenWahrnehmung vonMarken

Investigation, development andempirical testing of theconstruct brand imageconfusion

17

Paper Ausubel (1991) The Failure ofCompetition in the CreditCard Market

Irrational decision behaviour ofconsumer; immediategratifications are preferred evenwhen long term effects aremuch more beneficial

Burmann andKohtes (2014)

Variantenvielfalt und In-tramarkenimagekonfusion

Theoretical development of theconstruct brand imageconfusion and investigation ofpossible side effects as well asclarifying of the relevance thetopic

Chernev (2003) When More Is Less andLess Is More: The Role ofIdeal Point Availabilityand Assortment inConsumer Choice

Found that consumers haveweaker preferences when theychoose their product from anlarge assortment

Eppler andMengis (2004)

The Concept ofInformation Overload: AReview of Literature fromOrganization Science,Accounting, Marketing,MIS, and RelatedDisciplines

Detailed literature for theconcept of information overloadfor different scientific areas

Iyengar andLepper (2000)

When Choice isDemotivating: Can OneDesire Too Much of aGood Thing?

Effects of assortment width onpurchase decisions; people aremore likely to buy a product,when they have to choosebetween less option

Kahn, Moore,and Glazer(1987)

Experiments inConstrained Choice

Investigated effects for brandelimination during a decisionmaking process and how thefinal decision is made(hierarchical elimination modelvs. luce model); consider alarger choice set in generalbeneficial for consumers; datasuggest that brand eliminationwhen choosing betweendifferent brands has nature thatspeaks more for the eliminationmodel where brands (directcomparison of two brands perdecision step)

Kuhnimhof,Buehler, Wirtz,and Kalinowska(2012)

Travel trends amongyoung adults in Germany:Increasing multimodalityand declining car use formen

Declining access to personalcars for young adults;Increasing multimodalitybeneth cars (e.g. publictransport, bicycle, car sharing)

18

Mitchell andPapavassiliou(1999)

Marketing causes andimplications of consumerconfusion

Examination of marketing andpolicy implications of consumerconfusion; discuss the conciousand unconscious nature ofconsumer confusion; derivecompany sided approaches todeal with consumer confusion

O’Reilly (1980) Individuals andInformation Overload inOrganizations: Is MoreNecessarily Better?

Noticed that there’s a certainbreaking-point for the amountof information that should besupplied. Individuals proceedless information, if the amountof provided information exceedsthis breaking point; U-shapedcorrelation

Payne, Bettman,and Johnson(1993)

The adaptive decisionmaker

Tendency of consumers to usesimplifying decision makingrules in order to easedifficult/complex decisionrequirements

Ratchford (1987) New insights about theFCB grid

graphical illustration ofconsumer’s cognitive andaffective involvement towardsvarious product types

Sherif andCantril (1947)

The psychology ofego-involvements, socialattitudes & identifications

first scientific investigation anddevelopment of the involvementconstruct

Vohs and Faber(2007)

Spent Resources:Self-Regulatory ResourceAvailability AffectsImpulse Buying

Increased tendency of impulsebuying afterdistraction/cognitiveexhaustion through tasks thatrequire a certain amount ofself-regulation

Zaichkowsky(1985)

Measuring theInvolvement Construct

I.a. mostly quoted source of aninvolvement definition

Grey Lit. GTAI (2015) Industry Overview: TheAutomotive Industry inGermany

I.a. international increasingdemand of German premiumcars

4 Research Questions

The following chapter illustrates first ideas for possible research questions.

These ideas shouldn’t be considered as finally defined. It could be possible that

other research questions appeal more interesting through further investigation of the

theoretical literature. Please note that the underlined hypotheses are the one’s that

are assumed.

19

Weers (2008, cf. 180) could proof a causal relationship between the Brand Image

Confusion dimension ambiguity – which is identical to the equivalent Intra-Brand

Image Confusion dimension – and the information seeking behaviour of costumer’s of

β=-0.52, t=NA,p=NA. So it could be possible that the overall construct Intra-Brand

Image Confusion correlates with a tendency of consumer’s to use buying heuristics

(see Hypotheses 1).

H0.1: Intra-Brand Image Confusion isn’t significantly positively re-

lated with the usage of buying heuristics during a buying

process.

HA.1: Intra-Brand Image Confusion correlates significantly posi-

tively with the usage of buying heuristics during a buying

process.

The theoretical framework of Intra-Brand Image Confusion assumes that wide

assortments can lead to perceived similarity, ambiguity, and implausibility of a brand

and its products (cf. Figure 1). Since the central benefits of single products can’t no

longer be recognized, it can be expected that consumers tend to think an assortment

contains superfluous products (see Hypotheses 2). In this context a superfluous

describes a product that seems expendable with other products, lacks in substantial

differentiation characteristics (as benefits for the costumer) to other products, has an

overlapping reason for being with other products, and/or can be removed from the

assortment without a tangibly harming of the consumer-sided perceived brand image

(counterexample are i.a. Volkswagen and the Golf, and Apple and the iPhones).

In the same vein it can be assumed that Intra-Brand Image Confusion has neg-

ative effects on identification with the brand (see Hypotheses 3) and sympathy for

the brand (see Hypotheses 4), because a brand loses its central function.

H0.2: Intra-Brand Image Confusion isn’t significantly positively re-

lated with the tendency of consumers to view single products

of an assortment as superfluous.

HA.2: Intra-Brand Image Confusion correlates significantly posi-

tively with the tendency of consumers to view single products

of an assortment as superfluous.

H0.3: Intra-Brand Image Confusion isn’t significantly negatively re-

lated with consumer’s brand identification.

20

HA.3: Intra-Brand Image Confusion correlates significantly nega-

tively with consumer’s brand identification.

H0.4: Intra-Brand Image Confusion isn’t significantly negatively re-

lated with brand sympathizing.

HA.4: Intra-Brand Image Confusion correlates significantly nega-

tively with brand sympathizing.

Walsh (2002, cf. 180) examined the causal relationship between the Consumer

Confusion dimensions similarity and ambiguity – which are identical to the equiv-

alent Intra-Brand Image Confusion dimensions – and word-of-mouth recommen-

dation (Keul, Wagner, & Brandt-Pook, 2014, p. 479). Path coefficients of β=-

0.204, t=NA,p=NA (similarity to word-of-mouth recommendation) and β=-0.256,

t=NA,p=NA (ambiguity to word-of-mouth recommendation) have been observed.

Consequently it’s assumable that Intra-Brand Image Confusion correlates negatively

with the construct Net Promoter Score (see Hypotheses 5).

Moreover a causal relationship of β=-0.107, t=NA,p=NA between the Consumer

Confusion dimension similarity and delayed purchases was observed, as well as a

causal relationship of β=0.475, t=NA,p=NA between the aggregated construct Con-

sumer Confusion and delayed purchases. Therefore it can be assumed that Intra-

Brand Image Confusion correlates with a tendency of consumers to delay purchase

decisions (see Hypotheses 6).

H0.5: Intra-Brand Image Confusion isn’t significantly negatively re-

lated to Net Promoter Score.

HA.5: Intra-Brand Image Confusion correlates significantly nega-

tively with Net Promoter Score.

H0.5: Intra-Brand Image Confusion isn’t significantly positively re-

lated with the tendency of consumers to delay purchase de-

cisions.

HA.5: Intra-Brand Image Confusion correlates significantly posi-

tively with the tendency of consumers to delay purchase de-

cisions.

21

5 Methodology

It’s intended to conduct an quantitative approach in order to find sufficient

answers to the prior proposed research questions. The next chapter shows suggestions

for sufficient operationalisations of the utilised constructs; followed by ideas for the

data collection process.

5.1 Operationalisation

The following chapter will provide suggestions to measure the necessary con-

structs.

Automotive Affinity:

Participants should have at least a minimal affinity towards cars and auto-

mobility. Therefore, the automotive affinity should be asked initially through a

5-point Likert-scale (1: “not at all” – 5: “extremely”). Participants who state that

they aren’t affine towards cars and auto-mobility (1=“not at all”) should be filtered

and can’t further proceed.

Single item measurements are nowadays a convenient way to gather data. At the

moment 46% of the models published in top marketing journals use a single-item

measurement instead of multi-item measuring constructs (Hair, Sarstedt, Ringle, &

Mena, 2012, p. 423).

Brand Awareness:

The awareness of a brand is mandatory for the existence of a brand image (Ebel

& Hofer, 2014, p. 277). Therefore, it would normally be necessary to ask the partic-

ipants a aided question about the brand awareness of every brand. Participants that

would – for example – answer on a 5-point Likert-scale (‘How good do you know

the brand XYZ’; 1 = “not at all” – 5 = “very good”) that they don’t know the

brand at all had to be further proceeded within the survey without asking for their

further opinions towards the brand. However, automotive brands have a very high

aided knowledge in Germany (e.g. BMW: 95,6%; Volkswagen: 95,6%; Mercedes-

Benz: 95,4%; Audi: 94,4% (see Fleischmann, 2016, p. 117)). Therefore, brand

knowledge can be assumed, with regard to the generally high aided brand knowledge

for automotive brands among Germans. By doing so an actual questions for brand

knowledge can be neglect.

5.1 Operationalisation 22

Intra-Brand Image Confusion:

As in Table 1 illustrated the theoretical characteristics of the constructs Brand

Image Confusion and Intra-Brand Image Confusion are pretty similar. The main

difference between these two constructs is that the Brand Image Confusion focuses

on a brand confusion between several brands, whereas Intra Brand Image Confusion

focuses on a confusion inside one brand due to a too large assortment or too similar

products. Yet, there is no possibility published to measure Intra-Brand Image Con-

fusion. However, since similarity of the mentioned constructs, it would be possible

to adopt the items of the Brand Image Confusion construct to measure the confusion

inside one brand, instead of a confusion between different brands. A scale to mea-

sure Brand Image Confusion is published in the appendix of the work ‘brand image

confusion as management challenge: addressing memory and point-of-sales induced

confused perception of brands’ (Weers, 2008, pp. 216-217). Unfortunately there are

no further information in regard of which items measure which dimension (similar-

ity, ambiguity, implausibility), and which items are inverted and which are not. An

initial contact with the doctoral supervisor that has been forwarded to a doctoral

student of the chair hasn’t provided further information, yet. However, since the

construct measurement proofed to be valid and reliable, it should be possible to

generate the relevant factors once again with a (confirmatory) factor analyses, even

without knowing exactly which items represent which indicators. However, further

items with regard to the single dimensions will be developed and their fittings are

going to be tested through a pre-test.

The conduction of a pre-test shouldn’t be necessary to investigate the sufficiency

of the quality criteria since validity and reliability of the construct is given and the

precise quality can be examined after the main survey. Nevertheless, a pre-test will

be conducted to investigate which brand’s assortments provide a perception of Intra-

Brand Image Confusion. Without this step it could be possible that the main study

reveals that none of the selected brands provide a perception of an Intra-Brand Image

Confusion.

Heuristic Usage:

Schulze-Bentrop (2014, pp. 110-111) examined the quality of a German trans-

lated, three-item construct from Hong and Sternthal (2010) which measures how

intensively heuristic are used during the purchase of products. The investigation of

Schulze-Bentrop revealed a sufficient measurement quality of the construct; with a

Cronbach’s Alpha of 0.88, factor reliability of 0.88, and an average explained vari-

ance of 0.71. The items were measured with a 7-point Likert-scale (1 = “strongly

5.2 Data Collection 23

disagree” – 7 = “strongly agree”). However, within the surveys the items should be

measured through a 5-point Likert-scale in order to keep the data consistence with

other constructs. The inverted items are formulated as follows.

The strategy I used to examine product information allowed ...

(Zur Beurteilung des Produktes werde ich eine Vorgehensweise benutzen, ...)

• ... a detailed assessment of the features

(... die mir eine detaillierte Beurteilung der Produkteigenschaften ermoglicht.)

• ... a clear overview of the products

(... die es mir erlaubt, mir einen klaren Uberblick uber die Varianten des Produkts zu verschaffen.)

• ... a detailed assessment of alternative brands

(... die mir eine detaillierte Beurteilung verschiedener Marken dieses Produktes ermoglicht.)

Further Single-Item Measurement:

The following constructs could be obtained through single-item measurements (5-

point Likert-scale): Superfluous products, brand identification, brand sympathizing,

and delayed purchase. Net Promoter Score can also be examined through a single

item. However, a 10-point Liker-scale is the convenient method to examine the Net

Promoter Score and should be therefore used.

5.2 Data Collection

It’s planned to conduct an internet-based quantitative survey in order to an-

swer the research questions. The survey could be implemented on SoSci Survey;

The service is for academic as well as for non-commercial purposes free of charges

and without functionality restrictions. Furthermore, it’s possible to implement filter

questions and export the data in SPSS readable files. The implementation should

be realisable in a day since the author is already experienced in using the mentioned

platform. The implemented questionnaire should be finally checked before the survey

will be launched.

An initial pre-test should be conducted to investigate which automotive brands

provide an Intra-Brand Image Confusion. Participants should merely answer the

questions of the Intra-Brand Image Confusion scale (adapted items of the measure-

ment of Brand Image Confusion) for ten automotive brands. Possible brands could

be a selection of the following brands: Alfa Romeo, Audi, BMW, Citroen, Fiat, Ford,

Mazda, Mercedes-Benz, Mini, Opel, Peugeot, Porsche, Renault, Seat, Skoda, Smart,

5.2 Data Collection 24

Volkswagen, and Volvo. The obligatory question for automotive affinity is asked at

the beginning of the survey. Demographic questions aren’t absolutely necessary, but

could consist only of questions for gender and age, to get a first impression of the

sample, possible gender effects, and age tendencies. A sample size of 50 participants

should be sufficient. Following this, five brands are selected for the main survey.

As in the Preliminary TOC section mentioned, are – for now – three weeks for

the data acquisition of the main study calculated (excluding an additional week, if

the number of participants is insufficient). Social media platforms, mailing lists as

well as personal approaches could be used to acquire the necessary participants. An

English version can be set up beneath a German one, depending on which mailing

lists will be used. Yet, it’s not planned to raffle monetary incentives to encourage the

participation. The overall answer should be time around 10 minutes since too long

questionnaires are usually demotivating and generally lead to an increased breakup

rate.

Subsequently, a statistical structural equation model program (like SmartPLS,

ADANCO, or SPSS Amos) will be used for the data analysis. The data pool will be

checked to eliminate participants that haven’t answered seriously (indication through

unusual answer patters, etc.), before further steps will be conducted. Adequate

statistical tests will be conducted (parametric vs. non-parametric, etc.) in order to

answer the research questions.

25

6 Preliminary TOC

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2. Theoretical Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.1. Reasons for Assortment Widening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.1.1. Company-Internal Causes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.1.2. Company-External Causes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.2. Consequences of Assortment Widening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.2.1. Positive Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.2.2. Negative Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.2.2.1. Information Overload . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.2.2.2. Costs of More Choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.2.2.3. Consumer Confusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.2.2.4. Brand Image Confusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.3. Brand Variety and Intra Brand Image Confusion . . . . . . . . . . . . . . . . . . . . . . .

2.3.1. Consumer-Related Core Functions of Brands . . . . . . . . . . . . . . . . . . . . . .

2.3.2. Brand Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.3.3. Intra Brand Image Confusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.3.4. Distinction of Related Constructs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.4. Buying Decision Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.5. German Automotive Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3. Hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4. Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4.1. Experimental Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4.1.1. Constructs and Operationalisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4.1.2. Pre-Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4.1.3. Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4.2. Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4.2.1. Pre-Test Sample Audit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4.2.2. Sample Audit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4.2.3. Construct Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.1. Summary and Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.2. Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6.3. Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

26

7 Schedule

Table 2: Planned schedule

Period

( 5 months ≈ 22 weeks )

Steps

∼ 31.10.2016 Registration

31.10.2016 - 27.11.2016(4 weeks)

Writing of theoretical part

28.11.2016 - 04.12.2016(1 week)

Survey implementation

05.12.2016 - 11.12.2016(1 week)

Buffer

12.12.2016 Survey launch

12.12.2016 - 01.01.2017(3 weeks)

Acquisition period

12.12.2016 - 01.01.2017(see above)

Finalization of theoreticalpart

02.01.2017 - 08.01.2017(1 week)

Spacing for further acquisi-tions

09.01.2017 - 29.01.2017(3 weeks)

Data analysis

30.01.2016 - 05.02.2017(1 week)

Spacing if problems withdata occur

06.02.2016 - 26.02.2017(3 weeks)

Finalization of methodologi-cal part; Writing of discus-sion

27.02.2017 - 05.03.2017(1 week)

Writing of abstract

06.03.2017 - 19.03.2017(2 weeks)

Proof read and error fixing

20.03.2017 - 02.04.2017(2 weeks)

Feedback & additional buffer

est. deadline 03.04.2017 Submission

References IV

References

Ausubel, L. M. (1991). The failure of competition in the credit card market. TheAmerican Economic Review , 81 (1), 50–81.

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STATUTORY DECLARATION VIII

Statutory Declaration

I declare that I have developed and written the enclosed Master ThesisExpose completely by myself, and have not used sources or means withoutdeclaration in the text. Any thoughts from others or literal quotations are clearlymarked. The Master Thesis was not used in the same or in a similar version toachieve an academic grading or is being published elsewhere.

Darmstadt, October 27, 2016Malek Simon Grimm